Long History of IAM Comparisons

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

Smith, Steven J.; Clarke, Leon E.; Edmonds, James A.

2015-04-23

Correspondence to editor: We agree with the editors that the assumptions behind models of all types, including integrated assessment models (IAMs), should be as transparent as possible. The editors were in error, however, when they implied that the IAM community is just “now emulating the efforts of climate researchers by instigating their own model inter-comparison projects (MIPs).” In fact, model comparisons for integrated assessment and climate models followed a remarkably similar trajectory. Early General Circulation Model (GCM) comparison efforts, evolved to the first Atmospheric Model Inter-comparison Project (AMIP), which was initiated in the early 1990s. Atmospheric models evolved to coupledmore » atmosphere-ocean models (AOGCMs) and results from the first Coupled Model Inter-Comparison Project (CMIP1) become available about a decade later. Results of first energy model comparison exercise, conducted under the auspices of the Stanford Energy Modeling Forum, were published in 1977. A summary of the first comparison focused on climate change was published in 1993. As energy models were coupled to simple economic and climate models to form IAMs, the first comparison exercise for IAMs (EMF-14) was initiated in 1994, and IAM comparison exercises have been on-going since this time.« less

The Data Platform for Climate Research and Action: Introducing Climate Watch

NASA Astrophysics Data System (ADS)

Hennig, R. J.; Ge, M.; Friedrich, J.; Lebling, K.; Carlock, G.; Arcipowska, A.; Mangan, E.; Biru, H.; Tankou, A.; Chaudhury, M.

2017-12-01

The Paris Agreement, adopted through Decision 1/CP.21, brings all nations together to take on ambitious efforts to combat climate change. Open access to climate data supporting climate research, advancing knowledge, and informing decision making is key to encourage and strengthen efforts of stakeholders at all levels to address and respond to effects of climate change. Climate Watch is a robust online data platform developed in response to the urgent needs of knowledge and tools to empower climate research and action, including those of researchers, policy makers, the private sector, civil society, and all other non-state actors. Building on the rapid growing technology of open data and information sharing, Climate Watch is equipped with extensive amount of climate data, informative visualizations, concise yet efficient user interface, and connection to resources users need to gather insightful information on national and global progress towards delivering on the objective of the Convention and the Paris Agreement. Climate Watch brings together hundreds of quantitative and qualitative indicators for easy explore, visualize, compare, download at global, national, and sectoral levels: Greenhouse gas (GHG) emissions for more than 190 countries over the1850-2014 time period, covering all seven Kyoto Gases following IPCC source/sink categories; Structured information on over 150 NDCs facilitating the clarity, understanding and transparency of countries' contributions to address climate change; Over 6500 identified linkages between climate actions in NDCs across the 169 targets of the sustainable development goals (SDG); Over 200 indicators describing low carbon pathways from models and scenarios by integrated assessment models (IAMs) and national sources; and Data on vulnerability and risk, policies, finance, and many more. Climate Watch platform is developed as part of the broader efforts within the World Resources Institute, the NDC Partnership, and in collaboration with GIZ, UNFCCC, World Bank, and Climate Analytics.

The Urgent Need for Improved Climate Models and Predictions

NASA Astrophysics Data System (ADS)

Goddard, Lisa; Baethgen, Walter; Kirtman, Ben; Meehl, Gerald

2009-09-01

An investment over the next 10 years of the order of US$2 billion for developing improved climate models was recommended in a report (http://wcrp.wmo.int/documents/WCRP_WorldModellingSummit_Jan2009.pdf) from the May 2008 World Modelling Summit for Climate Prediction, held in Reading, United Kingdom, and presented by the World Climate Research Programme. The report indicated that “climate models will, as in the past, play an important, and perhaps central, role in guiding the trillion dollar decisions that the peoples, governments and industries of the world will be making to cope with the consequences of changing climate.” If trillions of dollars are going to be invested in making decisions related to climate impacts, an investment of $2 billion, which is less than 0.1% of that amount, to provide better climate information seems prudent. One example of investment in adaptation is the World Bank's Climate Investment Fund, which has drawn contributions of more than $6 billion for work on clean technologies and adaptation efforts in nine pilot countries and two pilot regions. This is just the beginning of expenditures on adaptation efforts by the World Bank and other mechanisms, focusing on only a small fraction of the nations of the world and primarily aimed at anticipated anthropogenic climate change. Moreover, decisions are being made now, all around the world—by individuals, companies, and governments—that affect people and their livelihoods today, not just 50 or more years in the future. Climate risk management, whether related to projects of the scope of the World Bank's or to the planning and decisions of municipalities, will be best guided by meaningful climate information derived from observations of the past and model predictions of the future.

Linking Climate Risk, Policy Networks and Adaptation Planning in Public Lands

NASA Astrophysics Data System (ADS)

Lubell, M.; Schwartz, M.; Peters, C.

2014-12-01

Federal public land management agencies in the United States have engaged a variety of planning efforts to address climate adaptation. A major goal of these efforts is to build policy networks that enable land managers to access information and expertise needed for responding to local climate risks. This paper investigates whether the perceived and modeled climate risk faced by different land managers is leading to larger networks or more participating in climate adaptation. In theory, the benefits of climate planning networks are larger when land managers are facing more potential changes. The basic hypothesis is tested with a survey of public land managers from hundreds of local and regional public lands management units in the Southwestern United States, as well as other stakeholders involved with climate adaptation planning. All survey respondents report their perceptions of climate risk along a variety of dimensions, as well as their participation in climate adaptation planning and information sharing networks. For a subset of respondents, we have spatially explicity GIS data about their location, which will be linked with downscaled climate model data. With the focus on climate change, the analysis is a subset of the overall idea of linking social and ecological systems.

Understanding climate-induced migration through computational modeling: A critical overview with guidance for future efforts

DOE PAGES

Till, Charlotte; Haverkamp, Jamie; White, Devin; ...

2016-11-22

Climate change has the potential to displace large populations in many parts of the developed and developing world. Understanding why, how, and when environmental migrants decide to move is critical to successful strategic planning within organizations tasked with helping the affected groups, and mitigating their systemic impacts. One way to support planning is through the employment of computational modeling techniques. Models can provide a window into possible futures, allowing planners and decision makers to test different scenarios in order to understand what might happen. While modeling is a powerful tool, it presents both opportunities and challenges. This paper builds amore » foundation for the broader community of model consumers and developers by: providing an overview of pertinent climate-induced migration research, describing some different types of models and how to select the most relevant one(s), highlighting three perspectives on obtaining data to use in said model(s), and the consequences associated with each. It concludes with two case studies based on recent research that illustrate what can happen when ambitious modeling efforts are undertaken without sufficient planning, oversight, and interdisciplinary collaboration. Lastly, we hope that the broader community can learn from our experiences and apply this knowledge to their own modeling research efforts.« less

Understanding climate-induced migration through computational modeling: A critical overview with guidance for future efforts

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

Till, Charlotte; Haverkamp, Jamie; White, Devin

Climate change has the potential to displace large populations in many parts of the developed and developing world. Understanding why, how, and when environmental migrants decide to move is critical to successful strategic planning within organizations tasked with helping the affected groups, and mitigating their systemic impacts. One way to support planning is through the employment of computational modeling techniques. Models can provide a window into possible futures, allowing planners and decision makers to test different scenarios in order to understand what might happen. While modeling is a powerful tool, it presents both opportunities and challenges. This paper builds amore » foundation for the broader community of model consumers and developers by: providing an overview of pertinent climate-induced migration research, describing some different types of models and how to select the most relevant one(s), highlighting three perspectives on obtaining data to use in said model(s), and the consequences associated with each. It concludes with two case studies based on recent research that illustrate what can happen when ambitious modeling efforts are undertaken without sufficient planning, oversight, and interdisciplinary collaboration. Lastly, we hope that the broader community can learn from our experiences and apply this knowledge to their own modeling research efforts.« less

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

PubMed

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

2018-01-01

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

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

USGS Publications Warehouse

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

2018-01-01

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

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

NASA Technical Reports Server (NTRS)

Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.;

Effective Climate Refugia for Cold-water Fishes

NASA Astrophysics Data System (ADS)

Ebersole, J. L.; Morelli, T. L.; Torgersen, C.; Isaak, D.; Keenan, D.; Labiosa, R.; Fullerton, A.; Massie, J.

2015-12-01

Climate change threatens to create fundamental shifts in in the distributions and abundances of endothermic organisms such as cold-water salmon and trout species (salmonids). Recently published projected declines in mid-latitude salmonid distributions under future climates range from modest to severe, depending on modeling approaches, assumptions, and spatial context of analyses. Given these projected losses, increased emphasis on management for ecosystem resilience to help buffer cold-water fish populations and their habitats against climate change is emerging. Using terms such as "climate-proofing", "climate-ready", and "climate refugia", such efforts stake a claim for an adaptive, anticipatory planning response to the climate change threat. To be effective, such approaches will need to address critical uncertainties in both the physical basis for projected landscape changes in water temperature and streamflow, as well as the biological responses of organisms. Recent efforts define future potential climate refugia based on projected streamflows, air temperatures, and associated water temperature changes. These efforts reflect the relatively strong conceptual foundation for linkages between regional climate change and local hydrological responses and thermal dynamics. Yet important questions remain. Drawing on case studies throughout the Pacific Northwest, we illustrate some key uncertainties in the responses of salmonids and their habitats to altered hydro-climatic regimes currently not well addressed by physical or ecological models. Key uncertainties include biotic interactions, organismal adaptive capacity, local climate decoupling due to groundwater-surface water interactions, the influence of human engineering responses, and synergies between climatic and other stressors. These uncertainties need not delay anticipatory planning, but rather highlight the need for identification and communication of actions with high probabilities of success, and targeted research within an adaptive management framework.

"The Effect of Alternative Representations of Lake Temperatures and Ice on WRF Regional Climate Simulations"

EPA Science Inventory

Lakes can play a significant role in regional climate, modulating inland extremes in temperature and enhancing precipitation. Representing these effects becomes more important as regional climate modeling (RCM) efforts focus on simulating smaller scales. When using the Weathe...

Finding "Models" in Clouds

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

Leung, Ruby

2017-05-01

Internationally recognized Climate Scientist Ruby Leung is a cloud gazer. But rather than looking for shapes, Ruby’s life’s calling is to develop regional atmospheric models to better predict and understand the effects of global climate change at scales relevant to humans and the environment. Ruby’s accomplishments include developing novel methods for modeling mountain clouds and precipitation in climate models, and improving understanding of hydroclimate variability and change. She also has led efforts to develop regional climate modeling capabilities in the Weather Research and Forecasting model that is widely adopted by scientists worldwide. Ruby is part of a team of PNNLmore » researchers studying the impacts of global warming.« less

Japanese and Taiwanese pelagic longline fleet dynamics and the impacts of climate change in the southern Indian Ocean

NASA Astrophysics Data System (ADS)

Michael, P. E.; Wilcox, C.; Tuck, G. N.; Hobday, A. J.; Strutton, P. G.

2017-06-01

Climate change is projected to continue shifting the distribution of marine species, leading to changes in local assemblages and different interactions with human activities. With regard to fisheries, understanding the relationship between fishing fleets, target species catch per unit effort (CPUE), and the environment enhances our ability to anticipate fisher response and is an essential step towards proactive management. Here, we explore the potential impact of climate change in the southern Indian Ocean by modelling Japanese and Taiwanese pelagic longline fleet dynamics. We quantify the mean and variability of target species CPUE and the relative value and cost of fishing in different areas. Using linear mixed models, we identify fleet-specific effort allocation strategies most related to observed effort and predict the future distribution of effort and tuna catch under climate change for 2063-2068. The Japanese fleet's strategy targets high-value species and minimizes the variability in CPUE of the primary target species. Conversely, the Taiwanese strategy indicated flexible targeting of a broad range of species, fishing in areas of high and low variability in catch, and minimizing costs. The projected future mean and variability in CPUE across species suggest a slight increase in CPUE in currently high CPUE areas for most species. The corresponding effort projections suggest a slight increase in Japanese effort in the western and eastern study area, and Taiwanese effort increasing east of Madagascar. This approach provides a useful method for managers to explore the impacts of different fishing and fleet management strategies for the future.

A coupled physical and economic model of the response of coastal real estate to climate risk

NASA Astrophysics Data System (ADS)

McNamara, Dylan E.; Keeler, Andrew

2013-06-01

Barring an unprecedented large-scale effort to raise island elevation, barrier-island communities common along the US East Coast are likely to eventually face inundation of the existing built environment on a timescale that depends on uncertain climatic forcing. Between the present and when a combination of sea-level rise and erosion renders these areas uninhabitable, communities must choose levels of defensive expenditures to reduce risks and individual residents must assess whether and when risk levels are unacceptably high to justify investment in housing. We model the dynamics of coastal adaptation as the interplay of underlying climatic risks, collective actions to mitigate those risks, and individual risk assessments based on beliefs in model predictions and processing of past climate events. Efforts linking physical and behavioural models to explore shoreline dynamics have not yet brought together this set of essential factors. We couple a barrier-island model with an agent-based model of real-estate markets to show that, relative to people with low belief in model predictions about climate change, informed property owners invest heavily in defensive expenditures in the near term and then abandon coastal real estate at some critical risk threshold that presages a period of significant price volatility.

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

NASA Technical Reports Server (NTRS)

Kirtman, Ben P.; Min, Dughong; Infanti, Johnna M.; Kinter, James L., III; Paolino, Daniel A.; Zhang, Qin; vandenDool, Huug; Saha, Suranjana; Mendez, Malaquias Pena; Becker, Emily;

Development of climate data input files for the Mechanistic-Empirical Pavement Design Guide (MEPDG).

DOT National Transportation Integrated Search

2011-06-30

Prior to this effort, Mississippi's MEPDG climate files were limited to 12 weather stations in only 10 countries and only seven weather stations had over 8 years (100 months)of data. Hence, building MEPDG climate input datasets improves modeling accu...

Predicting forest attributes from climate data using a recursive partitioning and regression tree algorithm

Treesearch

Greg C. Liknes; Christopher W. Woodall; Charles H. Perry

2009-01-01

Climate information frequently is included in geospatial modeling efforts to improve the predictive capability of other data sources. The selection of an appropriate climate data source requires consideration given the number of choices available. With regard to climate data, there are a variety of parameters (e.g., temperature, humidity, precipitation), time intervals...

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Integrating Climate Projections into Multi-Level City Planning: A Texas Case Study

NASA Astrophysics Data System (ADS)

Hayhoe, K.; Gelca, R.; Baumer, Z.; Gold, G.

2016-12-01

Climate change impacts on energy and water are a serious concern for many cities across the United States. Regional projections from the National Assessment process, or state-specific efforts as in California and Delaware, are typically used to quantify impacts at the regional scale. However, these are often insufficient to provide information at the scale of decision-making for an individual city. Here, we describe a multi-level approach to developing and integrating usable climate information into planning, using a case study from the City of Austin in Texas, a state where few official climate resources are available. Spearheaded by the Office of Sustainability in collaboration with Austin Water, the first step was to characterize observed trends and future projections of how global climate change might affect Austin's current climate. The City then assembled a team of city experts, consulting engineers, and climate scientists to develop a methodology to assess impacts on regional hydrology as part of its Integrated Water Resource Plan, Austin's 100-year water supply and demand planning effort, an effort which included calculating a range of climate indicators and developing and evaluating a new approach to generating climate inputs - including daily streamflow and evaporation - for existing water availability models. This approach, which brings together a range of public, private, and academic experts to support a stakeholder-initiated planning effort, provides concrete insights into the critical importance of multi-level, long-term engagement for development and application of actionable climate science at the local to regional scale.

The Great Plains low-level jet in 1.5C and 2C HAPPI simulations: Implications for changes in extreme climate events

NASA Astrophysics Data System (ADS)

Weaver, S. J.; Barcikowska, M. J.

2017-12-01

Global temperature targets have become the cornerstone for global climate policy discussions. Given the goal of the Paris Accord to limit the rise in global mean temperature to well below 2.0oC above pre-industrial levels, and pursue efforts toward the more ambitious 1.5oC goal, there is increasing focus in the climate science community on what the relative changes in regional climate extremes may be for these two scenarios. Despite the successes of major climate science modeling efforts, there is still a significant information gap regarding the regional and seasonal changes in some climate extremes over the U.S. as a function of these global mean temperature targets.During the spring and summer, large amounts of heat and moisture are transported northward into the central and eastern U.S. by the Great Plains Low-Level Jet (GPLLJ) - an atmospheric river which dominates the subcontinental scale climate variability during the warm half of the year. Accordingly, the GPLLJ and its vast spatiotemporal variability is highly influential over several types of extreme climate anomalies east of the Rocky Mountains, including, drought and pluvial events, tornadic activity, and the evolution of central U.S warming hole. Changes in the GPLLJ and its variability are probed from the perspective of several hundred climate realizations afforded by the availability of climate model experiments from the Half a degree additional warming, Prognosis, and Projected Impacts (HAPPI) effort - a suite of multi-model ensemble AMIP simulations forced by 1.5oC and 2oC levels of global warming. The multimodel analysis focuses on the variable magnitude of the seasonal changes in the mean GPLLJ and shifts in the extremes of the prominent modes of GPLLJ variability - both of which have implications for the future shifts in extreme climate events over the Great Plains, Midwest, and southeast regions of the U.S.

Misleading prioritizations from modelling range shifts under climate change

Treesearch

Helen R. Sofaer; Catherine S. Jarnevich; Curtis H. Flather

2018-01-01

Conservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated...

Collaborative Project: The problem of bias in defining uncertainty in computationally enabled strategies for data-driven climate model development. Final Technical Report.

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

Huerta, Gabriel

The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projectionsmore » of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta at the University of New Mexico is responsible for developing statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. This report reflects the main activities at the University of New Mexico where the PI (Huerta) and the Postdocs (Nosedal, Hattab and Karki) worked on the project.« less

Redesigning mental healthcare delivery: is there an effect on organizational climate?

PubMed

Joosten, T C M; Bongers, I M B; Janssen, R T J M

2014-02-01

Many studies have investigated the effect of redesign on operational performance; fewer studies have evaluated the effects on employees' perceptions of their working environment (organizational climate). Some authors state that redesign will lead to poorer organizational climate, while others state the opposite. The goal of this study was to empirically investigate this relation. Organizational climate was measured in a field experiment, before and after a redesign intervention. At one of the sites, a redesign project was conducted. At the other site, no redesign efforts took place. Two Dutch child- and adolescent-mental healthcare providers. Professionals that worked at one of the units at the start and/or the end of the intervention period. The main intervention was a redesign project aimed at improving timely delivery of services (modeled after the breakthrough series). Scores on the four models of the organizational climate measure, a validated questionnaire that measures organizational climate. Our analysis showed that climate at the intervention site changed on factors related to productivity and goal achievement (rational goal model). The intervention group scored worse than the comparison group on the part of the questionnaire that focuses on sociotechnical elements of organizational climate. However, observed differences were so small, that their practical relevance seems rather limited. Redesign efforts in healthcare, so it seems, do not influence organizational climate as much as expected.

ARM-Led Improvements Aerosols in Climate and Climate Models

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

Ghan, Steven J.; Penner, Joyce E.

2016-07-25

The DOE ARM program has played a foundational role in efforts to quantify aerosol effects on climate, beginning with the early back-of-the-envelope estimates of direct radiative forcing by anthropogenic sulfate and biomass burning aerosol (Penner et al., 1994). In this chapter we review the role that ARM has played in subsequent detailed estimates based on physically-based representations of aerosols in climate models. The focus is on quantifying the direct and indirect effects of anthropogenic aerosol on the planetary energy balance. Only recently have other DOE programs applied the aerosol modeling capability to simulate the climate response to the radiative forcing.

Managing Climate Change Refugia for Biodiversity ...

EPA Pesticide Factsheets

Climate change threatens to create fundamental shifts in in the distributions and abundances of species. Given projected losses, increased emphasis on management for ecosystem resilience to help buffer fish and wildlife populations against climate change is emerging. Such efforts stake a claim for an adaptive, anticipatory planning response to the climate change threat. To be effective, approaches will need to address critical uncertainties in both the physical basis for projected landscape changes, as well as the biological responses of organisms. Recent efforts define future potential climate refugia based on air temperatures and associated microclimatic changes. These efforts reflect the relatively strong conceptual foundation for linkages between regional climate change and local responses and thermal dynamics. Yet important questions remain. Drawing on case studies, we illustrate some key uncertainties in the responses of species and their habitats to altered hydro-climatic regimes currently not well addressed by physical or ecological models. These uncertainties need not delay anticipatory planning, but rather highlight the need for identification and communication of actions with high probabilities of success, and targeted research within an adaptive management framework.In this workshop, we will showcase the latest science on climate refugia and participants will interact through small group discussions, relevant examples, and facilitated dialogue to i

Climate Change Modeling Needs and Efforts for Hydroelectric System Operations in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Pytlak, E.

2014-12-01

This presentation will outline ongoing, multi-year hydroclimate change research between the Columbia River Management Joint Operating Committee (RMJOC), The University of Washington, Portland State University, and their many regional research partners and stakeholders. Climate change in the Columbia River Basin is of particular concern to the Bonneville Power Administration (BPA) and many Federal, Tribal and regional stakeholders. BPA, the U.S. Army Corp of Engineers, and U.S. Bureau of Reclamation, which comprise the RMJOC, conducted an extensive study in 2009-11 using climate change streamflows produced by the University of Washington Climate Impacts Group (CIG). The study reconfirmed that as more winter precipitation in the Columbia Basin falls as rain rather than snow by mid-century, particularly on the U.S. portion of the basin, increased winter runoff is likely, followed by an earlier spring snowmelt peak, followed by less summer flows as seasonal snowmelt diminished earlier in the water year. Since that initial effort, both global and regional climate change modeling has advanced. To take advantage of the new outputs from the Fifth Coupled Model Intercomparison Project (CMIP-5), the RMJOC, through BPA support, is sponsoring new hydroclimate research which considers not only the most recent information from the GCMs, but also the uncertainties introduced by the hydroclimate modeling process itself. Historical streamflows, which are used to calibrate hydrologic models and ascertain their reliability, are subject to both measurement and modeling uncertainties. Downscaling GCMs to a hydrologically useful spatial and temporal resolution introduces uncertainty, depending on the downscaling methods. Hydrologic modeling introduces uncertainties from calibration and geophysical states, some of which, like land surface characteristics, are likely to also change with time. In the upper Columbia Basin, glacier processes introduce yet another source of uncertainty. The latest joint effort attempts to ascertain the relative contributions of these uncertainties in comparison to the uncertainties brought by changing climate itself.

Consistency and Main Differences Between European Regional Climate Downscaling Intercomparison Results; From PRUDENCE and ENSEMBLES to CORDEX

NASA Astrophysics Data System (ADS)

Christensen, J. H.; Larsen, M. A. D.; Christensen, O. B.; Drews, M.

2017-12-01

For more than 20 years, coordinated efforts to apply regional climate models to downscale GCM simulations for Europe have been pursued by an ever increasing group of scientists. This endeavor showed its first results during EU framework supported projects such as RACCS and MERCURE. Here, the foundation for today's advanced worldwide CORDEX approach was laid out by a core of six research teams, who conducted some of the first coordinated RCM simulations with the aim to assess regional climate change for Europe. However, it was realized at this stage that model bias in GCMs as well as RCMs made this task very challenging. As an immediate outcome, the idea was conceived to make an even more coordinated effort by constructing a well-defined and structured set of common simulations; this lead to the PRUDENCE project (2001-2004). Additional coordinated efforts involving ever increasing numbers of GCMs and RCMs followed in ENSEMBLES (2004-2009) and the ongoing Euro-CORDEX (officially commenced 2011) efforts. Along with the overall coordination, simulations have increased their standard resolution from 50km (PRUDENCE) to about 12km (Euro-CORDEX) and from time slice simulations (PRUDENCE) to transient experiments (ENSEMBLES and CORDEX); from one driving model and emission scenario (PRUDENCE) to several (Euro-CORDEX). So far, this wealth of simulations have been used to assess the potential impacts of future climate change in Europe providing a baseline change as defined by a multi-model mean change with associated uncertainties calculated from model spread in the ensemble. But how has the overall picture of state-of-the-art regional climate change projections changed over this period of almost two decades? Here we compare across scenarios, model resolutions and model vintage the results from PRUDENCE, ENSEMBLES and Euro-CORDEX. By appropriate scaling we identify robust findings about the projected future of European climate expressed by temperature and precipitation changes that confirm the basic findings of PRUDENCE. For parameters such as snow cover and soil moisture availability we also identify major new results, which illustrate that model improvements and higher resolution offer new, physically grounded, robust information that could not have been identified twenty years ago with the approach taken at that time

Insights from Modeling the Integrated Climate, Biogeochemical Cycles, Human Activities and Their Interactions in the ACME Earth System Model

NASA Astrophysics Data System (ADS)

Leung, L. R.; Thornton, P. E.; Riley, W. J.; Calvin, K. V.

2017-12-01

Towards the goal of understanding the contributions from natural and managed systems to current and future greenhouse gas fluxes and carbon-climate and carbon-CO2 feedbacks, efforts have been underway to improve representations of the terrestrial, river, and human components of the ACME earth system model. Broadly, our efforts include implementation and comparison of approaches to represent the nutrient cycles and nutrient limitations on ecosystem production, extending the river transport model to represent sediment and riverine biogeochemistry, and coupling of human systems such as irrigation, reservoir operations, and energy and land use with the ACME land and river components. Numerical experiments have been designed to understand how terrestrial carbon, nitrogen, and phosphorus cycles regulate climate system feedbacks and the sensitivity of the feedbacks to different model treatments, examine key processes governing sediment and biogeochemistry in the rivers and their role in the carbon cycle, and exploring the impacts of human systems in perturbing the hydrological and carbon cycles and their interactions. This presentation will briefly introduce the ACME modeling approaches and discuss preliminary results and insights from numerical experiments that lay the foundation for improving understanding of the integrated climate-biogeochemistry-human system.

School Climate and Bullying Victimization: A Latent Class Growth Model Analysis

ERIC Educational Resources Information Center

Gage, Nicholas A.; Prykanowski, Debra A.; Larson, Alvin

2014-01-01

Researchers investigating school-level approaches for bullying prevention are beginning to discuss and target school climate as a construct that (a) may predict prevalence and (b) be an avenue for school-wide intervention efforts (i.e., increasing positive school climate). Although promising, research has not fully examined and established the…

The Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections

NASA Technical Reports Server (NTRS)

Barsugli, Joseph J.; Guentchev, Galina; Horton, Radley M.; Wood, Andrew; Mearns, Lindo O.; Liang, Xin-Zhong; Winkler, Julia A.; Dixon, Keith; Hayhoe, Katharine; Rood, Richard B.;

Practical (?) considerations for implementing assisted migration strategies for trees in North America

NASA Astrophysics Data System (ADS)

McKenney, D.; Pedlar, J.

2011-12-01

Climate is one of the major influences on forests and much effort has gone into projecting the impacts of rapid climate change on forest distribution and productivity. Such efforts are premised on the notion that the current generation of Global Climate Models (GCMs) provide reasonably accurate representations of future climate. But what is the appropriate level of faith to put in these projections when making relatively fine-scale resource management decisions such as the movement of plant genetic material? In this talk we review recent outcomes of climate envelope models for North American tree species that suggest optimal climate regimes could move on average ~700km within the next 100 years. Newer generation GCMs seem to confirm these results but much uncertainty remains for practical decision-making. Despite these uncertainties, assisted migration has been suggested as a climate change adaptation tool wherein populations of trees are moved up to a few hundred kilometers north (or a few hundred meters upslope) to keep pace with the anticipated changes in optimal climate regimes. A continent-wide web based tool (SEEDWHERE) is presented, which assists in identifying appropriate translocation distances for assisted migration initiatives. We finish with some suggestions for future work on the topic of forest regeneration decisions under an evolving and uncertain future climate.

Overview of the United States Department of Energy's ARM (Atmospheric Radiation Measurement) Program

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

Stokes, G.M.; Tichler, J.L.

The Department of Energy (DOE) is initiating a major atmospheric research effort, the Atmospheric Radiation Measurement Program (ARM). The program is a key component of DOE's research strategy to address global climate change and is a direct continuation of DOE's decade-long effort to improve the ability of General Circulation Models (GCMs) to provide reliable simulations of regional, and long-term climate change in response to increasing greenhouse gases. The effort is multi-disciplinary and multi-agency, involving universities, private research organizations and more than a dozen government laboratories. The objective of the ARM Research is to provide an experimental testbed for the studymore » of important atmospheric effects, particularly cloud and radiative processes, and to test parameterizations of these processes for use in atmospheric models. This effort will support the continued and rapid improvement of GCM predictive capability. 2 refs.« less

The Nested Regional Climate Model: An Approach Toward Prediction Across Scales

NASA Astrophysics Data System (ADS)

Hurrell, J. W.; Holland, G. J.; Large, W. G.

2008-12-01

The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is producing unique data sets of climate change scenarios of immense interest. In addition, all simulations are archived in a form that will be readily accessible to other researchers, thus enabling a wider group to investigate these important issues.

Check-Up of Planet Earth at the Turn of the Millennium: Anticipated New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Ramanathan, V.

1998-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite (EOS-AM) will repeat Langley's experiment, but for the entire planet, thus pioneering calibrated spectral observations from space. Conceived in response to real environmental problems, EOS-AM, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-AM can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment.

A Reusable Framework for Regional Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

2011-12-01

Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and utilizing large volumes of observational data for model evaluation research. We feel that the RCMES is particularly appealing in that it represents a principled, reusable architectural approach rather than a one-off technological implementation. In fact, early RCMES prototypes have already utilized a variety of implementation technologies in an effort to address different performance and scalability concerns. This has been greatly facilitated by the fact that, at the architectural level, the RCMES is fundamentally domain agnostic. Strictly separating the data model from the implementation has enabled us to create a reusable architecture that we believe can be modified and configured to suit the demands of researchers in other domains.

Transforming data into usable knowledge: the CIRC experience

NASA Astrophysics Data System (ADS)

Mote, P.; Lach, D.; Hartmann, H.; Abatzoglou, J. T.; Stevenson, J.

2017-12-01

NOAA's northwest RISA, the Climate Impacts Research Consortium, emphasizes the transformation of data into usable knowledge. This effort involves physical scientists (e.g., Abatzoglou) building web-based tools with climate and hydrologic data and model output, a team performing data mining to link crop loss claims to droughts, social scientists (eg., Lach, Hartmann) evaluating the effectiveness of such tools at communicating with end users, and two-way engagement with a wide variety of audiences who are interested in using and improving the tools. Unusual in this effort is the seamless integration across timescales past, present, and future; data mining; and the level of effort in evaluating the tools. We provide examples of agriculturally relevant climate variables (e.g. growing degree days, day of first fall freeze) and describe the iterative process of incorporating user feedback.

Pathogen-Host Associations and Predicted Range Shifts of Human Monkeypox in Response to Climate Change in Central Africa

PubMed Central

Thomassen, Henri A.; Fuller, Trevon; Asefi-Najafabady, Salvi; Shiplacoff, Julia A. G.; Mulembakani, Prime M.; Blumberg, Seth; Johnston, Sara C.; Kisalu, Neville K.; Kinkela, Timothée L.; Fair, Joseph N.; Wolfe, Nathan D.; Shongo, Robert L.; LeBreton, Matthew; Meyer, Hermann; Wright, Linda L.; Muyembe, Jean-Jacques; Buermann, Wolfgang; Okitolonda, Emile; Hensley, Lisa E.; Lloyd-Smith, James O.; Smith, Thomas B.; Rimoin, Anne W.

2013-01-01

Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts. PMID:23935820

Piloting Utility Modeling Applications (PUMA): Planning for Climate Change at the Portland Water Bureau

NASA Astrophysics Data System (ADS)

Heyn, K.; Campbell, E.

2016-12-01

The Portland Water Bureau has been studying the anticipated effects of climate change on its primary surface water source, the Bull Run Watershed, since the early 2000's. Early efforts by the bureau were almost exclusively reliant on outside expertise from climate modelers and researchers, particularly those at the Climate Impacts Group (CIG) at the University of Washington. Early work products from CIG formed the basis of the bureau's understanding of the most likely and consequential impacts to the watershed from continued GHG-caused warming. However, by mid-decade, as key supply and demand conditions for the bureau changed, it found it lacked the technical capacity and tools to conduct more refined and updated research to build on the outside analysis it had obtained. Beginning in 2010 through its participation in the Pilot Utility Modeling Applications (PUMA) project, the bureau identified and began working to address the holes in its technical and institutional capacity by embarking on a process to assess and select a hydrologic model while obtaining downscaled climate change data to utilize within it. Parallel to the development of these technical elements, the bureau made investments in qualified staff to lead the model selection, development and utilization, while working to establish productive, collegial and collaborative relationships with key climate research staff at the Oregon Climate Change Research Institute (OCCRI), the University of Washington and the University of Idaho. This presentation describes the learning process of a major metropolitan area drinking water utility as its approach to addressing the complex problem of climate change evolves, matures, and begins to influence broader aspects of the organization's planning efforts.

Past, Present and Future: Urgency of Dealing with Climate Change

EPA Science Inventory

This paper gives an historic perspective on 10 critical phases and actions in advancing an understanding of climate change and taking appropriate domestic and international action. Credit goes to atmospheric scientists for their committed efforts to understand, model and measure ...

Spread in the magnitude of climate model interdecadal global temperature variability traced to disagreements over high-latitude oceans

NASA Astrophysics Data System (ADS)

Brown, Patrick T.; Li, Wenhong; Jiang, Jonathan H.; Su, Hui

2016-12-01

Unforced variability in global mean surface air temperature can obscure or exaggerate global warming on interdecadal time scales; thus, understanding both the magnitude and generating mechanisms of such variability is of critical importance for both attribution studies as well as decadal climate prediction. Coupled atmosphere-ocean general circulation models (climate models) simulate a wide range of magnitudes of unforced interdecadal variability in global mean surface air temperature (UITglobal), hampering efforts to quantify the influence of UITglobal on contemporary global temperature trends. Recently, a preliminary consensus has emerged that unforced interdecadal variability in local surface temperatures (UITlocal) over the tropical Pacific Ocean is particularly influential on UITglobal. Therefore, a reasonable hypothesis might be that the large spread in the magnitude of UITglobal across climate models can be explained by the spread in the magnitude of simulated tropical Pacific UITlocal. Here we show that this hypothesis is mostly false. Instead, the spread in the magnitude of UITglobal is linked much more strongly to the spread in the magnitude of UITlocal over high-latitude regions characterized by significant variability in oceanic convection, sea ice concentration, and energy flux at both the surface and the top of the atmosphere. Thus, efforts to constrain the climate model produced range of UITglobal magnitude would be best served by focusing on the simulation of air-sea interaction at high latitudes.

The Earth System Model

NASA Technical Reports Server (NTRS)

Schoeberl, Mark; Rood, Richard B.; Hildebrand, Peter; Raymond, Carol

2003-01-01

The Earth System Model is the natural evolution of current climate models and will be the ultimate embodiment of our geophysical understanding of the planet. These models are constructed from components - atmosphere, ocean, ice, land, chemistry, solid earth, etc. models and merged together through a coupling program which is responsible for the exchange of data from the components. Climate models and future earth system models will have standardized modules, and these standards are now being developed by the ESMF project funded by NASA. The Earth System Model will have a variety of uses beyond climate prediction. The model can be used to build climate data records making it the core of an assimilation system, and it can be used in OSSE experiments to evaluate. The computing and storage requirements for the ESM appear to be daunting. However, the Japanese ES theoretical computing capability is already within 20% of the minimum requirements needed for some 2010 climate model applications. Thus it seems very possible that a focused effort to build an Earth System Model will achieve succcss.

Weather Forecaster Understanding of Climate Models

NASA Astrophysics Data System (ADS)

Bol, A.; Kiehl, J. T.; Abshire, W. E.

2013-12-01

Weather forecasters, particularly those in broadcasting, are the primary conduit to the public for information on climate and climate change. However, many weather forecasters remain skeptical of model-based climate projections. To address this issue, The COMET Program developed an hour-long online lesson of how climate models work, targeting an audience of weather forecasters. The module draws on forecasters' pre-existing knowledge of weather, climate, and numerical weather prediction (NWP) models. In order to measure learning outcomes, quizzes were given before and after the lesson. Preliminary results show large learning gains. For all people that took both pre and post-tests (n=238), scores improved from 48% to 80%. Similar pre/post improvement occurred for National Weather Service employees (51% to 87%, n=22 ) and college faculty (50% to 90%, n=7). We believe these results indicate a fundamental misunderstanding among many weather forecasters of (1) the difference between weather and climate models, (2) how researchers use climate models, and (3) how they interpret model results. The quiz results indicate that efforts to educate the public about climate change need to include weather forecasters, a vital link between the research community and the general public.

Modeled effects of climate change and plant invasion on watershed function across a steep tropical rainfall gradient

Treesearch

Ayron M. Strauch; Christian P. Giardina; Richard A. MacKenzie; Chris Heider; Tom W. Giambelluca; Ed Salminen; Gregory L. Bruland

2017-01-01

Climate change is anticipated to affect freshwater resources, but baseline data on the functioning of tropical watersheds is lacking, limiting efforts that seek to predict how watershed processes, water supply, and streamflow respond to anticipated changes in climate and vegetation change, and to management. To address this data gap, we applied the distributed...

Toward Collective Impact for Climate Resilience: Maximizing Climate Change Education for Preparedness, Adaptation, and Mitigation

NASA Astrophysics Data System (ADS)

Ledley, T. S.; Niepold, F., III; McCaffrey, M.

2014-12-01

Increasing the capacity of society to make informed climate decisions based on scientific evidence is imperative. While a wide range of education programs and communication efforts to improve understanding and facilitate responsible effective decision-making have been developed in recent years, these efforts have been largely disconnected. The interdisciplinary and trans-disciplinary nature of the problems and potential responses to climate change requires a broad range of expertise and a strategy that overcomes the inherent limitations of isolated programs and efforts. To extend the reach and impact of climate change education and engagement efforts, it is necessary to have a coordination that results in greater collective impact. The Collective Impact model, as described by Kania & Kramer (2011), requires five elements: 1) a common agenda; 2) shared measurement systems; 3) mutually reinforcing activities; 4) continuous communication; and 5) a well-funded backbone support organization. The CLEAN Network has facilitated a series of discussions at six professional meetings from late 2012 through spring 2014 to begin to develop and define the elements of collective impact on climate change education and engagement. These discussions have focused on getting input from the community on a common agenda and what a backbone support organization could do to help extend their reach and impact and enable a longer-term sustainability. These discussions will continue at future meetings, with the focus shifting to developing a common agenda and shared metrics. In this presentation we will summarize the outcomes of these discussions thus far, especially with respect to what activities a backbone support organization might provide to help increase the collective impact of climate change education effort and invite others to join the development of public-private partnership to improve the nations climate literacy. The cumulative input into this evolving discussion on collective impact on climate literacy can be viewed at http://tinyurl.com/mgwndtr.

Development of a ground hydrology model suitable for global climate modeling using soil morphology and vegetation cover, and an evaluation of remotely sensed information

NASA Technical Reports Server (NTRS)

Zobler, L.; Lewis, R.

1988-01-01

The long-term purpose was to contribute to scientific understanding of the role of the planet's land surfaces in modulating the flows of energy and matter which influence the climate, and to quantify and monitor human-induced changes to the land environment that may affect global climate. Highlights of the effort include the following: production of geo-coded, digitized World Soil Data file for use with the Goddard Institute for Space Studies (GISS) climate model; contribution to the development of a numerical physically-based model of ground hydrology; and assessment of the utility of remote sensing for providing data on hydrologically significant land surface variables.

Community-based benchmarking of the CMIP DECK experiments

NASA Astrophysics Data System (ADS)

Gleckler, P. J.

2015-12-01

A diversity of community-based efforts are independently developing "diagnostic packages" with little or no coordination between them. A short list of examples include NCAR's Climate Variability Diagnostics Package (CVDP), ORNL's International Land Model Benchmarking (ILAMB), LBNL's Toolkit for Extreme Climate Analysis (TECA), PCMDI's Metrics Package (PMP), the EU EMBRACE ESMValTool, the WGNE MJO diagnostics package, and CFMIP diagnostics. The full value of these efforts cannot be realized without some coordination. As a first step, a WCRP effort has initiated a catalog to document candidate packages that could potentially be applied in a "repeat-use" fashion to all simulations contributed to the CMIP DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. Some coordination of community-based diagnostics has the additional potential to improve how CMIP modeling groups analyze their simulations during model-development. The fact that most modeling groups now maintain a "CMIP compliant" data stream means that in principal without much effort they could readily adopt a set of well organized diagnostic capabilities specifically designed to operate on CMIP DECK experiments. Ultimately, a detailed listing of and access to analysis codes that are demonstrated to work "out of the box" with CMIP data could enable model developers (and others) to select those codes they wish to implement in-house, potentially enabling more systematic evaluation during the model development process.

The Program for climate Model diagnosis and Intercomparison: 20-th anniversary Symposium

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

Potter, Gerald L; Bader, David C; Riches, Michael

Twenty years ago, W. Lawrence (Larry) Gates approached the U.S. Department of Energy (DOE) Office of Energy Research (now the Office of Science) with a plan to coordinate the comparison and documentation of climate model differences. This effort would help improve our understanding of climate change through a systematic approach to model intercomparison. Early attempts at comparing results showed a surprisingly large range in control climate from such parameters as cloud cover, precipitation, and even atmospheric temperature. The DOE agreed to fund the effort at the Lawrence Livermore National Laboratory (LLNL), in part because of the existing computing environment andmore » because of a preexisting atmospheric science group that contained a wide variety of expertise. The project was named the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and it has changed the international landscape of climate modeling over the past 20 years. In spring 2009 the DOE hosted a 1-day symposium to celebrate the twentieth anniversary of PCMDI and to honor its founder, Larry Gates. Through their personal experiences, the morning presenters painted an image of climate science in the 1970s and 1980s, that generated early support from the international community for model intercomparison, thereby bringing PCMDI into existence. Four talks covered Gates's early contributions to climate research at the University of California, Los Angeles (UCLA), the RAND Corporation, and Oregon State University through the founding of PCMDI to coordinate the Atmospheric Model Intercomparison Project (AMIP). The speakers were, in order of presentation, Warren Washington [National Center for Atmospheric Research (NCAR)], Kelly Redmond (Western Regional Climate Center), George Boer (Canadian Centre for Climate Modelling and Analysis), and Lennart Bengtsson [University of Reading, former director of the European Centre for Medium-Range Weather Forecasts (ECMWF)]. The afternoon session emphasized the scientific ideas that are the basis of PCMDI's success, summarizing their evolution and impact. Four speakers followed the various PCMDI-supported climate model intercomparison projects, beginning with early work on cloud representations in models, presented by Robert D. Cess (Distinguished Professor Emeritus, Stony Brook University), and then the latest Cloud Feedback Model Intercomparison Projects (CFMIPs) led by Sandrine Bony (Laboratoire de M'©t'©orologie Dynamique). Benjamin Santer (LLNL) presented a review of the climate change detection and attribution (D & A) work pioneered at PCMDI, and Gerald A. Meehl (NCAR) ended the day with a look toward the future of climate change research.« less

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Prerequisites for understanding climate-change impacts on northern prairie wetlands

USGS Publications Warehouse

Anteau, Michael J.; Wiltermuth, Mark T.; Post van der Burg, Max; Pearse, Aaron T.

2016-01-01

The Prairie Pothole Region (PPR) contains ecosystems that are typified by an extensive matrix of grasslands and depressional wetlands, which provide numerous ecosystem services. Over the past 150 years the PPR has experienced numerous landscape modifications resulting in agricultural conversion of 75–99 % of native prairie uplands and drainage of 50–90 % of wetlands. There is concern over how and where conservation dollars should be spent within the PPR to protect and restore wetland basins to support waterbird populations that will be robust to a changing climate. However, while hydrological impacts of landscape modifications appear substantial, they are still poorly understood. Previous modeling efforts addressing impacts of climate change on PPR wetlands have yet to fully incorporate interacting or potentially overshadowing impacts of landscape modification. We outlined several information needs for building more informative models to predict climate change effects on PPR wetlands. We reviewed how landscape modification influences wetland hydrology and present a conceptual model to describe how modified wetlands might respond to climate variability. We note that current climate projections do not incorporate cyclical variability in climate between wet and dry periods even though such dynamics have shaped the hydrology and ecology of PPR wetlands. We conclude that there are at least three prerequisite steps to making meaningful predictions about effects of climate change on PPR wetlands. Those evident to us are: 1) an understanding of how physical and watershed characteristics of wetland basins of similar hydroperiods vary across temperature and moisture gradients; 2) a mechanistic understanding of how wetlands respond to climate across a gradient of anthropogenic modifications; and 3) improved climate projections for the PPR that can meaningfully represent potential changes in climate variability including intensity and duration of wet and dry periods. Once these issues are addressed, we contend that modeling efforts will better inform and quantify ecosystem services provided by wetlands to meet needs of waterbird conservation and broader societal interests such as flood control and water quality.

Modeling high resolution space-time variations in energy demand/CO2 emissions of human inhabited landscapes in the United States under a changing climate

NASA Astrophysics Data System (ADS)

Godbole, A. V.; Gurney, K. R.

2010-12-01

With urban and exurban areas now accounting for more than 50% of the world's population, projected to increase 20% by 2050 (UN World Urbanization Prospects, 2009), urban-climate interactions are of renewed interest to the climate change scientific community (Karl et. al, 1988; Kalnay and Cai, 2003; Seto and Shepherd, 2009). Until recently, climate modeling efforts treated urban-human systems as independent of the earth system. With studies pointing to the disproportionately large influence of urban areas on their surrounding environment (Small et. al, 2010), modeling efforts have begun to explicitly account for urban processes in land models, like the CLM 4.0 urban layer, for example (Oleson.et. al, 2008, 2010). A significant portion of the urban energy demand comes from the space heating and cooling requirement of the residential and commercial sectors - as much as 51% (DOE, RECS 2005) and 11% (Belzer, D. 2006) respectively, in the United States. Thus, these sectors are both responsible for a significant fraction of fossil fuel CO2 emissions and will be influenced by a changing climate through changes in energy use and energy supply planning. This points to the possibility of interactive processes and feedbacks with the climate system. Space conditioning energy demand is strongly driven by external air temperature (Ruth, M. et.al, 2006) in addition to other socio-economic variables such as building characteristics (age of structure, activity cycle, weekend/weekday usage profile), occupant characteristics (age of householder, household income) and energy prices (Huang, 2006; Santin et. al, 2009; Isaac and van Vuuren, 2009). All of these variables vary both in space and time. Projections of climate change have begun to simulate changes in temperature at much higher resolution than in the past (Diffenbaugh et. al, 2005). Hence, in order to understand how climate change and variability will potentially impact energy use/emissions and energy planning, these two components of the human-climate system must be coupled in climate modeling efforts to better understand the impacts and feedbacks. To implement modeling strategies for coupling the human and climate systems, their interactions must first be examined in greater detail at high spatial and temporal resolutions. This work attempts to quantify the impact of high resolution variations in projected climate change on energy use/emissions in the United States. We develop a predictive model for the space heating component of residential and commercial energy demand by leveraging results from the high resolution fossil fuel CO2 inventory of the Vulcan Project (Gurney et al., 2009). This predictive model is driven by high resolution temperature data from the RegCM3 model obtained by implementing a downscaling algorithm (Chow and Levermore, 2007). We will present the energy use/emissions in both the space and time domain from two different predictive models highlighting strengths and weaknesses in both. Furthermore, we will explore high frequency variations in the projected temperature field and how these might place potentially large burdens on energy supply and delivery.

Population response to climate change: linear vs. non-linear modeling approaches.

PubMed

Ellis, Alicia M; Post, Eric

2004-03-31

Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.

The Influence of the Green River Lake System on the Local Climate During the Early Eocene Period

NASA Astrophysics Data System (ADS)

Elguindi, N.; Thrasher, B.; Sloan, L. C.

2006-12-01

Several modeling efforts have attempted to reproduce the climate of the early Eocene North America. However when compared to proxy data, General Circulation Models (GCMs) tend to produce a large-scale cold-bias. Although higher resolution Regional Climate Models (RCMs) that are able to resolve many of the sub-GCM scale forcings improve this cold bias, RCMs are still unable to reproduce the warm climate of the Eocene. From geologic data, we know that the greater Green River and the Uinta basins were intermontane basins with a large lake system during portions of the Eocene. We speculate that the lack of presence of these lakes in previous modeling studies may explain part of the persistent cold-bias of GCMs and RCMs. In this study, we utilize a regional climate model coupled with a 1D-lake model in an attempt to reduce the uncertainties and biases associated with climate simulations over Eocene western North American. Specifically, we include the Green River Lake system in our RCM simulation and compare climates with and without lakes to proxy data.

Genomic signals of selection predict climate-driven population declines in a migratory bird.

PubMed

Bay, Rachael A; Harrigan, Ryan J; Underwood, Vinh Le; Gibbs, H Lisle; Smith, Thomas B; Ruegg, Kristen

2018-01-05

The ongoing loss of biodiversity caused by rapid climatic shifts requires accurate models for predicting species' responses. Despite evidence that evolutionary adaptation could mitigate climate change impacts, evolution is rarely integrated into predictive models. Integrating population genomics and environmental data, we identified genomic variation associated with climate across the breeding range of the migratory songbird, yellow warbler ( Setophaga petechia ). Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations. Broadly, our study suggests that the integration of genomic adaptation can increase the accuracy of future species distribution models and ultimately guide more effective mitigation efforts. Copyright © 2018, American Association for the Advancement of Science.

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

Southeast Atmosphere Studies: learning from model-observation syntheses

NASA Astrophysics Data System (ADS)

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu; McNeill, V. Faye; Tsigaridis, Kostas; McDonald, Brian C.; Warneke, Carsten; Guenther, Alex; Alvarado, Matthew J.; de Gouw, Joost; Mickley, Loretta J.; Leibensperger, Eric M.; Mathur, Rohit; Nolte, Christopher G.; Portmann, Robert W.; Unger, Nadine; Tosca, Mika; Horowitz, Larry W.

2018-02-01

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales.This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Southeast Atmosphere Studies: learning from model-observation syntheses

PubMed Central

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu; McNeill, V. Faye; Tsigaridis, Kostas; McDonald, Brian C.; Warneke, Carsten; Guenther, Alex; Alvarado, Matthew J.; de Gouw, Joost; Mickley, Loretta J.; Leibensperger, Eric M.; Mathur, Rohit; Nolte, Christopher G.; Portmann, Robert W.; Unger, Nadine; Tosca, Mika; Horowitz, Larry W.

2018-01-01

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Southeast Atmosphere Studies: Learning from Model-Observation Syntheses

NASA Technical Reports Server (NTRS)

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu;

Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor

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

Reed, Sasha C.; Yang, Xiaojuan; Thornton, Peter E.

2015-06-25

Myriad field, laboratory, and modeling studies show that nutrient availability plays a fundamental role in regulating CO 2 exchange between the Earth's biosphere and atmosphere, and in determining how carbon pools and fluxes respond to climatic change. Accordingly, global models that incorporate coupled climate-carbon cycle feedbacks made a significant advance with the introduction of a prognostic nitrogen cycle. Here we propose that incorporating phosphorus cycling represents an important next step in coupled climate-carbon cycling model development, particularly for lowland tropical forests where phosphorus availability is often presumed to limit primary production. We highlight challenges to including phosphorus in modeling effortsmore » and provide suggestions for how to move forward.« less

Systems View of School Climate: A Theoretical Framework for Research

ERIC Educational Resources Information Center

Rudasill, Kathleen Moritz; Snyder, Kate E.; Levinson, Heather; Adelson, Jill L.

2018-01-01

School climate has been widely examined through both empirical and theoretical means. However, there is little conceptual consensus underlying the landscape of this literature, offering inconsistent guidance for research examining this important construct. In order to best assist the efforts of developing causal models that describe how school…

Multi-profile analysis of soil moisture within the U.S. Climate Reference Network

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are crucial for hydrologic modeling and agricultural decision-support efforts. These measurements are also pivotal for long-term inquiries regarding the impacts of climate change and the resulting droughts over large spatial and temporal scales. However, it has only been t...

Energy, environment and climate assessment using the MARKAL energy system model

EPA Science Inventory

As part of EPA ORD’s efforts to develop an understanding of the potential environmental impacts of future changes in energy use, the Energy and Climate Assessment Team has developed a database representation of the U.S. energy system for use with the MARKet ALlocation (MARK...

Studies in the parameterization of cloudiness in climate models and the analysis of radiation fields in general circulation models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1990-01-01

Broad-band parameterizations for atmospheric radiative transfer were developed for clear and cloudy skies. These were in the shortwave and longwave regions of the spectrum. These models were compared with other models in an international effort called ICRCCM (Intercomparison of Radiation Codes for Climate Models). The radiation package developed was used for simulations of a General Circulation Model (GCM). A synopsis is provided of the research accomplishments in the two areas separately. Details are available in the published literature.

Toward a consistent modeling framework to assess multi-sectoral climate impacts.

PubMed

Monier, Erwan; Paltsev, Sergey; Sokolov, Andrei; Chen, Y-H Henry; Gao, Xiang; Ejaz, Qudsia; Couzo, Evan; Schlosser, C Adam; Dutkiewicz, Stephanie; Fant, Charles; Scott, Jeffery; Kicklighter, David; Morris, Jennifer; Jacoby, Henry; Prinn, Ronald; Haigh, Martin

2018-02-13

Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

Misleading prioritizations from modelling range shifts under climate change

USGS Publications Warehouse

Sofaer, Helen R.; Jarnevich, Catherine S.; Flather, Curtis H.

2018-01-01

AimConservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.LocationConterminous U.S.A.Time period1977–2014.Major taxa studiedPasserine birds.MethodsWe estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.ResultsSpecies distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.Main conclusionsModels failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and frameworks continue to be refined, performance assessments and validation efforts should focus on the measures of risk and vulnerability useful for decision-making.

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

PubMed

MacLeod, D A; Morse, A P

2014-12-02

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk

NASA Astrophysics Data System (ADS)

MacLeod, D. A.; Morse, A. P.

2014-12-01

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Representation of the Great Lakes in the Coupled Model Intercomparison Project Version 5

NASA Astrophysics Data System (ADS)

Briley, L.; Rood, R. B.

2017-12-01

The U.S. Great Lakes play a significant role in modifying regional temperatures and precipitation, and as the lakes change in response to a warming climate (i.e., warmer surface water temperatures, decreased ice cover, etc) lake-land-atmosphere dynamics are affected. Because the lakes modify regional weather and are a driver of regional climate change, understanding how they are represented in climate models is important to the reliability of model based information for the region. As part of the Great Lakes Integrated Sciences + Assessments (GLISA) Ensemble project, a major effort is underway to evaluate the Coupled Model Intercomparison Project version (CMIP) 5 global climate models for how well they physically represent the Great Lakes and lake-effects. The CMIP models were chosen because they are a primary source of information in many products developed for decision making (i.e., National Climate Assessment, downscaled future climate projections, etc.), yet there is very little description of how well they represent the lakes. This presentation will describe the results of our investigation of if and how the Great Lakes are represented in the CMIP5 models.

Climate vulnerability and resilience in the most valuable North American fishery.

PubMed

Le Bris, Arnault; Mills, Katherine E; Wahle, Richard A; Chen, Yong; Alexander, Michael A; Allyn, Andrew J; Schuetz, Justin G; Scott, James D; Pershing, Andrew J

2018-02-20

Managing natural resources in an era of increasing climate impacts requires accounting for the synergistic effects of climate, ecosystem changes, and harvesting on resource productivity. Coincident with recent exceptional warming of the northwest Atlantic Ocean and removal of large predatory fish, the American lobster has become the most valuable fishery resource in North America. Using a model that links ocean temperature, predator density, and fishing to population productivity, we show that harvester-driven conservation efforts to protect large lobsters prepared the Gulf of Maine lobster fishery to capitalize on favorable ecosystem conditions, resulting in the record-breaking landings recently observed in the region. In contrast, in the warmer southern New England region, the absence of similar conservation efforts precipitated warming-induced recruitment failure that led to the collapse of the fishery. Population projections under expected warming suggest that the American lobster fishery is vulnerable to future temperature increases, but continued efforts to preserve the stock's reproductive potential can dampen the negative impacts of warming. This study demonstrates that, even though global climate change is severely impacting marine ecosystems, widely adopted, proactive conservation measures can increase the resilience of commercial fisheries to climate change.

Understanding National Models for Climate Assessments

NASA Astrophysics Data System (ADS)

Dave, A.; Weingartner, K.

2017-12-01

National-level climate assessments have been produced or are underway in a number of countries. These efforts showcase a variety of approaches to mapping climate impacts onto human and natural systems, and involve a variety of development processes, organizational structures, and intended purposes. This presentation will provide a comparative overview of national `models' for climate assessments worldwide, drawing from a geographically diverse group of nations with varying capacities to conduct such assessments. Using an illustrative sampling of assessment models, the presentation will highlight the range of assessment mandates and requirements that drive this work, methodologies employed, focal areas, and the degree to which international dimensions are included for each nation's assessment. This not only allows the U.S. National Climate Assessment to be better understood within an international context, but provides the user with an entry point into other national climate assessments around the world, enabling a better understanding of the risks and vulnerabilities societies face.

