Integrating Climate Information and Decision Processes for Regional Climate Resilience

NASA Astrophysics Data System (ADS)

Buizer, James; Goddard, Lisa; Guido, Zackry

2015-04-01

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

The Promise and Limitations of Using Analogies to Improve Decision-Relevant Understanding of Climate Change.

PubMed

Raimi, Kaitlin T; Stern, Paul C; Maki, Alexander

2017-01-01

To make informed choices about how to address climate change, members of the public must develop ways to consider established facts of climate science and the uncertainties about its future trajectories, in addition to the risks attendant to various responses, including non-response, to climate change. One method suggested for educating the public about these issues is the use of simple mental models, or analogies comparing climate change to familiar domains such as medical decision making, disaster preparedness, or courtroom trials. Two studies were conducted using online participants in the U.S.A. to test the use of analogies to highlight seven key decision-relevant elements of climate change, including uncertainties about when and where serious damage may occur, its unprecedented and progressive nature, and tradeoffs in limiting climate change. An internal meta-analysis was then conducted to estimate overall effect sizes across the two studies. Analogies were not found to inform knowledge about climate literacy facts. However, results suggested that people found the medical analogy helpful and that it led people-especially political conservatives-to better recognize several decision-relevant attributes of climate change. These effects were weak, perhaps reflecting a well-documented and overwhelming effect of political ideology on climate change communication and education efforts in the U.S.A. The potential of analogies and similar education tools to improve understanding and communication in a polarized political environment are discussed.

Farmers' climate information needs for long-term adaptive decisions: A case study of almonds in CA

NASA Astrophysics Data System (ADS)

Jagannathan, K. A.; Jones, A. D.; Pathak, T. B.; Kerr, A. C.; Doll, D.

2016-12-01

Despite advances in climate modeling and projections, several sources report that current tools and models are not widely used in the agriculture sector. Farmers, depending on their local context, require information on very specific climatic metrics such as start of rains during the planting season, number of low temperature days during the growing season, etc. However, such specific climatic information is either not available, and/or is not synthesized and communicated in a manner that is accessible to these decision-makers. This research aims to bridge the gap between climate information and decision-making needs, by providing an improved understanding of what farmers' consider as relevant climate information, and how these needs compare with current modeling capabilities. Almond is a perennial crop, so any changes in climate within its 25-30 year lifetime can have an adverse impact on crop yield. This makes almond growers vulnerable to medium and long-term climate change. Hence, providing appropriate information on future climate projections can help guide their decisions on crop types & varieties, as well as management practices that are better adapted to future climatic conditions. Semi-structured exploratory interviews have been conducted with almond growers, farm advisors, and other industry stakeholders, with three goals: (1) to understand how growers have used climate information in the past; (2) to identify key climatic variables that are relevant - including appropriate temporal scales and acceptable uncertainty levels; and (3) to understand communication methods that could improve the usability of climate information for farm-level decision-making. The interviews showcased a great diversity amongst growers in terms of how they used weather/climate information. Discussions also indicated that there was a potential for climate information to impact long-term decisions, but only if it is provided within the right context, terminology, and communication channels. The findings offer valuable bottom-up insights into farmers' perspectives on relevance of climate information. These results will also be compared with current modeling capabilities in order to synthesize conclusions for improving the usability of climate science for agricultural decision-makers.

Developing and Evaluating Workshop Frameworks to Improve Climate Literacy

NASA Astrophysics Data System (ADS)

Averyt, K.; Alvord, C.; Joyce, L. A.; Lukas, J.; Barsugli, J. J.; Owen, G.; Udall, B.

2009-12-01

A burgeoning need for climate information is rising from a variety of stakeholders. A new federal report encourages federal resource management efforts to consider climate in assessments-leaving agency scientists and resource managers searching for appropriate data and methodologies. At the other end of the spectrum, small-scale decision makers realize the need to develop scientifically-informed climate adaptation plans, but are unclear about what science is relevant. It is becoming necessary to improve the climate literacy across all sectors. However, past examples illustrate that climate science has been insufficiently communicated, resulting in perceptions that misinform decision-making and planning. Given the necessity to include climate science in planning on multiple scales, scientific educators must work with stakeholders to determine how best to improve climate literacy. Doing so will reduce uncertainty in the application of climate data in planning, and thus mitigate vulnerabilities to the impacts of climate change. Here, we present the design and assessment of two workshop frameworks intended to improve the climate literacy of two distinct entities with different climate information needs. This work represents initial steps by the Western Water Assessment, a NOAA- Regionally Integrated Sciences and Assessments (RISA) Program, towards the development of a suite of process-oriented frameworks geared toward improving the climate literacy of different users with distinct informational needs. Both workshops focused on water-related climate issues: the first (Dealing with Drought: Climate Change in Colorado) was geared toward an audience with minimal exposure to climate information; the second was for US Forest Service hydrologists and managers with technical backgrounds. In both cases, the workshop format included presentations of relevant climate science, introductions to varied climate tools and products, and a needs-and-gaps assessment. Evaluation of each workshop drew upon a variety of tested social science methods, such as focus groups, decision games, surveys, and structured interviews. The efficacy of the framework developed was assessed by evaluating the relationship among the climate information presented, user perceptions about climate information, and incorporation into decision-making. In addition to climate literacy evaluations, participants were presented with a scenario at the beginning of the meeting, and were asked to report periodically on their thoughts on how to approach the scenario as new information was presented throughout the workshop. This allowed us to track the co-evolution of climate literacy, accuracy of data interpretation, and the sophistication of participants’ decision-making. In the 12-months after each workshop, we will track how the climate literacy of the participants evolves, and how their informational needs for decision-making change. The results here will frame a process for how a larger, federal climate-training program might be conducted, and how training needs can be assessed through climate literacy assessments.

The Promise and Limitations of Using Analogies to Improve Decision-Relevant Understanding of Climate Change

PubMed Central

Stern, Paul C.; Maki, Alexander

2017-01-01

To make informed choices about how to address climate change, members of the public must develop ways to consider established facts of climate science and the uncertainties about its future trajectories, in addition to the risks attendant to various responses, including non-response, to climate change. One method suggested for educating the public about these issues is the use of simple mental models, or analogies comparing climate change to familiar domains such as medical decision making, disaster preparedness, or courtroom trials. Two studies were conducted using online participants in the U.S.A. to test the use of analogies to highlight seven key decision-relevant elements of climate change, including uncertainties about when and where serious damage may occur, its unprecedented and progressive nature, and tradeoffs in limiting climate change. An internal meta-analysis was then conducted to estimate overall effect sizes across the two studies. Analogies were not found to inform knowledge about climate literacy facts. However, results suggested that people found the medical analogy helpful and that it led people—especially political conservatives—to better recognize several decision-relevant attributes of climate change. These effects were weak, perhaps reflecting a well-documented and overwhelming effect of political ideology on climate change communication and education efforts in the U.S.A. The potential of analogies and similar education tools to improve understanding and communication in a polarized political environment are discussed. PMID:28135337

Opportunities and Examples for Integration of Socio-environmental Approaches to Support Climate-informed Decisions

NASA Astrophysics Data System (ADS)

Kenney, M. A.