Collaboration in Action: Working with Indigenous peoples and Tribal communities to navigate climate decision support organizations and programs to assist Tribal communities in addressing climate resilience and sustainability efforts

NASA Astrophysics Data System (ADS)

Caldwell, C. M.

2017-12-01

Creating opportunities and appropriate spaces with Tribal communities to engage with western scientists on climate resiliency is a complex endeavor. The shifting of seasons predicted by climate models and the resulting impacts that climate scientists investigate often verify what Traditional knowledge has already revealed to Indigenous peoples as they continue to live on, manage, and care for the environment they have been a part of for thousands of years. However, this convergence of two ways of knowing about our human environmental relationships is often difficult to navigate because of the ongoing impacts of colonialism and the disadvantage that Tribes operate from as a result. Day to day priorities of the Tribe are therefore reflective of more immediate issues rather than specifically considering the uncertainties of climate change. The College of Menominee Nation Sustainable Development Institute has developed a climate resilience program aimed at combining western science methodologies with indigenous ways of knowing as a means to assist Tribes in building capacity to address climate and community resiliency through culturally appropriate activities led by the Tribes. The efforts of the Institute, as guided by the SDI theoretical model of sustainability, have resulted in a variety of research, education and outreach projects that have provided not only the Menominee community, but other Tribal communities with opportunities to address climate resiliency as they see fit.

Estimated effects of projected climate change on the basic reproductive number of the Lyme disease vector Ixodes scapularis.

PubMed

Ogden, Nicholas H; Radojevic, Milka; Wu, Xiaotian; Duvvuri, Venkata R; Leighton, Patrick A; Wu, Jianhong

2014-06-01

The extent to which climate change may affect human health by increasing risk from vector-borne diseases has been under considerable debate. We quantified potential effects of future climate change on the basic reproduction number (R0) of the tick vector of Lyme disease, Ixodes scapularis, and explored their importance for Lyme disease risk, and for vector-borne diseases in general. We applied observed temperature data for North America and projected temperatures using regional climate models to drive an I. scapularis population model to hindcast recent, and project future, effects of climate warming on R0. Modeled R0 increases were compared with R0 ranges for pathogens and parasites associated with variations in key ecological and epidemiological factors (obtained by literature review) to assess their epidemiological importance. R0 for I. scapularis in North America increased during the years 1971-2010 in spatio-temporal patterns consistent with observations. Increased temperatures due to projected climate change increased R0 by factors (2-5 times in Canada and 1.5-2 times in the United States), comparable to observed ranges of R0 for pathogens and parasites due to variations in strains, geographic locations, epidemics, host and vector densities, and control efforts. Climate warming may have co-driven the emergence of Lyme disease in northeastern North America, and in the future may drive substantial disease spread into new geographic regions and increase tick-borne disease risk where climate is currently suitable. Our findings highlight the potential for climate change to have profound effects on vectors and vector-borne diseases, and the need to refocus efforts to understand these effects.

Prevention of Spacecraft Anomalies: The Role of Space Climate and Space Weather Models

NASA Technical Reports Server (NTRS)

Barth, Janet L.

2003-01-01

Space-based systems are developing into critical infrastructure to support the quality of life on Earth. Mission requirements along with rapidly evolving technologies have outpaced efforts to accommodate detrimental space environment impacts on systems. This chapter describes approaches to accommodate space climate and space weather impacts on systems and notes areas where gaps in model development limit our ability to prevent spacecraft anomalies.

Producing a Climate-Quality Database of Global Upper Ocean Profile Temperatures - The IQuOD (International Quality-controlled Ocean Database) Project.

NASA Astrophysics Data System (ADS)

Sprintall, J.; Cowley, R.; Palmer, M. D.; Domingues, C. M.; Suzuki, T.; Ishii, M.; Boyer, T.; Goni, G. J.; Gouretski, V. V.; Macdonald, A. M.; Thresher, A.; Good, S. A.; Diggs, S. C.

2016-02-01

Historical ocean temperature profile observations provide a critical element for a host of ocean and climate research activities. These include providing initial conditions for seasonal-to-decadal prediction systems, evaluating past variations in sea level and Earth's energy imbalance, ocean state estimation for studying variability and change, and climate model evaluation and development. The International Quality controlled Ocean Database (IQuOD) initiative represents a community effort to create the most globally complete temperature profile dataset, with (intelligent) metadata and assigned uncertainties. With an internationally coordinated effort organized by oceanographers, with data and ocean instrumentation expertise, and in close consultation with end users (e.g., climate modelers), the IQuOD initiative will assess and maximize the potential of an irreplaceable collection of ocean temperature observations (tens of millions of profiles collected at a cost of tens of billions of dollars, since 1772) to fulfil the demand for a climate-quality global database that can be used with greater confidence in a vast range of climate change related research and services of societal benefit. Progress towards version 1 of the IQuOD database, ongoing and future work will be presented. More information on IQuOD is available at www.iquod.org.

Climate: Policy, Modeling, and Federal Priorities (Invited)

NASA Astrophysics Data System (ADS)

Koonin, S.; Department Of Energy Office Of The Under SecretaryScience

2010-12-01

The Administration has set ambitious national goals to reduce our dependence on fossil fuels and reduce anthropogenic greenhouse gas (GHG) emissions. The US and other countries involved in the U.N. Framework Convention on Climate Change continue to work toward a goal of establishing a viable treaty that would encompass limits on emissions and codify actions that nations would take to reduce emissions. These negotiations are informed by the science of climate change and by our understanding of how changes in technology and the economy might affect the overall climate in the future. I will describe the present efforts within the U.S. Department of Energy, and the federal government more generally, to address issues related to climate change. These include state-of-the-art climate modeling and uncertainty assessment, economic and climate scenario planning based on best estimates of different technology trajectories, adaption strategies for climate change, and monitoring and reporting for treaty verification.

Near term climate projections for invasive species distributions

USGS Publications Warehouse

Jarnevich, C.S.; Stohlgren, T.J.

2009-01-01

Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas. ?? 2008 Springer Science+Business Media B.V.

Soil mapping and processes models to support climate change mitigation and adaptation strategies: a review

NASA Astrophysics Data System (ADS)

Muñoz-Rojas, Miriam; Pereira, Paulo; Brevik, Eric; Cerda, Artemi; Jordan, Antonio

2017-04-01

As agreed in Paris in December 2015, global average temperature is to be limited to "well below 2 °C above pre-industrial levels" and efforts will be made to "limit the temperature increase to 1.5 °C above pre-industrial levels. Thus, reducing greenhouse gas emissions (GHG) in all sectors becomes critical and appropriate sustainable land management practices need to be taken (Pereira et al., 2017). Mitigation strategies focus on reducing the rate and magnitude of climate change by reducing its causes. Complementary to mitigation, adaptation strategies aim to minimise impacts and maximize the benefits of new opportunities. The adoption of both practices will require developing system models to integrate and extrapolate anticipated climate changes such as global climate models (GCMs) and regional climate models (RCMs). Furthermore, integrating climate models driven by socio-economic scenarios in soil process models has allowed the investigation of potential changes and threats in soil characteristics and functions in future climate scenarios. One of the options with largest potential for climate change mitigation is sequestering carbon in soils. Therefore, the development of new methods and the use of existing tools for soil carbon monitoring and accounting have therefore become critical in a global change context. For example, soil C maps can help identify potential areas where management practices that promote C sequestration will be productive and guide the formulation of policies for climate change mitigation and adaptation strategies. Despite extensive efforts to compile soil information and map soil C, many uncertainties remain in the determination of soil C stocks, and the reliability of these estimates depends upon the quality and resolution of the spatial datasets used for its calculation. Thus, better estimates of soil C pools and dynamics are needed to advance understanding of the C balance and the potential of soils for climate change mitigation. Here, we discuss the most recent advances on the application of soil mapping and modeling to support climate change mitigation and adaptation strategies; and These strategies are a key component of the implementation of sustainable land management policies need to be integrated are critical to. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. Muñoz-Rojas, M., Pereira, P., Brevic, E., Cerda, A., Jordan, A. (2017) Soil mapping and processes models for sustainable land management applied to modern challenges. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

Climate Change Effects on Agriculture: Economic Responses to Biophysical Shocks

NASA Technical Reports Server (NTRS)

Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlik, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina

2014-01-01

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(sup 2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Climate change effects on agriculture: Economic responses to biophysical shocks

PubMed Central

Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d’Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-01-01

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. PMID:24344285

Climate change effects on agriculture: economic responses to biophysical shocks.

PubMed

Nelson, Gerald C; Valin, Hugo; Sands, Ronald D; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d'Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-03-04

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

A review of national and international activities on modeling the effects of increased CO/sub 2/ concentrations on the simulation of regional crop production: (A report on linkage between climate and crop models): Progress report

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

Decker, W.L.; Achutuni, R.

1987-01-01

General circulation models have been used to estimate the probable changes in climate due to increased levels of carbon dioxide. These models, generally, project increases in the mean surface temperatures; but changes in precipitation due to CO/sub 2/ enrichment are not as clear. It appears that some process models, which utilize a minimum amount of empiricism, can be adopted for use in studying the impacts of both climate change scenarios and the direct effects of CO/sub 2/ fertilization. The CERES-Maize, CERES-Wheat, SORGF, GLYCIM, and SOYGRO are among those classified for this use. There is a great deal of effort beingmore » directed toward these developments. A WMO/UNEP/ICSU focus has sponsored at least two European meetings but with only limited success for testing production models. A similar effort has been conducted by the Commission of European Communities. An attempt has been made to modify the CERES models, which have been used in climate studies, for use in simulation of the direct effects. Initial simulations involving this modification, show that doubling CO/sub 2/ will increase corn production 12 to 30% at locations in northern Illinois for the four-year period 1982 to 1985. The increase in yield due to higher photosynthesis showed a greater effect than the impact of decreased transpiration.« less

Improving Climate Projections Using "Intelligent" Ensembles

NASA Technical Reports Server (NTRS)

Baker, Noel C.; Taylor, Patrick C.

2015-01-01

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

A Variable-Instar Climate-Driven Individual Beetle-Based Phenology Model for the Invasive Asian Longhorned Beetle (Coleoptera: Cerambycidae).

PubMed

Trotter, R Talbot; Keena, Melody A

2016-12-01

Efforts to manage and eradicate invasive species can benefit from an improved understanding of the physiology, biology, and behavior of the target species, and ongoing efforts to eradicate the Asian longhorned beetle (Anoplophora glabripennis Motschulsky) highlight the roles this information may play. Here, we present a climate-driven phenology model for A. glabripennis that provides simulated life-tables for populations of individual beetles under variable climatic conditions that takes into account the variable number of instars beetles may undergo as larvae. Phenology parameters in the model are based on a synthesis of published data and studies of A. glabripennis, and the model output was evaluated using a laboratory-reared population maintained under varying temperatures mimicking those typical of Central Park in New York City. The model was stable under variations in population size, simulation length, and the Julian dates used to initiate individual beetles within the population. Comparison of model results with previously published field-based phenology studies in native and invasive populations indicates both this new phenology model, and the previously published heating-degree-day model show good agreement in the prediction of the beginning of the flight season for adults. However, the phenology model described here avoids underpredicting the cumulative emergence of adults through the season, in addition to providing tables of life stages and estimations of voltinism for local populations. This information can play a key role in evaluating risk by predicting the potential for population growth, and may facilitate the optimization of management and eradication efforts. Published by Oxford University Press on behalf of Entomological Society of America 2016. This work is written by US Government employees and is in the public domain in the US.

On the use of Empirical Data to Downscale Non-scientific Scepticism About Results From Complex Physical Based Models

NASA Astrophysics Data System (ADS)

Germer, S.; Bens, O.; Hüttl, R. F.

2008-12-01

The scepticism of non-scientific local stakeholders about results from complex physical based models is a major problem concerning the development and implementation of local climate change adaptation measures. This scepticism originates from the high complexity of such models. Local stakeholders perceive complex models as black-box models, as it is impossible to gasp all underlying assumptions and mathematically formulated processes at a glance. The use of physical based models is, however, indispensible to study complex underlying processes and to predict future environmental changes. The increase of climate change adaptation efforts following the release of the latest IPCC report indicates that the communication of facts about what has already changed is an appropriate tool to trigger climate change adaptation. Therefore we suggest increasing the practice of empirical data analysis in addition to modelling efforts. The analysis of time series can generate results that are easier to comprehend for non-scientific stakeholders. Temporal trends and seasonal patterns of selected hydrological parameters (precipitation, evapotranspiration, groundwater levels and river discharge) can be identified and the dependence of trends and seasonal patters to land use, topography and soil type can be highlighted. A discussion about lag times between the hydrological parameters can increase the awareness of local stakeholders for delayed environment responses.

Making Scientific Data Available to Adaptation Practitioners - the Wallace Initiative

NASA Astrophysics Data System (ADS)

Price, J. T.; Warren, R. F.; Vanderwal, J.; Shoo, L.; Ramirez, J.; Jarvis, A.; Goswami, S.

2010-12-01

Conservation strategies have largely been developed under an assumption of a stationary climate. These strategies may fail with changing climates, especially when acting with existing anthropogenic pressures. The Wallace Initiative is a global effort to rapidly assess the potential impacts of climate change on nearly 50,000 plant and animal species. Climate change data from the Community Integrated Assessment System (CIAS) is then used to look at different future climate change scenarios. Governments and conservation organizations have dedicated extensive resources to protect biodiversity. These investments are at risk and efforts will need to take into account a dynamic climate. We used the species models to calculate projected changes in percent species richness - looking at areas likely to be refugia and areas likely to undergo the greatest loss. This information can provide guidance to natural resource managers on how they may need to adapt to climate change to avoid biodiversity loss. Managers will also need to take into account issues with spatial scale. While these models might project a species being “lost” in a 0.5° x 0.5° grid, thermal buffering (e.g., taking into account elevation, slope, aspect, distance to stream and canopy cover) provides guidance on areas that may allow a species to persist at more local scales (1-5 km). This approach may help alleviate the issues of downscaling climate and climate change data in data-poor areas. Understanding the vulnerability of biodiversity requires an understanding of the climate and projected climate changes. Thus, developing long term adaptation options requires robust vulnerability analyses at appropriate scales. These assessments are often hindered by data quality and availability, capacity and an understanding of appropriate scales, methods and tools. The program ClimaScope has been designed to help provide better access to climate data for modelers and practitioners, data that has also been linked to impacts. ClimaScope is a data visualization engine providing easy access to data without running the models. For a selected GCM pattern and emissions scenario, ClimaScope provides maps, charts and data on the projected climate changes with some indication of uncertainty range. Variables available include terrestrial temperature change (maximum, minimum and average), total precipitation, wet-day frequency, and sea-surface temperature. This data can be presented both as observed climate and/or projected climate for a user defined time period. Some of these data have been used in the Wallace Initiative and data from the Wallace Initiative are also available to users. So, practitioners can select family, genus, species, dispersal model, climate model, emission model, and time slice and get maps showing projected range of the species over time. These tools have been designed to help make scientific data more readily available to adaptation practitioners around the world, especially in developing countries.

Putting the Assessment into Practice: Applications of Climate and Health Data and Information

NASA Astrophysics Data System (ADS)

Balbus, J. M.; Morris, J.; Luber, G.

2016-12-01

The USGCRP Climate and Health Assessment represents the most up to date synthesis of the scientific literature on the health impacts of climate change in the United States. One of its key messages is that climate change is already affecting the health of people in the United States and around the world, and these impacts are likely to become more extensive over time. Another key message is that all Americans have some degree of vulnerability to the health impacts of climate change at some point in their lives. Conclusions as significant as those call for measures to translate current knowledge into specific actions to protect populations and enhance resilience to the health impacts of climate change. This presentation will summarize efforts underway across the federal government to apply research results and climate and health data to enhancing the resilience of populations. These efforts include the development of early warning systems and other applications of predictive models of weather and climate-related health hazards; partnerships with health professional societies to help translate the assessment's findings into specific recommendations for health professionals; and the development of educational materials to help enhance the resilience of students and their families by enhancing their understanding of the connections between climate, climate change and health.

Adapting California’s ecosystems to a changing climate

USGS Publications Warehouse

Elizabeth Chornesky,; David Ackerly,; Paul Beier,; Frank Davis,; Flint, Lorraine E.; Lawler, Joshua J.; Moyle, Peter B.; Moritz, Max A.; Scoonover, Mary; Byrd, Kristin B.; Alvarez, Pelayo; Heller, Nicole E.; Micheli, Elisabeth; Weiss, Stuart

2017-01-01

Significant efforts are underway to translate improved understanding of how climate change is altering ecosystems into practical actions for sustaining ecosystem functions and benefits. We explore this transition in California, where adaptation and mitigation are advancing relatively rapidly, through four case studies that span large spatial domains and encompass diverse ecological systems, institutions, ownerships, and policies. The case studies demonstrate the context specificity of societal efforts to adapt ecosystems to climate change and involve applications of diverse scientific tools (e.g., scenario analyses, downscaled climate projections, ecological and connectivity models) tailored to specific planning and management situations (alternative energy siting, wetland management, rangeland management, open space planning). They illustrate how existing institutional and policy frameworks provide numerous opportunities to advance adaptation related to ecosystems and suggest that progress is likely to be greatest when scientific knowledge is integrated into collective planning and when supportive policies and financing enable action.

On the Reprocessing and Reanalysis of Observations for Climate

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Kennedy, John; Dee, Dick; ONeill, Alan

2012-01-01

The long observational record is critical to our understanding of the Earth s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. WCRP provides the means to bridge the different motivating objectives on which national efforts focus.

Impacts of Participatory Modeling on Climate Change-related Water Management Impacts in Sonora, Mexico

NASA Astrophysics Data System (ADS)

Halvorsen, K. E.; Kossak, D. J.; Mayer, A. S.; Vivoni, E. R.; Robles-Morua, A.; Gamez Molina, V.; Dana, K.; Mirchi, A.

2013-12-01

Climate change-related impacts on water resources are expected to be particularly severe in the arid developing world. As a result, we conducted a series of participatory modeling workshops on hydrologic and water resources systems modeling in the face of climate change in Sonora, Mexico. Pre-surveys were administered to participants on Day 1 of a series of four workshops spaced out over three months in 2013. Post-surveys repeated many pre-survey questions and included questions assessing the quality of the workshops and models. We report on significant changes in participant perceptions of water resource models and problems and their assessment of the workshops. These findings will be of great value to future participatory modeling efforts, particularly within the developing world.

School climate and delinquency among Chinese adolescents: analyses of effortful control as a moderator and deviant peer affiliation as a mediator.

PubMed

Bao, Zhenzhou; Li, Dongping; Zhang, Wei; Wang, Yanhui

2015-01-01

School climate is the quality and character of school life and reflects the norms, goals, values, interpersonal relationships, teaching and learning practices, and the organizational structure of a school. There is substantial literature documenting the negative association between positive school climate and adolescent delinquency, but little is known about the moderating and mediating mechanisms underlying this relationship. The aim of this study was to examine whether the direct and indirect pathways between school climate and adolescent delinquency would be moderated by effortful control. A sample of 2,758 Chinese adolescents (M age = 13.53 years, SD = 1.06) from 10 middle schools completed anonymous questionnaires regarding school climate, effortful control, deviant peer affiliation, and delinquency. After gender, age, geographical area, and socioeconomic status were included as covariates, the results revealed that school climate was significantly associated with adolescent delinquent behavior. This direct association was moderated by effortful control, such that the negative relationship between positive school climate and delinquency was only significant among adolescents low in effortful control. Moreover, the indirect association between school climate and delinquency via deviant peer affiliation was also moderated by effortful control. Specifically, the moderating effect of effortful control was not only manifested in the relationship between school climate and deviant peer affiliation, but also in the relationship between deviant peer affiliation and delinquency. These findings contribute to understanding the mechanisms through which positive school climate might reduce delinquent behavior and have important implications for prevention efforts aimed at diminishing adolescent delinquency.

Accounting for Global Climate Model Projection Uncertainty in Modern Statistical Downscaling

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

Johannesson, G

2010-03-17

Future climate change has emerged as a national and a global security threat. To carry out the needed adaptation and mitigation steps, a quantification of the expected level of climate change is needed, both at the global and the regional scale; in the end, the impact of climate change is felt at the local/regional level. An important part of such climate change assessment is uncertainty quantification. Decision and policy makers are not only interested in 'best guesses' of expected climate change, but rather probabilistic quantification (e.g., Rougier, 2007). For example, consider the following question: What is the probability that themore » average summer temperature will increase by at least 4 C in region R if global CO{sub 2} emission increases by P% from current levels by time T? It is a simple question, but one that remains very difficult to answer. It is answering these kind of questions that is the focus of this effort. The uncertainty associated with future climate change can be attributed to three major factors: (1) Uncertainty about future emission of green house gasses (GHG). (2) Given a future GHG emission scenario, what is its impact on the global climate? (3) Given a particular evolution of the global climate, what does it mean for a particular location/region? In what follows, we assume a particular GHG emission scenario has been selected. Given the GHG emission scenario, the current batch of the state-of-the-art global climate models (GCMs) is used to simulate future climate under this scenario, yielding an ensemble of future climate projections (which reflect, to some degree our uncertainty of being able to simulate future climate give a particular GHG scenario). Due to the coarse-resolution nature of the GCM projections, they need to be spatially downscaled for regional impact assessments. To downscale a given GCM projection, two methods have emerged: dynamical downscaling and statistical (empirical) downscaling (SDS). Dynamic downscaling involves configuring and running a regional climate model (RCM) nested within a given GCM projection (i.e., the GCM provides bounder conditions for the RCM). On the other hand, statistical downscaling aims at establishing a statistical relationship between observed local/regional climate variables of interest and synoptic (GCM-scale) climate predictors. The resulting empirical relationship is then applied to future GCM projections. A comparison of the pros and cons of dynamical versus statistical downscaling is outside the scope of this effort, but has been extensively studied and the reader is referred to Wilby et al. (1998); Murphy (1999); Wood et al. (2004); Benestad et al. (2007); Fowler et al. (2007), and references within those. The scope of this effort is to study methodology, a statistical framework, to propagate and account for GCM uncertainty in regional statistical downscaling assessment. In particular, we will explore how to leverage an ensemble of GCM projections to quantify the impact of the GCM uncertainty in such an assessment. There are three main component to this effort: (1) gather the necessary climate-related data for a regional SDS study, including multiple GCM projections, (2) carry out SDS, and (3) assess the uncertainty. The first step is carried out using tools written in the Python programming language, while analysis tools were developed in the statistical programming language R; see Figure 1.« less

Structure and vulnerability of Pacific Northwest tidal wetlands – A summary of wetland climate change research by the Western Ecology Division, U.S. EPA

USGS Publications Warehouse

Folger, Christina L; Lee, Henry; Janousek, Christopher N.; Reusser, Deborah A.

2014-01-01

Climate change poses a serious threat to the tidal wetlands of the Pacific Northwest (PNW) region of the U.S. In response to this threat, scientists at the Western Ecology Division of the U.S. EPA at and the Western Fisheries Research Center of the U.S. Geological Survey, along with other partners, initiated a series of studies on the structure and vulnerability of tidal wetlands to climate change. One research thrust was to evaluate community structure of PNW marshes, experimentally assess the vulnerability of marsh plants to inundation and salinity stress (as would happen with sea level rise), and evaluate the utility of the National Wetland Inventory (NWI) classification system. Another research thrust was to develop tools that provide insights into possible impacts of climate change. This effort included enhancing the Sea Level Affecting Marshes Model (SLAMM) to predict the effects of sea level rise on submerged aquatic vegetation (Zostera marina) distributions, evaluating changes in river flow into coastal estuaries in response to precipitation changes, and synthesizing Pacific Coast estuary, watershed, and climate data in a downloadable tool. Because the research resulting from these efforts was published in multiple venues, we summarized them in this document. We anticipate that future research efforts by the U.S. EPA will continue with a focus on climate change impacts on a regional scale.

Projecting carbon footprint of Canadian dairy farms under future climate conditions with the integrated farm system model

USDA-ARS?s Scientific Manuscript database

Dairy farms are an important sector of Canadian agriculture, and there is an on-going effort to assess their environmental impact. In Canada, like many northern areas of the world, climate change is expected to increase agricultural productivity. This will likely come along with changes in environme...

NAME Modeling and Climate Process Team

NASA Astrophysics Data System (ADS)

Schemm, J. E.; Williams, L. N.; Gutzler, D. S.

2007-05-01

NAME Climate Process and Modeling Team (CPT) has been established to address the need of linking climate process research to model development and testing activities for warm season climate prediction. The project builds on two existing NAME-related modeling efforts. One major component of this project is the organization and implementation of a second phase of NAMAP, based on the 2004 season. NAMAP2 will re-examine the metrics proposed by NAMAP, extend the NAMAP analysis to transient variability, exploit the extensive observational database provided by NAME 2004 to analyze simulation targets of special interest, and expand participation. Vertical column analysis will bring local NAME observations and model outputs together in a context where key physical processes in the models can be evaluated and improved. The second component builds on the current NAME-related modeling effort focused on the diurnal cycle of precipitation in several global models, including those implemented at NCEP, NASA and GFDL. Our activities will focus on the ability of the operational NCEP Global Forecast System (GFS) to simulate the diurnal and seasonal evolution of warm season precipitation during the NAME 2004 EOP, and on changes to the treatment of deep convection in the complicated terrain of the NAMS domain that are necessary to improve the simulations, and ultimately predictions of warm season precipitation These activities will be strongly tied to NAMAP2 to ensure technology transfer from research to operations. Results based on experiments conducted with the NCEP CFS GCM will be reported at the conference with emphasis on the impact of horizontal resolution in predicting warm season precipitation over North America.

Hydrological processes and model representation: impact of soft data on calibration

Treesearch

J.G. Arnold; M.A. Youssef; H. Yen; M.J. White; A.Y. Sheshukov; A.M. Sadeghi; D.N. Moriasi; J.L. Steiner; Devendra Amatya; R.W. Skaggs; E.B. Haney; J. Jeong; M. Arabi; P.H. Gowda

2015-01-01

Hydrologic and water quality models are increasingly used to determine the environmental impacts of climate variability and land management. Due to differing model objectives and differences in monitored data, there are currently no universally accepted procedures for model calibration and validation in the literature. In an effort to develop accepted model calibration...

3ARM: A Fast, Accurate Radiative Transfer Model for Use in Climate Models

NASA Technical Reports Server (NTRS)

Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.

1996-01-01

A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.

3ARM: A Fast, Accurate Radiative Transfer Model for use in Climate Models

NASA Technical Reports Server (NTRS)

Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.

1996-01-01

A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.

3ARM: A Fast, Accurate Radiative Transfer Model For Use in Climate Models

NASA Technical Reports Server (NTRS)

Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.

1996-01-01

A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.

Simulating the Risk of Liver Fluke Infection using a Mechanistic Hydro-epidemiological Model

NASA Astrophysics Data System (ADS)

Beltrame, Ludovica; Dunne, Toby; Rose, Hannah; Walker, Josephine; Morgan, Eric; Vickerman, Peter; Wagener, Thorsten

2016-04-01

Liver Fluke (Fasciola hepatica) is a common parasite found in livestock and responsible for considerable economic losses throughout the world. Risk of infection is strongly influenced by climatic and hydrological conditions, which characterise the host environment for parasite development and transmission. Despite on-going control efforts, increases in fluke outbreaks have been reported in recent years in the UK, and have been often attributed to climate change. Currently used fluke risk models are based on empirical relationships derived between historical climate and incidence data. However, hydro-climate conditions are becoming increasingly non-stationary due to climate change and direct anthropogenic impacts such as land use change, making empirical models unsuitable for simulating future risk. In this study we introduce a mechanistic hydro-epidemiological model for Liver Fluke, which explicitly simulates habitat suitability for disease development in space and time, representing the parasite life cycle in connection with key environmental conditions. The model is used to assess patterns of Liver Fluke risk for two catchments in the UK under current and potential future climate conditions. Comparisons are made with a widely used empirical model employing different datasets, including data from regional veterinary laboratories. Results suggest that mechanistic models can achieve adequate predictive ability and support adaptive fluke control strategies under climate change scenarios.

Check-Up of Planet Earth at the Turn of the Millennium: Contribution of EOS-Terra to a New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Yoram

1999-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical developments that brought to the Terra mission, its objectives and example of application to biomass burning.

Eliciting climate experts' knowledge to address model uncertainties in regional climate projections: a case study of Guanacaste, Northwest Costa Rica

NASA Astrophysics Data System (ADS)

Grossmann, I.; Steyn, D. G.

2014-12-01

Global general circulation models typically cannot provide the detailed and accurate regional climate information required by stakeholders for climate adaptation efforts, given their limited capacity to resolve the regional topography and changes in local sea surface temperature, wind and circulation patterns. The study region in Northwest Costa Rica has a tropical wet-dry climate with a double-peak wet season. During the dry season the central Costa Rican mountains prevent tropical Atlantic moisture from reaching the region. Most of the annual precipitation is received following the northward migration of the ITCZ in May that allows the region to benefit from moist southwesterly flow from the tropical Pacific. The wet season begins with a short period of "early rains" and is interrupted by the mid-summer drought associated with the intensification and westward expansion of the North Atlantic subtropical high in late June. Model projections for the 21st century indicate a lengthening and intensification of the mid-summer drought and a weakening of the early rains on which current crop cultivation practices rely. We developed an expert elicitation to systematically address uncertainties in the available model projections of changes in the seasonal precipitation pattern. Our approach extends an elicitation approach developed previously at Carnegie Mellon University. Experts in the climate of the study region or Central American climate were asked to assess the mechanisms driving precipitation during each part of the season, uncertainties regarding these mechanisms, expected changes in each mechanism in a warming climate, and the capacity of current models to reproduce these processes. To avoid overconfidence bias, a step-by-step procedure was followed to estimate changes in the timing and intensity of precipitation during each part of the season. The questions drew upon interviews conducted with the regions stakeholders to assess their climate information needs. This study is part of the FuturAgua project funded by the Belmont Freshwater Security call. The expert opinions on expected changes in the seasonal precipitation pattern are being used to inform regional efforts to build drought resilience and to create and compare alternative water management strategies with the region's stakeholders.

Indicators and metrics for the assessment of climate engineering

NASA Astrophysics Data System (ADS)

Oschlies, A.; Held, H.; Keller, D.; Keller, K.; Mengis, N.; Quaas, M.; Rickels, W.; Schmidt, H.

2017-01-01

Selecting appropriate indicators is essential to aggregate the information provided by climate model outputs into a manageable set of relevant metrics on which assessments of climate engineering (CE) can be based. From all the variables potentially available from climate models, indicators need to be selected that are able to inform scientists and society on the development of the Earth system under CE, as well as on possible impacts and side effects of various ways of deploying CE or not. However, the indicators used so far have been largely identical to those used in climate change assessments and do not visibly reflect the fact that indicators for assessing CE (and thus the metrics composed of these indicators) may be different from those used to assess global warming. Until now, there has been little dedicated effort to identifying specific indicators and metrics for assessing CE. We here propose that such an effort should be facilitated by a more decision-oriented approach and an iterative procedure in close interaction between academia, decision makers, and stakeholders. Specifically, synergies and trade-offs between social objectives reflected by individual indicators, as well as decision-relevant uncertainties should be considered in the development of metrics, so that society can take informed decisions about climate policy measures under the impression of the options available, their likely effects and side effects, and the quality of the underlying knowledge base.

GCSS/WGNE Pacific Cross-section Intercomparison: Tropical and Subtropical Cloud Transitions

NASA Astrophysics Data System (ADS)

Teixeira, J.

2008-12-01

In this presentation I will discuss the role of the GEWEX Cloud Systems Study (GCSS) working groups in paving the way for substantial improvements in cloud parameterization in weather and climate models. The GCSS/WGNE Pacific Cross-section Intercomparison (GPCI) is an extension of GCSS and is a different type of model evaluation where climate models are analyzed along a Pacific Ocean transect from California to the equator. This approach aims at complementing the more traditional efforts in GCSS by providing a simple framework for the evaluation of models that encompasses several fundamental cloud regimes such as stratocumulus, shallow cumulus and deep cumulus, as well as the transitions between them. Currently twenty four climate and weather prediction models are participating in GPCI. We will present results of the comparison between models and recent satellite data. In particular, we will explore in detail the potential of the Atmospheric Infrared Sounder (AIRS) and CloudSat data for the evaluation of the representation of clouds and convection in climate models.

Climate change and adaptive water management measures in Chtouka Aït Baha region (Morocco).

PubMed

Seif-Ennasr, Marieme; Zaaboul, Rashyd; Hirich, Abdelaziz; Caroletti, Giulio Nils; Bouchaou, Lhoussaine; El Morjani, Zine El Abidine; Beraaouz, El Hassane; McDonnell, Rachael A; Choukr-Allah, Redouane

2016-12-15

This study evaluates the effect on the availability of water resources for agriculture of expected future changes in precipitation and temperature distributions in north-western Africa. It also puts forward some locally derived adaptation strategies to climate change that can have a positive impact on water resources in the Chtouka Aït Baha region. Historical baselines of precipitation and temperature were derived using satellite data respectively from CHIRPS and CRU, while future projections of temperature and precipitation were extracted from the Coordinated Regional Climate Downscaling Experiment database (CORDEX). Projections were also generated for two future periods (2030-2049 and 2080-2099) under two Representative Concentration Pathways: RCP4.5 and RCP8.5. Regional climate models and satellite data outputs were evaluated by calculating their bias and RMSE against historical baseline and observed data. Under the RCP8.5 scenario, temperature in the region shows an increase by 2°C for the 2030-2049 time period, and by 4 to 5°C towards the end of the 21st century. According to the RCP4.5 scenario, precipitation shows a reduction of 10 to 30% for the period 2030-2049, up to 60% for 2080-2099. Outputs from the climate change projections were used to force the HEC-HMS hydrological model. Simulation results indicate that water deficit at basin level will likely triple towards 2050 due to increase in water demand and decrease in aquifer recharge and dam storage. This alarming situation, in a country that already suffers from water insecurity, emphasizes the need for more efforts to implement climate change adaptation measures. This paper presents an assessment of 38 climate change adaptation measures according to several criteria. The evaluation shows that measures affecting the management of water resources have the highest benefit-to-efforts ratio, which indicates that decision makers and stakeholders should increasingly focus their efforts on management measures. Copyright © 2016 Elsevier B.V. All rights reserved.

On the Representation of Ice Nucleation in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

NASA Astrophysics Data System (ADS)

Storelvmo, T.

2015-12-01

Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework

USGS Publications Warehouse

Sojda, Richard S.; Towler, Erin; Roberts, Mike; Rajagopalan, Balaji

2013-01-01

[1] Despite the influence of hydroclimate on river ecosystems, most efforts to date have focused on using climate information to predict streamflow for water supply. However, as water demands intensify and river systems are increasingly stressed, research is needed to explicitly integrate climate into streamflow forecasts that are relevant to river ecosystem management. To this end, we present a five step risk-based framework: (1) define risk tolerance, (2) develop a streamflow forecast model, (3) generate climate forecast ensembles, (4) estimate streamflow ensembles and associated risk, and (5) manage for climate risk. The framework is successfully demonstrated for an unregulated watershed in southwest Montana, where the combination of recent drought and water withdrawals has made it challenging to maintain flows needed for healthy fisheries. We put forth a generalized linear modeling (GLM) approach to develop a suite of tools that skillfully model decision-relevant low flow characteristics in terms of climate predictors. Probabilistic precipitation forecasts are used in conjunction with the GLMs, resulting in season-ahead prediction ensembles that provide the full risk profile. These tools are embedded in an end-to-end risk management framework that directly supports proactive fish conservation efforts. Results show that the use of forecasts can be beneficial to planning, especially in wet years, but historical precipitation forecasts are quite conservative (i.e., not very “sharp”). Synthetic forecasts show that a modest “sharpening” can strongly impact risk and improve skill. We emphasize that use in management depends on defining relevant environmental flows and risk tolerance, requiring local stakeholder involvement.

An Improved Radiative Transfer Model for Climate Calculations

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.; Mlawer, Eli J.; Sokolik, Irina N.; Clough, Shepard A.; Toon, Owen B.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications, we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Improving Climate Projections by Understanding How Cloud Phase affects Radiation

NASA Technical Reports Server (NTRS)

Cesana, Gregory; Storelvmo, Trude

2017-01-01

Whether a cloud is predominantly water or ice strongly influences interactions between clouds and radiation coming down from the Sun or up from the Earth. Being able to simulate cloud phase transitions accurately in climate models based on observational data sets is critical in order to improve confidence in climate projections, because this uncertainty contributes greatly to the overall uncertainty associated with cloud-climate feedbacks. Ultimately, it translates into uncertainties in Earth's sensitivity to higher CO2 levels. While a lot of effort has recently been made toward constraining cloud phase in climate models, more remains to be done to document the radiative properties of clouds according to their phase. Here we discuss the added value of a new satellite data set that advances the field by providing estimates of the cloud radiative effect as a function of cloud phase and the implications for climate projections.

Sharing the Data along with the Responsibility: Examining an Analytic Scale-Based Model for Assessing School Climate.

ERIC Educational Resources Information Center

Shindler, John; Taylor, Clint; Cadenas, Herminia; Jones, Albert

This study was a pilot effort to examine the efficacy of an analytic trait scale school climate assessment instrument and democratic change system in two urban high schools. Pilot study results indicate that the instrument shows promising soundness in that it exhibited high levels of validity and reliability. In addition, the analytic trait format…

Dialogic Action in Climate Change Discussions: An International Study of High School Students in China, New Zealand, Norway and the United States

ERIC Educational Resources Information Center

Arya, Diana J.; Parker, Jessica K.

2015-01-01

Global efforts to prepare young developing minds for solving current and future challenges of climate change have advocated interdisciplinary, issues-based instructional approaches in order to transform traditional models of science education as delivering conceptual facts (UNESCO, 2014). This study is an exploration of the online interactions in…

A Statistical Modeling Framework for Projecting Future Ambient Ozone and its Health Impact due to Climate Change

PubMed Central

Chang, Howard H.; Hao, Hua; Sarnat, Stefanie Ebelt

2014-01-01

The adverse health effects of ambient ozone are well established. Given the high sensitivity of ambient ozone concentrations to meteorological conditions, the impacts of future climate change on ozone concentrations and its associated health effects are of concern. We describe a statistical modeling framework for projecting future ozone levels and its health impacts under a changing climate. This is motivated by the continual effort to evaluate projection uncertainties to inform public health risk assessment. The proposed approach was applied to the 20-county Atlanta metropolitan area using regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program. Future ozone levels and ozone-related excesses in asthma emergency department (ED) visits were examined for the period 2041–2070. The computationally efficient approach allowed us to consider 8 sets of climate model outputs based on different combinations of 4 RCMs and 4 general circulation models. Compared to the historical period of 1999–2004, we found consistent projections across climate models of an average 11.5% higher ozone levels (range: 4.8%, 16.2%), and an average 8.3% (range: −7% to 24%) higher number of ozone exceedance days. Assuming no change in the at-risk population, this corresponds to excess ozone-related ED visits ranging from 267 to 466 visits per year. Health impact projection uncertainty was driven predominantly by uncertainty in the health effect association and climate model variability. Calibrating climate simulations with historical observations reduced differences in projections across climate models. PMID:24764746

Climate change effects on agriculture: Economic responses to biophysical shocks

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

Nelson, Gerald; Valin, Hugo; Sands, Ronald

Agricultural production is sensitive to weather and will thus be directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments inmore » yields, area, consumption, and international trade. We apply biophysical shocks derived from the IPCC’s Representative Concentration Pathway that result in end-of-century radiative forcing of 8.5 watts per square meter. The mean biophysical impact on crop yield with no incremental CO2 fertilization is a 17 percent reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11 percent, increase area of major crops by 12 percent, and reduce consumption by 2 percent. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences includes model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.« less

Climate Change Boot Camps: Targeting Policy Makers and Outreach Trainers in Arizona to Improve Climate Literacy

NASA Astrophysics Data System (ADS)

Ferguson, D. B.; Guido, Z. S.; Buizer, J.; Roy, M.

2010-12-01

Bringing climate change issues into focus for decision makers is a growing challenge. Decision makers are often confronted with unique informational needs, a lack of useable information, and needs for customized climate change training, among other issues. Despite significant progress in improving climate literacy among certain stakeholders such as water managers, recent reports have highlighted the growing demand for climate-change information in regions and sectors across the US. In recent years many ventures have sprung up to address these gaps and have predominantly focused on K-12 education and resource management agencies such as the National Park Service and National Weather Service. However, two groups that are critical for integrating climate information into actions have received less attention: (1) policy makers and (2) outreach experts, such as Cooperative Extension agents. Climate Change Boot Camps (CCBC) is a joint effort between the Climate Assessment for the Southwest (CLIMAS)—a NOAA Regionally Integrated Sciences and Assessments (RISA) program—and researchers at Arizona State University to diagnose climate literacy and training gaps in Arizona and develop a process that converts these deficiencies into actionable knowledge among the two aforementioned groups. This presentation will highlight the initial phases of the CCBC process, which has as its outcomes the identification of effective strategies for reaching legislators, climate literacy and training needs for both policy makers and trainers, and effective metrics to evaluate the success of these efforts. Specific attention is given to evaluating the process from initial needs assessment to the effectiveness of the workshops. Web curriculum and training models made available on the internet will also be developed, drawing on extensive existing Web resources for other training efforts and converted to meet the needs of these two groups. CCBC will also leverage CLIMAS’ long history of engaging with stakeholders in the Southwest to facilitate to use of climate information in the decision process.

Climatic response variability and machine learning: development of a modular technology framework for predicting bio-climatic change in pacific northwest ecosystems"

NASA Astrophysics Data System (ADS)

Seamon, E.; Gessler, P. E.; Flathers, E.

2015-12-01

The creation and use of large amounts of data in scientific investigations has become common practice. Data collection and analysis for large scientific computing efforts are not only increasing in volume as well as number, the methods and analysis procedures are evolving toward greater complexity (Bell, 2009, Clarke, 2009, Maimon, 2010). In addition, the growth of diverse data-intensive scientific computing efforts (Soni, 2011, Turner, 2014, Wu, 2008) has demonstrated the value of supporting scientific data integration. Efforts to bridge this gap between the above perspectives have been attempted, in varying degrees, with modular scientific computing analysis regimes implemented with a modest amount of success (Perez, 2009). This constellation of effects - 1) an increasing growth in the volume and amount of data, 2) a growing data-intensive science base that has challenging needs, and 3) disparate data organization and integration efforts - has created a critical gap. Namely, systems of scientific data organization and management typically do not effectively enable integrated data collaboration or data-intensive science-based communications. Our research efforts attempt to address this gap by developing a modular technology framework for data science integration efforts - with climate variation as the focus. The intention is that this model, if successful, could be generalized to other application areas. Our research aim focused on the design and implementation of a modular, deployable technology architecture for data integration. Developed using aspects of R, interactive python, SciDB, THREDDS, Javascript, and varied data mining and machine learning techniques, the Modular Data Response Framework (MDRF) was implemented to explore case scenarios for bio-climatic variation as they relate to pacific northwest ecosystem regions. Our preliminary results, using historical NETCDF climate data for calibration purposes across the inland pacific northwest region (Abatzoglou, Brown, 2011), show clear ecosystems shifting over a ten-year period (2001-2011), based on multiple supervised classifier methods for bioclimatic indicators.

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.

Land use and climate affect Black Tern, Northern Harrier, and Marsh Wren abundance in the Prairie Pothole Region of the United States

USGS Publications Warehouse

Forcey, Greg M.; Thogmartin, Wayne E.; Linz, George M.; McKann, Patrick C.

2014-01-01

Bird populations are influenced by many environmental factors at both large and small scales. Our study evaluated the influences of regional climate and land-use variables on the Northern Harrier (Circus cyaneus), Black Tern (Childonias niger), and Marsh Wren (Cistothorus palustris) in the prairie potholes of the upper Midwest of the United States. These species were chosen because their diverse habitat preference represent the spectrum of habitat conditions present in the Prairie Potholes, ranging from open prairies to dense cattail marshes. We evaluated land-use covariates at three logarithmic spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and constructed models a priori using information from published habitat associations and climatic influences. The strongest influences on the abundance of each of the three species were the percentage of wetland area across all three spatial scales and precipitation in the year preceding that when bird surveys were conducted. Even among scales ranging over three orders of magnitude the influence of spatial scale was small, as models with the same variables expressed at different scales were often in the best model subset. Examination of the effects of large-scale environmental variables on wetland birds elucidated relationships overlooked in many smaller-scale studies, such as the influences of climate and habitat variables at landscape scales. Given the spatial variation in the abundance of our focal species within the prairie potholes, our model predictions are especially useful for targeting locations, such as northeastern South Dakota and central North Dakota, where management and conservation efforts would be optimally beneficial. This modeling approach can also be applied to other species and geographic areas to focus landscape conservation efforts and subsequent small-scale studies, especially in constrained economic climates.

Formulation, General Features and Global Calibration of a Bioenergetically-Constrained Fishery Model

PubMed Central

Bianchi, Daniele; Galbraith, Eric D.

2017-01-01

Human exploitation of marine resources is profoundly altering marine ecosystems, while climate change is expected to further impact commercially-harvested fish and other species. Although the global fishery is a highly complex system with many unpredictable aspects, the bioenergetic limits on fish production and the response of fishing effort to profit are both relatively tractable, and are sure to play important roles. Here we describe a generalized, coupled biological-economic model of the global marine fishery that represents both of these aspects in a unified framework, the BiOeconomic mArine Trophic Size-spectrum (BOATS) model. BOATS predicts fish production according to size spectra as a function of net primary production and temperature, and dynamically determines harvest spectra from the biomass density and interactive, prognostic fishing effort. Within this framework, the equilibrium fish biomass is determined by the economic forcings of catchability, ex-vessel price and cost per unit effort, while the peak harvest depends on the ecosystem parameters. Comparison of a large ensemble of idealized simulations with observational databases, focusing on historical biomass and peak harvests, allows us to narrow the range of several uncertain ecosystem parameters, rule out most parameter combinations, and select an optimal ensemble of model variants. Compared to the prior distributions, model variants with lower values of the mortality rate, trophic efficiency, and allometric constant agree better with observations. For most acceptable parameter combinations, natural mortality rates are more strongly affected by temperature than growth rates, suggesting different sensitivities of these processes to climate change. These results highlight the utility of adopting large-scale, aggregated data constraints to reduce model parameter uncertainties and to better predict the response of fisheries to human behaviour and climate change. PMID:28103280

Formulation, General Features and Global Calibration of a Bioenergetically-Constrained Fishery Model.

PubMed

Carozza, David A; Bianchi, Daniele; Galbraith, Eric D

2017-01-01

Human exploitation of marine resources is profoundly altering marine ecosystems, while climate change is expected to further impact commercially-harvested fish and other species. Although the global fishery is a highly complex system with many unpredictable aspects, the bioenergetic limits on fish production and the response of fishing effort to profit are both relatively tractable, and are sure to play important roles. Here we describe a generalized, coupled biological-economic model of the global marine fishery that represents both of these aspects in a unified framework, the BiOeconomic mArine Trophic Size-spectrum (BOATS) model. BOATS predicts fish production according to size spectra as a function of net primary production and temperature, and dynamically determines harvest spectra from the biomass density and interactive, prognostic fishing effort. Within this framework, the equilibrium fish biomass is determined by the economic forcings of catchability, ex-vessel price and cost per unit effort, while the peak harvest depends on the ecosystem parameters. Comparison of a large ensemble of idealized simulations with observational databases, focusing on historical biomass and peak harvests, allows us to narrow the range of several uncertain ecosystem parameters, rule out most parameter combinations, and select an optimal ensemble of model variants. Compared to the prior distributions, model variants with lower values of the mortality rate, trophic efficiency, and allometric constant agree better with observations. For most acceptable parameter combinations, natural mortality rates are more strongly affected by temperature than growth rates, suggesting different sensitivities of these processes to climate change. These results highlight the utility of adopting large-scale, aggregated data constraints to reduce model parameter uncertainties and to better predict the response of fisheries to human behaviour and climate change.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies

NASA Astrophysics Data System (ADS)

Pincus, R.; Stevens, B. B.; Forster, P.; Collins, W.; Ramaswamy, V.

2014-12-01

The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies An enormous amount of attention has been paid to the diversity of responses in the CMIP and other multi-model ensembles. This diversity is normally interpreted as a distribution in climate sensitivity driven by some distribution of feedback mechanisms. Identification of these feedbacks relies on precise identification of the forcing to which each model is subject, including distinguishing true error from model diversity. The Radiative Forcing Model Intercomparison Project (RFMIP) aims to disentangle the role of forcing from model sensitivity as determinants of varying climate model response by carefully characterizing the radiative forcing to which such models are subject and by coordinating experiments in which it is specified. RFMIP consists of four activities: 1) An assessment of accuracy in flux and forcing calculations for greenhouse gases under past, present, and future climates, using off-line radiative transfer calculations in specified atmospheres with climate model parameterizations and reference models 2) Characterization and assessment of model-specific historical forcing by anthropogenic aerosols, based on coordinated diagnostic output from climate models and off-line radiative transfer calculations with reference models 3) Characterization of model-specific effective radiative forcing, including contributions of model climatology and rapid adjustments, using coordinated climate model integrations and off-line radiative transfer calculations with a single fast model 4) Assessment of climate model response to precisely-characterized radiative forcing over the historical record, including efforts to infer true historical forcing from patterns of response, by direct specification of non-greenhouse-gas forcing in a series of coordinated climate model integrations This talk discusses the rationale for RFMIP, provides an overview of the four activities, and presents preliminary motivating results.

A multiscale climate emulator for long-term morphodynamics (MUSCLE-morpho)

NASA Astrophysics Data System (ADS)

Antolínez, José Antonio A.; Méndez, Fernando J.; Camus, Paula; Vitousek, Sean; González, E. Mauricio; Ruggiero, Peter; Barnard, Patrick

2016-01-01

Interest in understanding long-term coastal morphodynamics has recently increased as climate change impacts become perceptible and accelerated. Multiscale, behavior-oriented and process-based models, or hybrids of the two, are typically applied with deterministic approaches which require considerable computational effort. In order to reduce the computational cost of modeling large spatial and temporal scales, input reduction and morphological acceleration techniques have been developed. Here we introduce a general framework for reducing dimensionality of wave-driver inputs to morphodynamic models. The proposed framework seeks to account for dependencies with global atmospheric circulation fields and deals simultaneously with seasonality, interannual variability, long-term trends, and autocorrelation of wave height, wave period, and wave direction. The model is also able to reproduce future wave climate time series accounting for possible changes in the global climate system. An application of long-term shoreline evolution is presented by comparing the performance of the real and the simulated wave climate using a one-line model. This article was corrected on 2 FEB 2016. See the end of the full text for details.

Investigating the Role of Mesoscale Processes and Ice Dynamics in Carbon and Iron Fluxes in a Changing Amundsen Sea (INSPIRE)

NASA Astrophysics Data System (ADS)

Mu, L.; Yager, P. L.; St-Laurent, P.; Dinniman, M.; Oliver, H.; Stammerjohn, S. E.; Sherrell, R. M.; Hofmann, E. E.

2016-02-01

The Amundsen Sea, in the remote S. Pacific sector of the Southern Ocean, is one of the least studied Antarctic continental shelf regions. It shares key processes with other W. Antarctic shelf regions, such as formation of a recurring polynya, important ice shelf-ocean linkages, and high biological production, but has unique characteristics as well. The Amundsen Sea Polynya (ASP), features 1) large intrusions of modified Circumpolar Deep Water (mCDW) onto the continental shelf, 2) the fastest melting ice sheets in Antarctica, 3) the most productive coastal polynya and a large atmospheric CO2 sink, and 4) very rapid declines in seasonal sea ice. Here we report on a new effort for this region that unites independent, state-of-the-art modeling and field data synthesis efforts to address important unanswered questions about carbon fluxes, iron supply, and climate sensitivity in this key region of the coastal Antarctic. Following on the heels of a highly successful oceanographic field program, the Amundsen Sea Polynya International Research Expedition (ASPIRE; which sampled the ASP with high spatial resolution during the onset of the enormous phytoplankton bloom of 2011), the INSPIRE project is a collaboration between ASPIRE senior scientists and an experienced team of physical and biogeochemical modelers who can use ASPIRE field data to both validate and extend the capabilities of an existing Regional Ocean Modeling System (ROMS) for the Amundsen Sea. This new effort will add biology and biogeochemistry (including features potentially unique to the ASP region) to an existing physical model, allowing us to address key questions about bloom mechanisms and climate sensitivity that could not be answered by field campaigns or modeling alone. This project is expected to generate new insights and hypotheses that will ultimately guide sampling strategies of future field efforts investigating how present and future climate change impacts this important region of the world.

Climate Change and Implications for Prevention. California's Efforts to Provide Leadership.

PubMed

Balmes, John R

2018-04-01

The atmospheric concentration of carbon dioxide (CO 2 ) and the temperature of the earth's surface have been rising in parallel for decades, with the former recently reaching 400 parts per million, consistent with a 1.5°C increase in global warming. Climate change models predict that a "business as usual" approach, that is, no effort to control CO 2 emissions from combustion of fossil fuels, will result in a more than 2°C increase in annual average surface temperature by approximately 2034. With atmospheric warming comes increased air pollution. The concept of a "climate gap" in air quality control captures the decreased effectiveness of regulatory policies to reduce pollution with a hotter climate. Sources of greenhouse gases and climate-forcing aerosols ("black carbon") are the same sources of air pollutants that harm health. California has adopted robust climate change mitigation policies that are also designed to achieve public health cobenefits by improving air quality. These policies include advanced clean car standards, renewable energy, a sustainable communities strategy to limit suburban sprawl, a low carbon fuel standard, and energy efficiency. A market-based mechanism to put a price on CO 2 emissions is the cap-and-trade program that allows capped facilities to trade state-issued greenhouse gas emissions allowances. The "cap" limits total greenhouse gas emissions from all covered sources, and declines over time to progressively reduce emissions. An alternative approach is a carbon tax. California's leadership on air quality and climate change mitigation is increasingly important, given the efforts to slow or even reverse implementation of such policies at the U.S. national level.

Synergy between land use and climate change increases future fire risk in Amazon forests

NASA Astrophysics Data System (ADS)

Le Page, Yannick; Morton, Douglas; Hartin, Corinne; Bond-Lamberty, Ben; Cardoso Pereira, José Miguel; Hurtt, George; Asrar, Ghassem

2017-12-01

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change - Representative Concentration Pathway (RCP) 8.5 - projected understory fires increase in frequency and duration, burning 4-28 times more forest in 2080-2100 than during 1990-2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9-5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.

Land-Atmosphere Interactions in Cold Environments (LATICE): The role of Atmosphere - Biosphere - Cryosphere - Hydrosphere interactions in a changing climate

NASA Astrophysics Data System (ADS)

Burkhart, J. F.; Tallaksen, L. M.; Stordal, F.; Berntsen, T.; Westermann, S.; Kristjansson, J. E.; Etzelmuller, B.; Hagen, J. O.; Schuler, T.; Hamran, S. E.; Lande, T. S.; Bryn, A.

2015-12-01

Climate change is impacting the high latitudes more rapidly and significantly than any other region of the Earth because of feedback processes between the atmosphere and the underlying surface. A warmer climate has already led to thawing of permafrost, reducing snow cover and a longer growing season; changes, which in turn influence the atmospheric circulation and the hydrological cycle. Still, many studies rely on one-way coupling between the atmosphere and the land surface, thereby neglecting important interactions and feedbacks. The observation, understanding and prediction of such processes from local to regional and global scales, represent a major scientific challenge that requires multidisciplinary scientific effort. The successful integration of earth observations (remote and in-situ data) and model development requires a harmonized research effort between earth system scientists, modelers and the developers of technologies and sensors. LATICE, which is recognized as a priority research area by the Faculty of Mathematics and Natural Sciences at the University of Oslo, aims to advance the knowledge base concerning land atmosphere interactions and their role in controlling climate variability and climate change at high northern latitudes. The consortium consists of an interdisciplinary team of experts from the atmospheric and terrestrial (hydrosphere, cryosphere and biosphere) research groups, together with key expertise on earth observations and novel sensor technologies. LATICE addresses critical knowledge gaps in the current climate assessment capacity through: Improving parameterizations of processes in earth system models controlling the interactions and feedbacks between the land (snow, ice, permafrost, soil and vegetation) and the atmosphere at high latitudes, including the boreal, alpine and artic zone. Assessing the influence of climate and land cover changes on water and energy fluxes. Integrating remote earth observations with in-situ data and suitable models to allow studies of finer-scale processes governing land-atmosphere interactions. Addressing observational challenges through the development of novel observational products and networks.

A Field Guide to Extra-Tropical Cyclones: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Bauer, M.

2008-12-01

Climate it is said is the accumulation of weather. And weather is not the concern of climate models. Justification for this latter sentiment has long hidden behind coarse model resolutions and blunt validation tools based on climatological maps and the like. The spatial-temporal resolutions of today's models and observations are converging onto meteorological scales however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough, or at least lacks perverting biases, such that its accumulation does in fact result in a robust climate prediction. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from climate model output. These include the usual cyclone distribution statistics (maps, histograms), but also adaptive cyclone- centric composites. We have also created a complementary dataset, The MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid- latitude cyclones based on Reanalysis products. Using this we then extract complimentary composites from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools will be shown. dime.giss.nasa.gov/mcms/mcms.html

Fine-spatial scale predictions of understory species using climate- and LiDAR-derived terrain and canopy metrics

NASA Astrophysics Data System (ADS)

Nijland, Wiebe; Nielsen, Scott E.; Coops, Nicholas C.; Wulder, Michael A.; Stenhouse, Gordon B.