2014-12-01

Climate and environmental decisions require science that couples human and natural systems to quantify or articulate the observed physical, natural, and societal changes or likely consequences of different decision options. Despite the need for such policy-relevant research, multidisciplinary collaborations can be wrought with challenges of data integration, model interoperability, and communication across disciplinary divides. In this talk, I will present several examples where I have collaborated with colleagues from the physical, natural, and social sciences to develop novel, actionable science to inform decision-making. Specifically, I will discuss a cost analysis of water and sediment diversions to optimize land building in the Mississippi River delta (winner of American Geophysical Union Water Resources Research Editor's Choice Award 2014) and the development of a National Climate Indicator System that uses knowledge across the physical, natural, and social sciences to establish an end-to-end indicator system of climate changes, impacts, vulnerabilities, and responses. The latter project is in the process of moving from research to operations, an additional challenge and opportunity, as we work with the U.S. Global Change Research Program and their affiliated Federal agencies to establish it beyond the research prototype. Using these examples, I will provide some lessons learned that would have general applicability to socio-environmental research collaborations and integration of data, models, and information systems to support climate and environmental decision-making.

Bringing science to the table: Case studies in science-informed decision making on climate change and beyond

NASA Astrophysics Data System (ADS)

Goldman, G. T.; Phartiyal, P.; Mulvey, K.

2016-12-01

Federal government officials often rely on the research and advice of scientists to inform their decision making around climate change and other complex topics. Decision makers, however, are constrained by the time and accessibility needed to obtain and incorporate scientific information. At the same time, scientists have limited capacity and incentive to devote significant time to communicating their science to decision makers. The Union of Concerned Scientists has employed several strategies to produce policy-relevant scientific work and to facilitate engagement between scientists and decision makers across research areas. This talk will feature lessons learned and key strategies for science-informed decision making around climate change and other areas of the geosciences. Case studies will include conducting targeted sea level rise studies to inform rulemaking at federal agencies, bringing science to policy discussions on hydraulic fracturing, and leveraging the voice of the scientific community on specific policy proposals around climate change disclosure of companies. Recommendations and lessons learned for producing policy-relevant science and effectively communicating it with decision makers will be offered.

Translating Knowledge: The role of Shared Learning in Bridging the Science-Application Divide

NASA Astrophysics Data System (ADS)

Moench, M.

2014-12-01

As the organizers of this session state: "Understanding and managing our future relation with the Earth requires research and knowledge spanning diverse fields, and integrated, societally-relevant science that is geared toward solutions." In most cases, however, integration is weak and scientific outputs do not match decision maker requirements. As a result, while scientific results may be highly relevant to society that relevance is operationally far from clear. This paper explores the use of shared learning processes to bridge the gap between the evolving body of scientific information on climate change and its relevance for resilience planning in cities across Asia. Examples related to understanding uncertainty, the evolution of scientific knowledge from different sources, and data extraction and presentation are given using experiences generated over five years of work as part of the Rockefeller Foundation supported Asian Cities Climate Change Resilience Network and other programs. Results suggest that processes supporting effective translation of knowledge between different sources and different applications are essential for the identification of solutions that respond to the dynamics and uncertainties inherent in global change processes.

Development and Application of Future Climate Scenarios for Natural Resource Management in Southwestern Colorado

NASA Astrophysics Data System (ADS)

Rangwala, I.; Rondeau, R.; Wyborn, C.; Clifford, K. R.; Travis, W.

2015-12-01

Locally relevant projections of climate change provide critical insights for natural resource managers seeking to adapt their management activities to climate change in the context of uncertainty. To provide such information, we developed climate scenarios, in form of narratives and quantitative information, of future climate change and its impacts in southwestern Colorado. This information was intended to provide detailed insights into the range of changes that natural resource managers may face in the future. The scenarios were developed in an iterative process through interactions among the ecologists, social and climate scientists. In our scenario development process, climate uncertainty is acknowledged by having multiple scenarios, where each scenario is regarded as a storyline with equal likelihood as another scenario. We quantified changes in several decision relevant climate and ecological responses based on our best available understanding and provided a tight storyline for each scenario to facilitate (a) a more augmented use of scientific information in a decision-making process, (b) differential responses from stakeholders across the different scenarios, and (c) identification of strategies that could work across these multiple scenarios. Here, we discuss the process of selecting the scenarios, quantifying climate and ecological responses, and the criteria for building the narrative for each scenario. We also discuss the process by which these scenarios get used, and provide an assessment of their effectiveness and users' feedbacks that could inform the future development of these tools and processes. This research involvement and collaboration occurred, in part, as a result of the PACE Fellowship Program that is associated with NOAA Climate Program Office and the U.S. CLIVAR community.

Decision analysis of shoreline protection under climate change uncertainty

NASA Astrophysics Data System (ADS)

Chao, Philip T.; Hobbs, Benjamin F.

1997-04-01

If global warming occurs, it could significantly affect water resource distribution and availability. Yet it is unclear whether the prospect of such change is relevant to water resources management decisions being made today. We model a shoreline protection decision problem with a stochastic dynamic program (SDP) to determine whether consideration of the possibility of climate change would alter the decision. Three questions are addressed with the SDP: (l) How important is climate change compared to other uncertainties?, (2) What is the economic loss if climate change uncertainty is ignored?, and (3) How does belief in climate change affect the timing of the decision? In the case study, sensitivity analysis shows that uncertainty in real discount rates has a stronger effect upon the decision than belief in climate change. Nevertheless, a strong belief in climate change makes the shoreline protection project less attractive and often alters the decision to build it.

Beyond Prediction: the Many Ways in which Climate Science can Inform Adaptation Decisions

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2017-12-01

Climate science provides an increasingly rich understanding of current and future climate, but this understanding is often not fully incorporated into climate adaptation decisions. In particular, the provision of climate information is still trapped in a narrow prediction-based framework, which envisions a sequential process that begins with model-based forecasts of future climate and decision makers then acting on those forecasts. Among its challenges, this framework can discourage action when climate predictions are deemed too uncertain, encourage overconfidence when climate scientists and decision makers fail to focus on decision-relevant but poorly understood extreme events, and offers a too-narrow communication path among climate scientists and decision makers. This talk will describe how robust decision approaches, organized around the idea of stress testing proposed adaptation decisions over a wide range of futures, can enable a richer flow information among climate scientists and decision makers. The talk illustrates these themes with two examples: 1) conservation management that explores the tradeoffs among alternative climate information products with different combinations of ensemble size and spatial resolution and 2) water quality implementation planning that focuses on the handling of extremes.

The Climate Resilience Toolkit: Central gateway for risk assessment and resilience planning at all governance scales

NASA Astrophysics Data System (ADS)

Herring, D.; Lipschultz, F.

2016-12-01

As people and organizations grapple with a changing climate amid a range of other factors simultaneously shifting, there is a need for credible, legitimate & salient scientific information in useful formats. In addition, an assessment framework is needed to guide the process of planning and implementing projects that allow communities and businesses to adapt to specific changing conditions, while also building overall resilience to future change. We will discuss how the U.S. Climate Resilience Toolkit (CRT) can improve people's ability to understand and manage their climate-related risks and opportunities, and help them make their communities and businesses more resilient. In close coordination with the U.S. Climate Data Initiative, the CRT is continually evolving to offer actionable authoritative information, relevant tools, and subject matter expertise from across the U.S. federal government in one easy-to-use location. The Toolkit's "Climate Explorer" is designed to help people understand potential climate conditions over the course of this century. It offers easy access to downloadable maps, graphs, and data tables of observed and projected temperature, precipitation and other decision-relevant climate variables dating back to 1950 and out to 2100. Since climate is only one of many changing factors affecting decisions about the future, it also ties climate information to a wide range of relevant variables to help users explore vulnerabilities and impacts. New topic areas have been added, such as "Fisheries," "Regions," and "Built Environment" sections that feature case studies and personal experiences in making adaptation decisions. A curated "Reports" section is integrated with semantic web capabilities to help users locate the most relevant information sources. As part of the USGCRP's sustained assessment process, the CRT is aligning with other federal activities, such as the upcoming 4th National Climate Assessment.

Leveraging federal science data and tools to help communities & business build climate resilience

NASA Astrophysics Data System (ADS)

Herring, D.

2016-12-01

Decision-makers in every sector and region of the United States are seeking actionable science-based information to help them understand and manage their climate-related risks. Translating data, tools and information from the domain of climate science to the domains of municipal, social, and economic decision-making raises complex questions—e.g., how to communicate causes and impacts of climate variability and change; how to show projections of plausible future climate scenarios; how to characterize and quantify vulnerabilities, risks, and opportunities facing communities and businesses; and how to make and implement "win-win" adaptation plans. These are the types of challenges being addressed by a public-private partnership of federal agencies, academic institutions, non-governmental organizations, and private businesses that are contributing to the development of the U.S. Climate Resilience Toolkit (toolkit.climate.gov), a new website designed to help people build resilience to extreme events caused by both natural climate variability and long-term climate change. The site's Climate Explorer is designed to help people understand potential climate conditions over the course of this century. It offers easy access to downloadable maps, graphs, and data tables of observed and projected temperature, precipitation and other decision-relevant climate variables dating back to 1950 and out to 2100. Of course, climate change is only one of many variables affecting decisions about the future so the Toolkit also ties climate information to a wide range of other relevant tools and information to help users to explore their vulnerabilities and risks. In this session, we will describe recent enhancements to the Toolkit, lessons learned from user engagements, and evidence that our approach of coupling scientific information with actionable decision-making processes is helping Americans build resilience to climate-related impacts.

Evaluating the Effectiveness of Science for Decision-Making: Water Managers and Tree- Ring Data in the Western United States

NASA Astrophysics Data System (ADS)

Rice, J. L.; Woodhouse, C.; Lukas, J.

2008-12-01

Current climate variability, potential impacts of climate change, and limited resources in the face of growing demand are increasingly prompting water managers in the western United States to consider and use data from climate-related research in water resource planning. Much of these data are produced by stakeholder- driven science programs, such as NOAA's Regional Integrated Science Assessments (RISAs), but there have been few efforts to evaluate the effectiveness of these science-to-application efforts. Over the past several years, researchers with the Western Water Assessment (WWA) RISA have been providing tree-ring reconstructions of streamflow to water managers in Colorado and other western states, and presenting technical workshops explaining the applications of these tree-ring data for water management and planning. Using in-depth interviews and a survey questionnaire, we have assessed the effectiveness and outcomes of these engagements, addressing (1) the factors that have prompted water managers to seek out tree-ring data, (2) how paleoclimate data has been made relevant and accessible for water resource planning, and (3) how tree-ring data and information have been utilized by water managers and other workshop participants. We also provide an assessment of challenges and opportunities that exist in the translation of climate science for decision-making, including how tree-ring data are interpreted in the context of water planning paradigms, issues of credibility and acceptance of tree ring data, and what data needs exist in different planning environments. These findings have broader application in improving and evaluating science-policy interactions related to climate and climate change.

The NOAA Local Climate Analysis Tool - An Application in Support of a Weather Ready Nation

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Horsfall, F. M.

2012-12-01

Citizens across the U.S., including decision makers from the local to the national level, have a multitude of questions about climate, such as the current state and how that state fits into the historical context, and more importantly, how climate will impact them, especially with regard to linkages to extreme weather events. Developing answers to these types of questions for locations has typically required extensive work to gather data, conduct analyses, and generate relevant explanations and graphics. Too frequently providers don't have ready access to or knowledge of reliable, trusted data sets, nor sound, scientifically accepted analysis techniques such that they can provide a rapid response to queries they receive. In order to support National Weather Service (NWS) local office forecasters with information they need to deliver timely responses to climate-related questions from their customers, we have developed the Local Climate Analysis Tool (LCAT). LCAT uses the principles of artificial intelligence to respond to queries, in particular, through use of machine technology that responds intelligently to input from users. A user translates customer questions into primary variables and issues and LCAT pulls the most relevant data and analysis techniques to provide information back to the user, who in turn responds to their customer. Most responses take on the order of 10 seconds, which includes providing statistics, graphical displays of information, translations for users, metadata, and a summary of the user request to LCAT. Applications in Phase I of LCAT, which is targeted for the NWS field offices, include Climate Change Impacts, Climate Variability Impacts, Drought Analysis and Impacts, Water Resources Applications, Attribution of Extreme Events, and analysis techniques such as time series analysis, trend analysis, compositing, and correlation and regression techniques. Data accessed by LCAT are homogenized historical COOP and Climate Prediction Center climate division data available at NCDC. Applications for other NOAA offices and Federal agencies are currently being investigated, such as incorporation of tidal data, fish stocks, sea surface temperature, health-related data, and analyses relevant to those datasets. We will describe LCAT, its basic functionality, examples of analyses, and progress being made to provide the tool to a broader audience in support of ocean, fisheries, and health applications.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Identifying stakeholder-relevant climate change impacts: a case study in the Yakima River Basin, Washington, USA

USGS Publications Warehouse

Jenni, K.; Graves, D.; Hardiman, Jill M.; Hatten, James R.; Mastin, Mark C.; Mesa, Matthew G.; Montag, J.; Nieman, Timothy; Voss, Frank D.; Maule, Alec G.

2014-01-01

Designing climate-related research so that study results will be useful to natural resource managers is a unique challenge. While decision makers increasingly recognize the need to consider climate change in their resource management plans, and climate scientists recognize the importance of providing locally-relevant climate data and projections, there often remains a gap between management needs and the information that is available or is being collected. We used decision analysis concepts to bring decision-maker and stakeholder perspectives into the applied research planning process. In 2009 we initiated a series of studies on the impacts of climate change in the Yakima River Basin (YRB) with a four-day stakeholder workshop, bringing together managers, stakeholders, and scientists to develop an integrated conceptual model of climate change and climate change impacts in the YRB. The conceptual model development highlighted areas of uncertainty that limit the understanding of the potential impacts of climate change and decision alternatives by those who will be most directly affected by those changes, and pointed to areas where additional study and engagement of stakeholders would be beneficial. The workshop and resulting conceptual model highlighted the importance of numerous different outcomes to stakeholders in the basin, including social and economic outcomes that go beyond the physical and biological outcomes typically reported in climate impacts studies. Subsequent studies addressed several of those areas of uncertainty, including changes in water temperatures, habitat quality, and bioenergetics of salmonid populations.