2014-01-01

Food and habitat resources are critical components of wildlife management and conservation efforts. The grizzly bear (Ursus arctos) has diverse diets and habitat requirements particularly for understory plant species, which are impacted by human developments and forest management activities. We use light detection and ranging (LiDAR) data to predict the occurrence of 14 understory plant species relevant to bear forage and compare our predictions with more conventional climate- and land cover-based models. We use boosted regression trees to model each of the 14 understory species across 4435 km2 using occurrence (presence-absence) data from 1941 field plots. Three sets of models were fitted: climate only, climate and basic land and forest covers from Landsat 30-m imagery, and a climate- and LiDAR-derived model describing both the terrain and forest canopy. Resulting model accuracies varied widely among species. Overall, 8 of 14 species models were improved by including the LiDAR-derived variables. For climate-only models, mean annual precipitation and frost-free periods were the most important variables. With inclusion of LiDAR-derived attributes, depth-to-water table, terrain-intercepted annual radiation, and elevation were most often selected. This suggests that fine-scale terrain conditions affect the distribution of the studied species more than canopy conditions.

Framework for Detection and Localization of Extreme Climate Event with Pixel Recursive Super Resolution

NASA Astrophysics Data System (ADS)

Kim, S. K.; Lee, J.; Zhang, C.; Ames, S.; Williams, D. N.

2017-12-01

Deep learning techniques have been successfully applied to solve many problems in climate and geoscience using massive-scaled observed and modeled data. For extreme climate event detections, several models based on deep neural networks have been recently proposed and attend superior performance that overshadows all previous handcrafted expert based method. The issue arising, though, is that accurate localization of events requires high quality of climate data. In this work, we propose framework capable of detecting and localizing extreme climate events in very coarse climate data. Our framework is based on two models using deep neural networks, (1) Convolutional Neural Networks (CNNs) to detect and localize extreme climate events, and (2) Pixel recursive recursive super resolution model to reconstruct high resolution climate data from low resolution climate data. Based on our preliminary work, we have presented two CNNs in our framework for different purposes, detection and localization. Our results using CNNs for extreme climate events detection shows that simple neural nets can capture the pattern of extreme climate events with high accuracy from very coarse reanalysis data. However, localization accuracy is relatively low due to the coarse resolution. To resolve this issue, the pixel recursive super resolution model reconstructs the resolution of input of localization CNNs. We present a best networks using pixel recursive super resolution model that synthesizes details of tropical cyclone in ground truth data while enhancing their resolution. Therefore, this approach not only dramat- ically reduces the human effort, but also suggests possibility to reduce computing cost required for downscaling process to increase resolution of data.

Effects of Ensemble Configuration on Estimates of Regional Climate Uncertainties

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

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

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

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

NASA Astrophysics Data System (ADS)

MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

2015-04-01

The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

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.

Ice Sheet Model Intercomparison Project (ISMIP6) contribution to CMIP6

PubMed Central

Nowicki, Sophie M.J.; Payne, Tony; Larour, Eric; Seroussi, Helene; Goelzer, Heiko; Lipscomb, William; Gregory, Jonathan; Abe-Ouchi, Ayako; Shepherd, Andrew

2018-01-01

Reducing the uncertainty in the past, present and future contribution of ice sheets to sea-level change requires a coordinated effort between the climate and glaciology communities. The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) is the primary activity within the Coupled Model Intercomparison Project – phase 6 (CMIP6) focusing on the Greenland and Antarctic Ice Sheets. In this paper, we describe the framework for ISMIP6 and its relationship to other activities within CMIP6. The ISMIP6 experimental design relies on CMIP6 climate models and includes, for the first time within CMIP, coupled ice sheet – climate models as well as standalone ice sheet models. To facilitate analysis of the multi-model ensemble and to generate a set of standard climate inputs for standalone ice sheet models, ISMIP6 defines a protocol for all variables related to ice sheets. ISMIP6 will provide a basis for investigating the feedbacks, impacts, and sea-level changes associated with dynamic ice sheets and for quantifying the uncertainty in ice-sheet-sourced global sea-level change. PMID:29697697

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico.

PubMed

Johansson, Michael A; Reich, Nicholas G; Hota, Aditi; Brownstein, John S; Santillana, Mauricio

2016-09-26

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model.

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico

PubMed Central

Johansson, Michael A.; Reich, Nicholas G.; Hota, Aditi; Brownstein, John S.; Santillana, Mauricio

2016-01-01

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model. PMID:27665707

An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

NASA Astrophysics Data System (ADS)

Velázquez, J. A.; Schmid, J.; Ricard, S.; Muerth, M. J.; Gauvin St-Denis, B.; Minville, M.; Chaumont, D.; Caya, D.; Ludwig, R.; Turcotte, R.

2012-06-01

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs' members over a reference (1971-2000) and a future (2041-2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows.

Global Climate Models for the Classroom: The Educational Impact of Student Work with a Key Tool of Climate Scientists

NASA Astrophysics Data System (ADS)

Bush, D. F.; Sieber, R.; Seiler, G.; Chandler, M. A.; Chmura, G. L.

2017-12-01

Efforts to address climate change require public understanding of Earth and climate science. To meet this need, educators require instructional approaches and scientific technologies that overcome cultural barriers to impart conceptual understanding of the work of climate scientists. We compared student inquiry learning with now ubiquitous climate education toy models, data and tools against that which took place using a computational global climate model (GCM) from the National Aeronautics and Space Administration (NASA). Our study at McGill University and John Abbott College in Montreal, QC sheds light on how best to teach the research processes important to Earth and climate scientists studying atmospheric and Earth system processes but ill-understood by those outside the scientific community. We followed a pre/post, control/treatment experimental design that enabled detailed analysis and statistically significant results. Our research found more students succeed at understanding climate change when exposed to actual climate research processes and instruments. Inquiry-based education with a GCM resulted in significantly higher scores pre to post on diagnostic exams (quantitatively) and more complete conceptual understandings (qualitatively). We recognize the difficulty in planning and teaching inquiry with complex technology and we also found evidence that lectures support learning geared toward assessment exams.

Landscape-based population viability models demonstrate importance of strategic conservation planning for birds

Treesearch

Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh; D. Todd Jones-Farland

2013-01-01

Efforts to conserve regional biodiversity in the face of global climate change, habitat loss and fragmentation will depend on approaches that consider population processes at multiple scales. By combining habitat and demographic modeling, landscape-based population viability models effectively relate small-scale habitat and landscape patterns to regional population...

Global climatic trends as revealed by the recorded data

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

Ellsaesser, H.W.; MacCracken, M.C.; Walton, J.J.

Recent results from climate models have led to the prediction that a global warming due to increasing atmospheric CO/sub 2/ is now imminent, if it has not already occurred. In an effort to develop more definitive information on this question, a detailed review has been conducted of prior efforts to unravel climatic change from the various types of recorded observational data available. Most of the more definitive of the prior analyses: along with evaluative comments by the various authors: have been assembled herein. There appears little doubt that the average surface air temperature of at least northern hemisphere has beenmore » increasing since the beginning of recorded data with most of the warming occurring in a brief period circa 1920. The fragmentary early data suggest significant cooling prior to 1883 such that 25--50% of the subsequent warming may represent a return to earlier levels. Whether the overall warming constitutes a climate change remains an unresolved problem, as does the cause of the warming.« less

A Regional Climate Model Evaluation System based on contemporary Satellite and other Observations for Assessing Regional Climate Model Fidelity

NASA Astrophysics Data System (ADS)

Waliser, D. E.; Kim, J.; Mattman, C.; Goodale, C.; Hart, A.; Zimdars, P.; Lean, P.

2011-12-01

Evaluation of climate models against observations is an essential part of assessing the impact of climate variations and change on regionally important sectors and improving climate models. Regional climate models (RCMs) are of a particular concern. RCMs provide fine-scale climate needed by the assessment community via downscaling global climate model projections such as those contributing to the Coupled Model Intercomparison Project (CMIP) that form one aspect of the quantitative basis of the IPCC Assessment Reports. The lack of reliable fine-resolution observational data and formal tools and metrics has represented a challenge in evaluating RCMs. Recent satellite observations are particularly useful as they provide a wealth of information and constraints on many different processes within the climate system. Due to their large volume and the difficulties associated with accessing and using contemporary observations, however, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL and UCLA have developed the Regional Climate Model Evaluation System (RCMES) to help make satellite observations, in conjunction with in-situ and reanalysis datasets, more readily accessible to the regional modeling community. The system includes a central database (Regional Climate Model Evaluation Database: RCMED) to store multiple datasets in a common format and codes for calculating and plotting statistical metrics to assess model performance (Regional Climate Model Evaluation Tool: RCMET). This allows the time taken to compare model data with satellite observations to be reduced from weeks to days. RCMES is a component of the recent ExArch project, an international effort for facilitating the archive and access of massive amounts data for users using cloud-based infrastructure, in this case as applied to the study of climate and climate change. This presentation will describe RCMES and demonstrate its utility using examples from RCMs applied to the southwest US as well as to Africa based on output from the CORDEX activity. Application of RCMES to the evaluation of multi-RCM hindcast for CORDEX-Africa will be presented in a companion paper in A41.

Interactive effects of ozone and climate on tree growth and water use in a southern Appalachian forest in the USA

Treesearch

S.B. McLaughlin; S.D. Wullschleger; G. Sun

2007-01-01

A lack of data on responses of mature tree growth and water use to ambient ozone (O3) concentrations has been a major limitation in efforts to understand and model responses of forests to current and future changes in climate.Here, hourly to seasonal patterns of stem growth and sap flow velocity were...

Investigating the Roles of Neighborhood Environments and Housing-based Social Support in the Relocation of Persons Made Homeless by Hurricane Katrina

PubMed Central

Kloos, Bret; Flory, Kate; Hankin, Benjamin L.; Cheely, Catherine A.; Segal, Michelle

2008-01-01

This study examined whether social support tied to relocation efforts and neighborhood social climate may mediate the effects of stressful life events on mental health outcomes following Hurricane Katrina. Participants were 108 adult persons made homeless by Hurricane Katrina and evacuated to Columbia, SC. Civic leaders developed an intervention model that emphasized (a) a one-stop point of entry, (b) living in hotels and apartments rather than shelters, and (c) matching hotels with volunteer “hosts” to assist in relocation efforts. Results revealed that perceived neighborhood factors and satisfaction with host relationship were related to several mental health outcomes. Neighborhood social climate partially mediated several mental health outcomes. Implications of this intervention model and the utility of social ecological perspectives on homelessness interventions are discussed. PMID:19363774

Understanding, representing and communicating earth system processes in weather and climate within CNRCWP

NASA Astrophysics Data System (ADS)

Sushama, Laxmi; Arora, Vivek; de Elia, Ramon; Déry, Stephen; Duguay, Claude; Gachon, Philippe; Gyakum, John; Laprise, René; Marshall, Shawn; Monahan, Adam; Scinocca, John; Thériault, Julie; Verseghy, Diana; Zwiers, Francis

2017-04-01

The Canadian Network for Regional Climate and Weather Processes (CNRCWP) provides significant advances and innovative research towards the ultimate goal of reducing uncertainty in numerical weather prediction and climate projections for Canada's Northern and Arctic regions. This talk will provide an overview of the Network and selected results related to the assessment of the added value of high-resolution modelling that has helped fill critical knowledge gaps in understanding the dynamics of extreme temperature and precipitation events and the complex land-atmosphere interactions and feedbacks in Canada's northern and Arctic regions. In addition, targeted developments in the Canadian regional climate model, that facilitate direct application of model outputs in impact and adaptation studies, particularly those related to the water, energy and infrastructure sectors will also be discussed. The close collaboration between the Network and its partners and end users contributed significantly to this effort.

Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

PubMed

Steen, Valerie; Skagen, Susan K; Noon, Barry R

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971-2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981-2000 and projected future distributions to climate scenarios for 2040-2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

A strategy for assessing potential future changes in climate, hydrology, and vegetation in the Western United States

USGS Publications Warehouse

Thompson, Robert Stephen; Hostetler, Steven W.; Bartlein, Patrick J.; Anderson, Katherine H.

1998-01-01

Historical and geological data indicate that significant changes can occur in the Earth's climate on time scales ranging from years to millennia. In addition to natural climatic change, climatic changes may occur in the near future due to increased concentrations of carbon dioxide and other trace gases in the atmosphere that are the result of human activities. International research efforts using atmospheric general circulation models (AGCM's) to assess potential climatic conditions under atmospheric carbon dioxide concentrations of twice the pre-industrial level (a '2 X CO2' atmosphere) conclude that climate would warm on a global basis. However, it is difficult to assess how the projected warmer climatic conditions would be distributed on a regional scale and what the effects of such warming would be on the landscape, especially for temperate mountainous regions such as the Western United States. In this report, we present a strategy to assess the regional sensitivity to global climatic change. The strategy makes use of a hierarchy of models ranging from an AGCM, to a regional climate model, to landscape-scale process models of hydrology and vegetation. A 2 X CO2 global climate simulation conducted with the National Center for Atmospheric Research (NCAR) GENESIS AGCM on a grid of approximately 4.5o of latitude by 7.5o of longitude was used to drive the NCAR regional climate model (RegCM) over the Western United States on a grid of 60 km by 60 km. The output from the RegCM is used directly (for hydrologic models) or interpolated onto a 15-km grid (for vegetation models) to quantify possible future environmental conditions on a spatial scale relevant to policy makers and land managers.

On the Representation of Cloud Phase in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

NASA Astrophysics Data System (ADS)

Storelvmo, Trude; Sagoo, Navjit; Tan, Ivy

2016-04-01

Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

Communicating Climate Change: the Problem of Knowing and Doing.

NASA Astrophysics Data System (ADS)

Wildcat, D.

2008-12-01

The challenge of global warming and climate change may illustrate better than any recent phenomenon that quite independent of the science associated with our assessment, modeling, mitigation strategies and adaptation to the multiple complex processes that characterize this phenomenon, our greatest challenge resides in creating systems where knowledge can be usefully communicated to the general public. Knowledge transfer will pose significant challenges when addressing a topic that often leaves the ill-informed and non-scientist overwhelmed with pieces of information and paralyzed with a sense that there is nothing to be done to address this global problem. This communication problem is very acute in North American indigenous communities where a first-hand, on-the-ground, experience of climate change is indisputable, but where the charts, graphs and sophisticated models presented by scientists are treated with suspicion and often not explained very well. This presentation will discuss the efforts of the American Indian and Alaska Native Climate Change Working Group to prepare future generations of AI/AN geoscience professionals, educators, and a geoscience literate AI/AN workforce, while insuring that our Indigenous tribal knowledges of land- and sea-scapes, and climates are valued, used and incorporated into our tribal exercise of geoscience education and research. The Working Group's efforts are already suggesting the communication problem for Indigenous communities will best be solved by 'growing' our own culturally competent Indigenous geoscience professionals.

The foundation for climate services in Belgium: CORDEX.be

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Termonia, Piet; De Ridder, Koen; Fettweis, Xavier; Gobin, Anne; Luyten, Patrick; Marbaix, Philippe; Pottiaux, Eric; Stavrakou, Trissevgeni; Van Lipzig, Nicole; van Ypersele, Jean-Pascal; Willems, Patrick

2017-04-01

According to the Global Framework for Climate Services (GFCS) there are four pillars required to build climate services. As the first step towards the realization of a climate center in Belgium, the national project CORDEX.be focused on one pillar: research modelling and projection. By bringing together the Belgian climate and impact modeling research of nine groups a data-driven capacity development and community building in Belgium based on interactions with users. The project is based on the international CORDEX ("COordinated Regional Climate Downscaling Experiment") project where ".be" indicates it will go beyond for Belgium. Our national effort links to the regional climate initiatives through the contribution of multiple high-resolution climate simulations over Europe following the EURO-CORDEX guidelines. Additionally the same climate simulations were repeated at convection-permitting resolutions over Belgium (3 to 5 km). These were used to drive different local impact models to investigate the impact of climate change on urban effects, storm surges and waves, crop production and changes in emissions from vegetation. Akin to international frameworks such as CMIP and CORDEX a multi-model approach is adopted allowing for uncertainty estimation, a crucial aspect of climate projections for policy-making purposes. However, due to the lack of a large set of high resolution model runs, a combination of all available climate information is supplemented with the statistical downscaling approach. The organization of the project, together with its main results will be outlined. The proposed coordination framework could serve as a demonstration case for regions or countries where the climate-research capacity is present but a structure is required to assemble it coherently. Based on interactions and feedback with stakeholders different applications are planned, demonstrating the use of the climate data.

NASA's Climate Data Services Initiative

NASA Astrophysics Data System (ADS)

McInerney, M.; Duffy, D.; Schnase, J. L.; Webster, W. P.

2013-12-01

Our understanding of the Earth's processes is based on a combination of observational data records and mathematical models. The size of NASA's space-based observational data sets is growing dramatically as new missions come online. However a potentially bigger data challenge is posed by the work of climate scientists, whose models are regularly producing data sets of hundreds of terabytes or more. It is important to understand that the 'Big Data' challenge of climate science cannot be solved with a single technological approach or an ad hoc assemblage of technologies. It will require a multi-faceted, well-integrated suite of capabilities that include cloud computing, large-scale compute-storage systems, high-performance analytics, scalable data management, and advanced deployment mechanisms in addition to the existing, well-established array of mature information technologies. It will also require a coherent organizational effort that is able to focus on the specific and sometimes unique requirements of climate science. Given that it is the knowledge that is gained from data that is of ultimate benefit to society, data publication and data analytics will play a particularly important role. In an effort to accelerate scientific discovery and innovation through broader use of climate data, NASA Goddard Space Flight Center's Office of Computational and Information Sciences and Technology has embarked on a determined effort to build a comprehensive, integrated data publication and analysis capability for climate science. The Climate Data Services (CDS) Initiative integrates people, expertise, and technology into a highly-focused, next-generation, one-stop climate science information service. The CDS Initiative is providing the organizational framework, processes, and protocols needed to deploy existing information technologies quickly using a combination of enterprise-level services and an expanding array of cloud services. Crucial to its effectiveness, the CDS Initiative is developing the technical expertise to move new information technologies from R&D into operational use. This combination enables full, end-to-end support for climate data publishing and data analytics, and affords the flexibility required to meet future and unanticipated needs. Current science efforts being supported by the CDS Initiative include IPPC, OBS4MIP, ANA4MIPS, MERRA II, National Climate Assessment, the Ocean Data Assimilation project, NASA Earth Exchange (NEX), and the RECOVER Burned Area Emergency Response decision support system. Service offerings include an integrated suite of classic technologies (FTP, LAS, THREDDS, ESGF, GRaD-DODS, OPeNDAP, WMS, ArcGIS Server), emerging technologies (iRODS, UVCDAT), and advanced technologies (MERRA Analytic Services, MapReduce, Ontology Services, and the CDS API). This poster will describe the CDS Initiative, provide details about the Initiative's advanced offerings, and layout the CDS Initiative's deployment roadmap.

Improvement and Application of Atmospheric Radiative Transfer Models for Prediction of the Climatic Effects of Aerosol

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.; Mlawer, Eli J.; Sokolik, Irina N.; Clough, Shepard A.; Toon, Owen B.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models. To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications, we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Improvement and Application of Atmospheric Radiative Transfer Models for Prediction of the Climatic Effects of Aerosol

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models. To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Burden Sharing with Climate Change Impacts

NASA Astrophysics Data System (ADS)

Tavoni, M.; van Vuuren, D.; De Cian, E.; Marangoni, G.; Hof, A.

2014-12-01

Efficiency and equity have been at the center of the climate change policy making since the very first international environmental agreements on climate change, though over time how to implement these principles has taken different forms. Studies based on Integrated Assessment Models have also shown that the economic effort of achieving a 2 degree target in a cost-effective way would differ widely across regions (Tavoni et al. 2013) because of diverse economic and energy structure, baseline emissions, energy and carbon intensity. Policy instruments, such as a fully-fledged, global emission trading schemes can be used to pursuing efficiency and equity at the same time but the literature has analyzed the compensations required to redistribute only mitigation costs. However, most of these studies have neglected the potential impacts of climate change. In this paper we use two integrated assessment models -FAIR and WITCH- to explore the 2°C policy space when accounting for climate change impacts. Impacts are represented via two different reduced forms equations, which despite their simplicity allows us exploring the key sensitivities- Our results show that in a 2 degree stabilization scenarios residual damages remain significant (see Figure 1) and that if you would like to compensate those as part of an equal effort scheme - this would lead to a different allocation than focusing on a mitigation based perspective only. The residual damages and adaptation costs are not equally distributed - and while we do not cover the full uncertainty space - with 2 different models and 2 sets of damage curves we are still able to show quite similar results in terms of vulnerable regions and the relative position of the different scenarios. Therefore, accounting for the residual damages and the associated adaptation costs on top of the mitigation burden increases and redistributes the full burden of total climate change.

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.

Life cycles of transient planetary waves

NASA Technical Reports Server (NTRS)

Nathan, Terrence

1993-01-01

In recent years there has been an increasing effort devoted to understanding the physical and dynamical processes that govern the global-scale circulation of the atmosphere. This effort has been motivated, in part, from: (1) a wealth of new satellite data; (2) an urgent need to assess the potential impact of chlorofluorocarbons on our climate; (3) an inadequate understanding of the interactions between the troposphere and stratosphere and the role that such interactions play in short and long-term climate variability; and (4) the realization that addressing changes in our global climate requires understanding the interactions among various components of the earth system. The research currently being carried out represents an effort to address some of these issues by carrying out studies that combine radiation, ozone, seasonal thermal forcing and dynamics. Satellite and ground-based data that is already available is being used to construct basic states for our analytical and numerical models. Significant accomplishments from 1991-1992 are presented and include the following: ozone-dynamics interaction; (2) periodic local forcing and low frequency variability; and (3) steady forcing and low frequency variability.

A Regional Climate Model Evaluation System based on Satellite and other Observations

NASA Astrophysics Data System (ADS)

Lean, P.; Kim, J.; Waliser, D. E.; Hall, A. D.; Mattmann, C. A.; Granger, S. L.; Case, K.; Goodale, C.; Hart, A.; Zimdars, P.; Guan, B.; Molotch, N. P.; Kaki, S.

2010-12-01

Regional climate models are a fundamental tool needed for downscaling global climate simulations and projections, such as those contributing to the Coupled Model Intercomparison Projects (CMIPs) that form the basis of the IPCC Assessment Reports. The regional modeling process provides the means to accommodate higher resolution and a greater complexity of Earth System processes. Evaluation of both the global and regional climate models against observations is essential to identify model weaknesses and to direct future model development efforts focused on reducing the uncertainty associated with climate projections. However, the lack of reliable observational data and the lack of formal tools are among the serious limitations to addressing these objectives. Recent satellite observations are particularly useful as they provide a wealth of information on many different aspects of the climate system, but due to their large volume and the difficulties associated with accessing and using the data, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL / UCLA is developing a model evaluation system to help make satellite observations, in conjunction with in-situ, assimilated, and reanalysis datasets, more readily accessible to the modeling community. The system includes a central database to store multiple datasets in a common format and codes for calculating predefined statistical metrics to assess model performance. This allows the time taken to compare model simulations with satellite observations to be reduced from weeks to days. Early results from the use this new model evaluation system for evaluating regional climate simulations over California/western US regions will be presented.

Cold truths: how winter drives responses of terrestrial organisms to climate change.

PubMed

Williams, Caroline M; Henry, Hugh A L; Sinclair, Brent J

2015-02-01

Winter is a key driver of individual performance, community composition, and ecological interactions in terrestrial habitats. Although climate change research tends to focus on performance in the growing season, climate change is also modifying winter conditions rapidly. Changes to winter temperatures, the variability of winter conditions, and winter snow cover can interact to induce cold injury, alter energy and water balance, advance or retard phenology, and modify community interactions. Species vary in their susceptibility to these winter drivers, hampering efforts to predict biological responses to climate change. Existing frameworks for predicting the impacts of climate change do not incorporate the complexity of organismal responses to winter. Here, we synthesise organismal responses to winter climate change, and use this synthesis to build a framework to predict exposure and sensitivity to negative impacts. This framework can be used to estimate the vulnerability of species to winter climate change. We describe the importance of relationships between winter conditions and performance during the growing season in determining fitness, and demonstrate how summer and winter processes are linked. Incorporating winter into current models will require concerted effort from theoreticians and empiricists, and the expansion of current growing-season studies to incorporate winter. © 2014 The Authors. Biological Reviews © 2014 Cambridge Philosophical Society.

Mainstreaming Climate Change: Recent and Ongoing Efforts to Understand, Improve, and Expand Consideration of Climate Change in Federal Water Resources Planning

NASA Astrophysics Data System (ADS)

Ferguson, I. M.; McGuire, M.; Broman, D.; Gangopadhyay, S.

2017-12-01

The Bureau of Reclamation is a Federal agency tasked with developing and managing water supply and hydropower projects in the Western U.S. Climate and hydrologic variability and change significantly impact management actions and outcomes across Reclamation's programs and initiatives, including water resource planning and operations, infrastructure design and maintenance, hydropower generation, and ecosystem restoration, among others. Planning, design, and implementation of these programs therefore requires consideration of future climate and hydrologic conditions will impact program objectives. Over the past decade, Reclamation and other Federal agencies have adopted new guidelines, directives, and mandates that require consideration of climate change in water resources planning and decision making. Meanwhile, the scientific community has developed a large number of climate projections, along with an array of models, methods, and tools to facilitate consideration of climate projections in planning and decision making. However, water resources engineers, planners, and decision makers continue to face challenges regarding how best to use the available data and tools to support major decisions, including decisions regarding infrastructure investments and long-term operating criteria. This presentation will discuss recent and ongoing research towards understanding, improving, and expanding consideration of climate projections and related uncertainties in Federal water resources planning and decision making. These research efforts address a variety of challenges, including: How to choose between available climate projection datasets and related methods, models, and tools—many of which are considered experimental or research tools? How to select an appropriate decision framework when design or operating alternatives may differ between climate scenarios? How to effectively communicate results of a climate impacts analysis to decision makers? And, how to improve robustness and resilience of water resources systems in the face of significant uncertainty? Discussion will focus on the intersection between technical challenges and decision making paradigms and the need for improved scientist-decision maker engagement through the lens of this Federal water management agency.

Establishing a Framework for Community Modeling in Hydrologic Science: Recommendations from the CUAHSI CHyMP Initiative

NASA Astrophysics Data System (ADS)

Arrigo, J. S.; Famiglietti, J. S.; Murdoch, L. C.; Lakshmi, V.; Hooper, R. P.

2012-12-01

The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) continues a major effort towards supporting Community Hydrologic Modeling. From 2009 - 2011, the Community Hydrologic Modeling Platform (CHyMP) initiative held three workshops, the ultimate goal of which was to produce recommendations and an implementation plan to establish a community modeling program that enables comprehensive simulation of water anywhere on the North American continent. Such an effort would include connections to and advances in global climate models, biogeochemistry, and efforts of other disciplines that require an understanding of water patterns and processes in the environment. To achieve such a vision will require substantial investment in human and cyber-infrastructure and significant advances in the science of hydrologic modeling and spatial scaling. CHyMP concluded with a final workshop, held March 2011, and produced several recommendations. CUAHSI and the university community continue to advance community modeling and implement these recommendations through several related and follow on efforts. Key results from the final 2011 workshop included agreement among participants that the community is ready to move forward with implementation. It is recognized that initial implementation of this larger effort can begin with simulation capabilities that currently exist, or that can be easily developed. CHyMP identified four key activities in support of community modeling: benchmarking, dataset evaluation and development, platform evaluation, and developing a national water model framework. Key findings included: 1) The community supported the idea of a National Water Model framework; a community effort is needed to explore what the ultimate implementation of a National Water Model is. A true community modeling effort would support the modeling of "water anywhere" and would include all relevant scales and processes. 2) Implementation of a community modeling program could initially focus on continental scale modeling of water quantity (rather than quality). The goal of this initial model is the comprehensive description of water stores and fluxes in such a way to permit linkage to GCM's, biogeochemical, ecological, and geomorphic models. This continental scale focus allows systematic evaluation of our current state of knowledge and data, leverages existing efforts done by large scale modelers, contributes to scientific discovery that informs globally and societal relevant questions, and provides an initial framework to evaluate hydrologic information relevant to other disciplines and a structure into which to incorporate other classes of hydrologic models. 3) Dataset development will be a key aspect of any successful national water model implementation. Our current knowledge of the subsurface is limiting our ability to truly integrate soil and groundwater into large scale models, and to answering critical science questions with societal relevance (i.e. groundwater's influence on climate). 4) The CHyMP workshops and efforts to date have achieved collaboration between university scientists, government agencies and the private sector that must be maintained. Follow on efforts in community modeling should aim at leveraging and maintaining this collaboration for maximum scientific and societal benefit.

Efforts to integrate CMIP metadata and standards into NOAA-GFDL's climate model workflow

NASA Astrophysics Data System (ADS)

Blanton, C.; Lee, M.; Mason, E. E.; Radhakrishnan, A.

2017-12-01

Modeling centers participating in CMIP6 run model simulations, publish requested model output (conforming to community data standards), and document models and simulations using ES-DOC. GFDL developed workflow software implementing some best practices to meet these metadata and documentation requirements. The CMIP6 Data Request defines the variables that should be archived for each experiment and specifies their spatial and temporal structure. We used the Data Request's dreqPy python library to write GFDL model configuration files as an alternative to hand-crafted tables. There was also a largely successful effort to standardize variable names within the model to reduce the additional overhead of translating "GFDL to CMOR" variables at a later stage in the pipeline. The ES-DOC ecosystem provides tools and standards to create, publish, and view various types of community-defined CIM documents, most notably model and simulation documents. Although ES-DOC will automatically create simulation documents during publishing by harvesting NetCDF global attributes, the information must be collected, stored, and placed in the NetCDF files by the workflow. We propose to develop a GUI to collect the simulation document precursors. In addition, a new MIP for CMIP6-CPMIP, a comparison of computational performance of climate models-is documented using machine and performance CIM documents. We used ES-DOC's pyesdoc python library to automatically create these machine and performance documents. We hope that these and similar efforts will become permanent features of the GFDL workflow to facilitate future participation in CMIP-like activities.

Downscaling climate information for local disease mapping.

PubMed

Bernardi, M; Gommes, R; Grieser, J

2006-06-01

The study of the impacts of climate on human health requires the interdisciplinary efforts of health professionals, climatologists, biologists, and social scientists to analyze the relationships among physical, biological, ecological, and social systems. As the disease dynamics respond to variations in regional and local climate, climate variability affects every region of the world and the diseases are not necessarily limited to specific regions, so that vectors may become endemic in other regions. Climate data at local level are thus essential to evaluate the dynamics of vector-borne disease through health-climate models and most of the times the climatological databases are not adequate. Climate data at high spatial resolution can be derived by statistical downscaling using historical observations but the method is limited by the availability of historical data at local level. Since the 90s', the statistical interpolation of climate data has been an important priority of the Agrometeorology Group of the Food and Agriculture Organization of the United Nations (FAO), as they are required for agricultural planning and operational activities at the local level. Since 1995, date of the first FAO spatial interpolation software for climate data, more advanced applications have been developed such as SEDI (Satellite Enhanced Data Interpolation) for the downscaling of climate data, LOCCLIM (Local Climate Estimator) and the NEW_LOCCLIM in collaboration with the Deutscher Wetterdienst (German Weather Service) to estimate climatic conditions at locations for which no observations are available. In parallel, an important effort has been made to improve the FAO climate database including at present more than 30,000 stations worldwide and expanding the database from developing countries coverage to global coverage.

Check-Up of Planet Earth at the Turn of the Millennium Anticipated New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Yoram

1999-01-01

Langley's remarkable solar and lunar spectra collected from mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite named recently "Terra" (by Ms. Sasha Jones, a 17 year old student in St. Louis, MO) will repeat Langley's experiment, but for the entire planet, thus pioneering calibrated spectral observations from space. Conceived in response to real environmental problems, EOS-AM, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-AM can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In this talk I shall a give a historical perspective for the need for this expensive mission, give examples of the science that we anticipate to achieve using Terra measurements and describe this exciting mission.

Rural perspectives of climate change: a study from Saurastra and Kutch of Western India.

PubMed

Moghariya, Dineshkumar P; Smardon, Richard C

2014-08-01

This research reports on rural people's beliefs and understandings of climate change in the Saurastra/ Kutch region of Western India. Results suggest that although most rural respondents have not heard about the scientific concept of climate change, they have detected changes in the climate. They appear to hold divergent understandings about climate change and have different priorities for causes and solutions. Many respondents appear to base their understandings of climate change upon a mix of ideas drawn from various sources and rely on different kinds of reasoning in relation to both causes of and solutions to climate change to those used by scientists. Environmental conditions were found to influence individuals' understanding of climate change, while demographic factors were not. The results suggest a need to learn more about people's conceptual models and understandings of climate change and a need to include local climate research in communication efforts.

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2015-01-01

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Weather and extremes in the last Millennium - a challenge for climate modelling

NASA Astrophysics Data System (ADS)

Raible, Christoph C.; Blumer, Sandro R.; Gomez-Navarro, Juan J.; Lehner, Flavio

2015-04-01

Changes in the climate mean state are expected to influence society, but the socio-economic sensitivity to extreme events might be even more severe. Whether or not the current frequency and severity of extreme events is a unique characteristic of anthropogenic-driven climate change can be assessed by putting the observed changes in a long-term perspective. In doing so, early instrumental series and proxy archives are a rich source to investigate also extreme events, in particular during the last millennium, yet they suffer from spatial and temporal scarcity. Therefore, simulations with coupled general circulation models (GCMs) could fill such gaps and help in deepening our process understanding. In this study, an overview of past and current efforts as well as challenges in modelling paleo weather and extreme events is presented. Using simulations of the last millennium we investigate extreme midlatitude cyclone characteristics, precipitation, and their connection to large-scale atmospheric patterns in the North Atlantic European region. In cold climate states such as the Maunder Minimum, the North Atlantic Oscillation (NAO) is found to be predominantly in its negative phase. In this sense, simulations of different models agree with proxy findings for this period. However, some proxy data available for this period suggests an increase in storminess during this period, which could be interpreted as a positive phase of the NAO - a superficial contradiction. The simulated cyclones are partly reduced over Europe, which is consistent with the aforementioned negative phase of the NAO. However, as the meridional temperature gradient is increased during this period - which constitutes a source of low-level baroclincity - they also intensify. This example illustrates how model simulations could be used to improve our proxy interpretation and to gain additional process understanding. Nevertheless, there are also limitations associated with climate modeling efforts to simulate the last millennium. In particular, these models still struggle to properly simulate atmospheric blocking events, an important dynamical feature for dry conditions during summer times. Finally, new and promising ways in improving past climate modelling are briefly introduced. In particular, the use of dynamical downscaling is a powerful tool to bridge the gap between the coarsely resolved GCMs and characteristics of the regional climate, which is potentially recorded in proxy archives. In particular, the representation of extreme events could be improved by dynamical downscaling as processes are better resolved than GCMs.

Making the climate part of the human world: Why addressing beliefs and biases is necessary part of effective climate change education

NASA Astrophysics Data System (ADS)

Donner, S. D.

2009-12-01

Efforts to raise public awareness and understanding of the social, cultural and economic consequences of climate change often encounter skepticism. The primary causes of this skepticism, whether in the form of a mild rejection of proposed policy responses or an outright rejection of the basic scientific findings, is often cited to be the poor framing of issues by the scientific community, the quality of science education or public science literacy, disinformation campaigns by representatives of the coal and gas industry, individual resistance to behavioral change, and the hyperactive nature of the modern information culture. However, the root cause may be that the weather and climate, and by association climate change, is viewed as independent of the sphere of human influence in ancient and modern societies. In this presentation, I will outline how long-standing human beliefs in the separation between the earth and the sky and the modern framing of climate change as an “environmental” issue are limiting efforts to education the public about the causes, effects and possible response to climate change. First, sociological research in the Pacific Islands (Fiji, Kiribati, Tuvalu) finds strong evidence that beliefs in divine control of the weather and climate limit public acceptance of human-induced climate change. Second, media analysis and polling data from North America supports the role of belief and provides further evidence that climate change is viewed as a threat to an “other” labeled “the environment”, rather than a threat to people or society. The consequences of these mental models of the climate can be an outright reject of scientific theory related to climate change, a milder distrust of climate change predictions, a lack of urgency about mitigation, and an underestimate of the effort required to adapt to climate change. In order to be effective, public education about climate change needs to directly address the two, critical beliefs held by the majority of the audience. Proposed solutions include re-casting climate change as a broad societal concern, thus rejecting characterization of climate change as “environmental issue”, and clearly expressing to the audience the historical reasons why climate change may be hard to “believe”

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

PubMed

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

2018-03-01

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

Application of a Hybrid Forest Growth Model to Evaluate Climate Change Impacts on Productivity, Nutrient Cycling and Mortality in a Montane Forest Ecosystem.

PubMed

Seely, Brad; Welham, Clive; Scoullar, Kim

2015-01-01

Climate change introduces considerable uncertainty in forest management planning and outcomes, potentially undermining efforts at achieving sustainable practices. Here, we describe the development and application of the FORECAST Climate model. Constructed using a hybrid simulation approach, the model includes an explicit representation of the effect of temperature and moisture availability on tree growth and survival, litter decomposition, and nutrient cycling. The model also includes a representation of the impact of increasing atmospheric CO2 on water use efficiency, but no direct CO2 fertilization effect. FORECAST Climate was evaluated for its ability to reproduce the effects of historical climate on Douglas-fir and lodgepole pine growth in a montane forest in southern British Columbia, Canada, as measured using tree ring analysis. The model was subsequently used to project the long-term impacts of alternative future climate change scenarios on forest productivity in young and established stands. There was a close association between predicted sapwood production and measured tree ring chronologies, providing confidence that model is able to predict the relative impact of annual climate variability on tree productivity. Simulations of future climate change suggest a modest increase in productivity in young stands of both species related to an increase in growing season length. In contrast, results showed a negative impact on stemwood biomass production (particularly in the case of lodgepole pine) for established stands due to increased moisture stress mortality.

Application of a Hybrid Forest Growth Model to Evaluate Climate Change Impacts on Productivity, Nutrient Cycling and Mortality in a Montane Forest Ecosystem

PubMed Central

Seely, Brad; Welham, Clive; Scoullar, Kim

2015-01-01

Climate change introduces considerable uncertainty in forest management planning and outcomes, potentially undermining efforts at achieving sustainable practices. Here, we describe the development and application of the FORECAST Climate model. Constructed using a hybrid simulation approach, the model includes an explicit representation of the effect of temperature and moisture availability on tree growth and survival, litter decomposition, and nutrient cycling. The model also includes a representation of the impact of increasing atmospheric CO2 on water use efficiency, but no direct CO2 fertilization effect. FORECAST Climate was evaluated for its ability to reproduce the effects of historical climate on Douglas-fir and lodgepole pine growth in a montane forest in southern British Columbia, Canada, as measured using tree ring analysis. The model was subsequently used to project the long-term impacts of alternative future climate change scenarios on forest productivity in young and established stands. There was a close association between predicted sapwood production and measured tree ring chronologies, providing confidence that model is able to predict the relative impact of annual climate variability on tree productivity. Simulations of future climate change suggest a modest increase in productivity in young stands of both species related to an increase in growing season length. In contrast, results showed a negative impact on stemwood biomass production (particularly in the case of lodgepole pine) for established stands due to increased moisture stress mortality. PMID:26267446

REGRESSION MODELS THAT RELATE STREAMS TO WATERSHEDS: COPING WITH NUMEROUS, COLLINEAR PEDICTORS

EPA Science Inventory

GIS efforts can produce a very large number of watershed variables (climate, land use/land cover and topography, all defined for multiple areas of influence) that could serve as candidate predictors in a regression model of reach-scale stream features. Invariably, many of these ...

A multi-model assessment of the co-benefits of climate mitigation for global air quality

NASA Astrophysics Data System (ADS)

Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana; Riahi, Keywan; van Dingenen, Rita; Aleluia Reis, Lara; Calvin, Katherine; Dentener, Frank; Drouet, Laurent; Fujimori, Shinichiro; Harmsen, Mathijs; Luderer, Gunnar; Heyes, Chris; Strefler, Jessica; Tavoni, Massimo; van Vuuren, Detlef P.

2016-12-01

We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We include in our assessment, a range of alternative assumptions on the implementation of current and planned pollution control policies. The resulting air pollution emission ranges significantly extend those in the Representative Concentration Pathways. Climate mitigation policies complement current efforts on air pollution control through technology and fuel transformations in the energy system. A combination of stringent policies on air pollution control and climate change mitigation results in 40% of the global population exposed to PM levels below the WHO air quality guideline; with the largest improvements estimated for India, China, and Middle East. Our results stress the importance of integrated multisector policy approaches to achieve the Sustainable Development Goals.

Defining climate modeling user needs: which data are actually required to support impact analysis and adaptation policy development?

NASA Astrophysics Data System (ADS)

Swart, R. J.; Pagé, C.

2010-12-01

Until recently, the policy applications of Earth System Models in general and climate models in particular were focusing mainly on the potential future changes in the global and regional climate and attribution of observed changes to anthropogenic activities. Is climate change real? And if so, why do we have to worry about it? Following the broad acceptance of the reality of the risks by the majority of governments, particularly after the publication of IPCC’s 4th Assessment Report and the increasing number of observations of changes in ecological and socio-economic systems that are consistent with the observed climatic changes, governments, companies and other societal groups have started to evaluate their own vulnerability in more detail and to develop adaptation and mitigation strategies. After an early focus on the most vulnerable developing countries, recently, an increasing number of industrialized countries have embarked on the design of adaptation and mitigation plans, or on studies to evaluate the level of climate resilience of their development plans and projects. Which climate data are actually required to effectively support these activities? This paper reports on the efforts of the IS-ENES project, the infrastructure project of the European Network for Earth System Modeling, to address this question. How do we define user needs and can the existing gap between the climate modeling and impact research communities be bridged in support of the ENES long-term strategy? In contrast from the climate modeling community, which has a relatively long history of collaboration facilitated by a relatively uniform subject matter, commonly agreed definitions of key terminology and some level of harmonization of methods, the climate change impacts research community is very diverse and fragmented, using a wide variety of data sources, methods and tools. An additional complicating factor is that researchers working on adaptation usually closely collaborate with non-scientific stakeholders in government, civil society and the private sector, in a context which is different in many European countries. In the IS-ENES effort, a dialogue is set up between the communities in Europe, building on various existing research networks in the area of climate change impacts, vulnerability and adaptation. Generally, the data needs have not been well articulated. If asked, people working on impacts and adaptation routinely seem to ask for data with the highest possible resolution. However, in reality for many impact and adaptation applications this is not needed, and the large resulting data sets may exceed the analytical capacity of the impact researchers. For impact analysis often various types of climate indices, derived from primary climate model output variables, are required, including indices for extremes and in probabilistic format. Rather than making output from climate modeling generically available, e.g. through a climate service e-portal, context-specific tailoring of information for specific applications is important for effective use. This may require some level of interaction between the users and the data providers, dependent on the specific questions to be addressed.

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

NASA Technical Reports Server (NTRS)

Geller, Marvin A.; Alexadner, M. Joan; Love, Peter T.; Bacmeister, Julio; Ern, Manfred; Hertzog, Albert; Manzini, Elisa; Preusse, Peter; Sato, Kaoru; Scaife, Adam A.;

Robust Emergent Climate Phenomena Associated with the High-Sensitivity Tail

NASA Astrophysics Data System (ADS)

Boslough, M.; Levy, M.; Backus, G.

2010-12-01

Because the potential effects of climate change are more severe than had previously been thought, increasing focus on uncertainty quantification is required for risk assessment needed by policy makers. Current scientific efforts focus almost exclusively on establishing best estimates of future climate change. However, the greatest consequences occur in the extreme tail of the probability density functions for climate sensitivity (the “high-sensitivity tail”). To this end, we are exploring the impacts of newly postulated, highly uncertain, but high-consequence physical mechanisms to better establish the climate change risk. We define consequence in terms of dramatic change in physical conditions and in the resulting socioeconomic impact (hence, risk) on populations. Although we are developing generally applicable risk assessment methods, we have focused our initial efforts on uncertainty and risk analyses for the Arctic region. Instead of focusing on best estimates, requiring many years of model parameterization development and evaluation, we are focusing on robust emergent phenomena (those that are not necessarily intuitive and are insensitive to assumptions, subgrid-parameterizations, and tunings). For many physical systems, under-resolved models fail to generate such phenomena, which only develop when model resolution is sufficiently high. Our ultimate goal is to discover the patterns of emergent climate precursors (those that cannot be predicted with lower-resolution models) that can be used as a "sensitivity fingerprint" and make recommendations for a climate early warning system that would use satellites and sensor arrays to look for the various predicted high-sensitivity signatures. Our initial simulations are focused on the Arctic region, where underpredicted phenomena such as rapid loss of sea ice are already emerging, and because of major geopolitical implications associated with increasing Arctic accessibility to natural resources, shipping routes, and strategic locations. We anticipate that regional climate will be strongly influenced by feedbacks associated with a seasonally ice-free Arctic, but with unknown emergent phenomena. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE-AC04-94AL85000.

Climate Data Initiative: A Geocuration Effort to Support Climate Resilience

NASA Technical Reports Server (NTRS)

Ramachandran, Rahul; Bugbee, Kaylin; Tilmes, Curt; Pinheiro Privette, Ana

2015-01-01

Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. In this paper, we introduce the concept of geocuration and define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful compendium We present the Climate Data Initiative (CDI) project as an exemplar example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate-change preparedness. We describe the geocuration process used in CDI project, lessons learned, and suggestions to improve similar geocuration efforts in the future.

Climate data initiative: A geocuration effort to support climate resilience

NASA Astrophysics Data System (ADS)

Ramachandran, Rahul; Bugbee, Kaylin; Tilmes, Curt; Privette, Ana Pinheiro

2016-03-01

Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. In this paper, we introduce the concept of geocuration and define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful collection. We present the Climate Data Initiative (CDI) project as a prototypical example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate-change preparedness. We describe the geocuration process used in the CDI project, lessons learned, and suggestions to improve similar geocuration efforts in the future.

Ocean salinities reveal strong global water cycle intensification during 1950 to 2000.

PubMed

Durack, Paul J; Wijffels, Susan E; Matear, Richard J

2012-04-27

Fundamental thermodynamics and climate models suggest that dry regions will become drier and wet regions will become wetter in response to warming. Efforts to detect this long-term response in sparse surface observations of rainfall and evaporation remain ambiguous. We show that ocean salinity patterns express an identifiable fingerprint of an intensifying water cycle. Our 50-year observed global surface salinity changes, combined with changes from global climate models, present robust evidence of an intensified global water cycle at a rate of 8 ± 5% per degree of surface warming. This rate is double the response projected by current-generation climate models and suggests that a substantial (16 to 24%) intensification of the global water cycle will occur in a future 2° to 3° warmer world.

Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

PubMed

Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

2015-04-01

Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.

Lake Representations in Global Climate Models: An End-User Perspective

NASA Astrophysics Data System (ADS)

Rood, R. B.; Briley, L.; Steiner, A.; Wells, K.

2017-12-01

The weather and climate in the Great Lakes region of the United States and Canada are strongly influenced by the lakes. Within global climate models, lakes are incorporated in many ways. If one is interested in quantitative climate information for the Great Lakes, then it is a first principle requirement that end-users of climate model simulation data, whether scientists or practitioners, need to know if and how lakes are incorporated into models. We pose the basic question, how are lakes represented in CMIP models? Despite significant efforts by the climate community to document and publish basic information about climate models, it is unclear how to answer the question about lake representations? With significant knowledge of the practice of the field, then a reasonable starting point is to use the ES-DOC Comparator (https://compare.es-doc.org/ ). Once at this interface to model information, the end-user is faced with the need for more knowledge about the practice and culture of the discipline. For example, lakes are often categorized as a type of land, a counterintuitive concept. In some models, though, lakes are specified in ocean models. There is little evidence and little confidence that the information obtained through this process is complete or accurate. In fact, it is verifiably not accurate. This experience, then, motivates identifying and finding either human experts or technical documentation for each model. The conclusion from this exercise is that it can take months or longer to provide a defensible answer to if and how lakes are represented in climate models. Our experience with lake finding is that this is not a unique experience. This talk documents our experience and explores barriers we have identified and strategies for reducing those barriers.

MODELING THE EFFECTS OF CLIMATE AND LAND USE CHANGE ON CARBON AND TRACE GAS BUDGETS OVER THE AMAZON REGION USING NASA SATELLITE PRODUCTS

EPA Science Inventory

As part of the LBA-ECO Phase III synthesis efforts for remote sensing and predictive modeling of Amazon carbon, water, and trace gas fluxes, we are evaluating results from the regional ecosystem model called NASA-CASA (Carnegie-Ames Stanford Approach). The NASA-CASA model has bee...

Role of Atmospheric Chemistry in the Climate Impacts of Stratospheric Volcanic Injections

NASA Technical Reports Server (NTRS)

Legrande, Allegra N.; Tsigaridis, Kostas; Bauer, Susanne E.

2016-01-01

The climate impact of a volcanic eruption is known to be dependent on the size, location and timing of the eruption. However, the chemistry and composition of the volcanic plume also control its impact on climate. It is not just sulfur dioxide gas, but also the coincident emissions of water, halogens and ash that influence the radiative and climate forcing of an eruption. Improvements in the capability of models to capture aerosol microphysics, and the inclusion of chemistry and aerosol microphysics modules in Earth system models, allow us to evaluate the interaction of composition and chemistry within volcanic plumes in a new way. These modeling efforts also illustrate the role of water vapor in controlling the chemical evolution, and hence climate impacts, of the plume. A growing realization of the importance of the chemical composition of volcanic plumes is leading to a more sophisticated and realistic representation of volcanic forcing in climate simulations, which in turn aids in reconciling simulations and proxy reconstructions of the climate impacts of past volcanic eruptions. More sophisticated simulations are expected to help, eventually, with predictions of the impact on the Earth system of any future large volcanic eruptions.

Synergy between land use and climate change increases future fire risk in Amazon forests

DOE PAGES

Le Page, Yannick; Morton, Douglas; Hartin, Corinne; ...

2017-12-20

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactionsmore » between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.« less

Synergy between land use and climate change increases future fire risk in Amazon forests

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

Le Page, Yannick; Morton, Douglas; Hartin, Corinne

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactionsmore » between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.« less

Psychosocial influences on safety climate: evidence from community pharmacies.

PubMed

Phipps, Denham L; Ashcroft, Darren M

2011-12-01

To examine the relationship between psychosocial job characteristics and safety climate. Cross-sectional survey. Community pharmacies in Great Britain. Participants A random sample of community pharmacists registered in Great Britain (n = 860). Survey instruments Effort-reward imbalance (ERI) indicator and Job Content Questionnaire (JCQ). Main outcome measures Pharmacy Safety Climate Questionnaire (PSCQ). The profile of scores from the ERI indicated a relatively high risk of adverse psychological effects. The profile of scores from the JCQ indicated both high demand on pharmacists and a high level of psychological and social resources to meet these demands. Path analysis confirmed a model in which the ERI and JCQ measures, as well as the type of pharmacy and pharmacist role, predicted responses to the PSCQ (χ(2)(36) = 111.38, p < 0.001; Tucker-Lewis index = 0.96; comparative fit index = 0.98; root mean square error of approximation=0.05). Two general factors (effort vs reward and control vs demand) accounted for the effect of job characteristics on safety climate ratings; each had differential effects on the PSCQ scales. The safety climate in community pharmacies is influenced by perceptions of job characteristics, such as the level of job demands and the resources available to meet these demands. Hence, any efforts to improve safety should take into consideration the effect of the psychosocial work environment on safety climate. In addition, there is a need to address the presence of work-related stressors, which have the potential to cause direct or indirect harm to staff and service users. The findings of the current study provide a basis for future research to improve the safety climate and well-being, both in the pharmacy profession and in other healthcare settings.

Leadership, Organizational Climate, and Working Alliance in a Children's Mental Health Service System

PubMed Central

Green, Amy E.; Albanese, Brian J.; Cafri, Guy; Aarons, Gregory A.

2014-01-01

The goal of this study was to examine the relationships of transformational leadership and organizational climate with working alliance, in a children's mental health service system. Using multilevel structural equation modeling, the effect of leadership on working alliance was mediated by organizational climate. These results suggest that supervisors may be able to impact quality of care through improving workplace climate. Organizational factors should be considered in efforts to improve public sector services. Understanding these issues is important for program leaders, mental health service providers, and consumers because they can affect both the way services are delivered and ultimately, clinical outcomes. PMID:24323137

Leadership, organizational climate, and working alliance in a children's mental health service system.

PubMed

Green, Amy E; Albanese, Brian J; Cafri, Guy; Aarons, Gregory A

2014-10-01

The goal of this study was to examine the relationships of transformational leadership and organizational climate with working alliance, in a children's mental health service system. Using multilevel structural equation modeling, the effect of leadership on working alliance was mediated by organizational climate. These results suggest that supervisors may be able to impact quality of care through improving workplace climate. Organizational factors should be considered in efforts to improve public sector services. Understanding these issues is important for program leaders, mental health service providers, and consumers because they can affect both the way services are delivered and ultimately, clinical outcomes.

Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

NASA Astrophysics Data System (ADS)

Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

2017-12-01

At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.

Implications of climate change for wetland-dependent birds in the Prairie Pothole Region

USGS Publications Warehouse

Steen, Valerie; Skagen, Susan K.; Melcher, Cynthia P.

2016-01-01

The habitats and food resources required to support breeding and migrant birds dependent on North American prairie wetlands are threatened by impending climate change. The North American Prairie Pothole Region (PPR) hosts nearly 120 species of wetland-dependent birds representing 21 families. Strategic management requires knowledge of avian habitat requirements and assessment of species most vulnerable to future threats. We applied bioclimatic species distribution models (SDMs) to project range changes of 29 wetland-dependent bird species using ensemble modeling techniques, a large number of General Circulation Models (GCMs), and hydrological climate covariates. For the U.S. PPR, mean projected range change, expressed as a proportion of currently occupied range, was −0.31 (± 0.22 SD; range − 0.75 to 0.16), and all but two species were projected to lose habitat. Species associated with deeper water were expected to experience smaller negative impacts of climate change. The magnitude of climate change impacts was somewhat lower in this study than earlier efforts most likely due to use of different focal species, varying methodologies, different modeling decisions, or alternative GCMs. Quantification of the projected species-specific impacts of climate change using species distribution modeling offers valuable information for vulnerability assessments within the conservation planning process.

Identifying alternate pathways for climate change to impact inland recreational fishers

USGS Publications Warehouse

Hunt, Len M.; Fenichel, Eli P.; Fulton, David C.; Mendelsohn, Robert; Smith, Jordan W.; Tunney, Tyler D.; Lynch, Abigail J.; Paukert, Craig P.; Whitney, James E.

2016-01-01

Fisheries and human dimensions literature suggests that climate change influences inland recreational fishers in North America through three major pathways. The most widely recognized pathway suggests that climate change impacts habitat and fish populations (e.g., water temperature impacting fish survival) and cascades to impact fishers. Climate change also impacts recreational fishers by influencing environmental conditions that directly affect fishers (e.g., increased temperatures in northern climates resulting in extended open water fishing seasons and increased fishing effort). The final pathway occurs from climate change mitigation and adaptation efforts (e.g., refined energy policies result in higher fuel costs, making distant trips more expensive). To address limitations of past research (e.g., assessing climate change impacts for only one pathway at a time and not accounting for climate variability, extreme weather events, or heterogeneity among fishers), we encourage researchers to refocus their efforts to understand and document climate change impacts to inland fishers.

Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia

PubMed Central

Eastin, Matthew D.; Delmelle, Eric; Casas, Irene; Wexler, Joshua; Self, Cameron

2014-01-01

Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors—all of which are influenced by environmental factors. Predictive models of dengue incidence rate, based on local weather and regional climate parameters, could benefit disease mitigation efforts. Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011. Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C—the optimal range for mosquito survival and viral transmission. Two environment-based, multivariate, autoregressive forecast models are developed that allow dengue outbreaks to be anticipated from 2 weeks to 6 months in advance. These models have the potential to enhance existing dengue early warning systems, ultimately supporting public health decisions on the timing and scale of vector control efforts. PMID:24957546

Using Citizen Science Data to Model the Distributions of Common Songbirds of Turkey Under Different Global Climatic Change Scenarios

PubMed Central

Abolafya, Moris; Onmuş, Ortaç; Şekercioğlu, Çağan H.; Bilgin, Raşit

2013-01-01

In this study, we evaluated the potential impact of climate change on the distributions of Turkey’s songbirds in the 21st century by modelling future distributions of 20 resident and nine migratory species under two global climate change scenarios. We combined verified data from an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic variables to estimate species distributions and projections for future time periods. Model predictions for resident and migratory species showed high variability, with some species projected to lose and others projected to gain suitable habitat. Our study helps improve the understanding of the current and potential future distributions of Turkey’s songbirds and their responses to climate change, highlights effective strategies to maximize avian conservation efforts in the study region, and provides a model for using citizen science data for biodiversity research in a large developing country with few professional field biologists. Our results demonstrate that climate change will not affect every species equally in Turkey. Expected range reductions in some breeding species will increase the risk of local extinction, whereas others are likely to expand their ranges. PMID:23844151

Using citizen science data to model the distributions of common songbirds of Turkey under different global climatic change scenarios.

PubMed

Abolafya, Moris; Onmuş, Ortaç; Şekercioğlu, Çağan H; Bilgin, Raşit

2013-01-01

In this study, we evaluated the potential impact of climate change on the distributions of Turkey's songbirds in the 21st century by modelling future distributions of 20 resident and nine migratory species under two global climate change scenarios. We combined verified data from an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic variables to estimate species distributions and projections for future time periods. Model predictions for resident and migratory species showed high variability, with some species projected to lose and others projected to gain suitable habitat. Our study helps improve the understanding of the current and potential future distributions of Turkey's songbirds and their responses to climate change, highlights effective strategies to maximize avian conservation efforts in the study region, and provides a model for using citizen science data for biodiversity research in a large developing country with few professional field biologists. Our results demonstrate that climate change will not affect every species equally in Turkey. Expected range reductions in some breeding species will increase the risk of local extinction, whereas others are likely to expand their ranges.

Fire management, managed relocation, and land conservation options for long-lived obligate seeding plants under global changes in climate, urbanization, and fire regime.

PubMed

Bonebrake, Timothy C; Syphard, Alexandra D; Franklin, Janet; Anderson, Kurt E; Akçakaya, H Resit; Mizerek, Toni; Winchell, Clark; Regan, Helen M

2014-08-01

Most species face multiple anthropogenic disruptions. Few studies have quantified the cumulative influence of multiple threats on species of conservation concern, and far fewer have quantified the potential relative value of multiple conservation interventions in light of these threats. We linked spatial distribution and population viability models to explore conservation interventions under projected climate change, urbanization, and changes in fire regime on a long-lived obligate seeding plant species sensitive to high fire frequencies, a dominant plant functional type in many fire-prone ecosystems, including the biodiversity hotspots of Mediterranean-type ecosystems. First, we investigated the relative risk of population decline for plant populations in landscapes with and without land protection under an existing habitat conservation plan. Second, we modeled the effectiveness of relocating both seedlings and seeds from a large patch with predicted declines in habitat area to 2 unoccupied recipient patches with increasing habitat area under 2 projected climate change scenarios. Finally, we modeled 8 fire return intervals (FRIs) approximating the outcomes of different management strategies that effectively control fire frequency. Invariably, long-lived obligate seeding populations remained viable only when FRIs were maintained at or above a minimum level. Land conservation and seedling relocation efforts lessened the impact of climate change and land-use change on obligate seeding populations to differing degrees depending on the climate change scenario, but neither of these efforts was as generally effective as frequent translocation of seeds. While none of the modeled strategies fully compensated for the effects of land-use and climate change, an integrative approach managing multiple threats may diminish population declines for species in complex landscapes. Conservation plans designed to mitigate the impacts of a single threat are likely to fail if additional threats are ignored. © 2014 Society for Conservation Biology.

Computational data sciences for assessment and prediction of climate extremes

NASA Astrophysics Data System (ADS)

Ganguly, A. R.

2011-12-01

Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.

US forest response to projected climate-related stress: a tolerance perspective.

PubMed

Liénard, Jean; Harrison, John; Strigul, Nikolay

2016-08-01

Although it is widely recognized that climate change will require a major spatial reorganization of forests, our ability to predict exactly how and where forest characteristics and distributions will change has been rather limited. Current efforts to predict future distribution of forested ecosystems as a function of climate include species distribution models (for fine-scale predictions) and potential vegetation climate envelope models (for coarse-grained, large-scale predictions). Here, we develop and apply an intermediate approach wherein we use stand-level tolerances of environmental stressors to understand forest distributions and vulnerabilities to anticipated climate change. In contrast to other existing models, this approach can be applied at a continental scale while maintaining a direct link to ecologically relevant, climate-related stressors. We first demonstrate that shade, drought, and waterlogging tolerances of forest stands are strongly correlated with climate and edaphic conditions in the conterminous United States. This discovery allows the development of a tolerance distribution model (TDM), a novel quantitative tool to assess landscape level impacts of climate change. We then focus on evaluating the implications of the drought TDM. Using an ensemble of 17 climate change models to drive this TDM, we estimate that 18% of US ecosystems are vulnerable to drought-related stress over the coming century. Vulnerable areas include mostly the Midwest United States and Northeast United States, as well as high-elevation areas of the Rocky Mountains. We also infer stress incurred by shifting climate should create an opening for the establishment of forest types not currently seen in the conterminous United States. © 2016 John Wiley & Sons Ltd.

Assessing the effects of fire disturbances on ecosystems: A scientific agenda for research and management

USGS Publications Warehouse

Schmoldt, D.L.; Peterson, D.L.; Keane, R.E.; Lenihan, J.M.; McKenzie, D.; Weise, D.R.; Sandberg, D.V.

1999-01-01

A team of fire scientists and resource managers convened 17-19 April 1996 in Seattle, Washington, to assess the effects of fire disturbance on ecosystems. Objectives of this workshop were to develop scientific recommendations for future fire research and management activities. These recommendations included a series of numerically ranked scientific and managerial questions and responses focusing on (1) links among fire effects, fuels, and climate; (2) fire as a large-scale disturbance; (3) fire-effects modeling structures; and (4) managerial concerns, applications, and decision support. At the present time, understanding of fire effects and the ability to extrapolate fire-effects knowledge to large spatial scales are limited, because most data have been collected at small spatial scales for specific applications. Although we clearly need more large-scale fire-effects data, it will be more expedient to concentrate efforts on improving and linking existing models that simulate fire effects in a georeferenced format while integrating empirical data as they become available. A significant component of this effort should be improved communication between modelers and managers to develop modeling tools to use in a planning context. Another component of this modeling effort should improve our ability to predict the interactions of fire and potential climatic change at very large spatial scales. The priority issues and approaches described here provide a template for fire science and fire management programs in the next decade and beyond.

An Update on Experimental Climate Prediction and Analysis Products Being Developed at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2011-01-01

The Global Modeling and Assimilation Office at NASA's Goddard Space Flight Center is developing a number of experimental prediction and analysis products suitable for research and applications. The prediction products include a large suite of subseasonal and seasonal hindcasts and forecasts (as a contribution to the US National MME), a suite of decadal (10-year) hindcasts (as a contribution to the IPCC decadal prediction project), and a series of large ensemble and high resolution simulations of selected extreme events, including the 2010 Russian and 2011 US heat waves. The analysis products include an experimental atlas of climate (in particular drought) and weather extremes. This talk will provide an update on those activities, and discuss recent efforts by WCRP to leverage off these and similar efforts at other institutions throughout the world to develop an experimental global drought early warning system.

Climate change and dengue fever transmission in China: Evidences and challenges.

PubMed

Li, Chenlu; Lu, Yongmei; Liu, Jianing; Wu, Xiaoxu

2018-05-01

Dengue Fever (DF) has become one of the most serious infectious diseases in China. Dengue virus and its vector (Aedes mosquito) are known to be sensitive to climate condition. Climate impacts DF through affecting three essential bioecological aspects: DF virus, vector (mosquito) and DF transmission environment. Weather-based DF model, mosquito model and climate model are the three pillars to help the prediction of DF distribution. Through a systematic review of literature between 1980 and 2017, this paper summarizes empirical evidences in China on the impact of climate change on DF; it further reviews the related DF incidence models and their findings on how changes in weather factors may impact DF occurrences in China. Compared with some well-known research projects in the western countries, there is a lack of knowledge in China regarding how the spatiotemporal distribution of DF will respond to climate change. However, being able to predict DF distribution is key to China's efforts to prevent and control DF transmission. We conclude this paper by recommending four focused areas for China: promoting more advanced research on the relationship between extreme weather events and DF, developing regional-specific models for the high risk regions of DF in south China, encouraging interdisciplinary collaboration between climate studies and health services, and enhancing public health education and management at national, regional and local levels. Copyright © 2017 Elsevier B.V. All rights reserved.

Changing currents: a strategy for understanding and predicting the changing ocean circulation.

PubMed

Bryden, Harry L; Robinson, Carol; Griffiths, Gwyn

2012-12-13

Within the context of UK marine science, we project a strategy for ocean circulation research over the next 20 years. We recommend a focus on three types of research: (i) sustained observations of the varying and evolving ocean circulation, (ii) careful analysis and interpretation of the observed climate changes for comparison with climate model projections, and (iii) the design and execution of focused field experiments to understand ocean processes that are not resolved in coupled climate models so as to be able to embed these processes realistically in the models. Within UK-sustained observations, we emphasize smart, cost-effective design of the observational network to extract maximum information from limited field resources. We encourage the incorporation of new sensors and new energy sources within the operational environment of UK-sustained observational programmes to bridge the gap that normally separates laboratory prototype from operational instrument. For interpreting the climate-change records obtained through a variety of national and international sustained observational programmes, creative and dedicated UK scientists should lead efforts to extract the meaningful signals and patterns of climate change and to interpret them so as to project future changes. For the process studies, individual scientists will need to work together in team environments to combine observational and process modelling results into effective improvements in the coupled climate models that will lead to more accurate climate predictions.

Advancing Climate Change and Impacts Science Through Climate Informatics

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology

NASA Technical Reports Server (NTRS)

Jagge, Amy

2016-01-01

With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data for the NASA Johnson Space Center into a NASA-Wide GIS Institutional Portal.

Connecting today's climates to future climate analogs to facilitate movement of species under climate change.

PubMed

Littlefield, Caitlin E; McRae, Brad H; Michalak, Julia L; Lawler, Joshua J; Carroll, Carlos

2017-12-01

Increasing connectivity is an important strategy for facilitating species range shifts and maintaining biodiversity in the face of climate change. To date, however, few researchers have included future climate projections in efforts to prioritize areas for increasing connectivity. We identified key areas likely to facilitate climate-induced species' movement across western North America. Using historical climate data sets and future climate projections, we mapped potential species' movement routes that link current climate conditions to analogous climate conditions in the future (i.e., future climate analogs) with a novel moving-window analysis based on electrical circuit theory. In addition to tracing shifting climates, the approach accounted for landscape permeability and empirically derived species' dispersal capabilities. We compared connectivity maps generated with our climate-change-informed approach with maps of connectivity based solely on the degree of human modification of the landscape. Including future climate projections in connectivity models substantially shifted and constrained priority areas for movement to a smaller proportion of the landscape than when climate projections were not considered. Potential movement, measured as current flow, decreased in all ecoregions when climate projections were included, particularly when dispersal was limited, which made climate analogs inaccessible. Many areas emerged as important for connectivity only when climate change was modeled in 2 time steps rather than in a single time step. Our results illustrate that movement routes needed to track changing climatic conditions may differ from those that connect present-day landscapes. Incorporating future climate projections into connectivity modeling is an important step toward facilitating successful species movement and population persistence in a changing climate. © 2017 Society for Conservation Biology.

Climate Modeling and Causal Identification for Sea Ice Predictability

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

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

This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments inmore » which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.« less

Quantifying Impacts of Land-use and Land Cover Change in a Changing Climate at the Regional Scale using an Integrated Earth System Modeling Approach

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

Earth System models (ESMs) are effective tools for investigating the water-energy-food system interactions under climate change. In this presentation, I will introduce research efforts at the Pacific Northwest National Laboratory towards quantifying impacts of LULCC on the water-energy-food nexus in a changing climate using an integrated regional Earth system modeling framework: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Two studies will be discussed to showcase the capability of PRIMA: (1) quantifying changes in terrestrial hydrology over the Conterminous US (CONUS) from 2005 to 2095 using the Community Land Model (CLM) driven by high-resolution downscaled climate and land cover products from PRIMA, which was designed for assessing the impacts of and potential responses to climate and anthropogenic changes at regional scales; (2) applying CLM over the CONUS to provide the first county-scale model validation in simulating crop yields and assessing associated impacts on the water and energy budgets using CLM. The studies demonstrate the benefits of incorporating and coupling human activities into complex ESMs, and critical needs to account for the biogeophysical and biogeochemical effects of LULCC in climate impacts studies, and in designing mitigation and adaptation strategies at a scale meaningful for decision-making. Future directions in quantifying LULCC impacts on the water-energy-food nexus under a changing climate, as well as feedbacks among climate, energy production and consumption, and natural/managed ecosystems using an Integrated Multi-scale, Multi-sector Modeling framework will also be discussed.

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

Not all players are equally motivated: The role of narcissism.

PubMed

Roberts, Ross; Woodman, Tim; Lofthouse, Sian; Williams, Lucy

2015-01-01

Research on motivational climates consistently demonstrates that mastery-focused climates are associated with positive outcomes and ego-involving performance climates lead to maladaptive outcomes. However, the role of personality within such a framework has been largely ignored. To redress this imbalance, we examined the potential role of narcissism in moderating the effects of different motivational climates on leader-inspired extra effort in training. Training is where rugby players spend most of their rugby time and we were keen to examine the combination of personality and climate that might maximise the yield of such training environments. Female rugby players (n = 126) from 15 clubs completed measures of narcissism, motivational climate and effort. Moderated regression analyses revealed that narcissism moderated the relationship between motivational climate and effort. Increases in either performance or mastery climates were associated with increases in effort for narcissists; no such relationship was revealed for low narcissists. The findings demonstrate the importance of considering personality within rugby training environments, as it is clear that not every player will respond the same way to specific training conditions. Coaches who understand this and are able to tailor individualised motivational climates will likely gain the greatest benefits from their different players.

Extreme Precipitation, Stormwater, and Flooding in King County: Co-producing Research to Support Adaptation

NASA Astrophysics Data System (ADS)

Mauger, G. S.; Lorente-Plazas, R.; Salathe, E. P., Jr.; Mitchell, T. P.; Simmonds, J.; Lee, S. Y.; Hegewisch, K.; Warner, M.; Won, J.

2017-12-01

King County has experienced 12 federally declared flood disasters since 1990, and tens of thousands of county residents commute through, live, and work in floodplains. In addition to flooding, stormwater is a critical management challenge, exacerbated by aging infrastructure, combined sewer and drainage systems, and continued development. Even absent the effects of climate change these are challenging management issues. Recent studies clearly point to an increase in precipitation extremes for the Pacific Northwest (e.g., Warner et al. 2015). Yet very little information is available on the magnitude and spatial distribution of this change. Others clearly show that local-scale changes in extreme precipitation can only be accurately quantified with dynamical downscaling, i.e.: using a regional climate model. This talk will describe a suite of research and adaptation efforts developed in a close collaboration between King County and the UW Climate Impacts Group. Building on past collaborations, research efforts were defined in collaboration with King County managers, addressing three key science questions: (1) How are the mesoscale variations in extreme precipitation modulated by changes in large-scale weather conditions? (2) How will precipitation extremes change? This was assessed via two new high-resolution regional model projections using the Weather Research and Forecasting (WRF) mesoscale model (Skamarock et al. 2005). (3) What are the implications for stormwater and flooding in King County? This was assessed by both exploring the statistics of hourly precipitation extremes in the new projections, as well as new hydrologic modeling to assess the implications for river flooding. The talk will present results from these efforts, review the implications for King County planning and infrastructure, and synthesize lessons learned and opportunities for additional work.

Vulnerability of Breeding Waterbirds to Climate Change in the Prairie Pothole Region, U.S.A

PubMed Central

Steen, Valerie; Skagen, Susan K.; Noon, Barry R.

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts. PMID:24927165

Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

USGS Publications Warehouse

Steen, Valerie; Skagen, Susan K.; Noon, Barry R.

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

Adapted conservation measures are required to save the Iberian lynx in a changing climate

NASA Astrophysics Data System (ADS)

Fordham, D. A.; Akçakaya, H. R.; Brook, B. W.; Rodríguez, A.; Alves, P. C.; Civantos, E.; Triviño, M.; Watts, M. J.; Araújo, M. B.

2013-10-01

The Iberian lynx (Lynx pardinus) has suffered severe population declines in the twentieth century and is now on the brink of extinction. Climate change could further threaten the survival of the species, but its forecast effects are being neglected in recovery plans. Quantitative estimates of extinction risk under climate change have so far mostly relied on inferences from correlative projections of species' habitat shifts. Here we use ecological niche models coupled to metapopulation simulations with source-sink dynamics to directly investigate the combined effects of climate change, prey availability and management intervention on the persistence of the Iberian lynx. Our approach is unique in that it explicitly models dynamic bi-trophic species interactions in a climate change setting. We show that anticipated climate change will rapidly and severely decrease lynx abundance and probably lead to its extinction in the wild within 50 years, even with strong global efforts to mitigate greenhouse gas emissions. In stark contrast, we also show that a carefully planned reintroduction programme, accounting for the effects of climate change, prey abundance and habitat connectivity, could avert extinction of the lynx this century. Our results demonstrate, for the first time, why considering prey availability, climate change and their interaction in models is important when designing policies to prevent future biodiversity loss.

A Computing Infrastructure for Supporting Climate Studies

NASA Astrophysics Data System (ADS)

Yang, C.; Bambacus, M.; Freeman, S. M.; Huang, Q.; Li, J.; Sun, M.; Xu, C.; Wojcik, G. S.; Cahalan, R. F.; NASA Climate @ Home Project Team

2011-12-01

Climate change is one of the major challenges facing us on the Earth planet in the 21st century. Scientists build many models to simulate the past and predict the climate change for the next decades or century. Most of the models are at a low resolution with some targeting high resolution in linkage to practical climate change preparedness. To calibrate and validate the models, millions of model runs are needed to find the best simulation and configuration. This paper introduces the NASA effort on Climate@Home project to build a supercomputer based-on advanced computing technologies, such as cloud computing, grid computing, and others. Climate@Home computing infrastructure includes several aspects: 1) a cloud computing platform is utilized to manage the potential spike access to the centralized components, such as grid computing server for dispatching and collecting models runs results; 2) a grid computing engine is developed based on MapReduce to dispatch models, model configuration, and collect simulation results and contributing statistics; 3) a portal serves as the entry point for the project to provide the management, sharing, and data exploration for end users; 4) scientists can access customized tools to configure model runs and visualize model results; 5) the public can access twitter and facebook to get the latest about the project. This paper will introduce the latest progress of the project and demonstrate the operational system during the AGU fall meeting. It will also discuss how this technology can become a trailblazer for other climate studies and relevant sciences. It will share how the challenges in computation and software integration were solved.

Adapting to Climate Change in the Great Lakes Region: The Wisconsin Initiative on Climate Change Impacts

NASA Astrophysics Data System (ADS)

Vimont, D.; Liebl, D.

2012-12-01

The mission of the Wisconsin Initiative on Climate Change Impacts (WICCI; http://www.wicci.wisc.edu) is to assess the impacts of climate change on Wisconsin's natural, human, and built environments; and to assist in developing, recommending, and implementing climate adaptation strategies in Wisconsin. WICCI originated in 2007 as a partnership between the University of Wisconsin Nelson Institute and the Wisconsin Department of Natural Resources, and has since grown to include numerous other state, public, and private institutions. In 2011, WICCI released its First Assessment Report, which documents the efforts of over 200 individuals around the state in assessing vulnerability and estimating the risk that regional climate change poses to Wisconsin. The success of WICCI as an organization can be traced to its existence as a partnership between academic and state institutions, and as a boundary organization that catalyzes cross-disciplinary efforts between science and policy. WICCI's organizational structure and its past success at assessing climate impacts in Wisconsin will be briefly discussed. As WICCI moves into its second phase, it is increasing its emphasis on the second part of its mission: development, and implementation of adaptation strategies. Towards these goals WICCI has expanded its organizational structure to include a Communications and Outreach Committee that further ensures a necessary two-way communication of information between stakeholders / decision makers, and scientific efforts. WICCI is also increasing its focus on place-based efforts that include climate change information as one part of an integrated effort at sustainable development. The talk will include a discussion of current outreach and education efforts, as well as future directions for WICCI efforts.

Malaria ecology and climate change

NASA Astrophysics Data System (ADS)

McCord, G. C.

2016-05-01

Understanding the costs that climate change will exact on society is crucial to devising an appropriate policy response. One of the channels through while climate change will affect human society is through vector-borne diseases whose epidemiology is conditioned by ambient ecology. This paper introduces the literature on malaria, its cost on society, and the consequences of climate change to the physics community in hopes of inspiring synergistic research in the area of climate change and health. It then demonstrates the use of one ecological indicator of malaria suitability to provide an order-of-magnitude assessment of how climate change might affect the malaria burden. The average of Global Circulation Model end-of-century predictions implies a 47% average increase in the basic reproduction number of the disease in today's malarious areas, significantly complicating malaria elimination efforts.

Evaluating the utility of dynamical downscaling in agricultural impacts projections

PubMed Central

Glotter, Michael; Elliott, Joshua; McInerney, David; Best, Neil; Foster, Ian; Moyer, Elisabeth J.

2014-01-01

Interest in estimating the potential socioeconomic costs of climate change has led to the increasing use of dynamical downscaling—nested modeling in which regional climate models (RCMs) are driven with general circulation model (GCM) output—to produce fine-spatial-scale climate projections for impacts assessments. We evaluate here whether this computationally intensive approach significantly alters projections of agricultural yield, one of the greatest concerns under climate change. Our results suggest that it does not. We simulate US maize yields under current and future CO2 concentrations with the widely used Decision Support System for Agrotechnology Transfer crop model, driven by a variety of climate inputs including two GCMs, each in turn downscaled by two RCMs. We find that no climate model output can reproduce yields driven by observed climate unless a bias correction is first applied. Once a bias correction is applied, GCM- and RCM-driven US maize yields are essentially indistinguishable in all scenarios (<10% discrepancy, equivalent to error from observations). Although RCMs correct some GCM biases related to fine-scale geographic features, errors in yield are dominated by broad-scale (100s of kilometers) GCM systematic errors that RCMs cannot compensate for. These results support previous suggestions that the benefits for impacts assessments of dynamically downscaling raw GCM output may not be sufficient to justify its computational demands. Progress on fidelity of yield projections may benefit more from continuing efforts to understand and minimize systematic error in underlying climate projections. PMID:24872455

Review article: Hydrological modeling in glacierized catchments of central Asia - status and challenges

NASA Astrophysics Data System (ADS)

Chen, Yaning; Li, Weihong; Fang, Gonghuan; Li, Zhi

2017-02-01

Meltwater from glacierized catchments is one of the most important water supplies in central Asia. Therefore, the effects of climate change on glaciers and snow cover will have increasingly significant consequences for runoff. Hydrological modeling has become an indispensable research approach to water resources management in large glacierized river basins, but there is a lack of focus in the modeling of glacial discharge. This paper reviews the status of hydrological modeling in glacierized catchments of central Asia, discussing the limitations of the available models and extrapolating these to future challenges and directions. After reviewing recent efforts, we conclude that the main sources of uncertainty in assessing the regional hydrological impacts of climate change are the unreliable and incomplete data sets and the lack of understanding of the hydrological regimes of glacierized catchments of central Asia. Runoff trends indicate a complex response to changes in climate. For future variation of water resources, it is essential to quantify the responses of hydrologic processes to both climate change and shrinking glaciers in glacierized catchments, and scientific focus should be on reducing uncertainties linked to these processes.

Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor

USGS Publications Warehouse

Reed, Sasha C.; Yang, Xiaojuan; Thornton, Peter E.

2015-01-01

Myriad field, laboratory, and modeling studies show that nutrient availability plays a fundamental role in regulating CO2 exchange between the Earth's biosphere and atmosphere, and in determining how carbon pools and fluxes respond to climatic change. Accordingly, global models that incorporate coupled climate–carbon cycle feedbacks made a significant advance with the introduction of a prognostic nitrogen cycle. Here we propose that incorporating phosphorus cycling represents an important next step in coupled climate–carbon cycling model development, particularly for lowland tropical forests where phosphorus availability is often presumed to limit primary production. We highlight challenges to including phosphorus in modeling efforts and provide suggestions for how to move forward.

Evaluation of the multi-model CORDEX-Africa hindcast using RCMES

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, D. E.; Lean, P.; Mattmann, C. A.; Goodale, C. E.; Hart, A.; Zimdars, P.; Hewitson, B.; Jones, C.

2011-12-01

Recent global climate change studies have concluded with a high confidence level that the observed increasing trend in the global-mean surface air temperatures since mid-20th century is triggered by the emission of anthropogenic greenhouse gases (GHGs). The increase in the global-mean temperature due to anthropogenic emissions is nearly monotonic and may alter the climatological norms resulting in a new climate normal. In the presence of anthropogenic climate change, assessing regional impacts of the altered climate state and developing the plans for mitigating any adverse impacts are an important concern. Assessing future climate state and its impact remains a difficult task largely because of the uncertainties in future emissions and model errors. Uncertainties in climate projections propagates into impact assessment models and result in uncertainties in the impact assessments. In order to facilitate the evaluation of model data, a fundamental step for assessing model errors, the JPL Regional Climate Model Evaluation System (RCMES: Lean et al. 2010; Hart et al. 2011) has been developed through a joint effort of the investigators from UCLA and JPL. RCMES is also a regional climate component of a larger worldwide ExArch project. We will present the evaluation of the surface temperatures and precipitation from multiple RCMs participating in the African component of the Coordinated Regional Climate Downscaling Experiment (CORDEX) that has organized a suite of regional climate projection experiments in which multiple RCMs and GCMs are incorporated. As a part of the project, CORDEX organized a 20-year regional climate hindcast study in order to quantify and understand the uncertainties originating from model errors. Investigators from JPL, UCLA, and the CORDEX-Africa team collaborate to analyze the RCM hindcast data using RCMES. The analysis is focused on measuring the closeness between individual regional climate model outputs as well as their ensembles and observed data. The model evaluation is quantified in terms of widely used metrics. Details on the conceptual outline and architecture of RCMES is presented in two companion papers "The Regional climate model Evaluation System (RCMES) based on contemporary satellite and other observations for assessing regional climate model fidelity" and "A Reusable Framework for Regional Climate Model Evaluation" in GC07 and IN30, respectively.

Climate impacts on agricultural biomass production in the CORDEX.be project context

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van Schaeybroeck, Bert; Termonia, Piet; Willems, Patrick; Van Lipzig, Nicole; Marbaix, Philippe; van Ypersele, Jean-Pascal; Fettweis, Xavier; De Ridder, Koen; Stavrakou, Trissevgeni; Luyten, Patrick; Pottiaux, Eric

2016-04-01

The most important coordinated international effort to translate the IPCC-AR5 outcomes to regional climate modelling is the so-called "COordinated Regional climate Downscaling EXperiment" (CORDEX, http://wcrp-cordex.ipsl.jussieu.fr/). CORDEX.be is a national initiative that aims at combining the Belgian climate and impact modelling research into a single network. The climate network structure is naturally imposed by the top-down data flow, from the four participating upper-air Regional Climate Modelling groups towards seven Local Impact Models (LIMs). In addition to the production of regional climate projections following the CORDEX guidelines, very high-resolution results are provided at convection-permitting resolutions of about 4 km across Belgium. These results are coupled to seven local-impact models with severity indices as output. A multi-model approach is taken that allows uncertainty estimation, a crucial aspect of climate projections for policy-making purposes. The down-scaled scenarios at 4 km resolution allow for impact assessment in different Belgian agro-ecological zones. Climate impacts on arable agriculture are quantified using REGCROP which is a regional dynamic agri-meteorological model geared towards modelling climate impact on biomass production of arable crops (Gobin, 2010, 2012). Results from previous work show that heat stress and water shortages lead to reduced crop growth, whereas increased CO2-concentrations and a prolonged growing season have a positive effect on crop yields. The interaction between these effects depend on the crop type and the field conditions. Root crops such as potato will experience increased drought stress particularly when the probability rises that sensitive crop stages coincide with dry spells. This may be aggravated when wet springs cause water logging in the field and delay planting dates. Despite lower summer precipitation projections for future climate in Belgium, winter cereal yield reductions due to drought stress will be smaller due to earlier maturity. Preliminary results will be presented using the new scenario runs for Belgium.

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).

Evaluation of CSM-CROPGRO-Cotton for simulating effects of management and climate change on cotton growth and evapotranspiration in an arid environment

USDA-ARS?s Scientific Manuscript database

Originally developed for simulating soybean growth and development, the CROPGRO model was recently re-parameterized for cotton. However, further efforts are necessary to evaluate the model's performance against field measurements for new environments and management options. The objective of this stu...

Two Challenges to Communicating Climate Science

NASA Astrophysics Data System (ADS)

Oreskes, N.; Evans, J. H.; Feng, J.

2011-12-01

Climate scientists have been frustrated by the persistence of public opinion at odds with established scientific evidence about anthropogenic climate change. Traditionally, scientists have attributed the gap between scientific knowledge and public perception to scientific illiteracy, which could be remedied by a better and more abundant supply of well-communicated scientific information. Social scientific research, however, illustrates that this "deficit model" is insufficient to explain the current state of affairs: many individuals who reject the conclusions of climate scientists are highly educated, and some evidence suggests that, among certain demographics, more educated people are more likely than less educated ones to reject climate science. This talk explores two possible sources of resistance to, or outright rejection of, scientific conclusions about climate change: 1) the effects of long-standing organized efforts to challenge climate science and the credibility of climate scientists; 2) conservative Protestant religious beliefs concerning how factual claims about the earth are determined and how their significance is judged.

Half Moon Bay, Grays Harbor, Washington: Movable-Bed Physical Model Study

DTIC Science & Technology

2006-09-01

wave machine used in Half Moon Bay physical model.................................50 Figure 28. Wave analysis output from model wave measurements...Point Chehalis used to reduce strong longshore current................82 Figure 46. Analysis of irregular waves measured at model wave Gauge 4...required several reconstruction efforts between origi- nal construction and present day due to the harsh wave climate on the Washington coast. After

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

NASA Technical Reports Server (NTRS)

1997-01-01

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

Projection of wave conditions in response to climate change: A community approach to global and regional wave downscaling

USGS Publications Warehouse

Erikson, Li H.; Hemer, M.; Lionello, Piero; Mendez, Fernando J.; Mori, Nobuhito; Semedo, Alvaro; Wang, Xiaolan; Wolf, Judith

2015-01-01

Future changes in wind-wave climate have broad implications for coastal geomorphology and management. General circulation models (GCM) are now routinely used for assessing climatological parameters, but generally do not provide parameterizations of ocean wind-waves. To fill this information gap, a growing number of studies use GCM outputs to independently downscale wave conditions to global and regional levels. To consolidate these efforts and provide a robust picture of projected changes, we present strategies from the community-derived multi-model ensemble of wave climate projections (COWCLIP) and an overview of regional contributions. Results and strategies from one contributing regional study concerning changes along the eastern North Pacific coast are presented.

Projected climate-induced habitat loss for salmonids in the John Day River network, Oregon, U.S.A.

USGS Publications Warehouse

Ruesch, Aaron S.; Torgersen, Christian E.; Lawler, Joshua J.; Olden, Julian D.; Peterson, Erin E.; Volk, Carol J.; Lawrence, David J.

2012-01-01

Climate change will likely have profound effects on cold-water species of freshwater fishes. As temperatures rise, cold-water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate-driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate-induced changes in summer thermal habitat for 3 cold-water fish species—juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)—in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69–95%, 51–87%, and 86–100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.

Integrated Information Systems Across the Weather-Climate Continuum

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.; Higgins, W.; Nierenberg, C.; Trtanj, J.

2015-12-01

The increasing demand for well-organized (integrated) end-to-end research-based information has been highlighted in several National Academy studies, in IPCC Reports (such as the SREX and Fifth Assessment) and by public and private constituents. Such information constitutes a significant component of the "environmental intelligence" needed to address myriad societal needs for early warning and resilience across the weather-climate continuum. The next generation of climate research in service to the nation requires an even more visible, authoritative and robust commitment to scientific integration in support of adaptive information systems that address emergent risks and inform longer-term resilience strategies. A proven mechanism for resourcing such requirements is to demonstrate vision, purpose, support, connection to constituencies, and prototypes of desired capabilities. In this presentation we will discuss efforts at NOAA, and elsewhere, that: Improve information on how changes in extremes in key phenomena such as drought, floods, and heat stress impact management decisions for resource planning and disaster risk reduction Develop regional integrated information systems to address these emergent challenges, that integrate observations, monitoring and prediction, impacts assessments and scenarios, preparedness and adaptation, and coordination and capacity-building. Such systems, as illustrated through efforts such as NIDIS, have strengthened the integration across the foundational research enterprise (through for instance, RISAs, Modeling Analysis Predictions and Projections) by increasing agility for responding to emergent risks. The recently- initiated Climate Services Information System, in support of the WMO Global Framework for Climate Services draws on the above models and will be introduced during the presentation.

A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

NASA Astrophysics Data System (ADS)

Komurcu, M.; Huber, M.

2016-12-01

Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate change impacts assessments for New England. We present results focusing on future changes in New England extreme events.

The Regional Climate Model Evaluation System: A Systematic Evaluation Of CORDEX Simulations Using Obs4MIPs

NASA Astrophysics Data System (ADS)

Goodman, A.; Lee, H.; Waliser, D. E.; Guttowski, W.

2017-12-01

Observation-based evaluations of global climate models (GCMs) have been a key element for identifying systematic model biases that can be targeted for model improvements and for establishing uncertainty associated with projections of global climate change. However, GCMs are limited in their ability to represent physical phenomena which occur on smaller, regional scales, including many types of extreme weather events. In order to help facilitate projections in changes of such phenomena, simulations from regional climate models (RCMs) for 14 different domains around the world are being provided by the Coordinated Regional Climate Downscaling Experiment (CORDEX; www.cordex.org). However, although CORDEX specifies standard simulation and archiving protocols, these simulations are conducted independently by individual research and modeling groups representing each of these domains often with different output requirements and data archiving and exchange capabilities. Thus, with respect to similar efforts using GCMs (e.g., the Coupled Model Intercomparison Project, CMIP), it is more difficult to achieve a standardized, systematic evaluation of the RCMs for each domain and across all the CORDEX domains. Using the Regional Climate Model Evaluation System (RCMES; rcmes.jpl.nasa.gov) developed at JPL, we are developing easy to use templates for performing systematic evaluations of CORDEX simulations. Results from the application of a number of evaluation metrics (e.g., biases, centered RMS, and pattern correlations) will be shown for a variety of physical quantities and CORDEX domains. These evaluations are performed using products from obs4MIPs, an activity initiated by DOE and NASA, and now shepherded by the World Climate Research Program's Data Advisory Council.

Making the State of the Art the Classroom Benchmark: A Climate Change Curriculum Based on Synthesis Science

NASA Astrophysics Data System (ADS)

Nicholas, K. A.

2014-12-01

A hallmark of science in the Anthropocene is the increasing use of synthesis efforts to distill ever-growing data into the best available scientific knowledge. Thousands of scientists contribute substantial amounts of time towards these efforts, with the aim of producing authoritative work as a basis for informing both further research priorities and policy decisions. Organizations such as the IPCC are increasing their efforts to disseminate their scientific findings to broader audiences, for example, using text and video summaries targeted for policymakers. However, the results of such synthesis efforts have rarely been disseminated further back in the pipeline, in the classrooms where scientific literacy is shaped. Here, I will describe an emerging initiative to develop a program to translate state-of-the-art scientific synthesis findings into a modular, flexible climate change curriculum. This initiative is envisioned to compliment rather than compete with existing curriculum development efforts. Examples from innovation labs in healthcare delivery and other fields will be used to demonstrate a model for how a small, interdisciplinary team of early-career experts can use their content and pedagogical knowledge to transform synthesis results into ready-to-use teaching materials. The benefits of such a curriculum include improved student learning through constructive alignment of thoughtfully designed teaching and learning activities and assessment activities to promote intended learning outcomes, as well as the real-world illustration of the method of scientific inquiry applied to socially relevant problems. The curriculum can also improve teaching experiences through increased efficiency in course preparation, and in sharing best practices with participating colleagues. Initial scoping will examine the needs of university teachers of climate change courses as the constituents of this curriculum, and possible support models to mainstream such efforts. Ultimately, using scientific syntheses as the basis for university curricula would help close the gap between research and classroom learning, promote increased scientific understanding, and help ensure that the resources devoted to scientific synthesis efforts are translated to broader benefits for society.

TV Weathercasters as Climate Educators: Rationale, Evidence for Effectiveness, and Potential for Nationwide Scale-Up. (Invited)

NASA Astrophysics Data System (ADS)

Maibach, E.; Cullen, H. M.; Witte, J.

2013-12-01

Climate change is influencing every region of the nation through weather and climatic events including heat waves, droughts, extreme precipitation and floods, more intense hurricanes, and forest fires, yet most Americans continue to perceive climate change as a problem distant in time (with impacts a generation or more away), and in space (that will primarily affect other countries, not the United States). This may be caused, in part, due to the fact that climate change is often described in global, abstract, and analytical terms that are hard for people to connect to their own lives. The impacts of climate change, however, can be personally experienced at the local level, including through unusual weather events; cognitive science has shown that the human brain is more adept at learning through personal experience than through analytical reasoning. In this paper we will describe our efforts to enable America's TV weathercasters to embrace the role of climate educator. Weathercasters are a relatively small cohort of highly skilled communication professionals who are optimally positioned to reach a large majority of the American public, and help move their viewers beyond an abstract (distant) notion of global climate change and toward an understanding of climate change that is both local and concrete. Approximately 70% of American adults watch local TV news, and their primary reason for doing so is to learn about the weather. Our research has shown that TV weathercasters are second only to scientists and government science agencies as trusted sources of information about climate change. Our surveys have also shown that - in every region of the country - many TV weathercasters are willing to embrace the role of climate educator, if certain barriers can be overcome. Our experimental pilot-test - in Columbia, South Carolina - of a model developed to help overcome those barriers demonstrated that: when TV weathercasters make an effort to educate their viewers about the local ramifications of climate change, their viewers learn. Our current attempts to scale-up the model on a limited basis - in one state as a field experiment, and elsewhere around the nation on an uncontrolled basis - are showing promise in terms of attracting an increasing numbers of participating weathercasters. Lastly, professional associations that represent TV weathercasters (AMS and NWA), and government agencies that produce climate and weather data for meteorologists (NOAA and NASA), are committed to help scale up this model so that all interested TV weathercasters have easy access to localized information through which to educate their viewers about local weather and related implications of climate change. In sum, by engaging and empowering TV weathercasters as climate educators, we seek to increase public understanding of the relationships among climate, climate variability, climate change, weather extremes and community vulnerability, and we believe this model has considerable potential.

Linking regional initiatives to improve predictions of drought impacts on living marine resources in the U.S. Southeast: Apalachicola Bay oyster fishery as a potential test case

NASA Astrophysics Data System (ADS)

Petes, L.; McNutt, C.; Burkett, V.; Jones, S.

2009-12-01

In 2007, the U.S. Southeast experienced one of the worst droughts on record. Since 1970, moderate-to-severe droughts in the Southeast have increased by 12-14% and annual average temperature has risen over 1°C. Several global climate models also project warming across the Southeast and an increased rate of warming through the end of the century. The Southeast has also undergone unprecedented growth, with some counties of Florida and Georgia populations increasing by over 500% in the last several decades, further increasing the demand for water resources during times of drought. Two regional efforts are currently underway to help inform constituents about adaptation to climate variability and change in the Southeast region. The first effort is the National Integrated Drought Information System (NIDIS), led by NOAA. NIDIS serves as an early warning system for drought through the consolidation of physical/hydrological and socioeconomic impact data, engages those affected by drought, integrates observing networks, and delivers decision-support tools to end-users. The second effort is the USGS’ National Climate Change and Wildlife Science Center, which will facilitate linking global and regional climate models to ecological and biological responses at spatial and temporal resolutions that will inform resource management decisions. Both efforts will be operating in the Apalachicola-Chattahoochee-Flint (ACF) River Basin. During the 2007 drought, one of the most publicized impacts was on the oyster fishery in Apalachicola Bay. Reduced regional precipitation along with associated higher demands for water uses in the ACF reduced downstream flow into the Bay, producing harmful effects on the oyster fishery and associated ecosystem. Changes in estuarine salinity resulting from alterations in streamflow can lead to impacts on species abundance and community composition. Drought can also lead to changes in predator-prey interactions, as marine predators typically move into estuaries when salinity is high. Experiments have shown that Apalachicola oysters suffer significant mortality due to increased disease load and higher predation pressure under high-salinity, drought conditions. There is currently little information, however, on how drought will influence species interactions, distributions, and abundances in estuarine ecosystems, and how this in turn will affect biodiversity and ecosystem function. Improved linking of hydrologic and climatic models to biological systems is needed in order for resource managers to better predict and mitigate ecosystem changes resulting from drought and climate change. There now exists an opportunity to link the NIDIS and USGS regional efforts to gain a better understanding of how interrelated factors, such as competing demands for water resources in the ACF Basin, changes in the frequency and duration of drought, and management of the reservoirs will affect downstream ecosystems such as the estuarine environment and the oyster fishery in Apalachicola Bay.

Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program

NASA Technical Reports Server (NTRS)

Moore, Berrien, III; Sahagian, Dork

1997-01-01

The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.

Seasonal Prediction of Hydro-Climatic Extremes in the Greater Horn of Africa Under Evolving Climate Conditions to Support Adaptation Strategies

NASA Astrophysics Data System (ADS)

Tadesse, T.; Zaitchik, B. F.; Habib, S.; Funk, C. C.; Senay, G. B.; Dinku, T.; Policelli, F. S.; Block, P.; Baigorria, G. A.; Beyene, S.; Wardlow, B.; Hayes, M. J.

2014-12-01

The development of effective strategies to adapt to changes in the character of droughts and floods in Africa will rely on improved seasonal prediction systems that are robust to an evolving climate baseline and can be integrated into disaster preparedness and response. Many efforts have been made to build models to improve seasonal forecasts in the Greater Horn of Africa region (GHA) using satellite and climate data, but these efforts and models must be improved and translated into future conditions under evolving climate conditions. This has considerable social significance, but is challenged by the nature of climate predictability and the adaptability of coupled natural and human systems facing exposure to climate extremes. To address these issues, work is in progress under a project funded by NASA. The objectives of the project include: 1) Characterize and explain large-scale drivers in the ocean-atmosphere-land system associated with years of extreme flood or drought in the GHA. 2) Evaluate the performance of state-of-the-art seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes. 3) Apply seasonal forecast systems to prediction of socially relevant impacts on crops, flood risk, and economic outcomes, and assess the value of these predictions to decision makers. 4) Evaluate the robustness of seasonal prediction systems to evolving climate conditions. The National Drought Mitigation Center (University of Nebraska-Lincoln, USA) is leading this project in collaboration with the USGS, Johns Hopkins University, University of Wisconsin-Madison, the International Research Institute for Climate and Society, NASA, and GHA local experts. The project is also designed to have active engagement of end users in various sectors, university researchers, and extension agents in GHA through workshops and/or webinars. This project is expected improve and implement new and existing climate- and remote sensing-based agricultural, meteorological, and hydrologic drought and flood monitoring products (or indicators) that can enhance the preparedness for extreme climate events and climate change adaptation and mitigation strategies in the GHA. Even though this project is in its first year, the preliminary results and future plans to carry out the objectives will be presented.

Social norms and efficacy beliefs drive the Alarmed segment’s public-sphere climate actions

NASA Astrophysics Data System (ADS)

Doherty, Kathryn L.; Webler, Thomas N.

2016-09-01

Surprisingly few individuals who are highly concerned about climate change take action to influence public policies. To assess social-psychological and cognitive drivers of public-sphere climate actions of Global Warming’s Six Americas `Alarmed’ segment, we developed a behaviour model and tested it using structural equation modelling of survey data from Vermont, USA (N = 702). Our model, which integrates social cognitive theory, social norms research, and value belief norm theory, explains 36-64% of the variance in five behaviours. Here we show descriptive social norms, self-efficacy, personal response efficacy, and collective response efficacy as strong driving forces of: voting, donating, volunteering, contacting government officials, and protesting about climate change. The belief that similar others took action increased behaviour and strengthened efficacy beliefs, which also led to greater action. Our results imply that communication efforts targeting Alarmed individuals and their public actions should include strategies that foster beliefs about positive descriptive social norms and efficacy.

Changing crops in response to climate: virtual Nang Rong, Thailand in an agent based simulation

PubMed Central

Malanson, George P.; Verdery, Ashton M.; Walsh, Stephen J.; Sawangdee, Yothin; Heumann, Benjamin W.; McDaniel, Philip M.; Frizzelle, Brian G.; Williams, Nathalie E.; Yao, Xiaozheng; Entwisle, Barbara; Rindfuss, Ronald R.

2014-01-01

The effects of extended climatic variability on agricultural land use were explored for the type of system found in villages of northeastern Thailand. An agent based model developed for the Nang Rong district was used to simulate land allotted to jasmine rice, heavy rice, cassava, and sugar cane. The land use choices in the model depended on likely economic outcomes, but included elements of bounded rationality in dependence on household demography. The socioeconomic dynamics are endogenous in the system, and climate changes were added as exogenous drivers. Villages changed their agricultural effort in many different ways. Most villages reduced the amount of land under cultivation, primarily with reduction in jasmine rice, but others did not. The variation in responses to climate change indicates potential sensitivity to initial conditions and path dependence for this type of system. The differences between our virtual villages and the real villages of the region indicate effects of bounded rationality and limits on model applications. PMID:25061240

School climate and bullying victimization: a latent class growth model analysis.

PubMed

Gage, Nicholas A; Prykanowski, Debra A; Larson, Alvin

2014-09-01

Researchers investigating school-level approaches for bullying prevention are beginning to discuss and target school climate as a construct that (a) may predict prevalence and (b) be an avenue for school-wide intervention efforts (i.e., increasing positive school climate). Although promising, research has not fully examined and established the social-ecological link between school climate factors and bullying/peer aggression. To address this gap, we examined the association between school climate factors and bullying victimization for 4,742 students in Grades 3-12 across 3 school years in a large, very diverse urban school district using latent class growth modeling. Across 3 different models (elementary, secondary, and transition to middle school), a 3-class model was identified, which included students at high-risk for bullying victimization. Results indicated that, for all students, respect for diversity and student differences (e.g., racial diversity) predicted within-class decreases in reports of bullying. High-risk elementary students reported that adult support in school was a significant predictor of within-class reduction of bullying, and high-risk secondary students report peer support as a significant predictor of within-class reduction of bullying. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Climate change effects on international stability : a white paper.

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

Murphy, Kathryn; Taylor, Mark A.; Fujii, Joy

2004-12-01

This white paper represents a summary of work intended to lay the foundation for development of a climatological/agent model of climate-induced conflict. The paper combines several loosely-coupled efforts and is the final report for a four-month late-start Laboratory Directed Research and Development (LDRD) project funded by the Advanced Concepts Group (ACG). The project involved contributions by many participants having diverse areas of expertise, with the common goal of learning how to tie together the physical and human causes and consequences of climate change. We performed a review of relevant literature on conflict arising from environmental scarcity. Rather than simply reviewingmore » the previous work, we actively collected data from the referenced sources, reproduced some of the work, and explored alternative models. We used the unfolding crisis in Darfur (western Sudan) as a case study of conflict related to or triggered by climate change, and as an exercise for developing a preliminary concept map. We also outlined a plan for implementing agents in a climate model and defined a logical progression toward the ultimate goal of running both types of models simultaneously in a two-way feedback mode, where the behavior of agents influences the climate and climate change affects the agents. Finally, we offer some ''lessons learned'' in attempting to keep a diverse and geographically dispersed group working together by using Web-based collaborative tools.« less

Climate change impact assessments on the water resources of India under extensive human interventions.

PubMed

Madhusoodhanan, C G; Sreeja, K G; Eldho, T I

2016-10-01

Climate change is a major concern in the twenty-first century and its assessments are associated with multiple uncertainties, exacerbated and confounded in the regions where human interventions are prevalent. The present study explores the challenges for climate change impact assessment on the water resources of India, one of the world's largest human-modified systems. The extensive human interventions in the Energy-Land-Water-Climate (ELWC) nexus significantly impact the water resources of the country. The direct human interventions in the landscape may surpass/amplify/mask the impacts of climate change and in the process also affect climate change itself. Uncertainties in climate and resource assessments add to the challenge. Formulating coherent resource and climate change policies in India would therefore require an integrated approach that would assess the multiple interlinkages in the ELWC nexus and distinguish the impacts of global climate change from that of regional human interventions. Concerted research efforts are also needed to incorporate the prominent linkages in the ELWC nexus in climate/earth system modelling.

Modeling Forest Composition and Carbon Dynamics Under Projected Climate-Fire Interactions in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liang, S.; Hurteau, M. D.; Westerling, A. L.

2014-12-01

The Sierra Nevada Mountains are occupied by a diversity of forest types that sort by elevation. The interaction of changing climate and altered disturbance regimes (e.g. fire) has the potential to drive changes in forest distribution as a function of species-specific response. Quantifying the effects of these drivers on species distributions and productivity under future climate-fire interactions is necessary for informing mitigation and adaptation efforts. In this study, we assimilated forest inventory and soil survey data and species life history traits into a landscape model, LANDIS-II, to quantify the response of forest dynamics to the interaction of climate change and large wildfire frequency in the Sierra Nevada. We ran 100-year simulations forced with historical climate and climate projections from three models (GFDL, CNRM and CCSM3) driven by the A2 emission scenario. We found that non-growing season NPP is greatly enhanced by 15%-150%, depending on the specific climate projection. The greatest increase occurs in subalpine forests. Species-specific response varied as a function of life history characteristics. The distribution of drought and fire-tolerant species, such as ponderosa pine, expanded by 7.3-9.6% from initial conditions, while drought and fire-intolerant species, such as white fir, showed little change in the absence of fire. Changes in wildfire size and frequency influence species distributions by altering the successional stage of burned patches. The range of responses to different climate models demonstrates the sensitivity of these forests to climate variability. The scale of climate projections relative to the scale of forest simulations presents a source of uncertainty, particularly at the ecotone between forest types and for identifying topographically mediated climate refugia. Improving simulations will likely require higher resolution climate projections.

Analyzing the responses of species assemblages to climate change across the Great Basin, USA.

NASA Astrophysics Data System (ADS)

Henareh Khalyani, A.; Falkowski, M. J.; Crookston, N.; Yousef, F.

2016-12-01

The potential impacts of climate change on the future distribution of tree species in not well understood. Climate driven changes in tree species distribution could cause significant changes in realized species niches, potentially resulting in the loss of ecotonal species as well as the formation on novel assemblages of overlapping tree species. In an effort to gain a better understating of how the geographic distribution of tree species may respond to climate change, we model the potential future distribution of 50 different tree species across 70 million ha in the Great Basin, USA. This is achieved by leveraging a species realized niche model based on non-parametric analysis of species occurrences across climatic, topographic, and edaphic variables. Spatially explicit, high spatial resolution (30 m) climate variables (e.g., precipitation, and minimum, maximum, and mean temperature) and associated climate indices were generated on an annual basis between 1981-2010 by integrating climate station data with digital elevation data (Shuttle Radar Topographic Mission (SRTM) data) in a thin plate spline interpolation algorithm (ANUSPLIN). Bioclimate models of species niches in in the cotemporary period and three following 30 year periods were then generated by integrating the climate variables, soil data, and CMIP 5 general circulation model projections. Our results suggest that local scale contemporary variations in species realized niches across space are influenced by edaphic and topographic variables as well as climatic variables. The local variability in soil properties and topographic variability across space also affect the species responses to climate change through time and potential formation of species assemblages in future. The results presented here in will aid in the development of adaptive forest management techniques aimed at mitigating negative impacts of climate change on forest composition, structure, and function.

Community climate simulations to assess avoided impacts in 1.5 and 2 °C futures

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

Sanderson, Benjamin M.; Xu, Yangyang; Tebaldi, Claudia

The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5 °C above preindustrial levels and well below 2 °C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. Here, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2 °C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 andmore » 2 °C levels and an overshoot 1.5 °C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. We also describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60 % greater frequency in the 2 °C climate than in a 1.5 °C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0 °C climate than a 1.5 °C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0 °C scenario, and 1 in 40 years in the 1.5 °C scenario. Significance of impact differences with respect to multi-model variability is not assessed.« less

Community climate simulations to assess avoided impacts in 1.5 and 2 °C futures

DOE PAGES

Sanderson, Benjamin M.; Xu, Yangyang; Tebaldi, Claudia; ...

2017-09-19

The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5 °C above preindustrial levels and well below 2 °C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. Here, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2 °C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 andmore » 2 °C levels and an overshoot 1.5 °C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. We also describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60 % greater frequency in the 2 °C climate than in a 1.5 °C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0 °C climate than a 1.5 °C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0 °C scenario, and 1 in 40 years in the 1.5 °C scenario. Significance of impact differences with respect to multi-model variability is not assessed.« less

Key challenges and priorities for modelling European grasslands under climate change.

PubMed

Kipling, Richard P; Virkajärvi, Perttu; Breitsameter, Laura; Curnel, Yannick; De Swaef, Tom; Gustavsson, Anne-Maj; Hennart, Sylvain; Höglind, Mats; Järvenranta, Kirsi; Minet, Julien; Nendel, Claas; Persson, Tomas; Picon-Cochard, Catherine; Rolinski, Susanne; Sandars, Daniel L; Scollan, Nigel D; Sebek, Leon; Seddaiu, Giovanna; Topp, Cairistiona F E; Twardy, Stanislaw; Van Middelkoop, Jantine; Wu, Lianhai; Bellocchi, Gianni

2016-10-01

Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change. Copyright © 2016 Elsevier B.V. All rights reserved.

Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

NASA Astrophysics Data System (ADS)

Erfanian, A.; Fomenko, L.; Wang, G.

2016-12-01

Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

An international land-biosphere model benchmarking activity for the IPCC Fifth Assessment Report (AR5)

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

Hoffman, Forrest M; Randerson, James T; Thornton, Peter E

2009-12-01

The need to capture important climate feedbacks in general circulation models (GCMs) has resulted in efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, called Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results (Friedlingstein et al., 2006). This work suggests that a more rigorous set of global offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are needed. The Carbon-Land Model Intercomparison Projectmore » (C-LAMP) was designed to meet this need by providing a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). Recently, a similar effort in Europe, called the International Land Model Benchmark (ILAMB) Project, was begun to assess the performance of European land surface models. These two projects will now serve as prototypes for a proposed international land-biosphere model benchmarking activity for those models participating in the IPCC Fifth Assessment Report (AR5). Initially used for model validation for terrestrial biogeochemistry models in the NCAR Community Land Model (CLM), C-LAMP incorporates a simulation protocol for both offline and partially coupled simulations using a prescribed historical trajectory of atmospheric CO2 concentrations. Models are confronted with data through comparisons against AmeriFlux site measurements, MODIS satellite observations, NOAA Globalview flask records, TRANSCOM inversions, and Free Air CO2 Enrichment (FACE) site measurements. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the CLM version 3 in the Community Climate System Model version 3 (CCSM3): the CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons of the CLM3 offline results against observational datasets have been performed and are described in Randerson et al. (2009). CLM version 4 has been evaluated using C-LAMP, showing improvement in many of the metrics. Efforts are now underway to initiate a Nitrogen-Land Model Intercomparison Project (N-LAMP) to better constrain the effects of the nitrogen cycle in biosphere models. Presented will be new results from C-LAMP for CLM4, initial N-LAMP developments, and the proposed land-biosphere model benchmarking activity.« less

Compressing climate model simulations: reducing storage burden while preserving information

NASA Astrophysics Data System (ADS)

Hammerling, Dorit; Baker, Allison; Xu, Haiying; Clyne, John; Li, Samuel

2017-04-01

Climate models, which are run at high spatial and temporal resolutions, generate massive quantities of data. As our computing capabilities continue to increase, storing all of the generated data is becoming a bottleneck, which negatively affects scientific progress. It is thus important to develop methods for representing the full datasets by smaller compressed versions, which still preserve all the critical information and, as an added benefit, allow for faster read and write operations during analysis work. Traditional lossy compression algorithms, as for example used for image files, are not necessarily ideally suited for climate data. While visual appearance is relevant, climate data has additional critical features such as the preservation of extreme values and spatial and temporal gradients. Developing alternative metrics to quantify information loss in a manner that is meaningful to climate scientists is an ongoing process still in its early stages. We will provide an overview of current efforts to develop such metrics to assess existing algorithms and to guide the development of tailored compression algorithms to address this pressing challenge.

Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

NASA Astrophysics Data System (ADS)

Smith, B.

2015-12-01

In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs, and web browsers. The framework is designed to be scalable to large datasets, yet easy to use and familiar to scientists using previous tools. Integration in the ACME overall user interface facilitates data publication, further analysis, and quick feedback to model developers and scientists making component or coupled model runs.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

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

Boslough, Mark B.; Backus, George A.

2005-12-01

We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such modelsmore » do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3« less

The Continual Intercomparison of Radiation Codes: Results from Phase I

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Mlawer, Eli; Delamere, Jennifer; Shippert, Timothy; Cole, Jason; Iacono, Michael; Jin, Zhonghai; Li, Jiangnan; Manners, James; Raisanen, Petri;

The climate4impact platform: Providing, tailoring and facilitating climate model data access

NASA Astrophysics Data System (ADS)

Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael

2017-04-01

One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European contribution to ESGF and contributes to the ESGF open source effort, notably through the development of search, monitoring, quality control, and metadata services. In its second phase, IS-ENES2 supports the implementation of regional climate model results from the international Coordinated Regional Downscaling Experiments (CORDEX). These services were extended within the European FP7 Climate Information Portal for Copernicus (CLIPC) project, and some could be later integrated into the European Copernicus platform.