Emerging Climate-data Needs in the Air Transport Sector

NASA Astrophysics Data System (ADS)

Thompson, T. R.

2014-12-01

This paper addresses the nature of climate information needed within the air-transport sector. Air transport is not a single economic sector with uniform needs for climate data: airport, airline, and air-navigation services are the principal sub-sectors, each with their own particular climate-related decision contexts. For example, airports function as fixed infrastructure that is primarily affected by probabilities of extreme events that could hamper runway/taxiway operations, interfere with worker availability, or impede travel to and from the airport by passengers. Airlines, in contrast, are more concerned with changes in atmospheric conditions (upper-air turbulence, convective weather events, etc.) that might require consideration in long-term decisions related to flight-planning processes and aircraft equipage. Air-navigation service providers have needs that are primarily concerned with assurance of safe spatial separation of aircraft via sensor data and communications links. In addition to present-day commercial air transport, we discuss what climate data may be needed for new types of air transport that may emerge in the next couple of decades. These include, for example, small aircraft provided on-demand to non-pilot travelers, high-altitude supersonic business and commercial jets, and very large numbers of un-manned aircraft. Finally, we give examples relating to key technical challenges in providing decision-relevant climate data to the air-transport sector. These include: (1) identifying what types of climate data are most relevant the different decisions facing the several segments of this industry; (2) determining decision-appropriate time horizons for forecasts of this data; and (3) coupling the uncertainties inherent in these forecasts to the decision process.

Developing User-Driven Climate Information Services to Build Resilience Amongst Groups at Risk of Drought and Flood in Arid and Semi-Arid Land Counties in Kenya

NASA Astrophysics Data System (ADS)

Githungo, W. N.; Shaka, A.; Kniveton, D.; Muithya, L.; Powell, R.; Visman, E. L.

2014-12-01

The Arid and Semi-Arid Land (ASAL) counties of Kitui and Makueni in Kenya are experiencing increasing climate variability in seasonal rainfall, including changes in the onset, cessation and distribution of the two principal rains upon which the majority of the population's small-holder farmers and livestock keepers depend. Food insecurity is prevalent with significant numbers also affected by flooding during periods of intense rainfall. As part of a multi-partner Adaptation Consortium, Kenya Meteorological Services (KMS) are developing Climate Information Services (CIS) which can better support decision making amongst the counties' principal livelihoods groups and across County Government ministries. Building on earlier pilots and stakeholder discussion, the system combines the production of climate information tailored for transmission via regional and local radio stations with the establishment of a new SMS service. SMS are provided through a network of CIS intermediaries drawn from across key government ministries, religious networks, non-governmental and community groups, aiming to achieve one SMS recipient per 3-500 people. It also introduces a demand-led, premium-rate SMS weather information service which is designed to be self-financing in the long term. Supporting the ongoing process of devolution, KMS is downscaling national forecasts for each county, and providing seasonal, monthly, weekly and daily forecasts, as well as warnings of weather-related hazards. Through collaboration with relevant ministries, government bodies and research institutions, including livestock, agriculture, drought management and health, technical advisories are developed to provide guidance on application of the climate information. The system seeks to provide timely, relevant information which can enable people to use weather and climate information to support decisions which protect life and property and build resilience to ongoing climate variability and future change.

Workshop summary: 'Integrating air quality and climate mitigation - is there a need for new metrics to support decision making?'

NASA Astrophysics Data System (ADS)

von Schneidemesser, E.; Schmale, J.; Van Aardenne, J.

2013-12-01

Air pollution and climate change are often treated at national and international level as separate problems under different regulatory or thematic frameworks and different policy departments. With air pollution and climate change being strongly linked with regard to their causes, effects and mitigation options, the integration of policies that steer air pollutant and greenhouse gas emission reductions might result in cost-efficient, more effective and thus more sustainable tackling of the two problems. To support informed decision making and to work towards an integrated air quality and climate change mitigation policy requires the identification, quantification and communication of present-day and potential future co-benefits and trade-offs. The identification of co-benefits and trade-offs requires the application of appropriate metrics that are well rooted in science, easy to understand and reflect the needs of policy, industry and the public for informed decision making. For the purpose of this workshop, metrics were loosely defined as a quantified measure of effect or impact used to inform decision-making and to evaluate mitigation measures. The workshop held on October 9 and 10 and co-organized between the European Environment Agency and the Institute for Advanced Sustainability Studies brought together representatives from science, policy, NGOs, and industry to discuss whether current available metrics are 'fit for purpose' or whether there is a need to develop alternative metrics or reassess the way current metrics are used and communicated. Based on the workshop outcome the presentation will (a) summarize the informational needs and current application of metrics by the end-users, who, depending on their field and area of operation might require health, policy, and/or economically relevant parameters at different scales, (b) provide an overview of the state of the science of currently used and newly developed metrics, and the scientific validity of these metrics, (c) identify gaps in the current information base, whether from the scientific development of metrics or their application by different users.

Assessing what to address in science communication.

PubMed

Bruine de Bruin, Wändi; Bostrom, Ann

2013-08-20

As members of a democratic society, individuals face complex decisions about whether to support climate change mitigation, vaccinations, genetically modified food, nanotechnology, geoengineering, and so on. To inform people's decisions and public debate, scientific experts at government agencies, nongovernmental organizations, and other organizations aim to provide understandable and scientifically accurate communication materials. Such communications aim to improve people's understanding of the decision-relevant issues, and if needed, promote behavior change. Unfortunately, existing communications sometimes fail when scientific experts lack information about what people need to know to make more informed decisions or what wording people use to describe relevant concepts. We provide an introduction for scientific experts about how to use mental models research with intended audience members to inform their communication efforts. Specifically, we describe how to conduct interviews to characterize people's decision-relevant beliefs or mental models of the topic under consideration, identify gaps and misconceptions in their knowledge, and reveal their preferred wording. We also describe methods for designing follow-up surveys with larger samples to examine the prevalence of beliefs as well as the relationships of beliefs with behaviors. Finally, we discuss how findings from these interviews and surveys can be used to design communications that effectively address gaps and misconceptions in people's mental models in wording that they understand. We present applications to different scientific domains, showing that this approach leads to communications that improve recipients' understanding and ability to make informed decisions.

Will current probabilistic climate change information, as such, improve adaptation?

NASA Astrophysics Data System (ADS)

Lopez, A.; Smith, L. A.

2012-04-01

Probabilistic climate scenarios are currently being provided to end users, to employ as probabilities in adaptation decision making, with the explicit suggestion that they quantify the impacts of climate change relevant to a variety of sectors. These "probabilities" are, however, rather sensitive to the assumptions in, and the structure of the modelling approaches used to generate them. It is often argued that stakeholders require probabilistic climate change information to adequately evaluate and plan adaptation pathways. On the other hand, some circumstantial evidence suggests that on the ground decision making rarely uses well defined probability distributions of climate change as inputs. Nevertheless it is within this context of probability distributions of climate change that we discuss possible drawbacks of supplying information that, while presented as robust and decision relevant, , is in fact unlikely to be so due to known flaws both in the underlying models and in the methodology used to "account for" those known flaws. How might one use a probability forecast that is expected to change in the future, not due to a refinement in our information but due to fundamental flaws in its construction? What then are the alternatives? While the answer will depend on the context of the problem at hand, a good approach will be strongly informed by the timescale of the given planning decision, and the consideration of all the non-climatic factors that have to be taken into account in the corresponding risk assessment. Using a water resources system as an example, we illustrate an alternative approach to deal with these challenges and make robust adaptation decisions today.

The CAMI Project - Weather and Climate Services for Caribbean Food Security

NASA Astrophysics Data System (ADS)

Trotman, Adrian; Van Meerbeeck, Cedric

2013-04-01

Food security is major focus of Caribbean governments, with production being of particular concern. For the past three decades, Caribbean agriculture has been declining in relative importance, both in terms of its contribution to GDP and its share of the labour force. One of the problems Caribbean agriculture faces is the destructive impacts from weather and climate extremes. These include flood, drought, extreme temperatures, and strong winds from tropical cyclones. Other potential disasters, such as from pests and diseases attacks, are also weather and climate driven. These make weather and climate information critically important to decision-making in agriculture in the Caribbean region. In an effort to help reduce weather and climate related risks to the food security sector, The Caribbean Institute for Meteorology and Hydrology, along with its partners the Caribbean Agricultural Research and Development Institute, the World Meteorological Organization (WMO) and ten National Meteorological Services from within the Caribbean Community launched and implemented the Caribbean Agrometeorological Initiative (CAMI). From 2010 to 2013, CAMI set out to provide relevant information to farmers, and the industry in general, for decision and policy making. The project is funded by the European Union through the Science and Technology Programme of the African, Caribbean and Pacific Group of Countries' (ACP). The overarching objective of CAMI was to increase and sustain agricultural productivity at the farm level in the Caribbean region through improved applications of weather and climate information, using an integrated and coordinated approach. Currently, this is done through (i) provision of relevant climate information appropriately disseminated, (ii) predictions on seasonal rainfall and temperature, (iii) support for improved irrigation management, (iv) the development of strategically selected weather-driven pest and disease models, (v) use of crop simulation models, (vi) training of staff of National Meteorological Services (NMS) and two relevant regional research institutions (vi) and the staging of forums for farmers and Agriculture Extension officers. With its innovative actions and generated products, the thrusts of CAMI link well to the components of the WMO's Global Framework for Climate Services.

Shared Knowledge for Decision-making on Environment and Health Issues in the Arctic

NASA Technical Reports Server (NTRS)

Maynard, Nancy G.

2003-01-01

This paper will describe a remote sensing and GIs-based system to bring indigenous traditional knowledge together with contemporary scientific knowledge to address impacts resulting from changes in climate, environment, weather and pollution in the Arctic. As scientists and policy-makers from both indigenous and non-indigenous communities continue to build closer partnerships to address common sustainability issues such as the health impacts of climate change and anthropogenic activities, it becomes increasingly important to create shared information management systems which integrate all relevant factors for optimal information sharing and decision-making. This system is being designed to bring together remotely sensed, indigenous and other data and observations for analysis, measuring, and monitoring parameters of interest (e.g., snow cover, rainfall, temperature, ice conditions, vegetation, infrastructure, fires). A description of the system and its components as well as a preliminary application of the system in the Arctic will be presented.

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.

Multiple methods for multiple futures: Integrating qualitative scenario planning and quantitative simulation modeling for natural resource decision making

USGS Publications Warehouse

Symstad, Amy J.; Fisichelli, Nicholas A.; Miller, Brian W.; Rowland, Erika; Schuurman, Gregor W.

2017-01-01

Scenario planning helps managers incorporate climate change into their natural resource decision making through a structured “what-if” process of identifying key uncertainties and potential impacts and responses. Although qualitative scenarios, in which ecosystem responses to climate change are derived via expert opinion, often suffice for managers to begin addressing climate change in their planning, this approach may face limits in resolving the responses of complex systems to altered climate conditions. In addition, this approach may fall short of the scientific credibility managers often require to take actions that differ from current practice. Quantitative simulation modeling of ecosystem response to climate conditions and management actions can provide this credibility, but its utility is limited unless the modeling addresses the most impactful and management-relevant uncertainties and incorporates realistic management actions. We use a case study to compare and contrast management implications derived from qualitative scenario narratives and from scenarios supported by quantitative simulations. We then describe an analytical framework that refines the case study’s integrated approach in order to improve applicability of results to management decisions. The case study illustrates the value of an integrated approach for identifying counterintuitive system dynamics, refining understanding of complex relationships, clarifying the magnitude and timing of changes, identifying and checking the validity of assumptions about resource responses to climate, and refining management directions. Our proposed analytical framework retains qualitative scenario planning as a core element because its participatory approach builds understanding for both managers and scientists, lays the groundwork to focus quantitative simulations on key system dynamics, and clarifies the challenges that subsequent decision making must address.

Climate science informs participatory scenario development and applications to decision making in Alaska

NASA Astrophysics Data System (ADS)

Welling, L. A.; Winfree, R.; Mow, J.

2012-12-01

Climate change presents unprecedented challenges for managing natural and cultural resources into the future. Impacts are expected to be highly consequential but specific effects are difficult to predict, requiring a flexible process for adaptation planning that is tightly coupled to climate science delivery systems. Scenario planning offers a tool for making science-based decisions under uncertainty. The National Park Service (NPS) is working with the Department of the Interior Climate Science Centers (CSCs), the NOAA Regional Integrated Science and Assessment teams (RISAs), and other academic, government, non-profit, and private partners to develop and apply scenarios to long-range planning and decision frameworks. In April 2012, Alaska became the first region of the NPS to complete climate change scenario planning for every national park, preserve, and monument. These areas, which collectively make up two-thirds of the total area of the NPS, are experiencing visible and measurable effects attributable to climate change. For example, thawing sea ice, glaciers and permafrost have resulted in coastal erosion, loss of irreplaceable cultural sites, slope failures, flooding of visitor access routes, and infrastructure damage. With higher temperatures and changed weather patterns, woody vegetation has expanded into northern tundra, spruce and cedar diebacks have occurred in southern Alaska, and wildland fire severity has increased. Working with partners at the Alaska Climate Science Center and the Scenario Network for Alaska Planning the NPS integrates quantitative, model-driven data with qualitative, participatory techniques to scenario creation. The approach enables managers to access and understand current climate change science in a form that is relevant for their decision making. Collaborative workshops conducted over the past two years grouped parks from Alaska's southwest, northwest, southeast, interior and central areas. The emphasis was to identify and connect climate and social drivers of change to ecological processes and decision making. Components included review and synthesis of climate observations and projections, effects and impacts, and information on other relevant factors (e.g., subsistence activities, land cover, fire activity, land use change, sea level shifts). Although workshops focused primarily on park lands and waters, nearby communities and other land management units also participated. Results include a framework through which managers are beginning to analyze uncertainties associated with climate change and ecosystem responses and evaluate appropriate and effective actions. For example, at Kenai Fjords National Park, melting from the Harding Icefield and Exit Glacier is changing how managers respond to local flooding issues. The Exit Glacier is one of the park's iconic visitor experiences and in the last four years, the road to the glacier has been subject to mid-summer/fair weather flooding which are outside the historic norms. Rather than seek a traditional solution to the issue, park management has been working with highway engineers to evolve interim solutions as this dynamic system continues to rapidly change. Climate change scenarios established a set of possible plausible futures for the park and are also being used to "wind tunnel" potential responses.