MIDWESTERN REGIONAL CENTER OF THE DOE NATIONAL INSTITUTE FOR CLIMATIC CHANGE RESEARCH

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

Burton, Andrew J.

2014-02-28

The goal of NICCR (National Institute for Climatic Change Research) was to mobilize university researchers, from all regions of the country, in support of the climatic change research objectives of DOE/BER. The NICCR Midwestern Regional Center (MRC) supported work in the following states: North Dakota, South Dakota, Nebraska, Kansas, Oklahoma, Minnesota, Iowa, Missouri, Wisconsin, Illinois, Michigan, Indiana, and Ohio. The MRC of NICCR was able to support nearly $8 million in climatic change research, including $6,671,303 for twenty projects solicited and selected by the MRC over five requests for proposals (RFPs) and $1,051,666 for the final year of ten projectsmore » from the discontinued DOE NIGEC (National Institute for Global Environmental Change) program. The projects selected and funded by the MRC resulted in 135 peer-reviewed publications and supported the training of 25 PhD students and 23 Masters students. Another 36 publications were generated by the final year of continuing NIGEC projects supported by the MRC. The projects funded by the MRC used a variety of approaches to answer questions relevant to the DOE’s climate change research program. These included experiments that manipulated temperature, moisture and other global change factors; studies that sought to understand how the distribution of species and ecosystems might change under future climates; studies that used measurements and modeling to examine current ecosystem fluxes of energy and mass and those that would exist under future conditions; and studies that synthesized existing data sets to improve our understanding of the effects of climatic change on terrestrial ecosystems. In all of these efforts, the MRC specifically sought to identify and quantify responses of terrestrial ecosystems that were not well understood or not well modeled by current efforts. The MRC also sought to better understand and model important feedbacks between terrestrial ecosystems, atmospheric chemistry, and regional and global climate systems. The broad variety of projects the MRC has supported gave us a unique opportunity to greatly improve our ability to predict the future health, composition and function of important agricultural and natural terrestrial ecosystems within the Midwestern Region.« less

Global change modeling for Northern Eurasia: a review and strategies to move forward

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Sokolov, A. P.; Zhuang, Q.; Sokolik, I. N.; Lawford, R. G.; Kappas, M.; Paltsev, S.; Groisman, P. Y.

2017-12-01

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

A review of and perspectives on global change modeling for Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Kicklighter, David W.; Sokolov, Andrei P.; Zhuang, Qianlai; Sokolik, Irina N.; Lawford, Richard; Kappas, Martin; Paltsev, Sergey V.; Groisman, Pavel Ya

2017-08-01

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

The Influence of Ideological Filters upon Education about Climate

NASA Astrophysics Data System (ADS)

Rutherford, D.

2011-12-01

Religious and political ideologies serve as primary lenses through which people interpret information and education related to the climate system, climate change, and climate impacts upon human and environmental systems. Consequently, ideologies strongly affect (1) the levels of receptivity that people express toward communication messages and educational efforts related to climate topics, and (2) the amount of knowledge and understanding that people obtain from those messages and efforts. This paper begins with a brief overview of research that establishes a theoretical framework for understanding the role of ideology in communication and educational efforts. It then describes the ideological filtering of climate and environmental information that occurs in a substantial and powerful public in American society - the socially conservative, evangelical Christian population. Approaches are then offered for navigating the ideological filters of this specific population in order to improve understanding of climate related topics. More general principles also emerge that can apply across other populations

A Simple Water Balance Model Adapted for Arctic Hydrology Reveals Glacier and Streamflow Responses to Climate Change in the Copper River, Alaska

NASA Astrophysics Data System (ADS)

Valentin, M. M.; Hay, L.; Van Beusekom, A. E.; Viger, R. J.; Hogue, T. S.

2016-12-01

Forecasting the hydrologic response to climate change in Alaska's glaciated watersheds remains daunting for hydrologists due to sparse field data and few modeling tools, which frustrates efforts to manage and protect critical aquatic habitat. Approximately 20% of the 64,000 square kilometer Copper River watershed is glaciated, and its glacier-fed tributaries support renowned salmon fisheries that are economically, culturally, and nutritionally invaluable to the local communities. This study adapts a simple, yet powerful, conceptual hydrologic model to simulate changes in the timing and volume of streamflow in the Copper River, Alaska as glaciers change under plausible future climate scenarios. The USGS monthly water balance model (MWBM), a hydrologic tool used for two decades to evaluate a broad range of hydrologic questions in the contiguous U.S., was enhanced to include glacier melt simulations and remotely sensed data. In this presentation we summarize the technical details behind our MWBM adaptation and demonstrate its use in the Copper River Basin to evaluate glacier and streamflow responses to climate change.

Simulations of Tornadoes, Tropical Cyclones, MJOs, and QBOs, using GFDL's multi-scale global climate modeling system

NASA Astrophysics Data System (ADS)

Lin, Shian-Jiann; Harris, Lucas; Chen, Jan-Huey; Zhao, Ming

2014-05-01

A multi-scale High-Resolution Atmosphere Model (HiRAM) is being developed at NOAA/Geophysical Fluid Dynamics Laboratory. The model's dynamical framework is the non-hydrostatic extension of the vertically Lagrangian finite-volume dynamical core (Lin 2004, Monthly Wea. Rev.) constructed on a stretchable (via Schmidt transformation) cubed-sphere grid. Physical parametrizations originally designed for IPCC-type climate predictions are in the process of being modified and made more "scale-aware", in an effort to make the model suitable for multi-scale weather-climate applications, with horizontal resolution ranging from 1 km (near the target high-resolution region) to as low as 400 km (near the antipodal point). One of the main goals of this development is to enable simulation of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously thought impossible. We will present preliminary results, covering a very wide spectrum of temporal-spatial scales, ranging from simulation of tornado genesis (hours), Madden-Julian Oscillations (intra-seasonal), topical cyclones (seasonal), to Quasi Biennial Oscillations (intra-decadal), using the same global multi-scale modeling system.

Integrated Modelling on Flow and Water Quality Under the Impacts of Climate Change and Agricultural Activities

NASA Astrophysics Data System (ADS)

SHI, J.

2014-12-01

Climate change is expected to have a significant impact on flooding in the UK, inducing more intense and prolonged storms. Frequent flooding due to climate change already exacerbates catchment water quality. Land use is another contributing factor to poor water quality. For example, the move to intensive farming could cause an increase in faecal coliforms entering the water courses. In an effort to understand better the effects on water quality from land use and climate change, the hydrological and estuarine processes are being modelled using SWAT (Soil and Water Assessment Tool), linked to a 2-D hydrodynamic model DIVAST(Depth Integrated Velocity and Solute Transport). The coupled model is able to quantify how much of each pollutant from the catchment reaches the harbour and the impact on water quality within the harbour. The work is focused on the transportation and decay of faecal coliforms from agricultural runoff into the rivers Frome and Piddle in the UK. The impact from the agricultural land use and activities on the catchment river hydrology and water quality are evaluated. The coupled model calibration and validation showed the good model performance on flow and faecal coliform in the watershed and estuary.

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

NASA Technical Reports Server (NTRS)

1998-01-01

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

Charter School Discipline: Examples of Policies and School Climate Efforts from the Field

ERIC Educational Resources Information Center

Kern, Nora; Kim, Suzie

2016-01-01

Students need a safe and supportive school environment to maximize their academic and social-emotional learning potential. A school's discipline policies and practices directly impact school climate and student achievement. Together, discipline policies and positive school climate efforts can reinforce behavioral expectations and ensure student…

Prediction Activities at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2010-01-01

The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the climate community. An improved understanding of the nature of decadal variability and its predictability has important implications for efforts to assess the impacts of global change in the coming decades. In fact, the GMAO has taken on the challenge of carrying out experimental decadal predictions in support of the IPCC AR5 effort.

Mapping the current and potential distribution of red spruce in Virginia: implications for the restoration of degraded high elevation habitat

Treesearch

Heather Griscom; Helmut Kraenzle; Zachary. Bortolot

2010-01-01

The objective of our project is to create a habitat suitability model to predict potential and future red spruce forest distributions. This model will be used to better understand the influence of climate change on red spruce distribution and to help guide forest restoration efforts.

Quantifying Climate Feedbacks from Abrupt Changes in High-Latitude Trace-Gas Emissions

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

Schlosser, Courtney Adam; Walter-Anthony, Katey; Zhuang, Qianlai

2013-04-26

Our overall goal was to quantify the potential for threshold changes in natural emission rates of trace gases, particularly methane and carbon dioxide, from pan-arctic terrestrial systems under the spectrum of anthropogenically forced climate warming, and the extent to which these emissions provide a strong feedback mechanism to global climate warming. This goal is motivated under the premise that polar amplification of global climate warming will induce widespread thaw and degradation of the permafrost, and would thus cause substantial changes in the extent of wetlands and lakes, especially thermokarst (thaw) lakes, over the Arctic. Through a coordinated effort of fieldmore » measurements, model development, and numerical experimentation with an integrated assessment model framework, we have investigated the following hypothesis: There exists a climate-warming threshold beyond which permafrost degradation becomes widespread and thus instigates strong and/or sharp increases in methane emissions (via thermokarst lakes and wetland expansion). These would outweigh any increased uptake of carbon (e.g. from peatlands) and would result in a strong, positive feedback to global climate warming.« less

Challenges in the development of very high resolution Earth System Models for climate science

NASA Astrophysics Data System (ADS)

Rasch, Philip J.; Xie, Shaocheng; Ma, Po-Lun; Lin, Wuyin; Wan, Hui; Qian, Yun

2017-04-01

The authors represent the 20+ members of the ACME atmosphere development team. The US Department of Energy (DOE) has, like many other organizations around the world, identified the need for an Earth System Model capable of rapid completion of decade to century length simulations at very high (vertical and horizontal) resolution with good climate fidelity. Two years ago DOE initiated a multi-institution effort called ACME (Accelerated Climate Modeling for Energy) to meet this an extraordinary challenge, targeting a model eventually capable of running at 10-25km horizontal and 20-400m vertical resolution through the troposphere on exascale computational platforms at speeds sufficient to complete 5+ simulated years per day. I will outline the challenges our team has encountered in development of the atmosphere component of this model, and the strategies we have been using for tuning and debugging a model that we can barely afford to run on today's computational platforms. These strategies include: 1) evaluation at lower resolutions; 2) ensembles of short simulations to explore parameter space, and perform rough tuning and evaluation; 3) use of regionally refined versions of the model for probing high resolution model behavior at less expense; 4) use of "auto-tuning" methodologies for model tuning; and 5) brute force long climate simulations.

Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

NASA Astrophysics Data System (ADS)

Hanson, D. A.; Kotamarthi, V. R.; Foster, I. T.; Franklin, M.; Zhu, E.; Patel, D. M.

2008-12-01

Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.

Climate Literacy and Cyberlearning: Emerging Platforms and Programs

NASA Astrophysics Data System (ADS)

McCaffrey, M. S.; Wise, S. B.; Buhr, S. M.

2009-12-01

With the release of the Essential Principles of Climate Science Literacy: A Guide for Individuals and Communities in the Spring of 2009, an important step toward an shared educational and communication framework about climate science was achieved. Designed as a living document, reviewed and endorsed by the thirteen federal agencies in the U.S. Climate Change Science Program (now U.S. Global Change Research Program), the Essential Principles of Climate Literacy complement other Earth system literacy efforts. A variety of emerging efforts have begun to build on the framework using a variety of cyberlearning tools, including an online Climate Literacy course developed by Education and Outreach group at CIRES, the Cooperative Institute for Research in Environmental Sciences, and the Independent Learning program of the Continuing Education Division at the University of Colorado at Boulder. The online course, piloted during the Summer of 2009 with formal classroom teachers and informal science educators, made use of the online Climate Literacy Handbook, which was developed by CIRES Education and Outreach and the Encyclopedia of Earth, which is supported by the National Council for Science and the Environment and hosted by Boston University. This paper will explore challenges and opportunities in the use of cyberlearning tools to support climate literacy efforts, highlight the development of the online course and handbook, and note related emerging cyberlearning platforms and programs for climate literacy, including related efforts by the Climate Literacy Network, the NASA Global Climate Change Education programs, the National STEM Education Distributed Learning (NSDL) and AAAS Project 2061.

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

PubMed Central

Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241

Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

PubMed

Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

77 FR 59962 - John Heinz National Wildlife Refuge at Tinicum, DE and Philadelphia Counties, PA; Final...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-01

... efforts, and increase monitoring efforts for species and for climate change effects. Our environmental...-term relationships with schools and school districts. We would work to expand environmental... for climate change adaptation. However, under alternative C, we would delay much of these efforts to...

Model simulations and proxy-based reconstructions for the European region in the past millennium (Invited)

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-12-01

One of the objectives when comparing simulations of past climates to proxy-based climate reconstructions is to asses the skill of climate models to simulate climate change. This comparison may accomplished at large spatial scales, for instance the evolution of simulated and reconstructed Northern Hemisphere annual temperature, or at regional or point scales. In both approaches a 'fair' comparison has to take into account different aspects that affect the inevitable uncertainties and biases in the simulations and in the reconstructions. These efforts face a trade-off: climate models are believed to be more skillful at large hemispheric scales, but climate reconstructions are these scales are burdened by the spatial distribution of available proxies and by methodological issues surrounding the statistical method used to translate the proxy information into large-spatial averages. Furthermore, the internal climatic noise at large hemispheric scales is low, so that the sampling uncertainty tends to be also low. On the other hand, the skill of climate models at regional scales is limited by the coarse spatial resolution, which hinders a faithful representation of aspects important for the regional climate. At small spatial scales, the reconstruction of past climate probably faces less methodological problems if information from different proxies is available. The internal climatic variability at regional scales is, however, high. In this contribution some examples of the different issues faced when comparing simulation and reconstructions at small spatial scales in the past millennium are discussed. These examples comprise reconstructions from dendrochronological data and from historical documentary data in Europe and climate simulations with global and regional models. These examples indicate that the centennial climate variations can offer a reasonable target to assess the skill of global climate models and of proxy-based reconstructions, even at small spatial scales. However, as the focus shifts towards higher frequency variability, decadal or multidecadal, the need for larger simulation ensembles becomes more evident. Nevertheless,the comparison at these time scales may expose some lines of research on the origin of multidecadal regional climate variability.

Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts.

PubMed

Krause, Andreas; Pugh, Thomas A M; Bayer, Anita D; Li, Wei; Leung, Felix; Bondeau, Alberte; Doelman, Jonathan C; Humpenöder, Florian; Anthoni, Peter; Bodirsky, Benjamin L; Ciais, Philippe; Müller, Christoph; Murray-Tortarolo, Guillermo; Olin, Stefan; Popp, Alexander; Sitch, Stephen; Stehfest, Elke; Arneth, Almut

2018-07-01

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy. © 2018 John Wiley & Sons Ltd.

Coral reef habitat response to climate change scenarios.

PubMed

Freeman, Lauren A; Kleypas, Joan A; Miller, Arthur J

2013-01-01

Coral reef ecosystems are threatened by both climate change and direct anthropogenic stress. Climate change will alter the physico-chemical environment that reefs currently occupy, leaving only limited regions that are conducive to reef habitation. Identifying these regions early may aid conservation efforts and inform decisions to transplant particular coral species or groups. Here a species distribution model (Maxent) is used to describe habitat suitable for coral reef growth. Two climate change scenarios (RCP4.5, RCP8.5) from the National Center for Atmospheric Research's Community Earth System Model were used with Maxent to determine environmental suitability for corals (order Scleractinia). Environmental input variables best at representing the limits of suitable reef growth regions were isolated using a principal component analysis. Climate-driven changes in suitable habitat depend strongly on the unique region of reefs used to train Maxent. Increased global habitat loss was predicted in both climate projections through the 21(st) century. A maximum habitat loss of 43% by 2100 was predicted in RCP4.5 and 82% in RCP8.5. When the model is trained solely with environmental data from the Caribbean/Atlantic, 83% of global habitat was lost by 2100 for RCP4.5 and 88% was lost for RCP8.5. Similarly, global runs trained only with Pacific Ocean reefs estimated that 60% of suitable habitat would be lost by 2100 in RCP4.5 and 90% in RCP8.5. When Maxent was trained solely with Indian Ocean reefs, suitable habitat worldwide increased by 38% in RCP4.5 by 2100 and 28% in RCP8.5 by 2050. Global habitat loss by 2100 was just 10% for RCP8.5. This projection suggests that shallow tropical sites in the Indian Ocean basin experience conditions today that are most similar to future projections of worldwide conditions. Indian Ocean reefs may thus be ideal candidate regions from which to select the best strands of coral for potential re-seeding efforts.

Developing a calibrated CONUS-wide watershed-scale simulation platform for quantifying the influence of different sources of uncertainty on streamflow forecast skill

NASA Astrophysics Data System (ADS)

Newman, A. J.; Sampson, K. M.; Wood, A. W.; Hopson, T. M.; Brekke, L. D.; Arnold, J.; Raff, D. A.; Clark, M. P.

2013-12-01

Skill in model-based hydrologic forecasting depends on the ability to estimate a watershed's initial moisture and energy conditions, to forecast future weather and climate inputs, and on the quality of the hydrologic model's representation of watershed processes. The impact of these factors on prediction skill varies regionally, seasonally, and by model. We are investigating these influences using a watershed simulation platform that spans the continental US (CONUS), encompassing a broad range of hydroclimatic variation, and that uses the current simulation models of National Weather Service streamflow forecasting operations. The first phase of this effort centered on the implementation and calibration of the SNOW-17 and Sacramento soil moisture accounting (SAC-SMA) based hydrologic modeling system for a range of watersheds. The base configuration includes 630 basins in the United States Geological Survey's Hydro-Climatic Data Network 2009 (HCDN-2009, Lins 2012) conterminous U.S. basin subset. Retrospective model forcings were derived from Daymet (http://daymet.ornl.gov/), and where available, a priori parameter estimates were based on or compared with the operational NWS model parameters. Model calibration was accomplished by several objective, automated strategies, including the shuffled complex evolution (SCE) optimization approach developed within the NWS in the early 1990s (Duan et al. 1993). This presentation describes outcomes from this effort, including insights about measuring simulation skill, and on relationships between simulation skill and model parameters, basin characteristics (climate, topography, vegetation, soils), and the quality of forcing inputs. References: %Z Thornton, P.; Thornton, M.; Mayer, B.; Wilhelmi, N.; Wei, Y.; Devarakonda, R; Cook, R. Daymet: Daily Surface Weather on a 1 km Grid for North America. 1980-2008; Oak Ridge National Laboratory Distributed Active Archive Center: Oak Ridge, TN, USA, 2012; Volume 10.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity.

PubMed

Bustamante, Mercedes M C; Roitman, Iris; Aide, T Mitchell; Alencar, Ane; Anderson, Liana O; Aragão, Luiz; Asner, Gregory P; Barlow, Jos; Berenguer, Erika; Chambers, Jeffrey; Costa, Marcos H; Fanin, Thierry; Ferreira, Laerte G; Ferreira, Joice; Keller, Michael; Magnusson, William E; Morales-Barquero, Lucia; Morton, Douglas; Ometto, Jean P H B; Palace, Michael; Peres, Carlos A; Silvério, Divino; Trumbore, Susan; Vieira, Ima C G

2016-01-01

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation. © 2015 John Wiley & Sons Ltd.

Ice Sheet Model Intercomparison Project (ISMIP6) Contribution to CMIP6

NASA Technical Reports Server (NTRS)

Nowicki, Sophie M. J.; Payne, Tony; Larour, Eric; Seroussi, Helene; Goelzer, Heiko; Lipscomb, William; Gregory, Jonathan; Abe-Ouchi, Ayako; Shepherd, Andrew

2016-01-01

Reducing the uncertainty in the past, present, and future contribution of ice sheets to sea-level change requires a coordinated effort between the climate and glaciology communities. The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) is the primary activity within the Coupled Model Intercomparison Project phase 6 (CMIP6) focusing on the Greenland and Antarctic ice sheets. In this paper, we describe the framework for ISMIP6 and its relationship with other activities within CMIP6. The ISMIP6 experimental design relies on CMIP6 climate models and includes, for the first time within CMIP, coupled ice-sheetclimate models as well as standalone ice-sheet models. To facilitate analysis of the multi-model ensemble and to generate a set of standard climate inputs for standalone ice-sheet models, ISMIP6 defines a protocol for all variables related to ice sheets. ISMIP6 will provide a basis for investigating the feedbacks, impacts, and sea-level changes associated with dynamic ice sheets and for quantifying the uncertainty in ice-sheet-sourced global sea-level change.

Representing agriculture in Earth System Models: Approaches and priorities for development

NASA Astrophysics Data System (ADS)

McDermid, S. S.; Mearns, L. O.; Ruane, A. C.

2017-09-01

Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land-use and intensive in management, owing to 20th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture-climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate-crop models that capture dynamic feedbacks. We highlight the robust agriculture-climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land-use-climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Last, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate-surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.

A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier

NASA Astrophysics Data System (ADS)

Strigaro, Daniele; Moretti, Massimiliano; Mattavelli, Matteo; Frigerio, Ivan; Amicis, Mattia De; Maggi, Valter

2016-09-01

The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model, is developed in a GRASS GIS (GRASS Development Team, 2016) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change.

Creating Dynamically Downscaled Seasonal Climate Forecast and Climate Change Projection Information for the North American Monsoon Region Suitable for Decision Making Purposes

NASA Astrophysics Data System (ADS)

Castro, C. L.; Dominguez, F.; Chang, H.

2010-12-01

Current seasonal climate forecasts and climate change projections of the North American monsoon are based on the use of course-scale information from a general circulation model. The global models, however, have substantial difficulty in resolving the regional scale forcing mechanisms of precipitation. This is especially true during the period of the North American Monsoon in the warm season. Precipitation is driven primarily due to the diurnal cycle of convection, and this process cannot be resolve in coarse-resolution global models that have a relatively poor representation of terrain. Though statistical downscaling may offer a relatively expedient method to generate information more appropriate for the regional scale, and is already being used in the resource decision making processes in the Southwest U.S., its main drawback is that it cannot account for a non-stationary climate. Here we demonstrate the use of a regional climate model, specifically the Weather Research and Forecast (WRF) model, for dynamical downscaling of the North American Monsoon. To drive the WRF simulations, we use retrospective reforecasts from the Climate Forecast System (CFS) model, the operational model used at the U.S. National Center for Environmental Prediction, and three select “well performing” IPCC AR 4 models for the A2 emission scenario. Though relatively computationally expensive, the use of WRF as a regional climate model in this way adds substantial value in the representation of the North American Monsoon. In both cases, the regional climate model captures a fairly realistic and reasonable monsoon, where none exists in the driving global model, and captures the dominant modes of precipitation anomalies associated with ENSO and the Pacific Decadal Oscillation (PDO). Long-term precipitation variability and trends in these simulations is considered via the standardized precipitation index (SPI), a commonly used metric to characterize long-term drought. Dynamically downscaled climate projection data will be integrated into future water resource projections in the state of Arizona, through a cooperative effort involving numerous water resource stakeholders.

Adapting water treatment design and operations to the impacts of global climate change

NASA Astrophysics Data System (ADS)

Clark, Robert M.; Li, Zhiwei; Buchberger, Steven G.

2011-12-01

It is anticipated that global climate change will adversely impact source water quality in many areas of the United States and will therefore, potentially, impact the design and operation of current and future water treatment systems. The USEPA has initiated an effort called the Water Resources Adaptation Program (WRAP) which is intended to develop tools and techniques that can assess the impact of global climate change on urban drinking water and wastewater infrastructure. A three step approach for assessing climate change impacts on water treatment operation and design is being persude in this effort. The first step is the stochastic characterization of source water quality, the second step is the application of the USEPA Water Treatment Plant model and the third step is the application of cost algorithms to provide a metric that can be used to assess the coat impact of climate change. A model has been validated using data collected from Cincinnati's Richard Miller Water Treatment Plant for the USEPA Information Collection Rule (ICR) database. An analysis of the water treatment processes in response to assumed perturbations in raw water quality identified TOC, pH, and bromide as the three most important parameters affecting performance of the Miller WTP. The Miller Plant was simulated using the EPA WTP model to examine the impact of these parameters on selected regulated water quality parameters. Uncertainty in influent water quality was analyzed to estimate the risk of violating drinking water maximum contaminant levels (MCLs).Water quality changes in the Ohio River were projected for 2050 using Monte Carlo simulation and the WTP model was used to evaluate the effects of water quality changes on design and operation. Results indicate that the existing Miller WTP might not meet Safe Drinking Water Act MCL requirements for certain extreme future conditions. However, it was found that the risk of MCL violations under future conditions could be controlled by enhancing existing WTP design and operation or by process retrofitting and modification.

Promoting pro-environmental action in climate change deniers

NASA Astrophysics Data System (ADS)

Bain, Paul G.; Hornsey, Matthew J.; Bongiorno, Renata; Jeffries, Carla

2012-08-01

A sizeable (and growing) proportion of the public in Western democracies deny the existence of anthropogenic climate change. It is commonly assumed that convincing deniers that climate change is real is necessary for them to act pro-environmentally. However, the likelihood of `conversion' using scientific evidence is limited because these attitudes increasingly reflect ideological positions. An alternative approach is to identify outcomes of mitigation efforts that deniers find important. People have strong interests in the welfare of their society, so deniers may act in ways supporting mitigation efforts where they believe these efforts will have positive societal effects. In Study 1, climate change deniers (N=155) intended to act more pro-environmentally where they thought climate change action would create a society where people are more considerate and caring, and where there is greater economic/technological development. Study 2 (N=347) replicated this experimentally, showing that framing climate change action as increasing consideration for others, or improving economic/technological development, led to greater pro-environmental action intentions than a frame emphasizing avoiding the risks of climate change. To motivate deniers' pro-environmental actions, communication should focus on how mitigation efforts can promote a better society, rather than focusing on the reality of climate change and averting its risks.

Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

PubMed

Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

2014-08-01

Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate forecasts lead to ineffective prioritization of conservation activities and potentially to avoidable species extinctions. © 2014 John Wiley & Sons Ltd.

Modeling Climate Change Impacts on Landscape Evolution, Fire, and Hydrology

NASA Astrophysics Data System (ADS)

Sheppard, B. S.; O Connor, C.; Falk, D. A.; Garfin, G. M.

2015-12-01

Landscape disturbances such as wildfire interact with climate variability to influence hydrologic regimes. We coupled landscape, fire, and hydrologic models and forced them using projected climate to demonstrate climate change impacts anticipated at Fort Huachuca in southeastern Arizona, USA. The US Department of Defense (DoD) recognizes climate change as a trend that has implications for military installations, national security and global instability. The goal of this DoD Strategic Environmental Research and Development Program (SERDP) project (RC-2232) is to provide decision making tools for military installations in the southwestern US to help them adapt to the operational realities associated with climate change. For this study we coupled the spatially explicit fire and vegetation dynamics model FireBGCv2 with the Automated Geospatial Watershed Assessment tool (AGWA) to evaluate landscape vegetation change, fire disturbance, and surface runoff in response to projected climate forcing. A projected climate stream for the years 2005-2055 was developed from the Multivariate Adaptive Constructed Analogs (MACA) 4 km statistical downscaling of the CanESM2 GCM using Representative Concentration Pathway (RCP) 8.5. AGWA, an ArcGIS add-in tool, was used to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and the KINematic runoff and EROSion2 (KINEROS2) models based on GIS layers. Landscape raster data generated by FireBGCv2 project an increase in fire and drought associated tree mortality and a decrease in vegetative basal area over the years of simulation. Preliminary results from SWAT modeling efforts show an increase to surface runoff during years following a fire, and for future winter rainy seasons. Initial results from KINEROS2 model runs show that peak runoff rates are expected to increase 10-100 fold as a result of intense rainfall falling on burned areas.

Mind the wind: microclimate effects on incubation effort of an arctic seabird.

PubMed

Høyvik Hilde, Christoffer; Pélabon, Christophe; Guéry, Loreleï; Gabrielsen, Geir Wing; Descamps, Sébastien

2016-04-01

The energetic costs of reproduction in birds strongly depend on the climate experienced during incubation. Climate change and increasing frequency of extreme weather events may severely affect these costs, especially for species incubating in extreme environments. In this 3-year study, we used an experimental approach to investigate the effects of microclimate and nest shelter on the incubation effort of female common eiders (Somateria mollissima) in a wild Arctic population. We added artificial shelters to a random selection of nesting females, and compared incubation effort, measured as body mass loss during incubation, between females with and without shelter. Nonsheltered females had a higher incubation effort than females with artificial shelters. In nonsheltered females, higher wind speeds increased the incubation effort, while artificially sheltered females experienced no effect of wind. Although increasing ambient temperatures tended to decrease incubation effort, this effect was negligible in the absence of wind. Humidity had no marked effect on incubation effort. This study clearly displays the direct effect of a climatic variable on an important aspect of avian life-history. By showing that increasing wind speed counteracts the energetic benefits of a rising ambient temperature, we were able to demonstrate that a climatic variable other than temperature may also affect wild populations and need to be taken into account when predicting the effects of climate change.

Regional Climate Change Impact on Agricultural Land Use in West Africa

NASA Astrophysics Data System (ADS)

Ahmed, K. F.; Wang, G.; You, L.

2014-12-01

Agriculture is a key element of the human-induced land use land cover change (LULCC) that is influenced by climate and can potentially influence regional climate. Temperature and precipitation directly impact the crop yield (by controlling photosynthesis, respiration and other physiological processes) that then affects agricultural land use pattern. In feedback, the resulting changes in land use and land cover play an important role to determine the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. The assessment of future agricultural land use is, therefore, of great importance in climate change study. In this study, we develop a prototype land use projection model and, using this model, project the changes to land use pattern and future land cover map accounting for climate-induced yield changes for major crops in West Africa. Among the inputs to the land use projection model are crop yield changes simulated by the crop model DSSAT, driven with the climate forcing data from the regional climate model RegCM4.3.4-CLM4.5, which features a projected decrease of future mean crop yield and increase of inter-annual variability. Another input to the land use projection model is the projected changes of food demand in the future. In a so-called "dumb-farmer scenario" without any adaptation, the combined effect of decrease in crop yield and increase in food demand will lead to a significant increase in agricultural land use in future years accompanied by a decrease in forest and grass area. Human adaptation through land use optimization in an effort to minimize agricultural expansion is found to have little impact on the overall areas of agricultural land use. While the choice of the General Circulation Model (GCM) to derive initial and boundary conditions for the regional climate model can be a source of uncertainty in projecting the future LULCC, results from sensitivity experiments indicate that the changes in land use pattern are robust.

School Climate and Leadership: Levers for School Improvement Efforts

ERIC Educational Resources Information Center

Costa, Lois

2016-01-01

This qualitative study considers which aspects of school climate support or inhibit student achievement as each aspect relates to school leadership and school reform efforts. Due to the increased responsibility and accountability which schools face during these challenging times, school climate and the role of the school principal formed the basis…

Malaria Ecology, Disease Burden and Global Climate Change

NASA Astrophysics Data System (ADS)

Mccord, G. C.

2014-12-01

Malaria has afflicted human society for over 2 million years, and remains one of the great killer diseases today. The disease is the fourth leading cause of death for children under five in low income countries (after neonatal disorders, diarrhea, and pneumonia) and is responsible for at least one in every five child deaths in sub-Saharan Africa. It kills up to 3 million people a year, though in recent years scale up of anti-malaria efforts in Africa may have brought deaths to below 1 million. Malaria is highly conditioned by ecology, because of which climate change is likely to change the local dynamics of the disease through changes in ambient temperature and precipitation. To assess the potential implications of climate change for the malaria burden, this paper employs a Malaria Ecology Index from the epidemiology literature, relates it to malaria incidence and mortality using global country-level data , and then draws implications for 2100 by extrapolating the index using several general circulation model (GCM) predictions of temperature and precipitation. The results highlight the climate change driven increase in the basic reproduction number of the disease and the resulting complications for further gains in elimination. For illustrative purposes, I report the change in malaria incidence and mortality if climate change were to happen immediately under current technology and public health efforts.

Agricultural response functions to changes in carbon, temperature, and water based on the C3MP data set

NASA Astrophysics Data System (ADS)

Snyder, A.; Ruane, A. C.; Phillips, M.; Calvin, K. V.; Clarke, L.

2017-12-01

Agricultural yields vary depending on temperature, precipitation/irrigation conditions, fertilizer application, and CO2 concentration. The Coordinated Climate-Crop Modeling Project (C3MP), conducted as a component of the Agricultural Model Intercomparison and Improvement Project (AgMIP), organized a sensitivity experiments across carbon-temperature-water (CTW) space across 1100 management conditions in 50+ countries, sampling 15 crop species and 20 crop models. Such coordinated sensitivity tests allow for the building of emulators of yield response to changes in CTW values, allowing rapid estimation of yield changes from the types of climate changes projected by the climate modeling community. The resulting emulator may be used to supply agricultural responses to climate change in any user-defined scenario, rather than the restriction to the RCPs in many past works. We present the resulting emulators built from the C3MP output data set for use in the Global Change Assessment Model (GCAM) integrated assessment model that allows for the co-evolution of socioeconomic development, greenhouse gas emissions, climate change, and agricultural sector ramifications. C3MP-based emulators may be of use in designing agricultural impact studies in other IAMs, and we place them in the context of past crop modeling efforts, including the Challinor et al. Meta-analysis, the AgMIP Wheat team results, the AgMIP Global Gridded Crop Model Intercomparison (GGCMI) fast-track modeling results, and the MACSUR impact response surface results.

A fickle sun could be altering Earth`s climate after all

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

Kerr, R.A.

1995-08-01

A long effort to link slight fluctuations in solar output with climate on Earth may finally be succeeding. A cycle of temperature changes in much of the middle and low atmosphere matches the 11 year sunspot cycle over much of the Northern Hemisphere. The findings were reported at the International Union of Geodesy and Gophysics meeting in Colorado. This article discusses the evidence and the modeling which has been done to reveal this possible connection. 1 fig.

An overview of mineral dust modeling over East Asia

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Plant distributions along salinity and tidal gradients in Oregon tidal marshes

EPA Science Inventory

Accurately modeling climate change effects on tidal marshes in the Pacific Northwest requires understanding how plant assemblages and species are presently distributed along gradients of salinity and tidal inundation. We outline on-going field efforts by the EPA and USGS to dete...

Understanding Faculty Needs: An Institutional Imperative.

ERIC Educational Resources Information Center

O'Hara, Leonard F.

1996-01-01

Describes the importance of obtaining faculty support to ensure success in college reform efforts, and reviews strategies for improving institutional climate. Discusses a survey instrument designed to measure faculty perceptions of college atmosphere and developed as part of the Fourth Paradigm Governance Model. Includes a sample faculty…

The impact of shale gas on the cost and feasibility of meeting climate targets—A global energy system model analysis and an exploration of uncertainties

DOE PAGES

Few, Sheridan; Gambhir, Ajay; Napp, Tamaryn; ...

2017-01-27

There exists considerable uncertainty over both shale and conventional gas resource availability and extraction costs, as well as the fugitive methane emissions associated with shale gas extraction and its possible role in mitigating climate change. This study uses a multi-region energy system model, TIAM (TIMES integrated assessment model), to consider the impact of a range of conventional and shale gas cost and availability assessments on mitigation scenarios aimed at achieving a limit to global warming of below 2 °C in 2100, with a 50% likelihood. When adding shale gas to the global energy mix, the reduction to the global energymore » system cost is relatively small (up to 0.4%), and the mitigation cost increases by 1%–3% under all cost assumptions. The impact of a “dash for shale gas”, of unavailability of carbon capture and storage, of increased barriers to investment in low carbon technologies, and of higher than expected leakage rates, are also considered; and are each found to have the potential to increase the cost and reduce feasibility of meeting global temperature goals. Finally, we conclude that the extraction of shale gas is not likely to significantly reduce the effort required to mitigate climate change under globally coordinated action, but could increase required mitigation effort if not handled sufficiently carefully.« less

The impact of shale gas on the cost and feasibility of meeting climate targets—A global energy system model analysis and an exploration of uncertainties

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

Few, Sheridan; Gambhir, Ajay; Napp, Tamaryn

There exists considerable uncertainty over both shale and conventional gas resource availability and extraction costs, as well as the fugitive methane emissions associated with shale gas extraction and its possible role in mitigating climate change. This study uses a multi-region energy system model, TIAM (TIMES integrated assessment model), to consider the impact of a range of conventional and shale gas cost and availability assessments on mitigation scenarios aimed at achieving a limit to global warming of below 2 °C in 2100, with a 50% likelihood. When adding shale gas to the global energy mix, the reduction to the global energymore » system cost is relatively small (up to 0.4%), and the mitigation cost increases by 1%–3% under all cost assumptions. The impact of a “dash for shale gas”, of unavailability of carbon capture and storage, of increased barriers to investment in low carbon technologies, and of higher than expected leakage rates, are also considered; and are each found to have the potential to increase the cost and reduce feasibility of meeting global temperature goals. Finally, we conclude that the extraction of shale gas is not likely to significantly reduce the effort required to mitigate climate change under globally coordinated action, but could increase required mitigation effort if not handled sufficiently carefully.« less

Foraminifera Models to Interrogate Ostensible Proxy-Model Discrepancies During Late Pliocene

NASA Astrophysics Data System (ADS)

Jacobs, P.; Dowsett, H. J.; de Mutsert, K.

2017-12-01

Planktic foraminifera faunal assemblages have been used in the reconstruction of past oceanic states (e.g. the Last Glacial Maximum, the mid-Piacenzian Warm Period). However these reconstruction efforts have typically relied on inverse modeling using transfer functions or the modern analog technique, which by design seek to translate foraminifera into one or two target oceanic variables, primarily sea surface temperature (SST). These reconstructed SST data have then been used to test the performance of climate models, and discrepancies have been attributed to shortcomings in climate model processes and/or boundary conditions. More recently forward proxy models or proxy system models have been used to leverage the multivariate nature of proxy relationships to their environment, and to "bring models into proxy space". Here we construct ecological models of key planktic foraminifera taxa, calibrated and validated with World Ocean Atlas (WO13) oceanographic data. Multiple modeling methods (e.g. multilayer perceptron neural networks, Mahalanobis distance, logistic regression, and maximum entropy) are investigated to ensure robust results. The resulting models are then driven by a Late Pliocene climate model simulation with biogeochemical as well as temperature variables. Similarities and differences with previous model-proxy comparisons (e.g. PlioMIP) are discussed.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

PubMed Central

Pugh, T.A.M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand. PMID:27646707

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 Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

NASA Technical Reports Server (NTRS)

Pugh, T. A. M.; Mueller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

NASA Astrophysics Data System (ADS)

Pugh, T. A. M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-09-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

NASA Astrophysics Data System (ADS)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All approaches underline the technical difficulties of snow cover modelling during the monsoon season, in accordance with previous studies. The developed methods in combination with continuous in situ measurements provide a basis for further downscaling approaches.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

USGS Publications Warehouse

Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie A.; Reed, Sasha C.; Reich, Peter B.; Ryan, Michael G.; Wood, Tana E.; Yang, Xiaojuan

2017-01-01

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is to compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

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

Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO 2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is tomore » compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO 2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.« less

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

NASA Astrophysics Data System (ADS)

Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie; Reed, Sasha; Reich, Peter B.; Ryan, Michael G.; Wood, Tana E.; Yang, Xiaojuan

2017-10-01

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is to compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

DOE PAGES

Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie; ...

2017-10-23

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO 2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is tomore » compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO 2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.« less

Ensembles-based predictions of climate change impacts on bioclimatic zones in Northeast Asia

NASA Astrophysics Data System (ADS)

Choi, Y.; Jeon, S. W.; Lim, C. H.; Ryu, J.

2017-12-01

Biodiversity is rapidly declining globally and efforts are needed to mitigate this continually increasing loss of species. Clustering of areas with similar habitats can be used to prioritize protected areas and distribute resources for the conservation of species, selection of representative sample areas for research, and evaluation of impacts due to environmental changes. In this study, Northeast Asia (NEA) was classified into 14 bioclimatic zones using statistical techniques, which are correlation analysis and principal component analysis (PCA), and the iterative self-organizing data analysis technique algorithm (ISODATA). Based on these bioclimatic classification, we predicted shift of bioclimatic zones due to climate change. The input variables include the current climatic data (1960-1990) and the future climatic data of the HadGEM2-AO model (RCP 4.5(2050, 2070) and 8.5(2050, 2070)) provided by WorldClim. Using these data, multi-modeling methods including maximum likelihood classification, random forest, and species distribution modelling have been used to project the impact of climate change on the spatial distribution of bioclimatic zones within NEA. The results of various models were compared and analyzed by overlapping each result. As the result, significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward and some zones were predicted to disappear. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.

Association of Birthweight With Maternal Trajectories of Effort-Reward Imbalance and Demand-Control Across Pregnancy.

PubMed

Meyer, John D; O'Campo, Patricia; Warren, Nicolas; Muntaner, Carles

2017-02-01

We assessed longitudinal patterns of effort-reward imbalance (ERI) and demand-control (DC) scores in pregnancy, and their association with newborn birthweight (BW). Sixty-one women were surveyed four times across pregnancy using the ERI and DC questionnaires. Trajectories of change in ERI and DC scores across pregnancy were constructed using growth mixture modeling, and their associations with BW were examined with generalized linear regression. Declining ERI (diminishing effort with stable/increasing reward) was associated with higher BW (408 g; P = 0.015), and was robust to other work factors. DC trajectory was not significantly associated with BW. Declining ERI may reflect improved work psychosocial climate across pregnancy, or a conscious reduction in effort. The ERI model may represent more flexible work characteristics, whereas job control may be less amenable to short-term alteration. Surveys in more diverse pregnant working populations could be recommended.

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.

The Influence of Effortful Control and Empathy on Perception of School Climate

ERIC Educational Resources Information Center

Zorza, Juan P.; Marino, Julián; Mesas, Alberto Acosta

2015-01-01

The purpose of this study was to determine the predictive power of effortful control (EC) and empathy for perception of school climate. Self-report measures of EC, dispositional empathy, and perception of school climate were obtained for 398 students (204 females) aged 12 to 13. Sociometric status was peer-evaluated, and academic achievement was…

Addressing potential local adaptation in species distribution models: implications for conservation under climate change

USGS Publications Warehouse

Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.

2016-01-01

Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

Geospatial modeling of plant stable isotope ratios - the development of isoscapes

NASA Astrophysics Data System (ADS)

West, J. B.; Ehleringer, J. R.; Hurley, J. M.; Cerling, T. E.

2007-12-01

Large-scale spatial variation in stable isotope ratios can yield critical insights into the spatio-temporal dynamics of biogeochemical cycles, animal movements, and shifts in climate, as well as anthropogenic activities such as commerce, resource utilization, and forensic investigation. Interpreting these signals requires that we understand and model the variation. We report progress in our development of plant stable isotope ratio landscapes (isoscapes). Our approach utilizes a GIS, gridded datasets, a range of modeling approaches, and spatially distributed observations. We synthesize findings from four studies to illustrate the general utility of the approach, its ability to represent observed spatio-temporal variability in plant stable isotope ratios, and also outline some specific areas of uncertainty. We also address two basic, but critical questions central to our ability to model plant stable isotope ratios using this approach: 1. Do the continuous precipitation isotope ratio grids represent reasonable proxies for plant source water?, and 2. Do continuous climate grids (as is or modified) represent a reasonable proxy for the climate experienced by plants? Plant components modeled include leaf water, grape water (extracted from wine), bulk leaf material ( Cannabis sativa; marijuana), and seed oil ( Ricinus communis; castor bean). Our approaches to modeling the isotope ratios of these components varied from highly sophisticated process models to simple one-step fractionation models to regression approaches. The leaf water isosocapes were produced using steady-state models of enrichment and continuous grids of annual average precipitation isotope ratios and climate. These were compared to other modeling efforts, as well as a relatively sparse, but geographically distributed dataset from the literature. The latitudinal distributions and global averages compared favorably to other modeling efforts and the observational data compared well to model predictions. These results yield confidence in the precipitation isoscapes used to represent plant source water, the modified climate grids used to represent leaf climate, and the efficacy of this approach to modeling. Further work confirmed these observations. The seed oil isoscape was produced using a simple model of lipid fractionation driven with the precipitation grid, and compared well to widely distributed observations of castor bean oil, again suggesting that the precipitation grids were reasonable proxies for plant source water. The marijuana leaf δ2H observations distributed across the continental United States were regressed against the precipitation δ2H grids and yielded a strong relationship between them, again suggesting that plant source water was reasonably well represented by the precipitation grid. Finally, the wine water δ18O isoscape was developed from regressions that related precipitation isotope ratios and climate to observations from a single vintage. Favorable comparisons between year-specific wine water isoscapes and inter-annual variations in previous vintages yielded confidence in the climate grids. Clearly significant residual variability remains to be explained in all of these cases and uncertainties vary depending on the component modeled, but we conclude from this synthesis that isoscapes are capable of representing real spatial and temporal variability in plant stable isotope ratios.

Satellite Remote Sensing and Mesoscale Modeling of Biomass Burning Aerosols over the Southeast Asian Maritime Continent: Climatic Implications of Smokes on Regional Energy Balance, Cloud Formations and Precipitations

NASA Astrophysics Data System (ADS)

Feng, N.

2015-12-01

The influences of anthropogenic aerosols have been suggested as an important reason for climate changes over Southeast Asia (SE Asia, 10°S~20°N and 90°E~135°E). Accurate observations and modelling of aerosols effects on the weather and climate patterns is crucial for a better understanding and mitigation of anthropogenic climate change. This study uses NASA satellite observations along with online-coupled Weather Research and Forecasting model with Chemistry (WRF-Chem) to evaluate aerosols impacts on climate over SE Asia. We assess the direct and semi-direct radiative effects of smoke particles over this region during September, 2009 when a significant El Niño event caused the highest biomass burning activity during the last 15 years. Quantification efforts are made to assess how changes of radiative and non radiative parameters (sensible and latent heat) due to smoke aerosols would affect regional climate process such as precipitations, clouds and planetary boundary layer process. Comparison of model simulations for the current land cover conditions against surface meteorological observations and satellite observations of precipitations and cloudiness show satisfactory performance of the model over our study area. In order to quantitatively validate the model results, several experiments will be performed to test the aerosols radiative feedback under different radiation schemes and with/without considering aerosol effects explicitly in the model. Relevant ground-based data (e.g. AERONET), along with aerosol vertical profile data from CALIPSO, will also be applied.

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.

Estimating thermal regimes of bull trout and assessing the potential effects of climate warming on critical habitats

USGS Publications Warehouse

Jones, Leslie A.; Muhlfeld, Clint C.; Marshall, Lucy A.; McGlynn, Brian L.; Kershner, Jeffrey L.

2013-01-01

Understanding the vulnerability of aquatic species and habitats under climate change is critical for conservation and management of freshwater systems. Climate warming is predicted to increase water temperatures in freshwater ecosystems worldwide, yet few studies have developed spatially explicit modelling tools for understanding the potential impacts. We parameterized a nonspatial model, a spatial flow-routed model, and a spatial hierarchical model to predict August stream temperatures (22-m resolution) throughout the Flathead River Basin, USA and Canada. Model comparisons showed that the spatial models performed significantly better than the nonspatial model, explaining the spatial autocorrelation found between sites. The spatial hierarchical model explained 82% of the variation in summer mean (August) stream temperatures and was used to estimate thermal regimes for threatened bull trout (Salvelinus confluentus) habitats, one of the most thermally sensitive coldwater species in western North America. The model estimated summer thermal regimes of spawning and rearing habitats at <13 C° and foraging, migrating, and overwintering habitats at <14 C°. To illustrate the useful application of such a model, we simulated climate warming scenarios to quantify potential loss of critical habitats under forecasted climatic conditions. As air and water temperatures continue to increase, our model simulations show that lower portions of the Flathead River Basin drainage (foraging, migrating, and overwintering habitat) may become thermally unsuitable and headwater streams (spawning and rearing) may become isolated because of increasing thermal fragmentation during summer. Model results can be used to focus conservation and management efforts on populations of concern, by identifying critical habitats and assessing thermal changes at a local scale.

Autogenic and Allogenic: Emergent Coastline Patterns Interact With Forcing Variations

NASA Astrophysics Data System (ADS)

Murray, A. B.; Alvarez Antolinez, J. A.; Mendez, F. J.; Moore, L. J.; Wood, J.; Farley, G.

2017-12-01

A range of coastline shapes can emerge from large-scale morphodynamic interactions. Coastline shape determines local wave influences. Local wave influences (fluxes of alongshore momentum), determine sediment fluxes, and gradients in these sediment fluxes, in turn, alter coastline shape. Modeling studies show that such feedbacks lead to an instability, and to subsequent finite-amplitude interactions, producing self-organized patterns and emergent structures including sandwaves, capes, and spits (e.g. Ashton and Murray, 2006; Ashton et al., 2015); spiral bays on rocky coastlines (e.g. Barkwith et al., 2014); and convex, spit-bounded coastlines (Ells et al., in prep.). Coastline shapes depend sensitively on wave climate, defined as the angular distribution of wave influences on alongshore sediment transport. Therefore, shifts in wave climate arising from shifts in storms (decadal scale fluctuations or longer-term trends) will tend to change coastline shape. Previous efforts have detected changing coastline shape, likely related to changing influence from hurricane-generated waves, as expressed in changes in the location and intensity of coastal erosion zones along the cuspate capes in North Carolina, USA (Moore et al., 2013). These efforts involved the assumption that coastline response to changing forcing occurs in a quasi-equilibrium manner. However, in some cases coastline responses can exhibit long-term memory and path dependence (Thomas et al., 2016). Recently, we have hindcast the wave climate affecting the North Carolina coast since 1870, using a series of statistical analyses to downscale from basin-scale surface pressure fields to regional deep-water wave climate, and then a numerical transformation to local offshore wave climate. We used this wave climate as input for the Coastline Evolution Model (CEM). The results show that the emergent coastline features respond to decadal-scale shifts in wave climate, but with time lags that complicate the relationship between forcing and coastline shape. Comparisons between model predictions and observed shoreline-change patterns support the suggestion that the relationship between emergent coastline behaviours (autogenic processes) and external influences (autogenic forcing) involves such memory effects (Antolinez et al., in revision).

Geocuration Lessons Learned from the Climate Data Initiative Project

NASA Technical Reports Server (NTRS)

Ramachandran, Rahul; Bugbee, Kaylin; Tilmes, Curt; Pinheiro Privette, Ana

2015-01-01

Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. This presentation will introduce the concept of geocuration, which we define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful compendium. We also present the Climate Data Initiative (CDI) project as an prototypical example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate change preparedness. The geocuration process used in the CDI project, key lessons learned, and suggestions to improve similar geocuration efforts in the future will be part of this presentation.

Geocuration Lessons Learned from the Climate Data Initiative Project

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Bugbee, K.; Tilmes, C.; Privette, A. P.

2015-12-01

Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. This presentation will introduce the concept of geocuration, which we define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful compendium.We also present the Climate Data Initiative (CDI) project as an exemplar example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate-change preparedness. The geocuration process used in CDI project, key lessons learned, and suggestions to improve similar geocuration efforts in the future will be part of this presentation.

"Development of an interactive crop growth web service architecture to review and forecast agricultural sustainability"

NASA Astrophysics Data System (ADS)

Seamon, E.; Gessler, P. E.; Flathers, E.; Walden, V. P.

2014-12-01

As climate change and weather variability raise issues regarding agricultural production, agricultural sustainability has become an increasingly important component for farmland management (Fisher, 2005, Akinci, 2013). Yet with changes in soil quality, agricultural practices, weather, topography, land use, and hydrology - accurately modeling such agricultural outcomes has proven difficult (Gassman et al, 2007, Williams et al, 1995). This study examined agricultural sustainability and soil health over a heterogeneous multi-watershed area within the Inland Pacific Northwest of the United States (IPNW) - as part of a five year, USDA funded effort to explore the sustainability of cereal production systems (Regional Approaches to Climate Change for Pacific Northwest Agriculture - award #2011-68002-30191). In particular, crop growth and soil erosion were simulated across a spectrum of variables and time periods - using the CropSyst crop growth model (Stockle et al, 2002) and the Water Erosion Protection Project Model (WEPP - Flanagan and Livingston, 1995), respectively. A preliminary range of historical scenarios were run, using a high-resolution, 4km gridded dataset of surface meteorological variables from 1979-2010 (Abatzoglou, 2012). In addition, Coupled Model Inter-comparison Project (CMIP5) global climate model (GCM) outputs were used as input to run crop growth model and erosion future scenarios (Abatzoglou and Brown, 2011). To facilitate our integrated data analysis efforts, an agricultural sustainability web service architecture (THREDDS/Java/Python based) is under development, to allow for the programmatic uploading, sharing and processing of variable input data, running model simulations, as well as downloading and visualizing output results. The results of this study will assist in better understanding agricultural sustainability and erosion relationships in the IPNW, as well as provide a tangible server-based tool for use by researchers and farmers - for both small scale field examination, or more regionalized scenarios.

Modeling of Regional Climate Change Effects on Ground-Level Ozone and Childhood Asthma

PubMed Central

Sheffield, Perry E.; Knowlton, Kim; Carr, Jessie L.; Kinney, Patrick L.

2011-01-01

Background The adverse respiratory effects of ground-level ozone are well-established. Ozone is the air pollutant most consistently projected to increase under future climate change. Purpose To project future pediatric asthma emergency department visits associated with ground-level ozone changes, comparing 1990s to 2020s. Methods This study assessed future numbers of asthma emergency department visits for children aged 0–17 years using (1) baseline New York City metropolitan area emergency department rates, (2) a dose–response relationship between ozone levels and pediatric asthma emergency department visits, and (3) projected daily 8-hour maximum ozone concentrations for the 2020s as simulated by a global-to-regional climate change and atmospheric chemistry model. Sensitivity analyses included population projections and ozone precursor changes. This analysis occurred in 2010. Results In this model, climate change could cause an increase in regional summer ozone-related asthma emergency department visits for children aged 0–17 years of 7.3% across the New York City metropolitan region by the 2020s. This effect diminished with inclusion of ozone precursor changes. When population growth is included, the projections of morbidity related to ozone are even larger. Conclusions The results of this analysis demonstrate that the use of regional climate and atmospheric chemistry models make possible the projection of local climate change health effects for specific age groups and specific disease outcomes – such as emergency department visits for asthma. Efforts should be made to improve on this type of modeling to inform local and wider-scale climate change mitigation and adaptation policy. PMID:21855738

A Realization of Bias Correction Method in the GMAO Coupled System

NASA Technical Reports Server (NTRS)

Chang, Yehui; Koster, Randal; Wang, Hailan; Schubert, Siegfried; Suarez, Max

2018-01-01

Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of the climate system. The cold or warm sea surface temperature (SST) bias in the tropics is still a problem common to most coupled ocean atmosphere general circulation models (CGCMs). The precipitation biases in CGCMs are also accompanied by SST and surface wind biases. The deficiencies and biases over the equatorial oceans through their influence on the Walker circulation likely contribute the precipitation biases over land surfaces. In this study, we introduce an approach in the CGCM modeling to correct model biases. This approach utilizes the history of the model's short-term forecasting errors and their seasonal dependence to modify model's tendency term and to minimize its climate drift. The study shows that such an approach removes most of model climate biases. A number of other aspects of the model simulation (e.g. extratropical transient activities) are also improved considerably due to the imposed pre-processed initial 3-hour model drift corrections. Because many regional biases in the GEOS-5 CGCM are common amongst other current models, our approaches and findings are applicable to these other models as well.

Transient climate simulations of the deglaciation 21-9 thousand years before present (version 1) - PMIP4 Core experiment design and boundary conditions

NASA Astrophysics Data System (ADS)

Ivanovic, Ruza F.; Gregoire, Lauren J.; Kageyama, Masa; Roche, Didier M.; Valdes, Paul J.; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev

2016-07-01

The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21-9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part.

Integrating Climate Change into Great Lakes Protection

NASA Astrophysics Data System (ADS)

Hedman, S.

2012-12-01

Climate change is now recognized as one of the greatest threats to the Great Lakes. Projected climate change impacts to the Great Lakes include increases in surface water and air temperature; decreases in ice cover; shorter winters, early spring, and longer summers; increased frequency of intense storms; more precipitation falling as rain in the winter; less snowfall; and variations in water levels, among other effects. Changing climate conditions may compromise efforts to protect and restore the Great Lakes ecosystem and may lead to irrevocable impacts on the physical, chemical, and biological integrity of the Great Lakes. Examples of such potential impacts include the transformation of coastal wetlands into terrestrial ecosystems; reduced fisheries; increased beach erosion; change in forest species composition as species migrate northward; potential increase in toxic substance concentrations; potential increases in the frequency and extent of algal blooms; degraded water quality; and a potential increase in invasive species. The Great Lakes Restoration Initiative, signed into law by President Obama in 2010, represents the commitment of the federal government to protect, restore, and maintain the Great Lakes ecosystem. The GLRI Action Plan, issued in February 2010, identifies five focus areas: - Toxic Substances and Areas of Concern - Invasive Species - Nearshore Health and Nonpoint Source Pollution - Habitat and Wildlife Protection and Restoration - Accountability, Education, Monitoring, Evaluation, Communication, and Partnerships The Action Plan recognizes that the projected impacts of climate change on the Great Lakes have implications across all focus areas and encourages incorporation of climate change considerations into GLRI projects and programs as appropriate. Under the GLRI, EPA has funded climate change-related work by states, tribes, federal agencies, academics and NGOs through competitive grants, state and tribal capacity grants, and Interagency Agreements. EPA has provided GLRI funding for a diverse suite of climate change-related projects including Great Lakes climate change research and modeling; adaptation plan development and implementation; ecosystem vulnerability assessments; outreach and education programs; habitat restoration and protection projects that will increase ecosystem resilience; and other projects that address climate change impacts. This presentation will discuss how the GLRI is helping to improve the climate change science needed to support the Action Plan. It will further describe how the GLRI is helping coordinate climate change efforts among Great Lakes states, tribes, Federal agencies, and other stakeholders. Finally, it will discuss how the GLRI is facilitating adaptation planning by our Great Lakes partners. The draft Lake Superior Ecosystem Climate Change Adaptation Plan serves as a case study for an integrated, collaborative, and coordinated climate change effort.