Climateurope: a network to support Europe's research and innovation activities in the fields of Earth-System modeling and climate services

NASA Astrophysics Data System (ADS)

Bessembinder, Janette; Kotova, Lola; Manez, Maria; Jacob, Daniela; Hewitt, Chris; Garrett, Natalie; Monfray, Patrick; Doescher, Ralf; Doblas Reyes, Francisco; Joussaume, Sylvie; Toumi, Ralf; Buonocore, Mauro; Gualdi, Silvio; Nickovic, Slobodan

2017-04-01

Changes in the climate are affecting many sectors but the audience of decision- and policy-makers is so wide and varied that the requirements from each application can be quite different. There are a growing number of initiatives at the international and European level, from research networks of data providers, operational services, impact assessments, to coordination of government initiatives and provision of policy relevant recommendations; all provided on a wide range of timescales. The landscape of activities is very diverse. Users and providers of climate information currently face significant challenges in understanding this complex landscape. If we are to maximize the benefits of the investments and provide European citizens with the information and technology to develop a climate-smart society, then a mechanism is needed to coordinate the impressive and varied research and innovation effort. The overall concept behind the EU-project Climateurope is to create and manage a framework to coordinate, integrate and support Europe's research and innovation activities in the fields of Earth-System modeling and climate services. The purpose of this concept is to create greater social and economic value for Europe through improved preparation for, and management of, climate-related risks and opportunities arising from making European world-class knowledge more useable and thus more applicable to policy- and decision-making. This value will be felt by a range of actors including the public sector, governments, business and industry. Climateurope will provide a comprehensive overview of all the relevant activities to ensure the society at large can take full advantage of the investment Europe is making in research and innovation and associated development of services. The Climateurope network will facilitate dialog among climate science communities, funding bodies, climate service providers and users. Through the communication and dissemination activities, Climateurope will establish multidisciplinary expert groups to access the state-of-the-art of Earth system modeling and climate services and will identify existing gaps, new challenges and emerging needs. During this presentation the activities and progress of the project (website, webinars, discussion platform, festivals, state-of-the-art report) will be presented shortly and we will indicate how interested people can join the network.

Linking climate projections to performance: A yield-based decision scaling assessment of a large urban water resources system

NASA Astrophysics Data System (ADS)

Turner, Sean W. D.; Marlow, David; Ekström, Marie; Rhodes, Bruce G.; Kularathna, Udaya; Jeffrey, Paul J.

2014-04-01

Despite a decade of research into climate change impacts on water resources, the scientific community has delivered relatively few practical methodological developments for integrating uncertainty into water resources system design. This paper presents an application of the "decision scaling" methodology for assessing climate change impacts on water resources system performance and asks how such an approach might inform planning decisions. The decision scaling method reverses the conventional ethos of climate impact assessment by first establishing the climate conditions that would compel planners to intervene. Climate model projections are introduced at the end of the process to characterize climate risk in such a way that avoids the process of propagating those projections through hydrological models. Here we simulated 1000 multisite synthetic monthly streamflow traces in a model of the Melbourne bulk supply system to test the sensitivity of system performance to variations in streamflow statistics. An empirical relation was derived to convert decision-critical flow statistics to climatic units, against which 138 alternative climate projections were plotted and compared. We defined the decision threshold in terms of a system yield metric constrained by multiple performance criteria. Our approach allows for fast and simple incorporation of demand forecast uncertainty and demonstrates the reach of the decision scaling method through successful execution in a large and complex water resources system. Scope for wider application in urban water resources planning is discussed.

Linking science, public values, and decision-making: Case study development for public deliberations about climate change resilience

NASA Astrophysics Data System (ADS)

Weller, N.; Bennett, I.; Bernstein, M.; Farooque, M.; Lloyd, J.; Lowenthal, C.; Sittenfeld, D.

2016-12-01

Actionable science seeks to align scientific inquiry with decision-making priorities to overcome rifts between scientific knowledge and the needs of decision makers. Combining actionable science with explorations of public values and priorities creates useful support for decision makers facing uncertainty, tradeoffs, and limited resources. As part of a broader project to create public forums about climate change resilience, we convened workshops with decision makers, resilience experts, and community stakeholders to discuss climate change resilience. Our goals were 1) to create case studies of resilience strategies for use in public deliberations at science museums across 8 U.S. cities; and 2) to build relationships with decision makers and stakeholders interested in these public deliberations. Prior to workshops, we created summaries of resilience strategies using academic literature, government assessments, municipal resilience plans, and conversations with workshop participants. Workshops began with example deliberation activities followed by semi-structured discussions of resilience strategies centered on 4 questions: 1) What are the key decisions to be made regarding each strategy? 2) What stakeholders and perspectives are relevant to each strategy? 3) What available data are relevant to each strategy? 4) What visualizations or other resources are useful for communicating things about each strategy? Workshops yielded actionable dialogue regarding issues of justice, feasibility, and the socio-ecological-technical systems impacted by climate change hazards and resilience strategies. For example, discussions of drought revealed systemic and individual-level challenges and opportunities; discussions of sea level rise included ways to account for the cultural significance of many coastal communities. The workshops provide a model for identifying decision-making priorities and tradeoffs and building partnerships among stakeholders, scientists, and decision makers.

Precipitation Variability and Projection Uncertainties in Climate Change Adaptation: Go Local!

EPA Science Inventory

Presentations agenda includes: Regional and local climate change effects: The relevance; Variability and uncertainty in decision- making and adaptation approaches; Adaptation attributes for the U.S. Southwest: Water availability, storage capacity, and related; EPA research...

Sustaining a Stakeholder-Scientists Partnership in Co-producing Locally Relevant Data, Methods, and Tools

NASA Astrophysics Data System (ADS)

Asefa, T.

2017-12-01

This case study presents the experiences of two of the most successful boundary organizations that are engaged in co-producing decision relevant climate information for water resources management. The Water Utilities Climate Alliance (www.wucaonline.org) is a coalition of 11 of the nation's largest water utilities with customers base over 50 million. Whereas Florida Water and Climate Alliance (www.floridaWCA.org) is a state level collaborative Learning network that is engaged in co-exploration and co-development of actionable climate science. Lesson learned from these two structurally different organizations will be shared.

Improving Data Access for Climate Preparedness Through Public-Private Partnerships

NASA Astrophysics Data System (ADS)

Satkowski, L.; Tewksbury, J.

2017-12-01

With increasing exposure to extreme hurricane and flooding events, a growing number of communities, companies, and civil society organizations around the world are looking to assess climate impacts and vulnerability, and to develop resilience plans. Currently, efforts to turn data into actionable plans are constrained by limited access to robust, actionable data and information. The Partnership for Resilience and Preparedness (PREP), public-private collaboration that seeks to empower a data-driven approach to building climate resilience, aims to facilitate the process for planners, investors, resource managers, and others to routinely incorporate climate risks into their decisions, by enhancing access to relevant data and facilitating collective learning. Together, this peer-to-peer initiative of approximately 30 government, NGO, and business partners built PREPdata, an intuitive, open map-based platform that enables users to visualize, download and layer data to inform adaptation decision-making. The platform also connects practitioners to data providers, closing the feedback loop between them and enhancing the climate data ecosystem. In this session participants will learn how public-private partnerships can reduce barriers to discovering, accessing climate data and will be given an interactive tutorial on PREPdata, specific to the Gulf of Mexico and hurricane and flooding events. Participants will discover ways to incorporate local data with national and global data, learn about PREPdata application case studies, and how PREPdata can be used to analyze risk in hurricane vulnerable geographies.

Improving the relevance and impact of decision support research: A co-production framework and water management case study

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Dilling, L.; Basdekas, L.; Kaatz, L.

2016-12-01

In light of the unpredictable effects of climate change and population shifts, responsible resource management will require new types of information and strategies going forward. For water utilities, this means that water supply infrastructure systems must be expanded and/or managed for changes in overall supply and increased extremes. Utilities have begun seeking innovative tools and methods to support planning and decision making, but there are limited channels through which they can gain exposure to emerging tools from the research world, and for researchers to uptake important real-world planning and decision context. A transdisciplinary team of engineers, social and climate scientists, and water managers designed this study to develop and apply a co-production framework which explores the potential of an emerging decision support tool to enhance flexibility and adaptability in water utility planning. It also demonstrates how to improve the link between research and practice in the water sector. In this study we apply the co-production framework to the use of Multiobjective Evolutionary Algorithms (MOEAs). MOEAs have shown promise in being able to generate and evaluate new planning alternatives but they have had little testing or application in water utilities. Anchored by two workshops, this study (1) elicited input from water managers from six water suppliers on the Front Range of Colorado, USA, to create a testbed MOEA application, and (2) evaluated the managers' responses to multiobjective optimization results. The testbed consists of a Front Range-relevant hypothetical water supply model, the Borg MOEA, hydrology and demand scenarios, and a set of planning decisions and performance objectives that drive the link between the algorithm and the model. In this presentation we describe researcher-manager interactions at the initial workshop that served to establish relationships and provide in-depth information to researchers about regional water management context. We also describe the development of, and experiences from, the second workshop which included activities for water managers to interact directly with MOEA testbed results. Finally, we evaluate the co-production framework itself and the potential for the feedback from managers to shape future development of decision support tools.

Questioning the Relevance of Model-Based Probability Statements on Extreme Weather and Future Climate

NASA Astrophysics Data System (ADS)

Smith, L. A.

2007-12-01

We question the relevance of climate-model based Bayesian (or other) probability statements for decision support and impact assessment on spatial scales less than continental and temporal averages less than seasonal. Scientific assessment of higher resolution space and time scale information is urgently needed, given the commercial availability of "products" at high spatiotemporal resolution, their provision by nationally funded agencies for use both in industry decision making and governmental policy support, and their presentation to the public as matters of fact. Specifically we seek to establish necessary conditions for probability forecasts (projections conditioned on a model structure and a forcing scenario) to be taken seriously as reflecting the probability of future real-world events. We illustrate how risk management can profitably employ imperfect models of complicated chaotic systems, following NASA's study of near-Earth PHOs (Potentially Hazardous Objects). Our climate models will never be perfect, nevertheless the space and time scales on which they provide decision- support relevant information is expected to improve with the models themselves. Our aim is to establish a set of baselines of internal consistency; these are merely necessary conditions (not sufficient conditions) that physics based state-of-the-art models are expected to pass if their output is to be judged decision support relevant. Probabilistic Similarity is proposed as one goal which can be obtained even when our models are not empirically adequate. In short, probabilistic similarity requires that, given inputs similar to today's empirical observations and observational uncertainties, we expect future models to produce similar forecast distributions. Expert opinion on the space and time scales on which we might reasonably expect probabilistic similarity may prove of much greater utility than expert elicitation of uncertainty in parameter values in a model that is not empirically adequate; this may help to explain the reluctance of experts to provide information on "parameter uncertainty." Probability statements about the real world are always conditioned on some information set; they may well be conditioned on "False" making them of little value to a rational decision maker. In other instances, they may be conditioned on physical assumptions not held by any of the modellers whose model output is being cast as a probability distribution. Our models will improve a great deal in the next decades, and our insight into the likely climate fifty years hence will improve: maintaining the credibility of the science and the coherence of science based decision support, as our models improve, require a clear statement of our current limitations. What evidence do we have that today's state-of-the-art models provide decision-relevant probability forecasts? What space and time scales do we currently have quantitative, decision-relevant information on for 2050? 2080?

Assessing the continuum of applications and societal benefits of US CLIVAR science

NASA Astrophysics Data System (ADS)

Ray, A. J.; Garfin, G. M.

2015-12-01

The new US CLIVAR strategic plan seeks to address the challenges of communicating the climate knowledge generated through its activities and to collaborate with the research and operational communities that may use this knowledge for managing climate risks. This presentation provides results of an overview in progress of the continuum of potential applications of climate science organized and coordinated through US CLIVAR. We define applications more broadly than simply ready for operations or direct use, and find that there are several stages in a continuum of readiness for communication and collaboration with communities that use climate information. These stages include: 1) advancing scientific understanding to a readiness for the next research steps aimed at predictable signals; 2) application of understanding climate phenomena in collaboration with a boundary organization, such as NOAA RISAs DOI Climate Science Centers, and USDA Climate Hubs, to understand how predictable signals may be translated into useable products; 3) use of knowledge in risk framing for a decision process, or in a science synthesis, such as the National Climate Assessment, and 4) transitioning new science knowledge into operational products (e.g. R2O), such as intraseasonal climate prediction. In addition, US CLIVAR has sponsored efforts to build science-to-decisions capacity, e.g., the Postdocs Applying Climate Expertise (PACE) program, in its 7th cohort, which has embedded climate experts into decision-making institutions. We will spotlight accomplishments of US CLIVAR science that are ripe for application in communities that are managing climate risks -- such as drought outlooks, MJO forecasting, extremes, and ocean conditions -- for agricultural production, water use, and marine ecosystems. We will use these examples to demonstrate the usefulness of an "applications continuum framework" identifying pathways from research to applications.