A new physically-based windblown dust emission parametrization in CMAQ

EPA Science Inventory

Dust has significant impacts on weather and climate, air quality and visibility, and human health; therefore, it is important to include a windblown dust emission module in atmospheric and air quality models. In this presentation, we summarize our efforts in development of a phys...

The dendroclimatic proxies from the northern Quebec taiga in the PAGES 2K network: recent advances and future developments.

NASA Astrophysics Data System (ADS)

Gennaretti, Fabio; Naulier, Maud; Arseneault, Dominique; Savard, Martine; Bégin, Christian; Boucher, Etienne; Bégin, Yves; Guiot, Joël

2016-04-01

Northeastern North America was historically underrepresented in the network of climate proxies used for climate reconstructions over the last two millennia. Indeed, in North America most high-resolution climate proxies are long tree-ring chronologies but, in Northeastern North America, these chronologies are highly challenging due to short tree longevity, high frequency and severity of wildfires and remoteness of many areas. Here, we will present the efforts accomplished during the last decade by our team in developing millennial-long tree-ring chronologies in the northern Quebec taiga. We sampled black spruce [Picea mariana (Mill.) B.S.P] subfossil tree remains naturally fallen in the littoral zone of six lakes to build six site-specific ring-width chronologies as well as two chronologies of stable isotope ratios (δ18O and δ13C in tree-ring cellulose). These chronologies, which are now included in the PAGES 2K network, were independently used to reconstruct summer temperature variations showing a well-expressed Medieval Climate Anomaly and the impact of volcanic and solar forcings at regional scale. We will also discuss non-climatic influences on these chronologies (i.e. wildfires and sampling height inconsistency), as well as the ongoing effort to extend the reconstructions in time to cover the last 2500 years. Finally, a new European funded project called MAIDEN-SPRUCE will be introduced. Within MAIDEN-SPRUCE, we will use a data-model approach to improve our understanding of the links between forests and climate over the last millennium. More specifically, we will adapt the process-based ecophysiological model MAIDENiso to investigate factors influencing the growth and underlying biogeochemical processes of black spruce. One of our objectives is to provide the first multi-proxy (ring widths and δ18O and δ13C in tree-ring cellulose) regional climate reconstruction in Eastern North America over the last millennium taking into account mechanistic rules, including nonlinear or threshold relationships.

Toward optimizing the delivery and use of climate science for natural resource management: lessons learned from recent adaptation efforts in the southwestern U.S.

NASA Astrophysics Data System (ADS)

Enquist, C.

2014-12-01

Within the past decade, a wealth of federal, state, and NGO-driven initiatives has emerged across managed landscapes in the United States with the goal of facilitating a coordinated response to rapidly changing climate and environmental conditions. In addition to acquisition and translation of the latest climate science, climate vulnerability assessment and scenario planning at multiple spatial and temporal scales are typically major components of such broad adaptation efforts. Numerous approaches for conducting this work have emerged in recent years and have culminated in general guidance and trainings for resource professionals that are specifically designed to help practitioners face the challenges of climate change. In particular, early engagement of stakeholders across multiple jurisdictions is particularly critical to cultivate buy-in and other enabling conditions for moving the science to on-the-ground action. I report on a suite of adaptation efforts in the southwestern US and interior Rockies, highlighting processes used, actions taken, lessons learned, and recommended next steps to facilitate achieving desired management outcomes. This includes a discussion of current efforts to optimize funding for actionable climate science, formalize science-management collaborations, and facilitate new investments in approaches for strategic climate-informed monitoring and evaluation.

Towards Systematic Benchmarking of Climate Model Performance

NASA Astrophysics Data System (ADS)

Gleckler, P. J.

2014-12-01

The process by which climate models are evaluated has evolved substantially over the past decade, with the Coupled Model Intercomparison Project (CMIP) serving as a centralizing activity for coordinating model experimentation and enabling research. Scientists with a broad spectrum of expertise have contributed to the CMIP model evaluation process, resulting in many hundreds of publications that have served as a key resource for the IPCC process. For several reasons, efforts are now underway to further systematize some aspects of the model evaluation process. First, some model evaluation can now be considered routine and should not require "re-inventing the wheel" or a journal publication simply to update results with newer models. Second, the benefit of CMIP research to model development has not been optimal because the publication of results generally takes several years and is usually not reproducible for benchmarking newer model versions. And third, there are now hundreds of model versions and many thousands of simulations, but there is no community-based mechanism for routinely monitoring model performance changes. An important change in the design of CMIP6 can help address these limitations. CMIP6 will include a small set standardized experiments as an ongoing exercise (CMIP "DECK": ongoing Diagnostic, Evaluation and Characterization of Klima), so that modeling groups can submit them at any time and not be overly constrained by deadlines. In this presentation, efforts to establish routine benchmarking of existing and future CMIP simulations will be described. To date, some benchmarking tools have been made available to all CMIP modeling groups to enable them to readily compare with CMIP5 simulations during the model development process. A natural extension of this effort is to make results from all CMIP simulations widely available, including the results from newer models as soon as the simulations become available for research. Making the results from routine performance tests readily accessible will help advance a more transparent model evaluation process.

How uncertain are climate model projections of water availability indicators across the Middle East?

PubMed

Hemming, Debbie; Buontempo, Carlo; Burke, Eleanor; Collins, Mat; Kaye, Neil

2010-11-28

The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961-1990 and 2021-2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between -5 and -25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model ProjectionsAtmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.

Marginalization of end-use technologies in energy innovation for climate protection

NASA Astrophysics Data System (ADS)

Wilson, Charlie; Grubler, Arnulf; Gallagher, Kelly S.; Nemet, Gregory F.

2012-11-01

Mitigating climate change requires directed innovation efforts to develop and deploy energy technologies. Innovation activities are directed towards the outcome of climate protection by public institutions, policies and resources that in turn shape market behaviour. We analyse diverse indicators of activity throughout the innovation system to assess these efforts. We find efficient end-use technologies contribute large potential emission reductions and provide higher social returns on investment than energy-supply technologies. Yet public institutions, policies and financial resources pervasively privilege energy-supply technologies. Directed innovation efforts are strikingly misaligned with the needs of an emissions-constrained world. Significantly greater effort is needed to develop the full potential of efficient end-use technologies.

Global meta-analysis of leaf area index in wetlands indicates uncertainties in understanding of their ecosystem function

NASA Astrophysics Data System (ADS)

Dronova, I.; Taddeo, S.; Foster, K.

2017-12-01

Projecting ecosystem responses to global change relies on the accurate understanding of properties governing their functions in different environments. An important variable in models of ecosystem function is canopy leaf area index (LAI; leaf area per unit ground area) declared as one of the Essential Climate Variables in the Global Climate Observing System and extensively measured in terrestrial landscapes. However, wetlands have been largely under-represented in these efforts, which globally limits understanding of their contribution to carbon sequestration, climate regulation and resilience to natural and anthropogenic disturbances. This study provides a global synthesis of >350 wetland-specific LAI observations from 182 studies and compares LAI among wetland ecosystem and vegetation types, biomes and measurement approaches. Results indicate that most wetland types and even individual locations show a substantial local dispersion of LAI values (average coefficient of variation 65%) due to heterogeneity of environmental properties and vegetation composition. Such variation indicates that mean LAI values may not sufficiently represent complex wetland environments, and the use of this index in ecosystem function models needs to incorporate within-site variation in canopy properties. Mean LAI did not significantly differ between direct and indirect measurement methods on a pooled global sample; however, within some of the specific biomes and wetland types significant contrasts between these approaches were detected. These contrasts highlight unique aspects of wetland vegetation physiology and canopy structure affecting measurement principles that need to be considered in generalizing canopy properties in ecosystem models. Finally, efforts to assess wetland LAI using remote sensing strongly indicate the promise of this technology for cost-effective regional-scale modeling of canopy properties similar to terrestrial systems. However, such efforts urgently require more rigorous corrections for three-dimensional contributions of non-canopy material and non-vegetated surfaces to wetland canopy reflectance.

Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability

NASA Astrophysics Data System (ADS)

Dee, S. G.; Parsons, L. A.; Loope, G. R.; Overpeck, J. T.; Ault, T. R.; Emile-Geay, J.

2017-10-01

The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing (Laepple and Huybers, 2014a, 2014b). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled ;pseudoproxies; exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database (PAGES2K Consortium, 2013). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate record may exhibit larger low-frequency variability than GCMs currently simulate, indicative of incomplete physics and/or forcings.

Collaborative Project: Understanding Climate Model Biases in Tropical Atlantic and Their Impact on Simulations of Extreme Climate Events

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

Chang, Ping

Recent studies have revealed that among all the tropical oceans, the tropical Atlantic has experienced the most pronounced warming trend over the 20th century. Many extreme climate events affecting the U.S., such as hurricanes, severe precipitation and drought events, are influenced by conditions in the Gulf of Mexico and the Atlantic Ocean. It is therefore imperative to have accurate simulations of the climatic mean and variability in the Atlantic region to be able to make credible projections of future climate change affecting the U.S. and other countries adjoining the Atlantic Ocean. Unfortunately, almost all global climate models exhibit large biasesmore » in their simulations of tropical Atlantic climate. The atmospheric convection simulation errors in the Amazon region and the associated errors in the trade wind simulations are hypothesized to be a leading cause of the tropical Atlantic biases in climate models. As global climate models have resolutions that are too coarse to resolve some of the atmospheric and oceanic processes responsible for the model biases, we propose to use a high-resolution coupled regional climate model (CRCM) framework to address the tropical bias issue. We propose to combine the expertise in tropical coupled atmosphere-ocean modeling at Texas A&M University (TAMU) and the coupled land-atmosphere modeling expertise at Pacific Northwest National Laboratory (PNNL) to develop a comprehensive CRCM for the Atlantic sector within a general and flexible modeling framework. The atmospheric component of the CRCM will be the NCAR WRF model and the oceanic component will be the Rutgers/UCLA ROMS. For the land component, we will use CLM modified at PNNL to include more detailed representations of vegetation and soil hydrology processes. The combined TAMU-PNNL CRCM model will be used to simulate the Atlantic climate, and the associated land-atmosphere-ocean interactions at a horizontal resolution of 9 km or finer. A particular focus of the model development effort will be to optimize the performance of WRF and ROMS over several thousand of cores by focusing on both the parallel communication libraries and the I/O interfaces, in order to achieve the sustained throughput needed to perform simulations on such fine resolution grids. The CRCM model will be developed within the framework of the Coupler (CPL7) software that is part of the NCAR Community Earth System Model (CESM). Through efforts at PNNL and within the community, WRF and CLM have already been coupled via CPL7. Using the flux coupler approach for the whole CRCM model will allow us to flexibly couple WRF, ROMS, and CLM with each model running on its own grid at different resolutions. In addition, this framework will allow us to easily port parameterizations between CESM and the CRCM, and potentially allow partial coupling between the CESM and the CRCM. TAMU and PNNL will contribute cooperatively to this research endeavor. The TAMU team led by Chang and Saravanan has considerable experience in studying atmosphere-ocean interactions within tropical Atlantic sector and will focus on modeling issues that relate to coupling WRF and ROMS. The PNNL team led by Leung has extensive expertise in atmosphere-land interaction and will be responsible for improving the land surface parameterization. Both teams will jointly work on integrating WRF-ROMS and WRF-CLM to couple WRF, ROMS, and CLM through CPL7. Montuoro of the TAMU Supercomputing Center will be responsible for improving the MPI and Parallel IO interfaces of the CRCM. Both teams will contribute to the design and execution of the proposed numerical experiments and jointly perform analysis of the numerical experiments.« less

Research-informed Outreach informs Research: Using games to inform and understand farmer decisions in Sri Lanka

NASA Astrophysics Data System (ADS)

Gunda, T.; Yeung, K.; Hornberger, G. M.

2016-12-01

Researchers from the Agricultural Decision Making and Adaptation to Precipitation Trends in Sri Lanka (ADAPT-SL) team have been working for the past six years to understand Sri Lanka's agricultural vulnerability to climate change and how farmers and policy makers can adapt to and mitigate the variety of threats and uncertainties that climate change brings. In addition to academic publications, the compiled and developed knowledge from the ADAPT-SL research efforts are shared routinely with Sri Lankan stakeholders directly. While presentations are the norm for academic and government stakeholder outreach, we decided that an interactive component would increase farmers' learning. Drawing on teaching pedagogies, we designed a place-based, hands-on game that incorporated local climate and market characteristics to convey the impact of climate change on crop water needs for the Sri Lanka farmers. The process of developing the game, however, revealed gaps in our research knowledge, specifically regarding how farmers balance uncertainties associated with weather and market conditions. So we took advantage of the opportunity offered by the outreach effort to collect data; findings from the game led to the development of a system dynamics model. The game was well received by farmers and other Sri Lankan stakeholders in January 2016, with the former expressing that they played the game as if it was emulating actual farming decisions. The farmers also expressed a desire for more outreach efforts to be designed in such an interactive way. The game has since been used to engage U.S. students (from 5th grade to college seniors majoring in Sociology) regarding the complexities of tackling climate change issues.

Subseasonal-to-Seasonal Science and Prediction Initiatives of the NOAA MAPP Program

NASA Astrophysics Data System (ADS)

Archambault, H. M.; Barrie, D.; Mariotti, A.

2016-12-01

There is great practical interest in developing predictions beyond the 2-week weather timescale. Scientific communities have historically organized themselves around the weather and climate problems, but the subseasonal-to-seasonal (S2S) timescale range overall is recognized as new territory for which a concerted shared effort is needed. For instance, the climate community, as part of programs like CLIVAR, has historically tackled coupled phenomena and modeling, keys to harnessing predictability on longer timescales. In contrast, the weather community has focused on synoptic dynamics, higher-resolution modeling, and enhanced model initialization, of importance at the shorter timescales and especially for the prediction of extremes. The processes and phenomena specific to timescales between weather and climate require a unified approach to science, modeling, and predictions. Internationally, the WWRP/WCRP S2S Prediction Project is a promising catalyzer for these types of activities. Among the various contributing U.S. research programs, the Modeling, Analysis, Predictions and Projections (MAPP) program, as part of the NOAA Climate Program Office, has launched coordinated research and transition activities that help to meet the agency's goals to fill the weather-to-climate prediction gap and will contribute to advance international goals. This presentation will describe ongoing MAPP program S2S science and prediction initiatives, specifically the MAPP S2S Task Force and the SubX prediction experiment.

Understanding the Dynamics of Socio-Hydrological Environment: a Conceptual Framework

NASA Astrophysics Data System (ADS)

Woyessa, Y.; Welderufael, W.; Edossa, D.

2011-12-01

Human actions affect ecological systems and the services they provide through various activities, such as land use, water use, pollution and climate change. Climate change is perhaps one of the most important sustainable development challenges that threaten to undo many of the development efforts being made to reach the targets set for the Millennium Development Goals. Understanding the change of ecosystems under different scenarios of climate and biophysical conditions could assist in bringing the issue of ecosystem services into decision making process. Similarly, the impacts of land use change on ecosystems and biodiversity have received considerable attention from ecologists and hydrologists alike. Land use change in a catchment can impact on water supply by altering hydrological processes, such as infiltration, groundwater recharge, base flow and direct runoff. In the past a variety of models were used for predicting land-use changes. Recently the focus has shifted away from using mathematically oriented models to agent-based modelling (ABM) approach to simulate land use scenarios. A conceptual framework is being developed which integrates climate change scenarios and the human dimension of land use decision into a hydrological model in order to assess its impacts on the socio-hydrological dynamics of a river basin. The following figures present the framework for the analysis and modelling of the socio-hydrological dynamics. Keywords: climate change, land use, river basin

Overview of the Implementation of the Climate Data Initiative

NASA Astrophysics Data System (ADS)

Tilmes, C.; Goodman, H. M.; Privette, A. P.

2014-12-01

One of the efforts described in the President's Climate Action Plan is the Climate Data Initiative, a broad effort to leverage the federal government's extensive, freely-available climate-relevant data resources data to spur innovation and private-sector entrepreneurship in order to advance awareness of and preparedness for the impacts of climate change. The Climate Data Initiative, launched in March 2014, leverages commitments from government and the private sector to unleash data and make it accessible in ways that can be used by communities and companies to prepare for climate change. It builds on the White House's other Open Data Initiatives—in areas such as health, education, and safety. The Climate Data Initiative unleashes federal data relevant to addressing climate-related risks and vulnerabilities through the Climate.Data.gov web site. This talk will describe the Climate Data Initiative and its support and interactions with the Climate Resilience Toolkit.

The National Oceanic and Atmospheric Administration (NOAA) Climate Services Portal: A New Centralized Resource for Distributed Climate Information

NASA Astrophysics Data System (ADS)

Burroughs, J.; Baldwin, R.; Herring, D.; Lott, N.; Boyd, J.; Handel, S.; Niepold, F.; Shea, E.

2010-09-01

With the rapid rise in the development of Web technologies and climate services across NOAA, there has been an increasing need for greater collaboration regarding NOAA's online climate services. The drivers include the need to enhance NOAA's Web presence in response to customer requirements, emerging needs for improved decision-making capabilities across all sectors of society facing impacts from climate variability and change, and the importance of leveraging climate data and services to support research and public education. To address these needs, NOAA (during fiscal year 2009) embarked upon an ambitious program to develop a NOAA Climate Services Portal (NCS Portal). Four NOAA offices are leading the effort: 1) the NOAA Climate Program Office (CPO), 2) the National Ocean Service's Coastal Services Center (CSC), 3) the National Weather Service's Climate Prediction Center (CPC), and 4) the National Environmental Satellite, Data, and Information Service's (NESDIS) National Climatic Data Center (NCDC). Other offices and programs are also contributing in many ways to the effort. A prototype NCS Portal is being placed online for public access in January 2010, http://www.climate.gov. This website only scratches the surface of the many climate services across NOAA, but this effort, via direct user engagement, will gradually expand the scope and breadth of the NCS Portal to greatly enhance the accessibility and usefulness of NOAA's climate data and services.

Using Web 2.0 Techniques To Bring Global Climate Modeling To More Users

NASA Astrophysics Data System (ADS)

Chandler, M. A.; Sohl, L. E.; Tortorici, S.

2012-12-01

The Educational Global Climate Model has been used for many years in undergraduate courses and professional development settings to teach the fundamentals of global climate modeling and climate change simulation to students and teachers. While course participants have reported a high level of satisfaction in these courses and overwhelmingly claim that EdGCM projects are worth the effort, there is often a high level of frustration during the initial learning stages. Many of the problems stem from issues related to installation of the software suite and to the length of time it can take to run initial experiments. Two or more days of continuous run time may be required before enough data has been gathered to begin analyses. Asking users to download existing simulation data has not been a solution because the GCM data sets are several gigabytes in size, requiring substantial bandwidth and stable dedicated internet connections. As a means of getting around these problems we have been developing a Web 2.0 utility called EzGCM (Easy G-G-M) which emphasizes that participants learn the steps involved in climate modeling research: constructing a hypothesis, designing an experiment, running a computer model and assessing when an experiment has finished (reached equilibrium), using scientific visualization to support analysis, and finally communicating the results through social networking methods. We use classic climate experiments that can be "rediscovered" through exercises with EzGCM and are attempting to make this Web 2.0 tool an entry point into climate modeling for teachers with little time to cover the subject, users with limited computer skills, and for those who want an introduction to the process before tackling more complex projects with EdGCM.

Climate Hazard Assessment for Stakeholder Adaptation Planning in New York City

NASA Technical Reports Server (NTRS)

Horton, Radley M.; Gornitz, Vivien; Bader, Daniel A.; Ruane, Alex C.; Goldberg, Richard; Rosenzweig, Cynthia

2011-01-01

This paper describes a time-sensitive approach to climate change projections, developed as part of New York City's climate change adaptation process, that has provided decision support to stakeholders from 40 agencies, regional planning associations, and private companies. The approach optimizes production of projections given constraints faced by decision makers as they incorporate climate change into long-term planning and policy. New York City stakeholders, who are well-versed in risk management, helped pre-select the climate variables most likely to impact urban infrastructure, and requested a projection range rather than a single 'most likely' outcome. The climate projections approach is transferable to other regions and consistent with broader efforts to provide climate services, including impact, vulnerability, and adaptation information. The approach uses 16 Global Climate Models (GCMs) and three emissions scenarios to calculate monthly change factors based on 30-year average future time slices relative to a 30- year model baseline. Projecting these model mean changes onto observed station data for New York City yields dramatic changes in the frequency of extreme events such as coastal flooding and dangerous heat events. Based on these methods, the current 1-in-10 year coastal flood is projected to occur more than once every 3 years by the end of the century, and heat events are projected to approximately triple in frequency. These frequency changes are of sufficient magnitude to merit consideration in long-term adaptation planning, even though the precise changes in extreme event frequency are highly uncertain

Climate-driven polar motion

NASA Astrophysics Data System (ADS)

Celaya, Michael A.; Wahr, John M.; Bryan, Frank O.

1999-06-01

The output of a coupled climate system model provides a synthetic climate record with temporal and spatial coverage not attainable with observational data, allowing evaluation of climatic excitation of polar motion on timescales of months to decades. Analysis of the geodetically inferred Chandler excitation power shows that it has fluctuated by up to 90% since 1900 and that it has characteristics representative of a stationary Gaussian process. Our model-predicted climate excitation of the Chandler wobble also exhibits variable power comparable to the observed. Ocean currents and bottom pressure shifts acting together can alone drive the 14-month wobble. The same is true of the excitation generated by the combined effects of barometric pressure and winds. The oceanic and atmospheric contributions are this large because of a relatively high degree of constructive interference between seafloor pressure and currents and between atmospheric pressure and winds. In contrast, excitation by the redistribution of water on land appears largely insignificant. Not surprisingly, the full climate effect is even more capable of driving the wobble than the effects of the oceans or atmosphere alone are. Our match to the observed annual excitation is also improved, by about 17%, over previous estimates made with historical climate data. Efforts to explain the 30-year Markowitz wobble meet with less success. Even so, at periods ranging from months to decades, excitation generated by a model of a coupled climate system makes a close approximation to the amplitude of what is geodetically observed.

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.

Wave Climate and Wave Mixing in the Marginal Ice Zones of Arctic Seas, Observations and Modelling

DTIC Science & Technology

2014-09-30

At the same time, the PIs participate in Australian efforts of developing wave-ocean- ice coupled models for Antarctica . Specific new physics modules...Wave Mixing in the Marginal Ice Zones of Arctic Seas, Observations and Modelling Alexander V. Babanin Swinburne University of Technology, PO Box...operational forecast. Altimeter climatology and the wave models will be used to study the current and future wind/wave and ice trends. APPROACH

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.

Using a Global Climate Model in an On-line Climate Change Course

NASA Astrophysics Data System (ADS)

Randle, D. E.; Chandler, M. A.; Sohl, L. E.

2012-12-01

Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that arise are due to a lack of computer literacy amongst participants and we have found, through iterative improvements in the materials, that breaking assignments into discrete, well-supported tasks has been key to the success.

Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop

NASA Technical Reports Server (NTRS)

Sellers, Piers; Rienecker Michele; Randall, David; Frolking, Steve

2012-01-01

Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

Implementing climate change mitigation in health services: the importance of context.

PubMed

Desmond, Sharon

2016-10-01

Academic interest in strategies to reduce the impact of health services on climate change is quickening. Research has largely focused on local innovations with little consideration of the contextual and systemic elements that influence sustainable development across health systems. A realistic framework specifically to guide decision-making by health care providers is still needed. To address this deficit, the literature is explored in relation to health services and climate change mitigation strategies, and the contextual factors that influence efforts to mitigate climate effects in health service delivery environments are highlighted. A conceptual framework is proposed that offers a model for the pursuit of sustainable development practice in health services. A set of propositions is advanced to provide a systems approach to assist decision-making by decoding the challenges faced in implementing sustainable health services. This has important implications for health care providers, funders and legislators since the financial, policy and regulatory environment of health care, along with its leadership and models of care generally conflict with carbon literacy and climate change mitigation strategies. © The Author(s) 2016.

Projected continent-wide declines of the emperor penguin under climate change

NASA Astrophysics Data System (ADS)

Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Serreze, Mark; Barbraud, Christophe; Weimerskirch, Henri; Caswell, Hal

2014-08-01

Climate change has been projected to affect species distribution and future trends of local populations, but projections of global population trends are rare. We analyse global population trends of the emperor penguin (Aptenodytes forsteri), an iconic Antarctic top predator, under the influence of sea ice conditions projected by coupled climate models assessed in the Intergovernmental Panel on Climate Change (IPCC) effort. We project the dynamics of all 45 known emperor penguin colonies by forcing a sea-ice-dependent demographic model with local, colony-specific, sea ice conditions projected through to the end of the twenty-first century. Dynamics differ among colonies, but by 2100 all populations are projected to be declining. At least two-thirds are projected to have declined by >50% from their current size. The global population is projected to have declined by at least 19%. Because criteria to classify species by their extinction risk are based on the global population dynamics, global analyses are critical for conservation. We discuss uncertainties arising in such global projections and the problems of defining conservation criteria for species endangered by future climate change.

Influences of climate change on the potential distribution of Lutzomyia longipalpis sensu lato (Psychodidae: Phlebotominae).

PubMed

Peterson, A Townsend; Campbell, Lindsay P; Moo-Llanes, David A; Travi, Bruno; González, Camila; Ferro, María Cristina; Ferreira, Gabriel Eduardo Melim; Brandão-Filho, Sinval P; Cupolillo, Elisa; Ramsey, Janine; Leffer, Andreia Mauruto Chernaki; Pech-May, Angélica; Shaw, Jeffrey J

2017-09-01

This study explores the present day distribution of Lutzomyia longipalpis in relation to climate, and transfers the knowledge gained to likely future climatic conditions to predict changes in the species' potential distribution. We used ecological niche models calibrated based on occurrences of the species complex from across its known geographic range. Anticipated distributional changes varied by region, from stability to expansion or decline. Overall, models indicated no significant north-south expansion beyond present boundaries. However, some areas suitable both at present and in the future (e.g., Pacific coast of Ecuador and Peru) may offer opportunities for distributional expansion. Our models anticipated potential range expansion in southern Brazil and Argentina, but were variably successful in anticipating specific cases. The most significant climate-related change anticipated in the species' range was with regard to range continuity in the Amazon Basin, which is likely to increase in coming decades. Rather than making detailed forecasts of actual locations where Lu. longipalpis will appear in coming years, our models make interesting and potentially important predictions of broader-scale distributional tendencies that can inform heath policy and mitigation efforts. Copyright © 2017 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Coupled Climate-Economy-Biosphere (CoCEB) model - Part 1: Abatement share and investment in low-carbon technologies

NASA Astrophysics Data System (ADS)

Ogutu, K. B. Z.; D'Andrea, F.; Ghil, M.; Nyandwi, C.; Manene, M. M.; Muthama, J. N.

2015-04-01

The Coupled Climate-Economy-Biosphere (CoCEB) model described herein takes an integrated assessment approach to simulating global change. By using an endogenous economic growth module with physical and human capital accumulation, this paper considers the sustainability of economic growth, as economic activity intensifies greenhouse gas emissions that in turn cause economic damage due to climate change. Different types of fossil fuels and different technologies produce different volumes of carbon dioxide in combustion. The shares of different fuels and their future evolution are not known. We assume that the dynamics of hydrocarbon-based energy share and their replacement with renewable energy sources in the global energy balance can be modeled into the 21st century by use of logistic functions. Various climate change mitigation policy measures are considered. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, we consider abatement activities also as an investment in overall energy efficiency of the economy and decrease of overall carbon intensity of the energy system. The paper shows that these efforts help to reduce the volume of industrial carbon dioxide emissions, lower temperature deviations, and lead to positive effects in economic growth.

When 1+1 can be >2: Uncertainties compound when simulating climate, fisheries and marine ecosystems

NASA Astrophysics Data System (ADS)

Evans, Karen; Brown, Jaclyn N.; Sen Gupta, Alex; Nicol, Simon J.; Hoyle, Simon; Matear, Richard; Arrizabalaga, Haritz

2015-03-01

Multi-disciplinary approaches that combine oceanographic, biogeochemical, ecosystem, fisheries population and socio-economic models are vital tools for modelling whole ecosystems. Interpreting the outputs from such complex models requires an appreciation of the many different types of modelling frameworks being used and their associated limitations and uncertainties. Both users and developers of particular model components will often have little involvement or understanding of other components within such modelling frameworks. Failure to recognise limitations and uncertainties associated with components and how these uncertainties might propagate throughout modelling frameworks can potentially result in poor advice for resource management. Unfortunately, many of the current integrative frameworks do not propagate the uncertainties of their constituent parts. In this review, we outline the major components of a generic whole of ecosystem modelling framework incorporating the external pressures of climate and fishing. We discuss the limitations and uncertainties associated with each component of such a modelling system, along with key research gaps. Major uncertainties in modelling frameworks are broadly categorised into those associated with (i) deficient knowledge in the interactions of climate and ocean dynamics with marine organisms and ecosystems; (ii) lack of observations to assess and advance modelling efforts and (iii) an inability to predict with confidence natural ecosystem variability and longer term changes as a result of external drivers (e.g. greenhouse gases, fishing effort) and the consequences for marine ecosystems. As a result of these uncertainties and intrinsic differences in the structure and parameterisation of models, users are faced with considerable challenges associated with making appropriate choices on which models to use. We suggest research directions required to address these uncertainties, and caution against overconfident predictions. Understanding the full impact of uncertainty makes it clear that full comprehension and robust certainty about the systems themselves are not feasible. A key research direction is the development of management systems that are robust to this unavoidable uncertainty.

Climate Literacy: Supporting Teacher Professional Development

NASA Astrophysics Data System (ADS)

Haddad, N.; Ledley, T. S.; Dunlap, C.; Bardar, E.; Youngman, B.; Ellins, K. K.; McNeal, K. S.; Libarkin, J.

2012-12-01

Confronting the Challenges of Climate Literacy (CCCL) is an NSF-funded (DRK-12) project that includes curriculum development, teacher professional development, teacher leadership development, and research on student learning, all directed at high school teachers and students. The project's evaluation efforts inform and guide all major components of the project. The research effort addresses the question of what interventions are most effective in helping high school students grasp the complexities of the Earth system and climate processes, which occur over a range of spatial and temporal scales. The curriculum unit includes three distinct but related modules: Climate and the Cryosphere; Climate, Weather, and the Biosphere; and Climate and the Carbon Cycle. Climate-related themes that cut across all three modules include the Earth system, with the complexities of its positive and negative feedback loops; the range of temporal and spatial scales at which climate, weather, and other Earth system processes occur; and the recurring question, "How do we know what we know about Earth's past and present climate?" which addresses proxy data and scientific instrumentation. The professional development component of the project includes online science resources to support the teaching of the curriculum modules, summer workshops for high school teachers, and a support system for developing the teacher leaders who plan and implement those summer workshops. When completed, the project will provide a model high school curriculum with online support for implementing teachers and a cadre of leaders who can continue to introduce new teachers to the resource. This presentation will introduce the curriculum and the university partnerships that are key to the project's success, and describe how the project addresses the challenge of helping teachers develop their understanding of climate science and their ability to convey climate-related concepts articulated in the Next Generation Science Standards to their students. We will also describe the professional development and support system to develop teacher leaders and explain some of the challenges that accompany this approach of developing teacher leaders in the area of climate literacy.

Advances in Cross-Cutting Ideas for Computational Climate Science

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

Ng, Esmond; Evans, Katherine J.; Caldwell, Peter

This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less

Advances in Cross-Cutting Ideas for Computational Climate Science

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

Ng, E.; Evans, K.; Caldwell, P.

This report presents results from the DOE-sponsored workshop titled, Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less

Assessing the Assessment Methods: Climate Change and Hydrologic Impacts

NASA Astrophysics Data System (ADS)

Brekke, L. D.; Clark, M. P.; Gutmann, E. D.; Mizukami, N.; Mendoza, P. A.; Rasmussen, R.; Ikeda, K.; Pruitt, T.; Arnold, J. R.; Rajagopalan, B.

2014-12-01

The Bureau of Reclamation, the U.S. Army Corps of Engineers, and other water management agencies have an interest in developing reliable, science-based methods for incorporating climate change information into longer-term water resources planning. Such assessments must quantify projections of future climate and hydrology, typically relying on some form of spatial downscaling and bias correction to produce watershed-scale weather information that subsequently drives hydrology and other water resource management analyses (e.g., water demands, water quality, and environmental habitat). Water agencies continue to face challenging method decisions in these endeavors: (1) which downscaling method should be applied and at what resolution; (2) what observational dataset should be used to drive downscaling and hydrologic analysis; (3) what hydrologic model(s) should be used and how should these models be configured and calibrated? There is a critical need to understand the ramification of these method decisions, as they affect the signal and uncertainties produced by climate change assessments and, thus, adaptation planning. This presentation summarizes results from a three-year effort to identify strengths and weaknesses of widely applied methods for downscaling climate projections and assessing hydrologic conditions. Methods were evaluated from two perspectives: historical fidelity, and tendency to modulate a global climate model's climate change signal. On downscaling, four methods were applied at multiple resolutions: statistically using Bias Correction Spatial Disaggregation, Bias Correction Constructed Analogs, and Asynchronous Regression; dynamically using the Weather Research and Forecasting model. Downscaling results were then used to drive hydrologic analyses over the contiguous U.S. using multiple models (VIC, CLM, PRMS), with added focus placed on case study basins within the Colorado Headwaters. The presentation will identify which types of climate changes are expressed robustly across methods versus those that are sensitive to method choice; which method choices seem relatively more important; and where strategic investments in research and development can substantially improve guidance on climate change provided to water managers.

Protecting the Amazon with protected areas

PubMed Central

Walker, Robert; Moore, Nathan J.; Arima, Eugenio; Perz, Stephen; Simmons, Cynthia; Caldas, Marcellus; Vergara, Dante; Bohrer, Claudio

2009-01-01

This article addresses climate-tipping points in the Amazon Basin resulting from deforestation. It applies a regional climate model to assess whether the system of protected areas in Brazil is able to avoid such tipping points, with massive conversion to semiarid vegetation, particularly along the south and southeastern margins of the basin. The regional climate model produces spatially distributed annual rainfall under a variety of external forcing conditions, assuming that all land outside protected areas is deforested. It translates these results into dry season impacts on resident ecosystems and shows that Amazonian dry ecosystems in the southern and southeastern basin do not desiccate appreciably and that extensive areas experience an increase in precipitation. Nor do the moist forests dry out to an excessive amount. Evidently, Brazilian environmental policy has created a sustainable core of protected areas in the Amazon that buffers against potential climate-tipping points and protects the drier ecosystems of the basin. Thus, all efforts should be made to manage them effectively. PMID:19549819

Protecting the Amazon with protected areas.

PubMed

Walker, Robert; Moore, Nathan J; Arima, Eugenio; Perz, Stephen; Simmons, Cynthia; Caldas, Marcellus; Vergara, Dante; Bohrer, Claudio

2009-06-30

This article addresses climate-tipping points in the Amazon Basin resulting from deforestation. It applies a regional climate model to assess whether the system of protected areas in Brazil is able to avoid such tipping points, with massive conversion to semiarid vegetation, particularly along the south and southeastern margins of the basin. The regional climate model produces spatially distributed annual rainfall under a variety of external forcing conditions, assuming that all land outside protected areas is deforested. It translates these results into dry season impacts on resident ecosystems and shows that Amazonian dry ecosystems in the southern and southeastern basin do not desiccate appreciably and that extensive areas experience an increase in precipitation. Nor do the moist forests dry out to an excessive amount. Evidently, Brazilian environmental policy has created a sustainable core of protected areas in the Amazon that buffers against potential climate-tipping points and protects the drier ecosystems of the basin. Thus, all efforts should be made to manage them effectively.

Data Integration Plans for the NOAA National Climate Model Portal (NCMP) (Invited)

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Williams, D. N.; Deluca, C.; Hankin, S. C.; Compo, G. P.

2010-12-01

NOAA’s National Climatic Data Center (NCDC) and its collaborators have initiated a five-year development and implementation of an operational access capability for the next generation weather and climate model datasets. The NOAA National Climate Model Portal (NCMP) is being designed using format neutral open web based standards and tools where users at all levels of expertise can gain access and understanding to many of NOAA’s climate and weather model products. NCMP will closely coordinate with and reside under the emerging NOAA Climate Services Portal (NCSP). To carry out its mission, NOAA must be able to successfully integrate model output and other data and information from all of its discipline specific areas to understand and address the complexity of many environmental problems. The NCMP will be an initial access point for the emerging NOAA Climate Services Portal (NCSP), which is the basis for unified access to NOAA climate products and services. NCMP is currently collaborating with the emerging Environmental Projection Center (EPC) expected to be developed at the Earth System Research Laboratory in Boulder CO. Specifically, NCMP is being designed to: - Enable policy makers and resource managers to make informed national and global policy decisions using integrated climate and weather model outputs, observations, information, products, and other services for the scientist and the non-scientist; - Identify model to observational interoperability requirements for climate and weather system analysis and diagnostics; - Promote the coordination of an international reanalysis observational clearinghouse (i.e.., Reanalysis.org) spanning the worlds numerical processing Center’s for an “Ongoing Analysis of the Climate System”. NCMP will initially provide access capabilities to 3 of NOAA’s high volume Reanalysis data sets of the weather and climate systems: 1) NCEP’s Climate Forecast System Reanalysis (CFS-R); 2) NOAA’s Climate Diagnostics Center/ Earth System Research Laboratory (ESRL) Twentieth Century Reanalysis Project data set (20CR, G. Compo, et al.), a historical reanalysis that will provide climate information dating back to 1850 to the present; and 3) the CPC’s Upper Air Reanlaysis. NCMP will advance the highly successful NOAA National Operational Model Archive and Distribution System (NOMADS, Rutledge, BAMS 2006), and standards already in use including Unidata’s THREDDS (TDS), PMEL’s Live Access Server (LAS) and the GrADS Data Server (GDS) from COLA; the Department of Energy (DOE) Earth System Grid (ESG) and the associated IPCC Climate model archive located at the Program for Climate Model Diagnostics and Inter-comparison (PCMDI) through the ESG; and NOAA’s Unified Access Framework (UAF) effort; and core standards developed by Open Geospatial Consortium (OGC). The format neutral OPeNDAP protocol as used in the NOMADS system will also be a key aspect of the design of NCMP.

Human dimension in scientific models in high-mountain climate change and risk projects: Peruvian-Swiss experiences

NASA Astrophysics Data System (ADS)

Vicuña, Luis; Jurt, Christine; Minan, Fiorella; Huggel, Christian

2014-05-01

Models in a range of scientific disciplines are increasingly seen as indispensable for successful adaptation. Governments as well as international organizations and cooperations put their efforts in basing their adaptation projects on scientific results. Thereby, it is critical that scientific models are first put into the particular context in which they will be applied. This paper addresses the experience of the project 'Glaciers 513- Climate change adaptation and disaster risk management for glacier retreat in the Andes' conducted in the districts of Carhuaz (Ancash region) and Santa Teresa (Cusco region) in Peru. The Peruvian and the Swiss governments put their joint efforts in an adaptation project in the context of climate change and the retreat of the glaciers. The project is led by a consortium of Care Peru and the University of Zurich with additional Swiss partners and its principal aim is to improve the capacity for integral adaptation and reduce the risk of disasters from glaciers and high-mountain areas, and effects of climate change, particularly in the regions of Cusco and Ancash. The paper shows how the so called "human dimension" on the one hand, and models from a range of disciplines, including climatology, glaciology, and hydrology on the other hand, were conceptualized and perceived by the different actors involved in the project. Important aspects have been, among others, the role of local knowledge including ancestral knowledge, demographic information, socio-economic indicators as well as the social, political and cultural framework and the historical background. Here we analyze the role and context of local knowledge and the historical background. The analysis of the implications of the differences and similarities of the perceptions of a range of actors contributes to the discussion about how, and to what extent scientific models can be contextualized, what kind of information can be helpful for the contextualization and how it can be obtained. The results, thus, should contribute to more concerted, locally based and accepted risk and adaptation measures.

Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation.

PubMed

Lambert, Emily; Pierce, Graham J; Hall, Karen; Brereton, Tom; Dunn, Timothy E; Wall, Dave; Jepson, Paul D; Deaville, Rob; MacLeod, Colin D

2014-06-01

There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio-climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs "hindcasting" of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species-specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white-beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time-scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies. © 2014 John Wiley & Sons Ltd.

Development of a Regional U.S. MARKAL Database for Energy and Emissions Modeling

EPA Science Inventory

The U.S. Climate Change Science Program (CCSP) is a collaborative effort among 13 agencies of the U.S. federal government. From the CCSP's 2003 strategic plan, its mission is to: "facilitate the creation and application of knowledge of the earth's global environment through resea...

The Sustainable Energy Utility (SEU) Model for Energy Service Delivery

ERIC Educational Resources Information Center

Houck, Jason; Rickerson, Wilson

2009-01-01

Climate change, energy price spikes, and concerns about energy security have reignited interest in state and local efforts to promote end-use energy efficiency, customer-sited renewable energy, and energy conservation. Government agencies and utilities have historically designed and administered such demand-side measures, but innovative…

An open science approach to modeling and visualizing cyanobacteria blooms in lakes and ponds

EPA Science Inventory

It is expected that cyanobacteria blooms will increase in frequency, duration, and severity as inputs of nutrients increase and the impacts of climate change are realized. Partly in response to this, federal, state, and local entities have ramped up efforts to better understand b...

Climate Penalty on Air Quality and Human Health in China and India

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, S.; Garcia-Menendez, F.; Monier, E.; Selin, N. E.

2017-12-01

Climate change, favoring more heat waves and episodes of stagnant air, may deteriorate air quality by increasing ozone and fine particulate matter (PM2.5) concentrations and high pollution episodes. This effect, termed as "climate penalty", has been quantified and explained by many earlier studies in the U.S. and Europe, but research efforts in Asian countries are limited. We evaluate the impact of climate change on air quality and human health in China and India using a modeling framework that links the Massachusetts Institute of Technology Integrated Global System Model to the Community Atmosphere Model (MIT IGSM-CAM). Future climate fields are projected under three climate scenarios including a no-policy reference scenario and two climate stabilization scenarios with 2100 total radiative forcing targets of 9.7, 4.5 and 3.7 W m-2, respectively. Each climate scenario is run for five representations of climate variability to account for the role of natural variability. Thirty-year chemical transport simulations are conducted in 1981-2010 and 2086-2115 under the three climate scenarios with fixed anthropogenic emissions at year 2000 levels. We find that 2000—2100 climate change under the no-policy reference scenario would increase ozone concentrations in eastern China and northern India by up to 5 ppb through enhancing biogenic emissions and ozone production efficiency. Ozone extreme episodes also become more frequent in these regions, while climate policies can offset most of the increase in ozone episodes. Climate change between 2000 and 2100 would slightly increase anthropogenic PM2.5 concentrations in northern China and Sichuan province, but significantly reduce anthropogenic PM2.5 concentrations in southern China and northern India, primarily due to different chemical responses of sulfate-nitrate-ammonium aerosols to climate change in these regions. Our study also suggests that the mitigation costs of climate policies can be partially offset by health benefits from reduced climate-induced air pollution in China.

MISR Aerosol Typing

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2014-01-01

AeroCom is an open international initiative of scientists interested in the advancement of the understanding of global aerosol properties and aerosol impacts on climate. A central goal is to more strongly tie and constrain modeling efforts to observational data. A major element for exchanges between data and modeling groups are annual meetings. The meeting was held September 20 through October 2, 1014 and the organizers would like to post the presentations.

Assessing vulnerability of giant pandas to climate change in the Qinling Mountains of China.

PubMed

Li, Jia; Liu, Fang; Xue, Yadong; Zhang, Yu; Li, Diqiang

2017-06-01

Climate change might pose an additional threat to the already vulnerable giant panda ( Ailuropoda melanoleuca ). Effective conservation efforts require projections of vulnerability of the giant panda in facing climate change and proactive strategies to reduce emerging climate-related threats. We used the maximum entropy model to assess the vulnerability of giant panda to climate change in the Qinling Mountains of China. The results of modeling included the following findings: (1) the area of suitable habitat for giant pandas was projected to decrease by 281 km 2 from climate change by the 2050s; (2) the mean elevation of suitable habitat of giant panda was predicted to shift 30 m higher due to climate change over this period; (3) the network of nature reserves protect 61.73% of current suitable habitat for the species, and 59.23% of future suitable habitat; (4) current suitable habitat mainly located in Chenggu, Taibai, and Yangxian counties (with a total area of 987 km 2 ) was predicted to be vulnerable. Assessing the vulnerability of giant panda provided adaptive strategies for conservation programs and national park construction. We proposed adaptation strategies to ameliorate the predicted impacts of climate change on giant panda, including establishing and adjusting reserves, establishing habitat corridors, improving adaptive capacity to climate change, and strengthening monitoring of giant panda.

Heat waves in Africa and India: a multidisciplinary approach.

NASA Astrophysics Data System (ADS)

Janicot, Serge; Moron, Vincent; Oueslati, Boutheina; Pohl, Benjamin; Rome, Sandra; Lalou, Richard; Dos Santos, Stéphanie

2017-04-01

While the heat wave impacts on public health have been widely addressed in developed countries, less effort has been made to detect them and evaluate their impacts in least developed countries, especially in Africa and to a lesser extent in India, where climate is warmer and adaptation capacities are low. Climate and epidemiologic analyses show however that this problem is already present and climate projections indicate that such events should increase in frequency and intensity in the coming decades. However climate models display important temperature and radiative biases over this region, which must be reduced to provide robust information on the future evolution of heat waves. Moreover early warning systems have to face up to institutional malfunctions. This talk lays the elements for a multidisciplinary approach of tackling heat wave occurrences.

Through the minefield: teaching climate change in a misinformation-rich environment

NASA Astrophysics Data System (ADS)

Bedford, D. P.; Cook, J.; Schuenemann, K. C.; Mandia, S. A.; Cowtan, K.; Nuccitelli, D.

2016-12-01

It is now widely accepted that students enter science classrooms with their own, often erroneous, pre-existing models of basic scientific concepts. These misconceptions can interfere with student learning. However, the science of climate change is perhaps distinctive in that a deliberate effort has been undertaken by a variety of individuals and institutions to promulgate and perpetuate misconceptions. Both formal and informal efforts to communicate the science of climate change must therefore contend with the effects of these misconceptions, which may be passionately held and in strong opposition to the findings of peer-reviewed research. This presentation reports on the current state of research on misinformation and misconceptions; identifies common mistakes made in attempting to address misconceptions; and details a model which can help to avoid making most, if not all, of these common mistakes. In sum, research in cognitive psychology has shown that misconceptions are extraordinarily difficult to remove, with individuals commonly rejecting information that does not fit with their existing mental models. Attempts to address misconceptions directly can backfire if too much emphasis is placed on the misconception (i.e. leading with the myth) or by reinforcing the misconception at the expense of more accurate explanations (the familiarity backfire effect). Thus, a preferred approach involves a "myth sandwich" of facts followed by myth, followed by an explanation of how the myth distorts the facts. The misconception is therefore sandwiched between facts. This approach has been tested in a widely subscribed MOOC (Denial 101X, by Cook et al., 2015), and a textbook (Bedford and Cook, 2016). This presentation provides fundamental background on effective climate change myth debunking, and will include preliminary data regarding the efficacy of the "myth sandwich" approach.

Communicating climate information to end-users: an experience driven by the understanding and anticipation of user needs.

NASA Astrophysics Data System (ADS)

Chaumont, Diane; Huard, David; Logan, Travis; Sottile, Marie-France; Brown, Ross; Gauvin St-Denis, Blaise; Grenier, Patrick; Braun, Marco

2013-04-01

Planning and adapting to a changing climate requires credible information about the magnitude and rate of projected changes. Ouranos, a consortium on regional climatology and adaptation to climate change was launched in the Province of Québec, Canada, ten years ago, with the objective of developing and providing climate information and expertise in support to adaption. Ouranos differs from most other climate service centers by integrating climate modeling activities, impacts and adaptation expertise and climate analysis services under one roof. The Climate Scenarios Group operates at the interface between climate modellers and users and is responsible for developing, producing and communicating climate scenarios to end-users in a consistent manner. This process requires close collaboration with users to define, understand and eventually anticipate their needs. The varied scientific expertise of climate scenarios specialists --who also act as communicators-- has proven to be a key element for successful communication. A large amount of effort is spent on the characterization and communication of the uncertainties involved in scenario construction. Two main activities have been put in place by the experts in climate modeling to address this: (1) a training course on climate models and (2) a fact-sheet summarizing the uncertainty and robustness of the climate change scenario provided for each I&A application. The latter tool ensures the transparency, traceability, and accountability of our products, and at the same time, encourages a sense of shared responsibility for the final choice of climate scenarios. In addition to uncertainty, two other main issues have been identified as essential in communication with users: 1) observed natural variability at relevant scales and 2) reconciliation of the projected trend with the recent observed trend. Our group has devoted substantial resources for the advancement of communication with end-users in these particular areas. This presentation will provide an overview of progress in communicating climate information at the Ouranos Consortium. We will discuss success and failures and future plans, in particular the extent to which Ouranos needs to work with users in decision-making activities.

Climate Change: Integrating Science and Economics

NASA Astrophysics Data System (ADS)

Prinn, R. G.

2008-12-01

The world is facing an ever-growing conflict between environment and development. Climate change is a century-scale threat requiring a century-long effort in science, technology and policy analysis, and institutions that can sustain this effort over generations. To inform policy development and implementation there is urgent need for better integration of the diverse components of the problem. Motivated by this challenge, we have developed the Integrated Global System Model (IGSM) at MIT. It comprises coupled sub- models of economic development, atmospheric chemistry, climate dynamics and ecosystems. The results of a recent uncertainty analysis involving hundreds of runs of the IGSM imply that, without mitigation policies, the global average surface temperature may rise much faster than previously estimated. Polar temperatures are projected to rise even faster than the average rate with obvious great risks for high latitude ecosystems and ice sheets at the high end of this range. Analysis of policies for climate mitigation, show that the greatest effect of these policies is to lower the probability of extreme changes as opposed to lowering the medians. Faced with the above estimated impacts, the long lifetimes of most greenhouse gases in the atmosphere, the long delay in ultimate warming due to ocean heat uptake, and the capital-intensive global energy infrastructure, the case is strong for concerted action now. Results of runs of the IGSM indicate the need for transformation of the global energy industry on a very large scale to mitigate climate change. Carbon sequestration, renewable energy sources, and nuclear present new economic, technological, and environmental challenges when implemented at the needed scales. Economic analyses using the IGSM indicate that global implementation of efficient policies could allow the needed transformations at bearable costs.

The Effect of Latitudinal Variation on Shrimp Reproductive Strategies.

PubMed

van de Kerk, Madelon; Jones Littles, Chanda; Saucedo, Omar; Lorenzen, Kai

2016-01-01

Reproductive strategies comprise the timing and frequency of reproductive events and the number of offspring per reproductive event, depending on factors such as climate conditions. Therefore, species that exhibit plasticity in the allocation of reproductive effort can alter their behavior in response to climate change. Studying how the reproductive strategy of species varies along the latitudinal gradient can help us understand and predict how they will respond to climate change. We investigated the effects of the temporal allocation of reproductive effort on the population size of brown shrimp (Farfantepenaeus aztecus) along a latitudinal gradient. Multiple shrimp species exhibit variation in their reproductive strategies, and given the economic importance of brown shrimp to the commercial fishing sector of the Unites States, changes in the timing of their reproduction could have significant economic and social consequences. We used a stage-based, density-dependent matrix population model tailored to the life history of brown shrimp. Shrimp growth rates and environmental carrying capacity were varied based on the seasonal climate conditions at different latitudes, and we estimated the population size at equilibrium. The length of the growing season increased with decreasing latitude and the reproductive strategy leading to the highest population size changed from one annual birth pulse with high reproductive output to continuous low-output reproduction. Hence, our model confirms the classical paradigm of continuous reproduction at low latitudes, with increased seasonality of the breeding period towards the poles. Our results also demonstrate the potential for variation in climate to affect the optimal reproductive strategy for achieving maximum population sizes. Certainly, understanding these dynamics may inform more comprehensive management strategies for commercially important species like brown shrimp.

MALIBU: A High Spatial Resolution Multi-Angle Imaging Unmanned Airborne System to Validate Satellite-derived BRDF/Albedo Products

NASA Astrophysics Data System (ADS)

Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.

2016-12-01

Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and international partners.

Building non-traditional collaborations to innovatively address climate-related scientific and management needs

NASA Astrophysics Data System (ADS)

Bamzai, A.; Mcpherson, R. A.

2014-12-01

The South Central Climate Science Center (SC-CSC) is one of eight regional centers formed by the U.S. Department of the Interior in order to provide decision makers with the science, tools, and information they need to address the impacts of climate variability and change on their areas of responsibility. The SC-CSC is operated through the U.S. Geological Survey, in partnership with a consortium led by the University of Oklahoma that also includes Texas Tech University, Oklahoma State University, Louisiana State University, the Chickasaw Nation, the Choctaw Nation of Oklahoma, and NOAA's Geophysical Fluid Dynamics Lab (GFDL). The SC-CSC is distinct from all other CSCs in that we have strategically included non-traditional collaborators directly within our governing consortium. The SC-CSC is the only CSC to include any Tribal nations amongst our consortium (the Chickasaw Nation and the Choctaw Nation of Oklahoma) and to employ a full-time tribal liaison. As a result and in partnership with Tribes, we are able to identify the unique challenges that the almost 70 federally recognized Tribes within our region face. We also can develop culturally sensitive research projects or outreach efforts that bridge western science and traditional knowledge to address their needs. In addition, the SC-CSC is the only CSC to include another federal institution (GFDL) amongst our consortium membership. GFDL is a world-leader in climate modeling and model interpretation. Partnering GFDL's expertise in the evaluation of climate models and downscaling methods with the SC-CSC's stakeholder-driven approach allows for the generation and dissemination of guidance documents and training to accompany the high quality datasets already in development. This presentation will highlight the success stories and co-benefits of the SC-CSC's collaborations with Tribal nations and with GFDL, as well as include information on how other partners can connect to our ongoing efforts.

Projected Climate Impacts to South African Maize and Wheat Production in 2055: A Comparison of Empirical and Mechanistic Modeling Approaches

NASA Technical Reports Server (NTRS)

Estes, Lyndon D.; Beukes, Hein; Bradley, Bethany A.; Debats, Stephanie R.; Oppenheimer, Michael; Ruane, Alex C.; Schulze, Roland; Tadross, Mark

2013-01-01

Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were 3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EMMM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EMMM comparisons to provide a fuller picture of crop-climate response uncertainties.

America's Climate Choices: Limiting the Magnitude of Future Climate Change (Invited)

NASA Astrophysics Data System (ADS)

Carlson, A.; Fri, R.; Brown, M.; Geller, L.

2010-12-01

At the request of Congress, the National Academy of Sciences convened a series of coordinated activities to provide advice on actions and strategies the nation can take to respond to climate change. This suite of activities included a study on strategies for limiting the magnitude of future climate change (i.e. mitigation). Limiting climate change is a global effort that will require significant reductions of greenhouse gas emissions by countries around the world. U.S. action alone is not sufficient, but it is clearly necessary for the U.S. to make significant contributions to the global effort. While efforts to limit climate change are already underway across the U.S. (by state and local governments, businesses, non-governmental organizations, and individual households), we currently lack a framework of federal policies to help assure that all key actors participating and working towards coherent national goals. This study recommends a U.S. policy goal stated as a budget for cumulative greenhouse gas emissions through the year 2050, and offers an illustrative range of budget numbers derived from recent work of the Energy Modeling Forum. The report evaluates the types of changes to our nation's energy system that are needed to meet a budget in the proposed range, which leads to a conclusion that the U.S. must get started now in aggressively pursuing available emission reduction opportunities, while also investing heavily in R&D to create new emission reduction opportunities. The study offers a series of recommendations for how to move ahead in pursing these near-term and longer-term opportunities. The recommendations address the need for a carbon pricing system and strategically-targeted complimentary policies, for effective international engagement, for careful balancing of federal with state/local action, and for consideration of equity and employment impacts of response policies. The study also discusses the need to design policies that are both durable over the long-term, and have the capacity to evolve in response to new scientific, technological, and economic developments.

Cloud-Enabled Climate Analytics-as-a-Service using Reanalysis data: A case study.

NASA Astrophysics Data System (ADS)

Nadeau, D.; Duffy, D.; Schnase, J. L.; McInerney, M.; Tamkin, G.; Potter, G. L.; Thompson, J. H.

2014-12-01

The NASA Center for Climate Simulation (NCCS) maintains advanced data capabilities and facilities that allow researchers to access the enormous volume of data generated by weather and climate models. The NASA Climate Model Data Service (CDS) and the NCCS are merging their efforts to provide Climate Analytics-as-a-Service for the comparative study of the major reanalysis projects: ECMWF ERA-Interim, NASA/GMAO MERRA, NOAA/NCEP CFSR, NOAA/ESRL 20CR, JMA JRA25, and JRA55. These reanalyses have been repackaged to netCDF4 file format following the CMIP5 Climate and Forecast (CF) metadata convention prior to be sequenced into the Hadoop Distributed File System ( HDFS ). A small set of operations that represent a common starting point in many analysis workflows was then created: min, max, sum, count, variance and average. In this example, Reanalysis data exploration was performed with the use of Hadoop MapReduce and accessibility was achieved using the Climate Data Service(CDS) application programming interface (API) created at NCCS. This API provides a uniform treatment of large amount of data. In this case study, we have limited our exploration to 2 variables, temperature and precipitation, using 3 operations, min, max and avg and using 30-year of Reanalysis data for 3 regions of the world: global, polar, subtropical.

Readings from Visibility Meters: Do They Really Mean the Maximum Distance of Observing A Black Object?

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, S.; Garcia-Menendez, F.; Monier, E.; Selin, N. E.

2016-12-01

Climate change, favoring more heat waves and episodes of stagnant air, may deteriorate air quality by increasing ozone and fine particulate matter (PM2.5) concentrations and high pollution episodes. This effect, termed as "climate penalty", has been quantified and explained by many earlier studies in the U.S. and Europe, but research efforts in Asian countries are limited. We evaluate the impact of climate change on air quality and human health in China and India using a modeling framework that links the Massachusetts Institute of Technology Integrated Global System Model to the Community Atmosphere Model (MIT IGSM-CAM). Future climate fields are projected under three climate scenarios including a no-policy reference scenario and two climate stabilization scenarios with 2100 total radiative forcing targets of 9.7, 4.5 and 3.7 W m-2, respectively. Each climate scenario is run for five representations of climate variability to account for the role of natural variability. Thirty-year chemical transport simulations are conducted in 1981-2010 and 2086-2115 under the three climate scenarios with fixed anthropogenic emissions at year 2000 levels. We find that 2000—2100 climate change under the no-policy reference scenario would increase ozone concentrations in eastern China and northern India by up to 5 ppb through enhancing biogenic emissions and ozone production efficiency. Ozone extreme episodes also become more frequent in these regions, while climate policies can offset most of the increase in ozone episodes. Climate change between 2000 and 2100 would slightly increase anthropogenic PM2.5 concentrations in northern China and Sichuan province, but significantly reduce anthropogenic PM2.5 concentrations in southern China and northern India, primarily due to different chemical responses of sulfate-nitrate-ammonium aerosols to climate change in these regions. Our study also suggests that the mitigation costs of climate policies can be partially offset by health benefits from reduced climate-induced air pollution in China.

Climate Change, Health, and Communication: A Primer.

PubMed

Chadwick, Amy E

2016-01-01

Climate change is one of the most serious and pervasive challenges facing us today. Our changing climate has implications not only for the ecosystems upon which we depend, but also for human health. Health communication scholars are well-positioned to aid in the mitigation of and response to climate change and its health effects. To help theorists, researchers, and practitioners engage in these efforts, this primer explains relevant issues and vocabulary associated with climate change and its impacts on health. First, this primer provides an overview of climate change, its causes and consequences, and its impacts on health. Then, the primer describes ways to decrease impacts and identifies roles for health communication scholars in efforts to address climate change and its health effects.

Ni-Co laterite deposits

USGS Publications Warehouse

Marsh, Erin E.; Anderson, Eric D.

2011-01-01

Nickel-cobalt (Ni-Co) laterite deposits are an important source of nickel (Ni). Currently, there is a decline in magmatic Ni-bearing sulfide lode deposit resources. New efforts to develop an alternative source of Ni, particularly with improved metallurgy processes, make the Ni-Co laterites an important exploration target in anticipation of the future demand for Ni. This deposit model provides a general description of the geology and mineralogy of Ni-Co laterite deposits, and contains discussion of the influences of climate, geomorphology (relief), drainage, tectonism, structure, and protolith on the development of favorable weathering profiles. This model of Ni-Co laterite deposits represents part of the U.S. Geological Survey Mineral Resources Program's effort to update the existing models to be used for an upcoming national mineral resource assessment.

Biodiversity funds and conservation needs in the EU under climate change

PubMed Central

Lung, Tobias; Meller, Laura; van Teeffelen, Astrid J.A.; Thuiller, Wilfried; Cabeza, Mar

2014-01-01

Despite ambitious biodiversity policy goals, less than a fifth of the European Union’s (EU) legally protected species and habitats show a favorable conservation status. The recent EU biodiversity strategy recognizes that climate change adds to the challenge of halting biodiversity loss, and that an optimal distribution of financial resources is needed. Here, we analyze recent EU biodiversity funding from a climate change perspective. We compare the allocation of funds to the distribution of both current conservation priorities (within and beyond Natura 2000) and future conservation needs at the level of NUTS-2 regions, using modelled bird distributions as indicators of conservation value. We find that funding is reasonably well aligned with current conservation efforts but poorly fit with future needs under climate change, indicating obstacles for implementing adaptation measures. We suggest revising EU biodiversity funding instruments for the 2014-2020 budget period to better account for potential climate change impacts on biodiversity. PMID:25264456

Biodiversity funds and conservation needs in the EU under climate change.

PubMed

Lung, Tobias; Meller, Laura; van Teeffelen, Astrid J A; Thuiller, Wilfried; Cabeza, Mar

2014-07-01

Despite ambitious biodiversity policy goals, less than a fifth of the European Union's (EU) legally protected species and habitats show a favorable conservation status. The recent EU biodiversity strategy recognizes that climate change adds to the challenge of halting biodiversity loss, and that an optimal distribution of financial resources is needed. Here, we analyze recent EU biodiversity funding from a climate change perspective. We compare the allocation of funds to the distribution of both current conservation priorities (within and beyond Natura 2000) and future conservation needs at the level of NUTS-2 regions, using modelled bird distributions as indicators of conservation value. We find that funding is reasonably well aligned with current conservation efforts but poorly fit with future needs under climate change, indicating obstacles for implementing adaptation measures. We suggest revising EU biodiversity funding instruments for the 2014-2020 budget period to better account for potential climate change impacts on biodiversity.

Anthropology is missing: on the World Development Report 2010: Development and Climate Change.

PubMed

Trostle, James

2010-07-01

When the World Bank publishes a report on climate change, the world takes notice. What are its diagnoses and treatments, and how present is anthropology in this analysis? The 2010 World Development Report on climate change provides few new diagnostic tools and no clear Bank policy revisions. It often fails to harmonize neoliberal development rhetoric with new climate-change imperatives. It nods to the importance of social context and risk perception yet refers primarily to behavioral economics and psychological constructs. Although anthropologists are documenting the local effects and human responses to larger-scale, climate-driven processes, our work is absent in the report. To play a role at global scale we would do well to learn more about concepts like nonlinearity and emergence, systems analysis, modeling, and disease dynamics. Our adroitness in developing metaphors and methods for crossing scale will make our efforts more visible and applicable.

The role of clouds and oceans in global greenhouse warming. Final report

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

Hoffert, M.I.

1996-10-01

This research focuses on assessing connections between anthropogenic greenhouse gas emissions and global climatic change. it has been supported since the early 1990s in part by the DOE ``Quantitative Links`` Program (QLP). A three-year effort was originally proposed to the QLP to investigate effects f global cloudiness on global climate and its implications for cloud feedback; and to continue the development and application of climate/ocean models, with emphasis on coupled effects of greenhouse warming and feedbacks by clouds and oceans. It is well-known that cloud and ocean processes are major sources of uncertainty in the ability to predict climatic changemore » from humankind`s greenhouse gas and aerosol emissions. And it has always been the objective to develop timely and useful analytical tools for addressing real world policy issues stemming from anthropogenic climate change.« less

ParCAT: A Parallel Climate Analysis Toolkit

NASA Astrophysics Data System (ADS)

Haugen, B.; Smith, B.; Steed, C.; Ricciuto, D. M.; Thornton, P. E.; Shipman, G.

2012-12-01

Climate science has employed increasingly complex models and simulations to analyze the past and predict the future of our climate. The size and dimensionality of climate simulation data has been growing with the complexity of the models. This growth in data is creating a widening gap between the data being produced and the tools necessary to analyze large, high dimensional data sets. With single run data sets increasing into 10's, 100's and even 1000's of gigabytes, parallel computing tools are becoming a necessity in order to analyze and compare climate simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools that efficiently use parallel computing techniques to narrow the gap between data set size and analysis tools. ParCAT was created as a collaborative effort between climate scientists and computer scientists in order to provide efficient parallel implementations of the computing tools that are of use to climate scientists. Some of the basic functionalities included in the toolkit are the ability to compute spatio-temporal means and variances, differences between two runs and histograms of the values in a data set. ParCAT is designed to facilitate the "heavy lifting" that is required for large, multidimensional data sets. The toolkit does not focus on performing the final visualizations and presentation of results but rather, reducing large data sets to smaller, more manageable summaries. The output from ParCAT is provided in commonly used file formats (NetCDF, CSV, ASCII) to allow for simple integration with other tools. The toolkit is currently implemented as a command line utility, but will likely also provide a C library for developers interested in tighter software integration. Elements of the toolkit are already being incorporated into projects such as UV-CDAT and CMDX. There is also an effort underway to implement portions of the CCSM Land Model Diagnostics package using ParCAT in conjunction with Python and gnuplot. ParCAT is implemented in C to provide efficient file IO. The file IO operations in the toolkit use the parallel-netcdf library; this enables the code to use the parallel IO capabilities of modern HPC systems. Analysis that currently requires an estimated 12+ hours with the traditional CCSM Land Model Diagnostics Package can now be performed in as little as 30 minutes on a single desktop workstation and a few minutes for relatively small jobs completed on modern HPC systems such as ORNL's Jaguar.

A Energy Balance Analysis of the Climate Sensitivity to Variations in the Rate of Upwelling in the World Oceans.

NASA Astrophysics Data System (ADS)

Morantine, Michael Creighton

The climate system of the Earth has been under investigation for many years, and the "Green-House Effect" has introduced a sense of urgency into the effort. The globally averaged temperature of the Earth undergoes what is commonly referred to as natural fluctuations in the climate signal. One effort of climate modellers is to isolate the responses of particular climate forcings in order to better understand each effect. The use of energy balance climate models (EBM's) has been one of the major tools in this respect. Studies conducted on the response of the environment to the "Green-House Effect" predict a warming trend. After experiencing such a trend in the early 1900's, however, the globally averaged temperature of the Earth began to decrease in the 1940's and continued this trend for approximately 20 years before resuming its trend of increase. It will be shown that a reduction of ~10% in the upwelling rate in the oceans could produce a decrease in the globally averaged temperature sufficient to explain this departure from the expected trend. The analysis of paleoclimatic indicators has produced strong evidence that the orbital forcing with periods of approximately 21000, 41000 and 93000 years predicted by the Milankovitch Theory is the primary cause of the glacial cycles known to have occurred on the Earth. However, there is a dynamic interaction between the environment and the ice caps that is not completely understood at this time. The paleoclimatic indicators available for the last deglaciation are abundant and well preserved (relative to the evidence of previous glacial periods), and analysis of the evidence indicates that during the most recent deglaciation a pulsation in the polar front occurred on such a small time scale that Milankovitch forcing is ruled out as a possible cause. It will be shown that an abrupt shutdown in the deep-water formation process which feeds the upwelling in the oceans could produce an influence of appropriate magnitude and time-scale to be the source of the dynamic interaction responsible for this abrupt climatic event. The process employed in the dimension reduction used in the formulation of lower-order EBM's will be illustrated through the development of the equations, pointing out the inherent assumptions which must be made when developing one- and two-dimensional models as they are required. One -, two- and three-dimensional energy balance models will be analyzed and the results of climate sensitivity to upwelling variations will be presented graphically for each case.

Coastal and wetland ecosystems of the Chesapeake Bay watershed: Applying palynology to understand impacts of changing climate, sea level, and land use

USGS Publications Warehouse

Willard, Debra A.; Bernhardt, Christopher E.; Hupp, Cliff R.; Newell, Wayne L.

2015-01-01

The mid-Atlantic region and Chesapeake Bay watershed have been influenced by fluctuations in climate and sea level since the Cretaceous, and human alteration of the landscape began ~12,000 years ago, with greatest impacts since colonial times. Efforts to devise sustainable management strategies that maximize ecosystem services are integrating data from a range of scientific disciplines to understand how ecosystems and habitats respond to different climatic and environmental stressors. Palynology has played an important role in improving understanding of the impact of changing climate, sea level, and land use on local and regional vegetation. Additionally, palynological analyses have provided biostratigraphic control for surficial mapping efforts and documented agricultural activities of both Native American populations and European colonists. This field trip focuses on sites where palynological analyses have supported efforts to understand the impacts of changing climate and land use on the Chesapeake Bay ecosystem.

Climate changes, shifting ranges

USGS Publications Warehouse

Romañach, Stephanie

2015-01-01

Even a fleeting mention of the Everglades conjures colorful images of alligators, panthers, flamingos, and manatees. Over the centuries, this familiar cast of characters has become synonymous with life in south Florida. But the workings of a changing climate have the potential to significantly alter the menagerie of animals that call this area home. Global projections suggest south Florida wildlife will need to contend with higher temperatures, drier conditions, and rising seas in the years ahead. Recent modeling efforts shed new light on the potential outcomes these changes may have for threatened and endangered species in the area.

Comparison of Ice Cloud Particle Sizes Retrieved from Satellite Data Derived from In Situ Measurements

NASA Technical Reports Server (NTRS)

Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M.

1997-01-01

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al.), there is no comparable study for cirrus ice crystals. This study is an effort to supply such a data set.

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Progress and Preliminary Results

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2011-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Recent progress and the current status of AgMIP will be presented, highlighting three areas of activity: preliminary results from crop pilot studies, outcomes from regional workshops, and emerging scientific challenges. AgMIP crop modeling efforts are being led by pilot studies, which have been established for wheat, maize, rice, and sugarcane. These crop-specific initiatives have proven instrumental in testing and contributing to AgMIP protocols, as well as creating preliminary results for aggregation and input to agricultural trade models. Regional workshops are being held to encourage collaborations and set research activities in motion for key agricultural areas. The first of these workshops was hosted by Embrapa and UNICAMP and held in Campinas, Brazil. Outcomes from this meeting have informed crop modeling research activities within South America, AgMIP protocols, and future regional workshops. Several scientific challenges have emerged and are currently being addressed by AgMIP researchers. Areas of particular interest include geospatial weather generation, ensemble methods for climate scenarios and crop models, spatial aggregation of field-scale yields to regional and global production, and characterization of future changes in climate variability.

Assessing the sensitivity of avian species abundance to land cover and climate

USGS Publications Warehouse

LeBrun, Jaymi J.; Thogmartin, Wayne E.; Thompson, Frank R.; Dijak, William D.; Millspaugh, Joshua J.

2016-01-01

Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and climate on the abundance of five bird species in the Central United States that have habitat requirements ranging from grassland and shrubland to forest. We substituted space for time to examine potential impacts of a changing climate by assessing climate and land cover relationships over a broad latitudinal gradient. We found positive and negative relationships of climate and land cover factors with avian abundances. Habitat variables drove patterns of abundance in migratory and resident species, although climate was also influential in predicting abundance for some species occupying more open habitat (i.e., prairie warbler, blue-winged warbler, and northern bobwhite). Abundance of northern bobwhite increased with winter temperature and was the species exhibiting the most significant effect of climate. Models for birds primarily occupying early successional habitats performed better with a combination of habitat and climate variables whereas models of species found in contiguous forest performed best with land cover alone. These varied species-specific responses present unique challenges to land managers trying to balance species conservation over a variety of land covers. Management activities focused on increasing forest cover may play a role in mitigating effects of future climate by providing habitat refugia to species vulnerable to projected changes. Conservation efforts would be best served focusing on areas with high species abundances and an array of habitats. Future work managing forests for resilience and resistance to climate change could benefit species already susceptible to climate impacts.

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.

Magic - Marine Arm Gpci Investigation of Clouds

NASA Astrophysics Data System (ADS)

Lewis, E. R.; Wiscombe, W. J.; Albrecht, B. A.; Bland, G.; Flagg, C. N.; Klein, S. A.; Kollias, P.; Mace, G. G.; Reynolds, M.; Schwartz, S. E.; Siebesma, P.; Teixeira, J.; Wood, R.; Zhang, M.

2012-12-01

MAGIC, the Marine ARM (Atmospheric Radiation Measurement program) GPCI Investigation of Clouds, will deploy the Second ARM Mobile Facility (AMF2) aboard the Horizon Lines cargo container ship M/V Spirit traversing the route between Los Angeles, CA and Honolulu, HI from October, 2012 through September, 2013 (except from a few months in the middle of this time period when the ship will be in dry dock). During this time AMF2 will observe and characterize the properties of clouds and precipitation, aerosols, and atmospheric radiation; standard meteorological and oceanographic variables; and atmospheric structure. There will also be Intensive Observational Periods (IOPs), one in January, 2013 and one in July, 2013 during which more detailed measurements of the atmospheric structure will be made. Clouds remain a major source of uncertainty in climate projections. In this context, subtropical marine boundary layer (MBL) clouds play a key role in cloud-climate feedbacks that are not well understood yet play a large role in biases both in seasonal coupled model forecasts and annual mean climate forecasts. In particular, current climate models do not accurately represent the transition from the stratocumulus (Sc) regime, with its high albedo and large impact on the global radiative balance of Earth, to shallow trade-wind cumulus (Cu), which play a fundamental role in global surface evaporation and also albedo. Climate models do not yet adequately parameterize the small-scale physical processes associated with turbulence, convection, and radiation in these clouds. Part of this inability results from lack of accurate data on these clouds and the conditions responsible for their properties, including aerosol properties, radiation, and atmospheric and oceanographic conditions. The primary objectives of MAGIC are to improve the representation of the Sc-to-Cu transition in climate models by characterizing the essential properties of this transition, and to produce the observed statistics of these Sc-to-Cu characteristics for the deployment period along the transect. This first marine deployment of AMF2 will yield an unparalleled and extremely rich data set that will greatly enhance the ability to understand and parameterize clouds and precipitation, aerosols, and radiation and the interactions among them; the processes that determine their properties; and factors that control these processes. Deployment of AMF2 on a ship that routinely traverses this route will provide a long-term data set over a vast cloud region which is of intense interest to climate modelers. Specifically, the proposed transect lies closely along the cross section used for the GPCI, and the data collected will provide constraint, validation, and support for this modeling effort, and for associated modeling efforts such as the CGILS and EUCLIPSE.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

NASA Astrophysics Data System (ADS)

Way, M. J.; Aleinov, I.; Amundsen, David S.; Chandler, M. A.; Clune, T. L.; Del Genio, A. D.; Fujii, Y.; Kelley, M.; Kiang, N. Y.; Sohl, L.; Tsigaridis, K.

2017-07-01

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a three-dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of solar system and exoplanetary terrestrial planets. Its parent model, known as ModelE2, is used to simulate modern Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions, including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (from slower to more rapid than modern Earth’s, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the solar system such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn’s moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents, we can then further expand its capabilities to those exoplanetary rocky worlds that have been discovered in the past, as well as those to be discovered in the future. We also discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

NASA Technical Reports Server (NTRS)

Way, M. J.; Aleinov, I.; Amundsen, David S.; Chandler, M. A.; Clune, T. L.; Del Genio, A.; Fujii, Y.; Kelley, M.; Kiang, N. Y.; Sohl, L.;

Using Outreach and Engagement Efforts to Inform the Makah Tribe's Climate Adaptation Plan

NASA Astrophysics Data System (ADS)

Nelson, L. K.; Chang, M.; Howk, F.

2017-12-01

The Makah Tribe views climate change as one of the biggest challenges to their natural resource management, threatening their livelihoods, economy, and culture. As part of their work towards climate adaptation planning, the Makah Tribal Council and tribal natural resource managers prioritized early community outreach and engagement efforts in order to accomplish three goals: continually update and inform the tribal community about the Tribe's climate adaptation efforts; gather community input and priorities for the Makah Climate Adaptation Plan; and provide a series of targeted educational events to inform the tribal community about projected climate change impacts to our resources. Our first community climate event, the Makah Climate Change Awareness Dinner, was held on February 8, 2017. At this event, we provided an overview of the Makah Tribe's Climate Vulnerability Assessment and administered an initial climate survey that gathered information regarding community members' observed environmental changes, knowledge about climate change and impacts, and any concerns and priorities to include in the Tribe's adaptation plan. We developed a framework for incorporating community engagement into climate adaptation planning and used results of our community survey to ensure community concerns were being addressed in the plan in addition to risks identified in western science. We also used survey results to inform a series of educational events to address knowledge gaps in the community and requested topics. These are two of next steps that the Makah Tribe is pursuing towards climate adaptation planning.

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

Satellite Remote Sensing is Key to Water Cycle Integrator

NASA Astrophysics Data System (ADS)

Koike, T.

2016-12-01

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

Forecasting the effects of land-use and climate change on wildlife communities and habitats in the lower Mississippi Valley

USGS Publications Warehouse

Faulkner, Stephen P.

2010-01-01

Landscape patterns and processes reflect both natural ecosystem attributes and the policy and management decisions of individual Federal, State, county, and private organizations. Land-use regulation, water management, and habitat conservation and restoration efforts increasingly rely on landscape-level approaches that incorporate scientific information into the decision-making process. Since management actions are implemented to affect future conditions, decision-support models are necessary to forecast potential future conditions resulting from these decisions. Spatially explicit modeling approaches enable testing of different scenarios and help evaluate potential outcomes of management actions in conjunction with natural processes such as climate change. The ability to forecast the effects of changing land use and climate is critically important to land and resource managers since their work is inherently site specific, yet conservation strategies and practices are expressed at higher spatial and temporal scales that must be considered in the decisionmaking process.

Can role-play with interactive simulations enhance climate change knowledge, affect and intent to act?

NASA Astrophysics Data System (ADS)

Rooney-varga, J. N.; Sterman, J.; Fracassi, E. P.; Franck, T.; Kapmeier, F.; Kurker, V.; Jones, A.; Rath, K.

2017-12-01

The strong scientific consensus about the reality and risks of anthropogenic climate change stands in stark contrast to widespread confusion and complacency among the public. Many efforts to close that gap, grounded in the information deficit model of risk communication, provide scientific information on climate change through reports and presentations. However, research shows that showing people research does not work: the gap between scientific and public understanding of climate change remains wide. Tools that are rigorously grounded in the science and motivate action on climate change are urgently needed. Here we assess the impact of one such tool, an interactive, role-play simulation, World Climate. Participants take the roles of delegates to the UN climate negotiations and are challenged to create an agreement limiting warming to no more than 2°C. The C-ROADS climate simulation model then provides participants with immediate feedback about the expected impacts of their decisions. Participants use C-ROADS to explore the climate system and use the results to refine their negotiating positions, learning about climate change while experiencing the social dynamics of negotiations and decision-making. Pre- and post-survey results from 21 sessions in eight nations showed significant gains in participants' climate change knowledge, affective engagement, intent to take action, and desire to learn. Contrary to the deficit model, gains in participants' desire to learn more and intention to act were associated with gains in affective engagement, particularly feelings of urgency and hope, but not climate knowledge. Gains were just as strong among participants who oppose government regulation, suggesting the simulation's potential to reach across political divides. Results indicate that simulations like World Climate offer a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed by science.

Effects of climate change on streamflow extremes and implications for reservoir inflow in the United States

DOE PAGES

Naz, Bibi S.; Kao, Shih -Chieh; Ashfaq, Moetasim; ...

2017-11-15

The magnitude and frequency of hydrometeorological extremes are expected to increase in the conterminous United States (CONUS) over the rest of this century, and their increase will significantly impact water resource management. While previous efforts focused on the effects of reservoirs on downstream discharge, the effects of climate change on reservoir inflows in upstream areas are not well understood. We evaluated the large-scale climate change effects on extreme hydrological events and their implications for reservoir inflows in 178 headwater basins across CONUS using the Variable Infiltration Capacity (VIC) hydrologic model. The VIC model was forced with a 10-member ensemble ofmore » global circulation models under the Representative Concentration Pathway 8.5 that were dynamically downscaled using a regional climate model (RegCM4) and bias-corrected to 1/24° grid cell resolution. The results projected an increase in the likelihood of flood risk by 44% for a majority of subbasins upstream of flood control reservoirs in the central United States and increased drought risk by 11% for subbasins upstream of hydropower reservoirs across the western United States. Increased risk of both floods and droughts can potentially make reservoirs across CONUS more vulnerable to future climate conditions. In conclusion, this study estimates reservoir inflow changes over the next several decades, which can be used to optimize water supply management downstream.« less

Effects of climate change on streamflow extremes and implications for reservoir inflow in the United States

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

Naz, Bibi S.; Kao, Shih -Chieh; Ashfaq, Moetasim

The magnitude and frequency of hydrometeorological extremes are expected to increase in the conterminous United States (CONUS) over the rest of this century, and their increase will significantly impact water resource management. While previous efforts focused on the effects of reservoirs on downstream discharge, the effects of climate change on reservoir inflows in upstream areas are not well understood. We evaluated the large-scale climate change effects on extreme hydrological events and their implications for reservoir inflows in 178 headwater basins across CONUS using the Variable Infiltration Capacity (VIC) hydrologic model. The VIC model was forced with a 10-member ensemble ofmore » global circulation models under the Representative Concentration Pathway 8.5 that were dynamically downscaled using a regional climate model (RegCM4) and bias-corrected to 1/24° grid cell resolution. The results projected an increase in the likelihood of flood risk by 44% for a majority of subbasins upstream of flood control reservoirs in the central United States and increased drought risk by 11% for subbasins upstream of hydropower reservoirs across the western United States. Increased risk of both floods and droughts can potentially make reservoirs across CONUS more vulnerable to future climate conditions. In conclusion, this study estimates reservoir inflow changes over the next several decades, which can be used to optimize water supply management downstream.« less

Integrating Climate Science, Marine Ecology, and Fisheries Economics to Predict the Effects of Climate Change on New England lobster Fisheries

NASA Astrophysics Data System (ADS)

Le Bris, A.; Pershing, A. J.; Holland, D. S.; Mills, K.; Sun, C. H. J.

2016-02-01

The Gulf of Maine and the northwest Atlantic shelf have experienced one of the fastest warming rates of the global ocean over the past decade, and concerns are growing about the long-term sustainability of the fishing industries in the region. The lucrative American lobster fishery occurs over a steep temperature gradient, providing a unique opportunity to evaluate the consequences of climate change and variability on marine socio-ecological systems. This study aims at developing an integrated climate, population dynamics, and fishery economics model to predict consequences of climate change on the American lobster fishery. In this talk, we first describe a mechanistic model that combines life-history theory and a size-spectrum approach to simulate the dynamics of the population. Results show that as temperature increases, early growth rate and predation on small individuals increases, while size-at-maturity, maximum length and predation on large individuals decreases, resulting in a lower recruitment in the southern New-England and higher recruitment in the northern Gulf of Maine. Second, we present an integrated fishery and economic module that links temperature to landings and price through its influence on catchability and abundance. Preliminary results show that temperature is positively correlated with landings and negatively correlated with price in the Gulf of Maine. Finally, we discuss how model simulations under various fishing effort, market and climate scenarios can be used to identify adaptation opportunities to improve the resilience of the fishery to climate change.

Climate envelope predictions indicate an enlarged suitable wintering distribution for Great Bustards (Otis tarda dybowskii) in China for the 21st century

PubMed Central

Mi, Chunrong; Falk, Huettmann

2016-01-01

The rapidly changing climate makes humans realize that there is a critical need to incorporate climate change adaptation into conservation planning. Whether the wintering habitats of Great Bustards (Otis tarda dybowskii), a globally endangered migratory subspecies whose population is approximately 1,500–2,200 individuals in China, would be still suitable in a changing climate environment, and where this could be found, is an important protection issue. In this study, we selected the most suitable species distribution model for bustards using climate envelopes from four machine learning models, combining two modelling approaches (TreeNet and Random Forest) with two sets of variables (correlated variables removed or not). We used common evaluation methods area under the receiver operating characteristic curves (AUC) and the True Skill Statistic (TSS) as well as independent test data to identify the most suitable model. As often found elsewhere, we found Random Forest with all environmental variables outperformed in all assessment methods. When we projected the best model to the latest IPCC-CMIP5 climate scenarios (Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 in three Global Circulation Models (GCMs)), and averaged the project results of the three models, we found that suitable wintering habitats in the current bustard distribution would increase during the 21st century. The Northeast Plain and the south of North China were projected to become two major wintering areas for bustards. However, the models suggest that some currently suitable habitats will experience a reduction, such as Dongting Lake and Poyang Lake in the Middle and Lower Yangtze River Basin. Although our results suggested that suitable habitats in China would widen with climate change, greater efforts should be undertaken to assess and mitigate unstudied human disturbance, such as pollution, hunting, agricultural development, infrastructure construction, habitat fragmentation, and oil and mine exploitation. All of these are negatively and intensely linked with global change. PMID:26855870

Climate envelope predictions indicate an enlarged suitable wintering distribution for Great Bustards (Otis tarda dybowskii) in China for the 21st century.

PubMed

Mi, Chunrong; Falk, Huettmann; Guo, Yumin

2016-01-01

The rapidly changing climate makes humans realize that there is a critical need to incorporate climate change adaptation into conservation planning. Whether the wintering habitats of Great Bustards (Otis tarda dybowskii), a globally endangered migratory subspecies whose population is approximately 1,500-2,200 individuals in China, would be still suitable in a changing climate environment, and where this could be found, is an important protection issue. In this study, we selected the most suitable species distribution model for bustards using climate envelopes from four machine learning models, combining two modelling approaches (TreeNet and Random Forest) with two sets of variables (correlated variables removed or not). We used common evaluation methods area under the receiver operating characteristic curves (AUC) and the True Skill Statistic (TSS) as well as independent test data to identify the most suitable model. As often found elsewhere, we found Random Forest with all environmental variables outperformed in all assessment methods. When we projected the best model to the latest IPCC-CMIP5 climate scenarios (Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 in three Global Circulation Models (GCMs)), and averaged the project results of the three models, we found that suitable wintering habitats in the current bustard distribution would increase during the 21st century. The Northeast Plain and the south of North China were projected to become two major wintering areas for bustards. However, the models suggest that some currently suitable habitats will experience a reduction, such as Dongting Lake and Poyang Lake in the Middle and Lower Yangtze River Basin. Although our results suggested that suitable habitats in China would widen with climate change, greater efforts should be undertaken to assess and mitigate unstudied human disturbance, such as pollution, hunting, agricultural development, infrastructure construction, habitat fragmentation, and oil and mine exploitation. All of these are negatively and intensely linked with global change.

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.

Evaluation of GCMs in the context of regional predictive climate impact studies.

NASA Astrophysics Data System (ADS)

Kokorev, Vasily; Anisimov, Oleg

2016-04-01

Significant improvements in the structure, complexity, and general performance of earth system models (ESMs) have been made in the recent decade. Despite these efforts, the range of uncertainty in predicting regional climate impacts remains large. The problem is two-fold. Firstly, there is an intrinsic conflict between the local and regional scales of climate impacts and adaptation strategies, on one hand, and larger scales, at which ESMs demonstrate better performance, on the other. Secondly, there is a growing understanding that majority of the impacts involve thresholds, and are thus driven by extreme climate events, whereas accent in climate projections is conventionally made on gradual changes in means. In this study we assess the uncertainty in projecting extreme climatic events within a region-specific and process-oriented context by examining the skills and ranking of ESMs. We developed a synthetic regionalization of Northern Eurasia that accounts for the spatial features of modern climatic changes and major environmental and socio-economical impacts. Elements of such fragmentation could be considered as natural focus regions that bridge the gap between the spatial scales adopted in climate-impacts studies and patterns of climate change simulated by ESMs. In each focus region we selected several target meteorological variables that govern the key regional impacts, and examined the ability of the models to replicate their seasonal and annual means and trends by testing them against observations. We performed a similar evaluation with regard to extremes and statistics of the target variables. And lastly, we used the results of these analyses to select sets of models that demonstrate the best performance at selected focus regions with regard to selected sets of target meteorological parameters. Ultimately, we ranked the models according to their skills, identified top-end models that "better than average" reproduce the behavior of climatic parameters, and eliminated the outliers. Since the criteria of selecting the "best" models are somewhat loose, we constructed several regional ensembles consisting of different number of high-ranked models and compared results from these optimized ensembles with observations and with the ensemble of all models. We tested our approach in specific regional application of the terrestrial Russian Arctic, considering permafrost and Artic biomes as key regional climate-dependent systems, and temperature and precipitation characteristics governing their state as target meteorological parameters. Results of this case study are deposited on the web portal www.permafrost.su/gcms

Comparing Amazon Basin CO2 fluxes from an atmospheric inversion with TRENDY biosphere models

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.; Alden, C. B.; Harper, A. B.; Ahlström, A.; Touma, D. E.; Miller, J. B.; Gatti, L. V.; Gloor, M.

2015-12-01

Net exchange of carbon dioxide (CO2) between the atmosphere and the terrestrial biosphere is sensitive to environmental conditions, including extreme heat and drought. Of particular importance for local and global carbon balance and climate are the expansive tracts of tropical rainforest located in the Amazon Basin. Because of the Basin's size and ecological heterogeneity, net biosphere CO2 exchange with the atmosphere remains largely un-constrained. In particular, the response of net CO2 exchange to changes in environmental conditions such as temperature and precipitation are not yet well known. However, proper representation of these relationships in biosphere models is a necessary constraint for accurately modeling future climate and climate-carbon cycle feedbacks. In an effort to compare biosphere response to climate across different biosphere models, the TRENDY model intercomparison project coordinated the simulation of CO2 fluxes between the biosphere and atmosphere, in response to historical climate forcing, by 9 different Dynamic Global Vegetation Models. We examine the TRENDY model results in the Amazon Basin, and compare this "bottom-up" method with fluxes derived from a "top-down" approach to estimating net CO2 fluxes, obtained through atmospheric inverse modeling using CO2 measurements sampled by aircraft above the basin. We compare the "bottom-up" and "top-down" fluxes in 5 sub-regions of the Amazon basin on a monthly basis for 2010-2012. Our results show important periods of agreement between some models in the TRENDY suite and atmospheric inverse model results, notably the simulation of increased biosphere CO2 loss during wet season heat in the Central Amazon. During the dry season, however, model ability to simulate observed response of net CO2 exchange to drought was varied, with few models able to reproduce the "top-down" inversion flux signals. Our results highlight the value of atmospheric trace gas observations for helping to narrow the possibilities of future carbon-climate interactions, especially in historically under-observed regions like the Amazon.

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.

NOAA Climate Test Bed: CFSv.3 Planning Meeting (August 25-26, 2011)

Science.gov Websites

: Experience of porting CFSv2 NASA Ames SGI ICE platform (Marx) 12:30-14:00 Breakout discussion (1) Group 1A :00 NASA (Suarez) 09:00-09:20 GFDL (Rosati) 09:20-09:40 ECMWF (Molteni) 09:40-10:00 CMCC (Navarra) 10 modeling efforts at other modeling centers (e.g., GFDL, NCAR, NASA, COLA, DOE, ECMWF). Meeting Format: The

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea.

PubMed

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

2015-06-01

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countries with more limited commitments. In the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

DOE PAGES

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

2015-05-28

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countriesmore » with more limited commitments. Finally, in the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.« less

Climate Analytics as a Service

NASA Technical Reports Server (NTRS)

Schnase, John L.; Duffy, Daniel Q.; McInerney, Mark A.; Webster, W. Phillip; Lee, Tsengdar J.

2014-01-01

Climate science is a big data domain that is experiencing unprecedented growth. In our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). CAaaS combines high-performance computing and data-proximal analytics with scalable data management, cloud computing virtualization, the notion of adaptive analytics, and a domain-harmonized API to improve the accessibility and usability of large collections of climate data. MERRA Analytic Services (MERRA/AS) provides an example of CAaaS. MERRA/AS enables MapReduce analytics over NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of key climate variables. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, CAaaS is providing the agility required to meet our customers' increasing and changing data management and data analysis needs.

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

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

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countriesmore » with more limited commitments. Finally, in the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.« less

Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants

USGS Publications Warehouse

Sofaer, Helen R.; Jarnevich, Catherine S.

2017-01-01

AimThe distributions of exotic species reflect patterns of human-mediated dispersal, species climatic tolerances and a suite of other biotic and abiotic factors. The relative importance of each of these factors will shape how the spread of exotic species is affected by ongoing economic globalization and climate change. However, patterns of trade may be correlated with variation in scientific sampling effort globally, potentially confounding studies that do not account for sampling patterns.LocationGlobal.Time periodMuseum records, generally from the 1800s up to 2015.Major taxa studiedPlant species exotic to the United States.MethodsWe used data from the Global Biodiversity Information Facility (GBIF) to summarize the number of plant species with exotic occurrences in the United States that also occur in each other country world-wide. We assessed the relative importance of trade and climatic similarity for explaining variation in the number of shared species while evaluating several methods to account for variation in sampling effort among countries.ResultsAccounting for variation in sampling effort reversed the relative importance of trade and climate for explaining numbers of shared species. Trade was strongly correlated with numbers of shared U.S. exotic plants between the United States and other countries before, but not after, accounting for sampling variation among countries. Conversely, accounting for sampling effort strengthened the relationship between climatic similarity and species sharing. Using the number of records as a measure of sampling effort provided a straightforward approach for the analysis of occurrence data, whereas species richness estimators and rarefaction were less effective at removing sampling bias.Main conclusionsOur work provides support for broad-scale climatic limitation on the distributions of exotic species, illustrates the need to account for variation in sampling effort in large biodiversity databases, and highlights the difficulty in inferring causal links between the economic drivers of invasion and global patterns of exotic species occurrence.

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.

Improving High-Resolution Weather Forecasts Using the Weather Research and Forecasting (WRF) Model with an Updated Kain–Fritsch Scheme

EPA Science Inventory

Efforts to improve the prediction accuracy of high-resolution (1–10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at ...

"Investigation of Trends in Aerosol Direct Radiative Effects over North America Using a Coupled Meteorology-Chemistry Model"

EPA Science Inventory

While aerosol radiative effects have been recognized as some of the largest sources of uncertainty among the forcers of climate change, there has been little effort devoted to verification of the spatial and temporal variability of the magnitude and directionality of aerosol radi...

Climate change: Evolving technologies, U.S. business, and the world economy in the 21. century

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

Harter, J.J.

1996-12-31

The International Climate Change Partnership presents this report as one of its efforts to present current information on climate change to the public. One often hears about the expenses entailed in protecting the environment. Unfortunately, one hears less about the economic benefits that may be associated with prudent actions to counter environmental threats. This conference is particularly useful because it focuses attention on profitable business opportunities in the United States and elsewhere that arise from practical efforts to mitigate the risks of climate change. The report contains a brief synopsis of each speaker`s address on climate change.

Engaging Minority University STEM Education Professors in the Science of Climate Change: Recruitment, Implementation and Evaluation

NASA Astrophysics Data System (ADS)

Hayden, L. B.; Hale, S. R.; Johnson, D.

2013-12-01

Elizabeth City State University has joined with the University of New Hampshire under the NASA Innovations in Climate Education (NICE) to empower faculty of education programs at Minority Serving Institutions (MSIs) to better engage their pre-service teachers in teaching and learning about global climate change through the use of NASA Earth observation data sets. This project is designed to impact teaching first on college campuses within science education classes. Second, as pre-service teachers transition into in-service teachers, the impact will extend to elementary and secondary classrooms. Our goal is to empower faculty of education programs at Minority Serving Institutions to better engage their pre-service teachers in teaching and learning about global climate change through the use of NASA Earth observation data sets. This presentation documents the efforts to recruit two cohorts of STEM education faculty from MSIs along with the associated implementation and program evaluation efforts. To date, thirty-four (34) faculty from over a dozen MSIs have participated in the summer workshops. Recruitment efforts have focused on interactions with faculty in campus and conference settings. This has included the Johnson C. Smith University conference, the Minorities (QEM) Network Workshop on Evidence-Based STEM Instructional Strategies and the Annual Minority Serving Institutions Technical Assistance and Capacity Conference. The primary implementation mechanism was a one-week summer workshop conducted each year. ECSU hosted the first summer workshop and UNH hosted the second workshop. During each workshop, faculty had an opportunity to engage in activities using NASA Earth observation data, and benefited from engaged instruction and interaction with scientists who routinely use these datasets in their professional practice. This provided a comprehensive learning environment ensuring the transfer of the know-how on utilizing NASA datasets and tools in climate change education from researcher to science educator to pre-service STEM teacher. The faculty conducted field work that emphasizes place-based pedagogy. They worked with NASA satellite imagery data from the MODIS and SeaWiFS sensors, and discussed the challenges and approaches to integrating all or some of the lessons into their courses. Program Evaluation efforts, led by Learning Innovations at WestEd, includes formative and summative evaluation related to the outcomes of the project. Evaluators worked with project staff to create a logic model that clearly articulates a theory of action for the project. Included in the evaluation model were online questionnaires and focus group protocols. There exist evidence to show that the MSI faculty who participate in the workshop are using the information learned to engage their pre-service teachers in teaching and learning about global climate change through the use of NASA Earth observation sets.

Climatic impact of Amazon deforestation - a mechanistic model study

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

Ning Zeng; Dickinson, R.E.; Xubin Zeng

1996-04-01

Recent general circulation model (GCM) experiments suggest a drastic change in the regional climate, especially the hydrological cycle, after hypothesized Amazon basinwide deforestation. To facilitate the theoretical understanding os such a change, we develop an intermediate-level model for tropical climatology, including atmosphere-land-ocean interaction. The model consists of linearized steady-state primitive equations with simplified thermodynamics. A simple hydrological cycle is also included. Special attention has been paid to land-surface processes. It generally better simulates tropical climatology and the ENSO anomaly than do many of the previous simple models. The climatic impact of Amazon deforestation is studied in the context of thismore » model. Model results show a much weakened Atlantic Walker-Hadley circulation as a result of the existence of a strong positive feedback loop in the atmospheric circulation system and the hydrological cycle. The regional climate is highly sensitive to albedo change and sensitive to evapotranspiration change. The pure dynamical effect of surface roughness length on convergence is small, but the surface flow anomaly displays intriguing features. Analysis of the thermodynamic equation reveals that the balance between convective heating, adiabatic cooling, and radiation largely determines the deforestation response. Studies of the consequences of hypothetical continuous deforestation suggest that the replacement of forest by desert may be able to sustain a dry climate. Scaling analysis motivated by our modeling efforts also helps to interpret the common results of many GCM simulations. When a simple mixed-layer ocean model is coupled with the atmospheric model, the results suggest a 1{degrees}C decrease in SST gradient across the equatorial Atlantic Ocean in response to Amazon deforestation. The magnitude depends on the coupling strength. 66 refs., 16 figs., 4 tabs.« less

Continental-scale assessment of risk to the Australian odonata from climate change.

PubMed

Bush, Alex A; Nipperess, David A; Duursma, Daisy E; Theischinger, Gunther; Turak, Eren; Hughes, Lesley

2014-01-01

Climate change is expected to have substantial impacts on the composition of freshwater communities, and many species are threatened by the loss of climatically suitable habitat. In this study we identify Australian Odonata (dragonflies and damselflies) vulnerable to the effects of climate change on the basis of exposure, sensitivity and pressure to disperse in the future. We used an ensemble of species distribution models to predict the distribution of 270 (85%) species of Australian Odonata, continent-wide at the subcatchment scale, and for both current and future climates using two emissions scenarios each for 2055 and 2085. Exposure was scored according to the departure of temperature, precipitation and hydrology from current conditions. Sensitivity accounted for change in the area and suitability of projected climatic habitat, and pressure to disperse combined measurements of average habitat shifts and the loss experienced with lower dispersal rates. Streams and rivers important to future conservation efforts were identified based on the sensitivity-weighted sum of habitat suitability for the most vulnerable species. The overall extent of suitable habitat declined for 56-69% of the species modelled by 2085 depending on emissions scenario. The proportion of species at risk across all components (exposure, sensitivity, pressure to disperse) varied between 7 and 17% from 2055 to 2085 and a further 3-17% of species were also projected to be at high risk due to declines that did not require range shifts. If dispersal to Tasmania was limited, many south-eastern species are at significantly increased risk. Conservation efforts will need to focus on creating and preserving freshwater refugia as part of a broader conservation strategy that improves connectivity and promotes adaptive range shifts. The significant predicted shifts in suitable habitat could potentially exceed the dispersal capacity of Odonata and highlights the challenge faced by other freshwater species.

Continental-Scale Assessment of Risk to the Australian Odonata from Climate Change

PubMed Central

Bush, Alex A.; Nipperess, David A.; Duursma, Daisy E.; Theischinger, Gunther; Turak, Eren; Hughes, Lesley

2014-01-01

Climate change is expected to have substantial impacts on the composition of freshwater communities, and many species are threatened by the loss of climatically suitable habitat. In this study we identify Australian Odonata (dragonflies and damselflies) vulnerable to the effects of climate change on the basis of exposure, sensitivity and pressure to disperse in the future. We used an ensemble of species distribution models to predict the distribution of 270 (85%) species of Australian Odonata, continent-wide at the subcatchment scale, and for both current and future climates using two emissions scenarios each for 2055 and 2085. Exposure was scored according to the departure of temperature, precipitation and hydrology from current conditions. Sensitivity accounted for change in the area and suitability of projected climatic habitat, and pressure to disperse combined measurements of average habitat shifts and the loss experienced with lower dispersal rates. Streams and rivers important to future conservation efforts were identified based on the sensitivity-weighted sum of habitat suitability for the most vulnerable species. The overall extent of suitable habitat declined for 56–69% of the species modelled by 2085 depending on emissions scenario. The proportion of species at risk across all components (exposure, sensitivity, pressure to disperse) varied between 7 and 17% from 2055 to 2085 and a further 3–17% of species were also projected to be at high risk due to declines that did not require range shifts. If dispersal to Tasmania was limited, many south-eastern species are at significantly increased risk. Conservation efforts will need to focus on creating and preserving freshwater refugia as part of a broader conservation strategy that improves connectivity and promotes adaptive range shifts. The significant predicted shifts in suitable habitat could potentially exceed the dispersal capacity of Odonata and highlights the challenge faced by other freshwater species. PMID:24551197

Evaluation of Offline Models Used to Simulate Components of the Permafrost Carbon Feedback: Experience from the Permafrost Carbon Network Model Integration Group

NASA Astrophysics Data System (ADS)

McGuire, A. D.

2016-12-01

The Model Integration Group of the Permafrost Carbon Network (see http://www.permafrostcarbon.org/) has conducted studies to evaluate the sensitivity of offline terrestrial permafrost and carbon models to both historical and projected climate change. These studies indicate that there is a wide range of (1) initial states permafrost extend and carbon stocks simulated by these models and (2) responses of permafrost extent and carbon stocks to both historical and projected climate change. In this study, we synthesize what has been learned about the variability in initial states among models and the driving factors that contribute to variability in the sensitivity of responses. We conclude the talk with a discussion of efforts needed by (1) the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost carbon feedback and (2) the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.

Enhancing global climate policy ambition towards a 1.5 °C stabilization: a short-term multi-model assessment

NASA Astrophysics Data System (ADS)

Vrontisi, Zoi; Luderer, Gunnar; Saveyn, Bert; Keramidas, Kimon; Reis Lara, Aleluia; Baumstark, Lavinia; Bertram, Christoph; Sytze de Boer, Harmen; Drouet, Laurent; Fragkiadakis, Kostas; Fricko, Oliver; Fujimori, Shinichiro; Guivarch, Celine; Kitous, Alban; Krey, Volker; Kriegler, Elmar; Broin, Eoin Ó.; Paroussos, Leonidas; van Vuuren, Detlef

2018-04-01

The Paris Agreement is a milestone in international climate policy as it establishes a global mitigation framework towards 2030 and sets the ground for a potential 1.5 °C climate stabilization. To provide useful insights for the 2018 UNFCCC Talanoa facilitative dialogue, we use eight state-of-the-art climate-energy-economy models to assess the effectiveness of the Intended Nationally Determined Contributions (INDCs) in meeting high probability 1.5 and 2 °C stabilization goals. We estimate that the implementation of conditional INDCs in 2030 leaves an emissions gap from least cost 2 °C and 1.5 °C pathways for year 2030 equal to 15.6 (9.0–20.3) and 24.6 (18.5–29.0) GtCO2eq respectively. The immediate transition to a more efficient and low-carbon energy system is key to achieving the Paris goals. The decarbonization of the power supply sector delivers half of total CO2 emission reductions in all scenarios, primarily through high penetration of renewables and energy efficiency improvements. In combination with an increased electrification of final energy demand, low-carbon power supply is the main short-term abatement option. We find that the global macroeconomic cost of mitigation efforts does not reduce the 2020–2030 annual GDP growth rates in any model more than 0.1 percentage points in the INDC or 0.3 and 0.5 in the 2 °C and 1.5 °C scenarios respectively even without accounting for potential co-benefits and avoided climate damages. Accordingly, the median GDP reductions across all models in 2030 are 0.4%, 1.2% and 3.3% of reference GDP for each respective scenario. Costs go up with increasing mitigation efforts but a fragmented action, as implied by the INDCs, results in higher costs per unit of abated emissions. On a regional level, the cost distribution is different across scenarios while fossil fuel exporters see the highest GDP reductions in all INDC, 2 °C and 1.5 °C scenarios.

Ancillary health effects of climate mitigation scenarios as drivers of policy uptake: a review of air quality, transportation and diet co-benefits modeling studies

NASA Astrophysics Data System (ADS)

Chang, Kelly M.; Hess, Jeremy J.; Balbus, John M.; Buonocore, Jonathan J.; Cleveland, David A.; Grabow, Maggie L.; Neff, Roni; Saari, Rebecca K.; Tessum, Christopher W.; Wilkinson, Paul; Woodward, Alistair; Ebi, Kristie L.

2017-11-01

Background: Significant mitigation efforts beyond the Nationally Determined Commitments (NDCs) coming out of the 2015 Paris Climate Agreement are required to avoid warming of 2 °C above pre-industrial temperatures. Health co-benefits represent selected near term, positive consequences of climate policies that can offset mitigation costs in the short term before the beneficial impacts of those policies on the magnitude of climate change are evident. The diversity of approaches to modeling mitigation options and their health effects inhibits meta-analyses and syntheses of results useful in policy-making. Methods/Design: We evaluated the range of methods and choices in modeling health co-benefits of climate mitigation to identify opportunities for increased consistency and collaboration that could better inform policy-making. We reviewed studies quantifying the health co-benefits of climate change mitigation related to air quality, transportation, and diet published since the 2009 Lancet Commission ‘Managing the health effects of climate change’ through January 2017. We documented approaches, methods, scenarios, health-related exposures, and health outcomes. Results/Synthesis: Forty-two studies met the inclusion criteria. Air quality, transportation, and diet scenarios ranged from specific policy proposals to hypothetical scenarios, and from global recommendations to stakeholder-informed local guidance. Geographic and temporal scope as well as validity of scenarios determined policy relevance. More recent studies tended to use more sophisticated methods to address complexity in the relevant policy system. Discussion: Most studies indicated significant, nearer term, local ancillary health benefits providing impetus for policy uptake and net cost savings. However, studies were more suited to describing the interaction of climate policy and health and the magnitude of potential outcomes than to providing specific accurate estimates of health co-benefits. Modeling the health co-benefits of climate policy provides policy-relevant information when the scenarios are reasonable, relevant, and thorough, and the model adequately addresses complexity. Greater consistency in selected modeling choices across the health co-benefits of climate mitigation research would facilitate evaluation of mitigation options particularly as they apply to the NDCs and promote policy uptake.

Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

NASA Astrophysics Data System (ADS)

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

2018-01-01

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

Using critical evaluation to reappraise plausibility judgments: A critical cognitive component of conceptual change

NASA Astrophysics Data System (ADS)

Lombardi, D.

2011-12-01

Plausibility judgments-although well represented in conceptual change theories (see, for example, Chi, 2005; diSessa, 1993; Dole & Sinatra, 1998; Posner et al., 1982)-have received little empirical attention until our recent work investigating teachers' and students' understanding of and perceptions about human-induced climate change (Lombardi & Sinatra, 2010, 2011). In our first study with undergraduate students, we found that greater plausibility perceptions of human-induced climate accounted for significantly greater understanding of weather and climate distinctions after instruction, even after accounting for students' prior knowledge (Lombardi & Sinatra, 2010). In a follow-up study with inservice science and preservice elementary teachers, we showed that anger about the topic of climate change and teaching about climate change was significantly related to implausible perceptions about human-induced climate change (Lombardi & Sinatra, 2011). Results from our recent studies helped to inform our development of a model of the role of plausibility judgments in conceptual change situations. The model applies to situations involving cognitive dissonance, where background knowledge conflicts with an incoming message. In such situations, we define plausibility as a judgment on the relative potential truthfulness of incoming information compared to one's existing mental representations (Rescher, 1976). Students may not consciously think when making plausibility judgments, expending only minimal mental effort in what is referred to as an automatic cognitive process (Stanovich, 2009). However, well-designed instruction could facilitate students' reappraisal of plausibility judgments in more effortful and conscious cognitive processing. Critical evaluation specifically may be one effective method to promote plausibility reappraisal in a classroom setting (Lombardi & Sinatra, in progress). In science education, critical evaluation involves the analysis of how evidentiary data support a hypothesis and its alternatives. The presentation will focus on how instruction promoting critical evaluation can encourage individuals to reappraise their plausibility judgments and initiate knowledge reconstruction. In a recent pilot study, teachers experienced an instructional scaffold promoting critical evaluation of two competing climate change theories (i.e., human-induced and increasing solar irradiance) and significantly changed both their plausibility judgments and perceptions of correctness toward the scientifically-accepted model of human-induced climate change. A comparison group of teachers who did not experience the critical evaluation activity showed no significant change. The implications of these studies for future research and instruction will be discussed in the presentation, including effective ways to increase students' and teachers' ability to be critically evaluative and reappraise their plausibility judgments. With controversial science issues, such as climate change, such abilities may be necessary to facilitate conceptual change.

The second Southern African Bird Atlas Project: Causes and consequences of geographical sampling bias.

PubMed

Hugo, Sanet; Altwegg, Res

2017-09-01

Using the Southern African Bird Atlas Project (SABAP2) as a case study, we examine the possible determinants of spatial bias in volunteer sampling effort and how well such biased data represent environmental gradients across the area covered by the atlas. For each province in South Africa, we used generalized linear mixed models to determine the combination of variables that explain spatial variation in sampling effort (number of visits per 5' × 5' grid cell, or "pentad"). The explanatory variables were distance to major road and exceptional birding locations or "sampling hubs," percentage cover of protected, urban, and cultivated area, and the climate variables mean annual precipitation, winter temperatures, and summer temperatures. Further, we used the climate variables and plant biomes to define subsets of pentads representing environmental zones across South Africa, Lesotho, and Swaziland. For each environmental zone, we quantified sampling intensity, and we assessed sampling completeness with species accumulation curves fitted to the asymptotic Lomolino model. Sampling effort was highest close to sampling hubs, major roads, urban areas, and protected areas. Cultivated area and the climate variables were less important. Further, environmental zones were not evenly represented by current data and the zones varied in the amount of sampling required representing the species that are present. SABAP2 volunteers' preferences in birding locations cause spatial bias in the dataset that should be taken into account when analyzing these data. Large parts of South Africa remain underrepresented, which may restrict the kind of ecological questions that may be addressed. However, sampling bias may be improved by directing volunteers toward undersampled regions while taking into account volunteer preferences.

Applying Corporate Climate Principles to Dental School Operations.

PubMed

Robinson, Michelle A; Reddy, Michael S

2016-12-01

Decades of research have shown that organizational climate has the potential to form the basis of workplace operations and impact an organization's performance. Culture is related to climate but is not the same. "Culture" is the broader term, defining how things are done in an organization, while "climate" is a component of culture that describes how people perceive their environment. Climate can be changed but requires substantial effort over time by management and the workforce. Interest has recently grown in culture and climate in dental education due to the humanistic culture accreditation standard. The aim of this study was to use corporate climate principles to examine how organizational culture and, subsequently, workplace operations can be improved through specific strategic efforts in a U.S. dental school. The school's parent institution initiated a climate survey that the dental school used with qualitative culture data to drive strategic planning and change in the school. Administration of the same survey to faculty and staff members three times over a six-year period showed significant changes to the school's climate occurred as a new strategic plan was implemented that focused on reforming areas of weakness. Concentrated efforts in key areas in the strategic plan resulted in measurable improvements in climate perception. The study discovered that culture was an area previously overlooked but explicitly linked to the success of the organization.

Species distribution modelling for conservation of an endangered endemic orchid

PubMed Central

Wang, Hsiao-Hsuan; Wonkka, Carissa L.; Treglia, Michael L.; Grant, William E.; Smeins, Fred E.; Rogers, William E.

2015-01-01

Concerns regarding the long-term viability of threatened and endangered plant species are increasingly warranted given the potential impacts of climate change and habitat fragmentation on unstable and isolated populations. Orchidaceae is the largest and most diverse family of flowering plants, but it is currently facing unprecedented risks of extinction. Despite substantial conservation emphasis on rare orchids, populations continue to decline. Spiranthes parksii (Navasota ladies' tresses) is a federally and state-listed endangered terrestrial orchid endemic to central Texas. Hence, we aimed to identify potential factors influencing the distribution of the species, quantify the relative importance of each factor and determine suitable habitat for future surveys and targeted conservation efforts. We analysed several geo-referenced variables describing climatic conditions and landscape features to identify potential factors influencing the likelihood of occurrence of S. parksii using boosted regression trees. Our model classified 97 % of the cells correctly with regard to species presence and absence, and indicated that probability of existence was correlated with climatic conditions and landscape features. The most influential variables were mean annual precipitation, mean elevation, mean annual minimum temperature and mean annual maximum temperature. The most likely suitable range for S. parksii was the eastern portions of Leon and Madison Counties, the southern portion of Brazos County, a portion of northern Grimes County and along the borders between Burleson and Washington Counties. Our model can assist in the development of an integrated conservation strategy through: (i) focussing future survey and research efforts on areas with a high likelihood of occurrence, (ii) aiding in selection of areas for conservation and restoration and (iii) framing future research questions including those necessary for predicting responses to climate change. Our model could also incorporate new information on S. parksii as it becomes available to improve prediction accuracy, and our methodology could be adapted to develop distribution maps for other rare species of conservation concern. PMID:25900746

Species distribution modelling for conservation of an endangered endemic orchid.

PubMed

Wang, Hsiao-Hsuan; Wonkka, Carissa L; Treglia, Michael L; Grant, William E; Smeins, Fred E; Rogers, William E

2015-04-21

Concerns regarding the long-term viability of threatened and endangered plant species are increasingly warranted given the potential impacts of climate change and habitat fragmentation on unstable and isolated populations. Orchidaceae is the largest and most diverse family of flowering plants, but it is currently facing unprecedented risks of extinction. Despite substantial conservation emphasis on rare orchids, populations continue to decline. Spiranthes parksii (Navasota ladies' tresses) is a federally and state-listed endangered terrestrial orchid endemic to central Texas. Hence, we aimed to identify potential factors influencing the distribution of the species, quantify the relative importance of each factor and determine suitable habitat for future surveys and targeted conservation efforts. We analysed several geo-referenced variables describing climatic conditions and landscape features to identify potential factors influencing the likelihood of occurrence of S. parksii using boosted regression trees. Our model classified 97 % of the cells correctly with regard to species presence and absence, and indicated that probability of existence was correlated with climatic conditions and landscape features. The most influential variables were mean annual precipitation, mean elevation, mean annual minimum temperature and mean annual maximum temperature. The most likely suitable range for S. parksii was the eastern portions of Leon and Madison Counties, the southern portion of Brazos County, a portion of northern Grimes County and along the borders between Burleson and Washington Counties. Our model can assist in the development of an integrated conservation strategy through: (i) focussing future survey and research efforts on areas with a high likelihood of occurrence, (ii) aiding in selection of areas for conservation and restoration and (iii) framing future research questions including those necessary for predicting responses to climate change. Our model could also incorporate new information on S. parksii as it becomes available to improve prediction accuracy, and our methodology could be adapted to develop distribution maps for other rare species of conservation concern. Published by Oxford University Press on behalf of the Annals of Botany Company.

Visions 2025 and Linkage to NEXT

NASA Technical Reports Server (NTRS)

Wiscombe, W.; Lau, William K. M. (Technical Monitor)

2002-01-01

This talk will describe the progress to date on creating a science-driven vision for the NASA Earth Science Enterprise (ESE) in the post-2010 period. This effort began in the Fall of 2001 by organizing five science workgroups with representatives from NASA, academia and other agencies: Long-Term Climate, Medium-Term Climate, Extreme Weather, Biosphere & Ecosystems, and Solid Earth, Ice Sheets, & Sea Level. Each workgroup was directed to scope out one Big Question, including not just the science but the observational and modeling requirements, the information system requirements, and the applications and benefits to society. This first set of five Big Questions is now in hand and has been presented to the ESE Director. It includes: water resources, intraseasonal predictability, tropical cyclogenesis, invasive species, and sea level. Each of these topics will be discussed briefly. How this effort fits into the NEXT vision exercise and into Administrator O'Keefe's new vision for NASA will also be discussed.

Economic tools to promote transparency and comparability in the Paris Agreement

NASA Astrophysics Data System (ADS)

Aldy, Joseph; Pizer, William; Tavoni, Massimo; Reis, Lara Aleluia; Akimoto, Keigo; Blanford, Geoffrey; Carraro, Carlo; Clarke, Leon E.; Edmonds, James; Iyer, Gokul C.; McJeon, Haewon C.; Richels, Richard; Rose, Steven; Sano, Fuminori

2016-11-01

The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years. An important policy task will be to assess and compare these contributions. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.

Socioemotional self-perceptions, family climate, and hopeful thinking among students with learning disabilities and typically achieving students from the same classes.

PubMed

Idan, Orly; Margalit, Malka

2014-01-01

This study aimed at examining the adjustment of students with learning disabilities (LD) and at exploring the mediating role of hope. By means of a multidimensional approach, the interactions between risk and protective factors emerging from internal and external resources among 856 high school students (10th to 12th grades) were analyzed. A total of 529 typically achieving students and 327 students with LD attending general education classes in seven high schools completed seven instruments measuring sense of coherence, basic psychological needs, loneliness, family climate, hope, academic self-efficacy, and effort. The students' achievements in English, history, and mathematics were collected. The analysis used structural equation modeling, and the results emphasized the significant role of hope as a mediator between risk and protective factors and academic self-efficacy and its significance for students with and without LD in explaining achievements and effort investment.

A National Energy-Water System Assessment Framework (NEWS): Synopsis of Stage 1 Research Strategy and Results

NASA Astrophysics Data System (ADS)

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

2017-12-01

The focus of this talk is on climate adaptation and the reliability of power supply infrastructure when viewed through the lens of strategic water issues. Power supply is critically dependent upon water resources, particularly to cool thermoelectric plants, making the sector particularly sensitive to any shifts in the geography or seasonality of water supply. We report on results from an NSF-Funded Water Sustainability and Climate effort aimed at uncovering key energy and economic system vulnerabilities. We have developed the National Energy-Water System assessment framework (NEWS) to systematically evaluate: a) the performance of the nation's electricity sector under multiple climate scenarios; b) the feasibility of alternative pathways to improve climate adaptation; and, c) the impacts of energy technology and investment tradeoffs on the economic productivity, water availability and aquatic ecosystem condition. Our project combines core engineering and geophysical models (ReEDS [Regional Energy Deployment System], TP2M [Thermoelectric Power and Thermal Pollution], and WBM [Water Balance]) through unique digital "handshake" protocols that operate across different institutions and modeling platforms. Combined system outputs are fed into a regional-to-national scale economic input/output model to evaluate economic consequences of climate constraints, technology choices, and environmental regulation. The impact assessments in NEWS are carried out through a series of climate/energy policy scenario studies to 2050. We find that despite significant climate-water impacts on individual plants, the current US power supply infrastructure shows potential for adaptation to future climates by capitalizing on the size of regional power systems, grid configuration and improvements in thermal efficiencies. However, the magnitude and implications of climate-water impacts vary depending on the configuration of the future power sector. To evaluate future power supply performance, we model alternative electricity sector pathways in combination with varying climate-water conditions. Further, water-linked disruptions in electricity supply yield substantial impacts on regional economies yet system-level shocks can be attenuated through different technology mixes and infrastructure.

Projected Changes on the Global Surface Wave Drift Climate towards the END of the Twenty-First Century

NASA Astrophysics Data System (ADS)

Carrasco, Ana; Semedo, Alvaro; Behrens, Arno; Weisse, Ralf; Breivik, Øyvind; Saetra, Øyvind; Håkon Christensen, Kai

2016-04-01

The global wave-induced current (the Stokes Drift - SD) is an important feature of the ocean surface, with mean values close to 10 cm/s along the extra-tropical storm tracks in both hemispheres. Besides the horizontal displacement of large volumes of water the SD also plays an important role in the ocean mix-layer turbulence structure, particularly in stormy or high wind speed areas. The role of the wave-induced currents in the ocean mix-layer and in the sea surface temperature (SST) is currently a hot topic of air-sea interaction research, from forecast to climate ranges. The SD is mostly driven by wind sea waves and highly sensitive to changes in the overlaying wind speed and direction. The impact of climate change in the global wave-induced current climate will be presented. The wave model WAM has been forced by the global climate model (GCM) ECHAM5 wind speed (at 10 m height) and ice, for present-day and potential future climate conditions towards the end of the end of the twenty-first century, represented by the Intergovernmental Panel for Climate Change (IPCC) CMIP3 (Coupled Model Inter-comparison Project phase 3) A1B greenhouse gas emission scenario (usually referred to as a ''medium-high emissions'' scenario). Several wave parameters were stored as output in the WAM model simulations, including the wave spectra. The 6 hourly and 0.5°×0.5°, temporal and space resolution, wave spectra were used to compute the SD global climate of two 32-yr periods, representative of the end of the twentieth (1959-1990) and twenty-first (1969-2100) centuries. Comparisons of the present climate run with the ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-40 reanalysis are used to assess the capability of the WAM-ECHAM5 runs to produce realistic SD results. This study is part of the WRCP-JCOMM COWCLIP (Coordinated Ocean Wave Climate Project) effort.

Co-production and modeling landscape change - successes and challenges in developing useful climate science

NASA Astrophysics Data System (ADS)

Timm, K.; Reynolds, J.; Littell, J. S.; Murphy, K.; Euskirchen, E. S.; Breen, A. L.; Gray, S. T.; McGuire, A. D.; Rupp, S. T.

2017-12-01

Responding to the impacts of climate change and generating information that helps inform resource management requires exceptional communication and collaboration among researchers, managers, and other stakeholders. However, there is relatively little guidance on how to practically develop, facilitate, and evaluate this process given the highly specific and localized nature of many co-production efforts in terms of information needs, research questions, partners, and associated institutions. The Integrated Ecosystem Model (IEM) for Alaska and Northwest Canada was developed to understand how climate change influences interactions among disturbance (e.g. wildfire, thermokarst), permafrost, hydrology, and vegetation and identify how these changes affect valuable ecosystem services. The IEM was a unique co-production effort in that it was driven by broad management interests (rather than one research question), and because of the landscape-scale outputs, much broader engagement was warranted. Communication between the research team and the broader community of resource managers was facilitated by the Alaska Landscape Conservation Cooperatives and the Alaska Climate Science Center. Team members' reflections on the project confirm the importance of deliberate approaches to collaboration, where everyone has frequent opportunities to discuss goals, assumptions, and presumed outcomes of the project itself, as well as the elements of the process (i.e. meetings, reports, etc.). However, managing these activities requires significant time, resources, and perhaps more dedicated personnel. The lessons learned from the design and application of the IEM are highly relevant to researchers and land managers in other regions that are considering the development of a similar tool or an undertaking of similar magnitude, scale, and complexity.

Teaching Climate Social Science and Its Practices: A Two-Pronged Approach to Climate Literacy

NASA Astrophysics Data System (ADS)

Shwom, R.; Isenhour, C.; McCright, A.; Robinson, J.; Jordan, R.

2014-12-01

The Essential Principles of Climate Science Literacy states that a climate-literate individual can: "understand the essential principles of Earth's climate system, assess scientifically credible information about climate change, communicate about climate and climate change in a meaningful way, and make informed and responsible decisions with regard to actions that may affect climate." We argue that further integration of the social science dimensions of climate change will advance the climate literacy goals of communication and responsible actions. The underlying rationale for this argues: 1) teaching the habits of mind and scientific practices that have synergies across the social and natural sciences can strengthen students ability to understand and assess science in general and that 2) understanding the empirical research on the social, political, and economic processes (including climate science itself) that are part of the climate system is an important step for enabling effective action and communication. For example, while climate literacy has often identified the public's faulty mental models of climate processes as a partial explanation of complacency, emerging research suggests that the public's mental models of the social world are equally or more important in leading to informed and responsible climate decisions. Building student's ability to think across the social and natural sciences by understanding "how we know what we know" through the sciences and a scientific understanding of the social world allows us to achieve climate literacy goals more systematically and completely. To enable this integration we first identify the robust social science insights for the climate science literacy principles that involve social systems. We then briefly identify significant social science contributions to climate science literacy that do not clearly fit within the seven climate literacy principles but arguably could advance climate literacy goals. We conclude with suggestions on how the identified social science insights could be integrated into climate literacy efforts.

Climate-chemical interactions and effects of changing atmospheric trace gases

NASA Technical Reports Server (NTRS)

Ramanathan, V.; Callis, L.; Cess, R.; Hansen, J.; Isaksen, I.

1987-01-01

The paper considers trace gas-climate effects including the greenhouse effect of polyatomic trace gases, the nature of the radiative-chemical interactions, and radiative-dynamical interactions in the stratosphere, and the role of these effects in governing stratospheric climate change. Special consideration is given to recent developments in the investigations of the role of oceans in governing the transient climate responses, and a time-dependent estimate of the potential trace gas warming from the preindustrial era to the early 21st century. The importance of interacting modeling and observational efforts is emphasized. One of the problems remaining on the observational front is the lack of certainty in current estimates of the rate of growth of CO, O3, and NOx; the primary challenge is the design of a strategy that will minimize the sampling errors.

Towards Improving Sea Ice Predictabiity: Evaluating Climate Models Against Satellite Sea Ice Observations

NASA Astrophysics Data System (ADS)

Stroeve, J. C.

2014-12-01

The last four decades have seen a remarkable decline in the spatial extent of the Arctic sea ice cover, presenting both challenges and opportunities to Arctic residents, government agencies and industry. After the record low extent in September 2007 effort has increased to improve seasonal, decadal-scale and longer-term predictions of the sea ice cover. Coupled global climate models (GCMs) consistently project that if greenhouse gas concentrations continue to rise, the eventual outcome will be a complete loss of the multiyear ice cover. However, confidence in these projections depends o HoHoweon the models ability to reproduce features of the present-day climate. Comparison between models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 5 (CMIP5) and observations of sea ice extent and thickness show that (1) historical trends from 85% of the model ensemble members remain smaller than observed, and (2) spatial patterns of sea ice thickness are poorly represented in most models. Part of the explanation lies with a failure of models to represent details of the mean atmospheric circulation pattern that governs the transport and spatial distribution of sea ice. These results raise concerns regarding the ability of CMIP5 models to realistically represent the processes driving the decline of Arctic sea ice and to project the timing of when a seasonally ice-free Arctic may be realized. On shorter time-scales, seasonal sea ice prediction has been challenged to predict the sea ice extent from Arctic conditions a few months to a year in advance. Efforts such as the Sea Ice Outlook (SIO) project, originally organized through the Study of Environmental Change (SEARCH) and now managed by the Sea Ice Prediction Network project (SIPN) synthesize predictions of the September sea ice extent based on a variety of approaches, including heuristic, statistical and dynamical modeling. Analysis of SIO contributions reveals that when the September sea ice extent is near the long-term trend, contributions tend to be accurate. Years when the observed extent departs from the trend have proven harder to predict. Predictability skill does not appear to be more accurate for dynamical models over statistical ones, nor is there a measurable improvement in skill as the summer progresses.

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

NASA Astrophysics Data System (ADS)

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

2002-05-01

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

Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers.

PubMed

Avise, Jeremy; Abraham, Rodrigo Gonzalez; Chung, Serena H; Chen, Jack; Lamb, Brian; Salathé, Eric P; Zhang, Yongxin; Nolte, Christopher G; Loughlin, Daniel H; Guenther, Alex; Wiedinmyer, Christine; Duhl, Tiffany

2012-09-01

The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB). We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

Evaluating the impact of climate policies on regional food availability and accessibility using an Integrated Assessment Model

NASA Astrophysics Data System (ADS)

Gilmore, E.; Cui, Y. R.; Waldhoff, S.

2015-12-01

Beyond 2015, eradicating hunger will remain a critical part of the global development agenda through the Sustainable Development Goals (SDG). Efforts to limit climate change through both mitigation of greenhouse gas emissions and land use policies may interact with food availability and accessibility in complex and unanticipated ways. Here, we develop projections of regional food accessibility to 2050 under the alternative futures outlined by the Shared Socioeconomic Pathways (SSPs) and under different climate policy targets and structures. We use the Global Change Assessment Model (GCAM), an integrated assessment model (IAM), for our projections. We calculate food access as the weighted average of consumption of five staples and the portion of income spend on those commodities and extend the GCAM calculated universal global producer price to regional consumer prices drawing on historical relationships of these prices. Along the SSPs, food access depends largely on expectations of increases in population and economic status. Under a more optimistic scenario, the pressures on food access from increasing demand and rising prices can be counterbalanced by faster economic development. Stringent climate policies that increase commodity prices, however, may hinder vulnerable regions, namely Sub-Saharan Africa, from achieving greater food accessibility.

Climate-driven endemic cholera is modulated by human mobility in a megacity

NASA Astrophysics Data System (ADS)

Perez-Saez, Javier; King, Aaron A.; Rinaldo, Andrea; Yunus, Mohammad; Faruque, Abu S. G.; Pascual, Mercedes

2017-10-01

Although a differential sensitivity of cholera dynamics to climate variability has been reported in the spatially heterogeneous megacity of Dhaka, Bangladesh, the specific patterns of spread of the resulting risk within the city remain unclear. We build on an established probabilistic spatial model to investigate the importance and role of human mobility in modulating spatial cholera transmission. Mobility fluxes were inferred using a straightforward and generalizable methodology that relies on mapping population density based on a high resolution urban footprint product, and a parameter-free human mobility model. In accordance with previous findings, we highlight the higher sensitivity to the El Niño Southern Oscillation (ENSO) in the highly populated urban center than in the more rural periphery. More significantly, our results show that cholera risk is largely transmitted from the climate-sensitive core to the periphery of the city, with implications for the planning of control efforts. In addition, including human mobility improves the outbreak prediction performance of the model with an 11 month lead. The interplay between climatic and human mobility factors in cholera transmission is discussed from the perspective of the rapid growth of megacities across the developing world.

A Simple Exploration of Complexity at the Climate-Weather-Social-Conflict Nexus

NASA Astrophysics Data System (ADS)

Shaw, M.

2017-12-01

The conceptualization, exploration, and prediction of interplay between climate, weather, important resources, and social and economic - so political - human behavior is cast, and analyzed, in terms familiar from statistical physics and nonlinear dynamics. A simple threshold toy model is presented which emulates human tendencies to either actively engage in responses deriving, in part, from environmental circumstances or to maintain some semblance of status quo, formulated based on efforts drawn from the sociophysics literature - more specifically vis a vis a model akin to spin glass depictions of human behavior - with threshold/switching of individual and collective dynamics influenced by relatively more detailed weather and land surface model (hydrological) analyses via a land data assimilation system (a custom rendition of the NASA GSFC Land Information System). Parameters relevant to human systems' - e.g., individual and collective switching - sensitivity to hydroclimatology are explored towards investigation of overall system behavior; i.e., fixed points/equilibria, oscillations, and bifurcations of systems composed of human interactions and responses to climate and weather through, e.g., agriculture. We discuss implications in terms of conceivable impacts of climate change and associated natural disasters on socioeconomics, politics, and power transfer, drawing from relatively recent literature concerning human conflict.

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

NASA Astrophysics Data System (ADS)

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

2018-01-01

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG) emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model - Storm Water Management Model - was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020-2040 compared to the volume in 1971-2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. This study highlights the importance of accounting for local adaptation when coping with future urban floods.

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

DOE PAGES

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

2018-01-15

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG)more » emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model – Storm Water Management Model – was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020–2040 compared to the volume in 1971–2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. Furthermore, this study highlights the importance of accounting for local adaptation when coping with future urban floods.« less

Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

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

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG)more » emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model – Storm Water Management Model – was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020–2040 compared to the volume in 1971–2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. Furthermore, this study highlights the importance of accounting for local adaptation when coping with future urban floods.« less

The Climate Literacy Network: Leveraging a Diverse Community to Broaden the Reach of Your Climate Literacy Efforts

NASA Astrophysics Data System (ADS)

Ledley, T. S.; Carley, S.; Niepold, F.; Duggan-Haas, D. A.; Hollweg, K.; McCaffrey, M. S.

2012-12-01

There are a wide range of programs, activities, and projects focused on improving the understanding of climate science by citizens in a multitude of contexts. While most of these are necessarily customized for the particular audiences, communities, or regions they address, they can learn a lot from each other by sharing their experiences, expertise, and materials. The Climate Literacy Network (CLN, http://cleanet.org/cln), established in 2008 to facilitate the implementation of the Climate Literacy Essential Principles of Climate Science, is a diverse group of over 370 stakeholders with a wide range of expertise in, for example, science, policy, media, arts, economics, psychology, education, and social sciences. The CLN meets virtually weekly to share information about ongoing activities and new resources, discuss controversial public issues and ways to address them, get input from this diverse community on directions individual efforts might take, organize climate literacy sessions at professional meetings, provide input on documents relevant to climate literacy, and address common needs of the individual members. The weekly CLN teleconferences are also a venue for presentations from climate change education efforts to extend their reach and potential impact. The teleconferences are supported by an active listserv that is archived on the CLN website along with recordings of past teleconference and the schedule of upcoming teleconferences (http://cleanet.org/clean/community/cln/telecon_schedule.html). In this presentation we will describe the details of these various activities, give examples of how discussions within the CLN has led to funded efforts and expanded partnerships, and identify ways you can participate in and leverage this very active community.

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.

Development of a Cloud Resolving Model for Heterogeneous Supercomputers

NASA Astrophysics Data System (ADS)

Sreepathi, S.; Norman, M. R.; Pal, A.; Hannah, W.; Ponder, C.

2017-12-01

A cloud resolving climate model is needed to reduce major systematic errors in climate simulations due to structural uncertainty in numerical treatments of convection - such as convective storm systems. This research describes the porting effort to enable SAM (System for Atmosphere Modeling) cloud resolving model on heterogeneous supercomputers using GPUs (Graphical Processing Units). We have isolated a standalone configuration of SAM that is targeted to be integrated into the DOE ACME (Accelerated Climate Modeling for Energy) Earth System model. We have identified key computational kernels from the model and offloaded them to a GPU using the OpenACC programming model. Furthermore, we are investigating various optimization strategies intended to enhance GPU utilization including loop fusion/fission, coalesced data access and loop refactoring to a higher abstraction level. We will present early performance results, lessons learned as well as optimization strategies. The computational platform used in this study is the Summitdev system, an early testbed that is one generation removed from Summit, the next leadership class supercomputer at Oak Ridge National Laboratory. The system contains 54 nodes wherein each node has 2 IBM POWER8 CPUs and 4 NVIDIA Tesla P100 GPUs. This work is part of a larger project, ACME-MMF component of the U.S. Department of Energy(DOE) Exascale Computing Project. The ACME-MMF approach addresses structural uncertainty in cloud processes by replacing traditional parameterizations with cloud resolving "superparameterization" within each grid cell of global climate model. Super-parameterization dramatically increases arithmetic intensity, making the MMF approach an ideal strategy to achieve good performance on emerging exascale computing architectures. The goal of the project is to integrate superparameterization into ACME, and explore its full potential to scientifically and computationally advance climate simulation and prediction.

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.

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.

ELICITED EXPERT PERCEPTIONS FOR CLIMATE CHANGE RISKS AND ADAPTATION IN AGRICULTURE AND FOOD PRODUCTION THROUGH MENTAL MODELS APPROACH

NASA Astrophysics Data System (ADS)

Suda, Eiko; Kubota, Hiromi; Baba, Kenshi; Hijioka, Yasuaki; Takahashi, Kiyoshi; Hanasaki, Naota

Impacts of climate change have become obvious in agriculture and food production in Japan these days, and researches to adapt to their risks have been conducted as a key effort to cope with the climate change. Numerous scientific findings on climate change impacts have been presented so far; however, prospective risks to be adapted to and their management in the context of individual on-site situations have not been investigated in detail. The structure of climate change risks and their management vary depending on geographical and social features in the regions where the adaptation options should be applied; therefore, a practical adaptation strategy should consider actual on-site situations. This study intended to clarify climate change risks to be adapted to in the Japanese agricultural sector, and factors to be considered in adaptation options, for encouragement of decision-making on adaptation implementation in the field. Semi-structured individual interviews have been conducted with 9 multidisciplinary experts engaging in climate change impacts research in agricultural production, economics, engineering, policy, and so on. Based on the results of the interviews, and the latest literatures available for risk assessment and adaptation, an expert mental model including their perceptions which cover the process from climate change impacts assessment to adaptation has been developed. The prospective risks, adaptation options, and issues to be examined to progress the development of practical and effective adaptation options and to support individual or social decision-making, have been shown on the developed expert mental model. It is the basic information for developing social communication and stakeholders cooperations in climate change adaptation strategies in agriculture and food production in Japan.

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 Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Einaudi, Franco (Technical Monitor)

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution better than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have first images that demonstrate the most innovative capability from EOS Terra 5 instruments: MODIS - 1.37 micron cirrus cloud channel; 250m daily coverage for clouds and vegetation change; 7 solar channels for land and aerosol studies; new fire channels; Chlorophyll fluorescence; MISR - first 9 multi angle views of clouds and vegetation; MOPITT - first global CO maps and C114 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution smaller than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have some first images that demonstrate the most innovative capability from EOS Terra: MODIS - 1.37 microns cirrus channel; 250 m daily cover for clouds and vegetation change; 7 solar channels for land and aerosol; new fire channels; Chlorophyll fluorescence; MISR - 9 multi angle views of clouds and vegetation; MOPITT - Global CO maps and CH4 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

Seeing through the Smoke: A collaborative, multidisciplinary effort to address the interplay between wildfire, climate, air quality, and health

NASA Astrophysics Data System (ADS)

Brey, S. J.; Fischer, E. V.; Pierce, J. R.; Ford, B.; Lassman, W.; Pfister, G.; Volckens, J.; Gan, R.; Magzamen, S.; Barnes, E. A.

2015-12-01

Exposure to wildfire smoke plumes represents an episodic, uncertain, and potentially growing threat to public health in the western United States. The area burned by wildfires in this region has increased over recent decades, and the future of fires within this region is largely unknown. Future fire emissions are intimately linked to future meteorological conditions, which are uncertain due to the variability of climate model outputs and differences between representative concentration pathways (RCP) scenarios. We know that exposure to wildfire smoke is harmful, particularly for vulnerable populations. However the literature on the heath effects of wildfire smoke exposure is thin, particularly when compared to the depth of information we have on the effects of exposure to smoke of anthropogenic origin. We are exploring the relationships between climate, fires, air quality and public health through multiple interdisciplinary collaborations. We will present several examples from these projects including 1) an analysis of the influence of fire on ozone abundances over the United States, and 2) efforts to use a high-resolution weather forecasting model to nail down exposure within specific smoke plumes. We will also highlight how our team works together. This discussion will include examples of the university structure that facilitates our current collaborations, and the lessons we have learned by seeking stakeholder input to make our science more useful.

Co-producing simulation models to inform resource management: a case study from southwest South Dakota

USGS Publications Warehouse

Miller, Brian W.; Symstad, Amy J.; Frid, Leonardo; Fisichelli, Nicholas A.; Schuurman, Gregor W.

2017-01-01

Simulation models can represent complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond to different scenarios. However, simulation models have limited relevance to real-world applications when designed without input from people who could use the simulated scenarios to inform their decisions. Here, we report on a state-and-transition simulation model of vegetation dynamics that was coupled to a scenario planning process and co-produced by researchers, resource managers, local subject-matter experts, and climate change adaptation specialists to explore potential effects of climate scenarios and management alternatives on key resources in southwest South Dakota. Input from management partners and local experts was critical for representing key vegetation types, bison and cattle grazing, exotic plants, fire, and the effects of climate change and management on rangeland productivity and composition given the paucity of published data on many of these topics. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between grazer density and vegetation composition, as well as between the short- and long-term costs of invasive species management. It also pointed to impactful uncertainties related to the effects of fire and grazing on vegetation. More broadly, a scenario-based approach to model co-production bracketed the uncertainty associated with climate change and ensured that the most important (and impactful) uncertainties related to resource management were addressed. This cooperative study demonstrates six opportunities for scientists to engage users throughout the modeling process to improve model utility and relevance: (1) identifying focal dynamics and variables, (2) developing conceptual model(s), (3) parameterizing the simulation, (4) identifying relevant climate scenarios and management alternatives, (5) evaluating and refining the simulation, and (6) interpreting the results. We also reflect on lessons learned and offer several recommendations for future co-production efforts, with the aim of advancing the pursuit of usable science.

Assessing Impact of Aerosol Intercontinental Transport on Regional Air Quality and Climate: What Satellites Can Help

NASA Technical Reports Server (NTRS)

Yu, Hongbin

2011-01-01

Mounting evidence for intercontinental transport of aerosols suggests that aerosols from a region could significantly affect climate and air quality in downwind regions and continents. Current assessment of these impacts for the most part has been based on global model simulations that show large variability. The aerosol intercontinental transport and its influence on air quality and climate involve many processes at local, regional, and intercontinental scales. There is a pressing need to establish modeling systems that bridge the wide range of scales. The modeling systems need to be evaluated and constrained by observations, including satellite measurements. Columnar loadings of dust and combustion aerosols can be derived from the MODIS and MISR measurements of total aerosol optical depth and particle size and shape information. Characteristic transport heights of dust and combustion aerosols can be determined from the CALIPSO lidar and AIRS measurements. CALIPSO liar and OMI UV technique also have a unique capability of detecting aerosols above clouds, which could offer some insights into aerosol lofting processes and the importance of above-cloud transport pathway. In this presentation, I will discuss our efforts of integrating these satellite measurements and models to assess the significance of intercontinental transport of dust and combustion aerosols on regional air quality and climate.

From Risk Towards Resilience: Assessing Vulnerability and Adaptability to Climate Change in the Mekong Delta

NASA Astrophysics Data System (ADS)

Ling, F. H.; Yasuhara, K.; Tamura, M.; Tabayashi, Y.

2012-12-01

While efforts to mainstream climate adaptation have only begun in recent years, many developing regions are already taking measures to proof themselves from various natural disasters, including storm surges, flooding, land subsidence, and erosion. In the Asia-Pacific region, one of the most vulnerable in the world, climate resilience is urgently needed due to sea level rise and the increasing frequency and intensity of climate events. Yet, many regions and communities are unprepared due to insufficient awareness of disaster risks. In order to utilize the science of the changing environment more effectively, there is a critical need to understand the social context and perception of those who are affected by climate change. Using the Mekong Delta region in Vietnam as an example, we discuss our current efforts to develop a vulnerability and adaptation index for building climate resilience in the Asia-Pacific Region. A survey of current adaptation efforts in this region will be shown and preliminary findings from our survey to understand the perception of disaster risk in this region will be discussed.

Overcoming scepticism: Interacting influences of geographical location on perceived climate change adaptation measures to water resources in Spain

NASA Astrophysics Data System (ADS)

Iglesias, Ana; Garrote, Luis; Bardaji, Isabel; Iglesias, Pedro; Granados, Alfredo

2016-04-01

Though many climate adaptation efforts attempt to be defined with the participation of local communities, these strategies may be ineffective because among citizens affected equally, a local risk perception rather than scientific understanding largely drives adaptation choices. Further, the geographical location may polarize climate risk perceptions, making some adaptation efforts ineffective among sceptics. This study examines how the local degradation of the environment and water resources relates to adaption choices and in turn, climate change risk perception among a range of citizens in the Tagus basin, Spain (n = 300). We find respondents of less degraded areas have individualistic responses, and are significantly less likely to accept adaptation strategies than respondents in water stressed communities. The interaction between climate knowledge and adaptation choices is positively related to acceptance of adaptation choices in both groups, and had a stronger positive relationship among individualists. There is no statistical difference in acceptance of adaptation between individualists and communitarians at high levels of knowledge (top decile). Thus, education efforts specific to climate change may counteract divisions based geographical location and environmental stress.

Final Report for UW-Madison Portion of DE-SC0005301, "Collaborative Project: Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate"

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

Vimont, Daniel

This project funded two efforts at understanding the interactions between Central Pacific ENSO events, the mid-latitude atmosphere, and decadal variability in the Pacific. The first was an investigation of conditions that lead to Central Pacific (CP) and East Pacific (EP) ENSO events through the use of linear inverse modeling with defined norms. The second effort was a modeling study that combined output from the National Center for Atmospheric Research (NCAR) Community Atmospheric Model (CAM4) with the Battisti (1988) intermediate coupled model. The intent of the second activity was to investigate the relationship between the atmospheric North Pacific Oscillation (NPO), themore » Pacific Meridional Mode (PMM), and ENSO. These two activities are described herein.« less

Adapting to rates versus amounts of climate change: a case of adaptation to sea-level rise

NASA Astrophysics Data System (ADS)

Shayegh, Soheil; Moreno-Cruz, Juan; Caldeira, Ken

2016-10-01

Adaptation is the process of adjusting to climate change in order to moderate harm or exploit beneficial opportunities associated with it. Most adaptation strategies are designed to adjust to a new climate state. However, despite our best efforts to curtail greenhouse gas emissions, climate is likely to continue changing far into the future. Here, we show how considering rates of change affects the projected optimal adaptation strategy. We ground our discussion with an example of optimal investment in the face of continued sea-level rise, presenting a quantitative model that illustrates the interplay among physical and economic factors governing coastal development decisions such as rate of sea-level rise, land slope, discount rate, and depreciation rate. This model shows that the determination of optimal investment strategies depends on taking into account future rates of sea-level rise, as well as social and political constraints. This general approach also applies to the development of improved strategies to adapt to ongoing trends in temperature, precipitation, and other climate variables. Adaptation to some amount of change instead of adaptation to ongoing rates of change may produce inaccurate estimates of damages to the social systems and their ability to respond to external pressures.

Modelling effects of geoengineering options in response to climate change and global warming: implications for coral reefs.

PubMed

Crabbe, M J C

2009-12-01

Climate change will have serious effects on the planet and on its ecosystems. Currently, mitigation efforts are proving ineffectual in reducing anthropogenic CO2 emissions. Coral reefs are the most sensitive ecosystems on the planet to climate change, and here we review modelling a number of geoengineering options, and their potential influence on coral reefs. There are two categories of geoengineering, shortwave solar radiation management and longwave carbon dioxide removal. The first set of techniques only reduce some, but not all, effects of climate change, while possibly creating other problems. They also do not affect CO2 levels and therefore fail to address the wider effects of rising CO2, including ocean acidification, important for coral reefs. Solar radiation is important to coral growth and survival, and solar radiation management is not in general appropriate for this ecosystem. Longwave carbon dioxide removal techniques address the root cause of climate change, rising CO2 concentrations, they have relatively low uncertainties and risks. They are worthy of further research and potential implementation, particularly carbon capture and storage, biochar, and afforestation methods, alongside increased mitigation of atmospheric CO2 concentrations.

The Carbon-Land Model Intercomparison Project (C-LAMP): A Model-Data Comparison System for Evaluation of Coupled Biosphere-Atmosphere Models

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

Hoffman, Forrest M; Randerson, Jim; Thornton, Peter E

2009-01-01

The need to capture important climate feebacks in general circulation models (GCMs) has resulted in new efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, now often referred to as Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results, suggesting that a more rigorous set of offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are warranted. The Carbon-Land Model Intercomparison Project (C-LAMP) providesmore » a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). C-LAMP provides feedback to the modeling community regarding model improvements and to the measurement community by suggesting new observational campaigns. C-LAMP Experiment 1 consists of a set of uncoupled simulations of terrestrial carbon models specifically designed to examine the ability of the models to reproduce surface carbon and energy fluxes at multiple sites and to exhibit the influence of climate variability, prescribed atmospheric carbon dioxide (CO{sub 2}), nitrogen (N) deposition, and land cover change on projections of terrestrial carbon fluxes during the 20th century. Experiment 2 consists of partially coupled simulations of the terrestrial carbon model with an active atmosphere model exchanging energy and moisture fluxes. In all experiments, atmospheric CO{sub 2} follows the prescribed historical trajectory from C{sup 4}MIP. In Experiment 2, the atmosphere model is forced with prescribed sea surface temperatures (SSTs) and corresponding sea ice concentrations from the Hadley Centre; prescribed CO{sub 2} is radiatively active; and land, fossil fuel, and ocean CO{sub 2} fluxes are advected by the model. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the Community Land Model version 3 (CLM3) in the Community Climate System Model version 3 (CCSM3): The CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons against Ameriflus site measurements, MODIS satellite observations, NOAA flask records, TRANSCOM inversions, and Free Air CO{sub 2} Enrichment (FACE) site measurements, and other datasets have been performed and are described in Randerson et al. (2009). The C-LAMP diagnostics package was used to validate improvements to CASA and CN for use in the next generation model, CLM4. It is hoped that this effort will serve as a prototype for an international carbon-cycle model benchmarking activity for models being used for the Inter-governmental Panel on Climate Change (IPCC) Fifth Assessment Report. More information about C-LAMP, the experimental protocol, performance metrics, output standards, and model-data comparisons from the CLM3-CASA and CLM3-CN models are available at http://www.climatemodeling.org/c-lamp.« less

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

NASA Astrophysics Data System (ADS)

Ocko, Ilissa B.; Ginoux, Paul A.

2017-04-01

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

Phenology research for natural resource management in the United States.

PubMed

Enquist, Carolyn A F; Kellermann, Jherime L; Gerst, Katharine L; Miller-Rushing, Abraham J

2014-05-01

Natural resource professionals in the United States recognize that climate-induced changes in phenology can substantially affect resource management. This is reflected in national climate change response plans recently released by major resource agencies. However, managers on-the-ground are often unclear about how to use phenological information to inform their management practices. Until recently, this was at least partially due to the lack of broad-based, standardized phenology data collection across taxa and geographic regions. Such efforts are now underway, albeit in very early stages. Nonetheless, a major hurdle still exists: phenology-linked climate change research has focused more on describing broad ecological changes rather than making direct connections to local to regional management concerns. To help researchers better design relevant research for use in conservation and management decision-making processes, we describe phenology-related research topics that facilitate "actionable" science. Examples include research on evolution and phenotypic plasticity related to vulnerability, the demographic consequences of trophic mismatch, the role of invasive species, and building robust ecological forecast models. Such efforts will increase phenology literacy among on-the-ground resource managers and provide information relevant for short- and long-term decision-making, particularly as related to climate response planning and implementing climate-informed monitoring in the context of adaptive management. In sum, we argue that phenological information is a crucial component of the resource management toolbox that facilitates identification and evaluation of strategies that will reduce the vulnerability of natural systems to climate change. Management-savvy researchers can play an important role in reaching this goal.

Measuring Workplace Climate in Community Clinics and Health Centers.

PubMed

Friedberg, Mark W; Rodriguez, Hector P; Martsolf, Grant R; Edelen, Maria O; Vargas Bustamante, Arturo

2016-10-01

The effectiveness of community clinics and health centers' efforts to improve the quality of care might be modified by clinics' workplace climates. Several surveys to measure workplace climate exist, but their relationships to each other and to distinguishable dimensions of workplace climate are unknown. To assess the psychometric properties of a survey instrument combining items from several existing surveys of workplace climate and to generate a shorter instrument for future use. We fielded a 106-item survey, which included items from 9 existing instruments, to all clinicians and staff members (n=781) working in 30 California community clinics and health centers, receiving 628 responses (80% response rate). We performed exploratory factor analysis of survey responses, followed by confirmatory factor analysis of 200 reserved survey responses. We generated a new, shorter survey instrument of items with strong factor loadings. Six factors, including 44 survey items, emerged from the exploratory analysis. Two factors (Clinic Workload and Teamwork) were independent from the others. The remaining 4 factors (staff relationships, quality improvement orientation, managerial readiness for change, and staff readiness for change) were highly correlated, indicating that these represented dimensions of a higher-order factor we called "Clinic Functionality." This 2-level, 6-factor model fit the data well in the exploratory and confirmatory samples. For all but 1 factor, fewer than 20 survey responses were needed to achieve clinic-level reliability >0.7. Survey instruments designed to measure workplace climate have substantial overlap. The relatively parsimonious item set we identified might help target and tailor clinics' quality improvement efforts.

Climate change and vector-borne diseases: what are the implications for public health research and policy?

PubMed Central

Campbell-Lendrum, Diarmid; Manga, Lucien; Bagayoko, Magaran; Sommerfeld, Johannes

2015-01-01

Vector-borne diseases continue to contribute significantly to the global burden of disease, and cause epidemics that disrupt health security and cause wider socioeconomic impacts around the world. All are sensitive in different ways to weather and climate conditions, so that the ongoing trends of increasing temperature and more variable weather threaten to undermine recent global progress against these diseases. Here, we review the current state of the global public health effort to address this challenge, and outline related initiatives by the World Health Organization (WHO) and its partners. Much of the debate to date has centred on attribution of past changes in disease rates to climate change, and the use of scenario-based models to project future changes in risk for specific diseases. While these can give useful indications, the unavoidable uncertainty in such analyses, and contingency on other socioeconomic and public health determinants in the past or future, limit their utility as decision-support tools. For operational health agencies, the most pressing need is the strengthening of current disease control efforts to bring down current disease rates and manage short-term climate risks, which will, in turn, increase resilience to long-term climate change. The WHO and partner agencies are working through a range of programmes to (i) ensure political support and financial investment in preventive and curative interventions to bring down current disease burdens; (ii) promote a comprehensive approach to climate risk management; (iii) support applied research, through definition of global and regional research agendas, and targeted research initiatives on priority diseases and population groups. PMID:25688013

Measuring Workplace Climate in Community Clinics and Health Centers

PubMed Central

Friedberg, Mark W.; Rodriguez, Hector P.; Martsolf, Grant; Edelen, Maria Orlando; Vargas-Bustamante, Arturo

2018-01-01

Background The effectiveness of community clinics and health centers’ efforts to improve the quality of care might be modified by clinics’ workplace climates. Several surveys to measure workplace climate exist, but their relationships to each other and to distinguishable dimensions of workplace climate are unknown. Objective To assess the psychometric properties of a survey instrument combining items from several existing surveys of workplace climate and to generate a shorter instrument for future use. Methods We fielded a 106-item survey, which included items from 9 existing instruments, to all clinicians and staff members (n=781) working in 30 California community clinics and health centers, receiving 628 responses (80% response rate). We performed exploratory factor analysis of survey responses, followed by confirmatory factor analysis of 200 reserved survey responses. We generated a new, shorter survey instrument of items with strong factor loadings. Results Six factors, including 44 survey items, emerged from the exploratory analysis. Two factors (Clinic Workload and Teamwork) were independent from the others. The remaining 4 factors (Staff Relationships, Quality Improvement Orientation, Managerial Readiness for Change, and Staff Readiness for Change) were highly correlated, indicating that these represented dimensions of a higher-order factor we called “Clinic Functionality.” This two-level, six-factor model fit the data well in the exploratory and confirmatory samples. For all but one factor, fewer than 20 survey responses were needed to achieve clinic-level reliability >0.7. Conclusion Survey instruments designed to measure workplace climate have substantial overlap. The relatively parsimonious item set we identified might help target and tailor clinics’ quality improvement efforts. PMID:27326549

Data gathering and simulation of climate change impacts in mountainous areas

NASA Astrophysics Data System (ADS)

Bachelet, D.; Baker, B.; Hicke, J.; Conklin, D.; McKelvey, K.

2007-12-01

High mountains include species most at risk in a warming environment and are a critical link in the water supply chain for both human and natural systems. Scientists are monitoring and simulating these systems as snowpack depth changes, snowmelt timing changes, frozen soils melt and destabilize, and low elevation populations migrate upslope. Natural climate cycles and human activities interact with climate change trends and complicate the interpretation of the signal we observe. For ex. over the past 4 years in Yunnan (China), we documented that herbaceous alpine meadows are contracting as forest tree line advances and alpine shrub biomass increases. This is a result of interactions between human land use alteration and observed shifts in climate. In North America as snowpack decreases, wolverines and lynx denning conditions are jeopardized as human pressure reduces their extent. Coarse scale vegetation shift models using downscaled future climate scenarios fail to capture complex terrain features and microclimatic conditions that can either ensure critical habitat for the in-situ survival of threatened species or make things worse (ex. rockfalls) for climate migrants. Recent simulation efforts focus on high resolution models that address aspect, slope, soil types, and microclimate variations that affect local and migrating plants, their associated pollinators and insect herbivores, modifying habitat availability for birds and mammals

A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

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

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

Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). Formore » all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.« less

On the key role of droughts in the dynamics of summer fires in Mediterranean Europe.

PubMed

Turco, Marco; von Hardenberg, Jost; AghaKouchak, Amir; Llasat, Maria Carmen; Provenzale, Antonello; Trigo, Ricardo M

2017-03-06

Summer fires frequently rage across Mediterranean Europe, often intensified by high temperatures and droughts. According to the state-of-the-art regional fire risk projections, in forthcoming decades climate effects are expected to become stronger and possibly overcome fire prevention efforts. However, significant uncertainties exist and the direct effect of climate change in regulating fuel moisture (e.g. warmer conditions increasing fuel dryness) could be counterbalanced by the indirect effects on fuel structure (e.g. warmer conditions limiting fuel amount), affecting the transition between climate-driven and fuel-limited fire regimes as temperatures increase. Here we analyse and model the impact of coincident drought and antecedent wet conditions (proxy for the climatic factor influencing total fuel and fine fuel structure) on the summer Burned Area (BA) across all eco-regions in Mediterranean Europe. This approach allows BA to be linked to the key drivers of fire in the region. We show a statistically significant relationship between fire and same-summer droughts in most regions, while antecedent climate conditions play a relatively minor role, except in few specific eco-regions. The presented models for individual eco-regions provide insights on the impacts of climate variability on BA, and appear to be promising for developing a seasonal forecast system supporting fire management strategies.

Mass support for global climate agreements depends on institutional design.

PubMed

Bechtel, Michael M; Scheve, Kenneth F

2013-08-20

Effective climate mitigation requires international cooperation, and these global efforts need broad public support to be sustainable over the long run. We provide estimates of public support for different types of climate agreements in France, Germany, the United Kingdom, and the United States. Using data from a large-scale experimental survey, we explore how three key dimensions of global climate cooperation--costs and distribution, participation, and enforcement--affect individuals' willingness to support these international efforts. We find that design features have significant effects on public support. Specifically, our results indicate that support is higher for global climate agreements that involve lower costs, distribute costs according to prominent fairness principles, encompass more countries, and include a small sanction if a country fails to meet its emissions reduction targets. In contrast to well-documented baseline differences in public support for climate mitigation efforts, opinion responds similarly to changes in climate policy design in all four countries. We also find that the effects of institutional design features can bring about decisive changes in the level of public support for a global climate agreement. Moreover, the results appear consistent with the view that the sensitivity of public support to design features reflects underlying norms of reciprocity and individuals' beliefs about the potential effectiveness of specific agreements.

Climate Model Ensemble Methodology: Rationale and Challenges

NASA Astrophysics Data System (ADS)

Vezer, M. A.; Myrvold, W.

2012-12-01

A tractable model of the Earth's atmosphere, or, indeed, any large, complex system, is inevitably unrealistic in a variety of ways. This will have an effect on the model's output. Nonetheless, we want to be able to rely on certain features of the model's output in studies aiming to detect, attribute, and project climate change. For this, we need assurance that these features reflect the target system, and are not artifacts of the unrealistic assumptions that go into the model. One technique for overcoming these limitations is to study ensembles of models which employ different simplifying assumptions and different methods of modelling. One then either takes as reliable certain outputs on which models in the ensemble agree, or takes the average of these outputs as the best estimate. Since the Intergovernmental Panel on Climate Change's Fourth Assessment Report (IPCC AR4) modellers have aimed to improve ensemble analysis by developing techniques to account for dependencies among models, and to ascribe unequal weights to models according to their performance. The goal of this paper is to present as clearly and cogently as possible the rationale for climate model ensemble methodology, the motivation of modellers to account for model dependencies, and their efforts to ascribe unequal weights to models. The method of our analysis is as follows. We will consider a simpler, well-understood case of taking the mean of a number of measurements of some quantity. Contrary to what is sometimes said, it is not a requirement of this practice that the errors of the component measurements be independent; one must, however, compensate for any lack of independence. We will also extend the usual accounts to include cases of unknown systematic error. We draw parallels between this simpler illustration and the more complex example of climate model ensembles, detailing how ensembles can provide more useful information than any of their constituent models. This account emphasizes the epistemic importance of considering degrees of model dependence, and the practice of ascribing unequal weights to models of unequal skill.

Transient climate simulations of the deglaciation 21-9 thousand years before present; PMIP4 Core experiment design and boundary conditions

NASA Astrophysics Data System (ADS)

Ivanovic, Ruza; Gregoire, Lauren; Kageyama, Masa; Roche, Didier; Valdes, Paul; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev

2016-04-01

The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 thousand years. Here, we present the design of a coordinated Core simulation over the period 21-9 thousand years before present (ka) with time varying orbital forcing, greenhouse gases, ice sheets, and other geographical changes. A choice of two ice sheet reconstructions is given. Additional focussed simulations will also be coordinated on an ad-hoc basis by the working group, for example to investigate the effect of ice sheet and iceberg meltwater, and the uncertainty in other forcings. Some of these focussed simulations will concentrate on shorter durations around specific events to allow the more computationally expensive models to take part. Ivanovic, R. F., Gregoire, L. J., Kageyama, M., Roche, D. M., Valdes, P. J., Burke, A., Drummond, R., Peltier, W. R., and Tarasov, L.: Transient climate simulations of the deglaciation 21-9 thousand years before present; PMIP4 Core experiment design and boundary conditions, Geosci. Model Dev. Discuss., 8, 9045-9102, doi:10.5194/gmdd-8-9045-2015, 2015.

Translating climate data for business decisions

NASA Astrophysics Data System (ADS)

Steinberg, N.

2015-12-01

Businesses are bound to play an integral role in global and local climate change adaptation efforts, and integrating climate science into business decision-making can help protect companies' bottom-line and the communities which they depend upon. Yet many companies do not have good means to measure and manage climate risks. There are inherent limiting factors to incorporating climate data into existing operations and sourcing strategies. Spatial and temporal incongruities between climate and business models can make integration cumbersome. Even when such incongruities are resolved, raw climate data must undergo multiple transformations until the data is deemed actionable or otherwise translatable in dollar terms. However, the predictability of future impacts is advancing along with the use of second-order variables such as Cooling Degree Days and Water-Limited Crop productivity, helping business managers make better decisions about future energy and water demand requirements under the prospect of rising temperatures and more variable rainfall. This presentation will discuss the methods and opportunities for transforming raw climate data into business metrics. Results for the 2015 Corporate Adaptation Survey, led by Four Twenty Seven and in partnership with Notre Dame Global Adaptation Index, will also be presented to illustrate existing gaps between climate science and its application in the business context.

Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2016-02-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation-climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America - 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

Beyond scenario planning: projecting the future using models at Wind Cave National Park (USA)

NASA Astrophysics Data System (ADS)

King, D. A.; Bachelet, D. M.; Symstad, A. J.

2011-12-01

Scenario planning has been used by the National Park Service as a tool for natural resource management planning in the face of climate change. Sets of plausible but divergent future scenarios are constructed from available information and expert opinion and serve as starting point to derive climate-smart management strategies. However, qualitative hypotheses about how systems would react to a particular set of conditions assumed from coarse scale climate projections may lack the scientific rigor expected from a federal agency. In an effort to better assess the range of likely futures at Wind Cave National Park, a project was conceived to 1) generate high resolution historic and future climate time series to identify local weather patterns that may or may not persist, 2) simulate the hydrological cycle in this geologically varied landscape and its response to future climate, 3) project vegetation dynamics and ensuing changes in the biogeochemical cycles given grazing and fire disturbances under new climate conditions, and 4) synthesize and compare results with those from the scenario planning exercise. In this framework, we tested a dynamic global vegetation model against local information on vegetation cover, disturbance history and stream flow to better understand the potential resilience of these ecosystems to climate change. We discuss the tradeoffs between a coarse scale application of the model showing regional trends with limited ability to project the fine scale mosaic of vegetation at Wind Cave, and a finer scale approach that can account for local slope effects on water balance and better assess the vulnerability of landscape facets, but requires more intensive data acquisition. We elaborate on the potential for sharing information between models to mitigate the often-limited treatment of biological feedbacks in the physical representations of soil and atmospheric processes.

The fate of threatened coastal dune habitats in Italy under climate change scenarios.

PubMed

Prisco, Irene; Carboni, Marta; Acosta, Alicia T R

2013-01-01

Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an "indirect" plant-species-based one and a simple "direct" one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the "direct" approach was unsatisfactory, "indirect" models had a good predictive performance, highlighting the importance of using species' responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats' distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future.

The Fate of Threatened Coastal Dune Habitats in Italy under Climate Change Scenarios

PubMed Central

Prisco, Irene; Carboni, Marta; Acosta, Alicia T. R.

2013-01-01

Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an “indirect” plant-species-based one and a simple “direct” one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the “direct” approach was unsatisfactory, “indirect” models had a good predictive performance, highlighting the importance of using species’ responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats’ distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future. PMID:23874787

Interagency Collaboration in Support of Climate Change Education

NASA Astrophysics Data System (ADS)

Schoedinger, S. E.; Chambers, L. H.; Karsten, J. L.; McDougall, C.; Campbell, D.

2011-12-01

NASA, NOAA and NSF support climate change education (CCE) through their grant programs. As the agencies' investment in CCE has grown, coordination among the agencies has become increasingly important. Although the political landscape and budgets continue to change, the agencies are committed to continued coordination and collaboration. To date, this has taken the form of jointly hosted principal investigator (PI) meetings, the largest of which was held last February (see Eos Vol. 92, No. 24, 14 June 2011). The joint goals are: (1) increased collaboration among grantees and across programs; (2) building capacity among grantees in areas of mutual interest; (3) identification of gaps in investments to date; and (4) identification of opportunities for coordination of evaluation efforts. NOAA's primary funding opportunity for CCE projects is its Environmental Literacy Grant (ELG) Program. Although not exclusively focused on climate, there has been increased emphasis on this area since 2009. Through ELG, NOAA encourages the use of NOAA assets (data, facilities, educational resources, and people) in grantees' work. Thirty awards with a primary focus on CCE have been awarded to institutions of higher education, informal science education, and non-profit organizations involved in K-12 and informal/non-formal education. We anticipate this funding opportunity will continue to support the improvement of climate literacy among various audiences of learners in the future. NASA supported efforts in CCE in an ad hoc way for years. It became a focus area in 2008 with the launch of the NASA Global Climate Change Education (GCCE) Project. This project funded 57 awards in 2008-2010, the vast majority of them in teacher professional development, or use of data, models, or simulations. Beginning in FY11, NASA moved the project into the Minority University Research and Education Program. Fourteen awards were made to minority higher education institutions, non-profit organizations, and community colleges. These efforts are expected to continue in FY12 and beyond under NASA Innovations in Climate Education (NICE). A solicitation for the NICE project is currently anticipated in Summer 2012. Through its core programs, NSF supports a variety of efforts designed to improve teaching and learning about CCE in formal and informal settings, often through leveraging NSF-supported climate research. In 2009, dedicated CCE funding supported 10 new awards aimed at focusing NSF investments in key areas: preparing innovators for the workforce; strategies for scaling up and disseminating effective curricula and instructional resources; assessment of student learning of complex climate issues; and, increasing access to CCE and professional development for learners, educators, and policymakers. Phase I of the Climate Change Education Partnership (CCEP) program, launched in 2010, supports strategic planning activities within 15 regional and thematic partnerships that bring together climate scientists, learning scientists, and education practitioners. A solicitation for CCEP Phase II implementation is anticipated in Fall 2011. We will discuss agency funding opportunities, examples of collaborations, and common metrics/sharing tools for evaluation of CCE projects.

Information-computational platform for collaborative multidisciplinary investigations of regional climatic changes and their impacts

NASA Astrophysics Data System (ADS)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2013-04-01

Analysis of growing volume of related to climate change data from sensors and model outputs requires collaborative multidisciplinary efforts of researchers. To do it timely and in reliable way one needs in modern information-computational infrastructure supporting integrated studies in the field of environmental sciences. Recently developed experimental software and hardware platform Climate (http://climate.scert.ru/) provides required environment for regional climate change related investigations. The platform combines modern web 2.0 approach, GIS-functionality and capabilities to run climate and meteorological models, process large geophysical datasets and support relevant analysis. It also supports joint software development by distributed research groups, and organization of thematic education for students and post-graduate students. In particular, platform software developed includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also run of integrated into the platform WRF and «Planet Simulator» models, modeling results data preprocessing and visualization is provided. All functions of the platform are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of selection of geographical region of interest (pan and zoom), data layers manipulation (order, enable/disable, features extraction) and visualization of results. Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches. Using it even unskilled user without specific knowledge can perform reliable computational processing and visualization of large meteorological, climatic and satellite monitoring datasets through unified graphical web-interface. Partial support of RF Ministry of Education and Science grant 8345, SB RAS Program VIII.80.2 and Projects 69, 131, 140 and APN CBA2012-16NSY project is acknowledged.