The Value of Civic Science Literacy (Invited)

NASA Astrophysics Data System (ADS)

Kahan, D.

2013-12-01

The persistence of public conflict over climate change is commonly understood to be evidence of the cost borne by our democracy by the failure of citizens to recognize the best available decision-relevant science. This conclusion is true; what's not is the usual understanding of cause and effect that accompanies this perspective. Ordinarily, the inability of citizens to comprehend decision-relevant science is identified as the source of persistent political conflict over climate change (along myriad other issues that feature disputed facts that admit of scientific investigation). The truth, however, is it is the persistence of public conflict that disables citizens from recognizing and making effective use of decision-relevant science. As a result, efforts to promote civic science literacy can't be expected to dissipate such conflict. Instead, the root, cultural and psychological sources of such conflict must themselves be extinguished (with the use of tools and strategies themselves identified through valid scientific inquiry) so our democracy can realize the value of educators' considerable skills in making citizens science literate.

NASA and the National Climate Assessment: Promoting awareness of NASA Earth science

NASA Astrophysics Data System (ADS)

Leidner, A. K.

2014-12-01

NASA Earth science observations, models, analyses, and applications made significant contributions to numerous aspects of the Third National Climate Assessment (NCA) report and are contributing to sustained climate assessment activities. The agency's goal in participating in the NCA was to ensure that NASA scientific resources were made available to understand the current state of climate change science and climate change impacts. By working with federal agency partners and stakeholder communities to develop and write the report, the agency was able to raise awareness of NASA climate science with audiences beyond the traditional NASA community. To support assessment activities within the NASA community, the agency sponsored two competitive programs that not only funded research and tools for current and future assessments, but also increased capacity within our community to conduct assessment-relevant science and to participate in writing assessments. Such activities fostered the ability of graduate students, post-docs, and senior researchers to learn about the science needs of climate assessors and end-users, which can guide future research activities. NASA also contributed to developing the Global Change Information System, which deploys information from the NCA to scientists, decision makers, and the public, and thus contributes to climate literacy. Finally, NASA satellite imagery and animations used in the Third NCA helped the pubic and decision makers visualize climate changes and were frequently used in social media to communicate report key findings. These resources are also key for developing educational materials that help teachers and students explore regional climate change impacts and opportunities for responses.

Physical, Ecological, and Societal Indicators for the National Climate Assessment

NASA Technical Reports Server (NTRS)

Kenney, Melissa A.; Chen, Robert; Baptista, Sandra R.; Quattrochi, Dale; O'Brien, Sheila

2011-01-01

The National Climate Assessment (NCA) is being conducted under the auspices of the U.S. Global Change Research Program (USGCRP), pursuant to the Global Change Research Act of 1990, Section 106, which requires a report to Congress every 4 years. The current NCA (http://globalchange.gov/what-we-do/assessment/) differs in multiple ways from previous U.S. climate assessment efforts, being: (1) more focused on supporting the Nation s activities in adaptation and mitigation and on evaluating the current state of scientific knowledge relative to climate impacts and trends; (2) a long-term, consistent process for evaluation of climate risks and opportunities and providing information to support decision-making processes within regions and sectors; and (3) establishing a permanent assessment capacity both inside and outside of the federal government. As a part of ongoing, long-term assessment activities, the NCA intends to develop an integrated strategic framework and deploy climate-relevant physical, ecological, and societal indicators. The NCA indicators framework is underdevelopment by the NCA Development and Advisory Committee Indicators Working Group and are envisioned as a relatively small number of policy-relevant integrated indicators designed to provide a consistent, objective, and transparent overview of major variations in climate impacts, vulnerabilities, adaptation, and mitigation activities across sectors, regions, and timeframes. The potential questions that could be addressed by these indicators include: How do we know that there is a changing climate and how is it expected to change in the future? Are important climate impacts and opportunities occurring or predicted to occur in the future? Are we adapting successfully? What are the vulnerabilities and resiliencies given a changing climate? Are we preparing adequately for extreme events? It is not expected that the NCA societal indicators would be linked directly to a single decision or portfolio of decisions, but subsets of indicators, or the data supporting the indicator, might be used to inform decision-making processes such as the development and implementation of climate adaptation strategies in a particular sector or region.

Physical, Ecological, and Societal Indicators for the National Climate Assessment

NASA Astrophysics Data System (ADS)

O'Brien, S.; Kenney, M.; Chen, R. S.; Baptista, S. R.; Quattrochi, D. A.

2011-12-01

The National Climate Assessment (NCA) is being conducted under the auspices of the U.S. Global Change Research Program (USGCRP), pursuant to the Global Change Research Act of 1990, Section 106, which requires a report to Congress every 4 years. The current NCA (http://globalchange.gov/what-we-do/assessment/) differs in multiple ways from previous U.S. climate assessment efforts, being: (1) more focused on supporting the Nation's activities in adaptation and mitigation and on evaluating the current state of scientific knowledge relative to climate impacts and trends; (2) a long-term, consistent process for evaluation of climate risks and opportunities and providing information to support decision-making processes within regions and sectors; and (3) establishing a permanent assessment capacity both inside and outside of the federal government. As a part of ongoing, long-term assessment activities, the NCA intends to develop an integrated strategic framework and deploy climate-relevant physical, ecological, and societal indicators. The NCA indicators framework is underdevelopment by the NCA Development and Advisory Committee Indicators Working Group and are envisioned as a relatively small number of policy-relevant integrated indicators designed to provide a consistent, objective, and transparent overview of major variations in climate impacts, vulnerabilities, adaptation, and mitigation activities across sectors, regions, and timeframes. The potential questions that could be addressed by these indicators include: -How do we know that there is a changing climate and how is it expected to change in the future? -Are important climate impacts and opportunities occurring or predicted to occur in the future? -Are we adapting successfully? -What are the vulnerabilities and resiliencies given a changing climate? -Are we preparing adequately for extreme events? It is not expected that the NCA indicators would be linked directly to a single decision or portfolio of decisions, but subsets of indicators, or the data supporting the indicator, might be used to inform decision-making processes such as the development and implementation of climate adaptation strategies in a particular sector or region.

Decision-relevant evaluation of climate models: A case study of chill hours in California

NASA Astrophysics Data System (ADS)

Jagannathan, K. A.; Jones, A. D.; Kerr, A. C.

2017-12-01

The past decade has seen a proliferation of different climate datasets with over 60 climate models currently in use. Comparative evaluation and validation of models can assist practitioners chose the most appropriate models for adaptation planning. However, such assessments are usually conducted for `climate metrics' such as seasonal temperature, while sectoral decisions are often based on `decision-relevant outcome metrics' such as growing degree days or chill hours. Since climate models predict different metrics with varying skill, the goal of this research is to conduct a bottom-up evaluation of model skill for `outcome-based' metrics. Using chill hours (number of hours in winter months where temperature is lesser than 45 deg F) in Fresno, CA as a case, we assess how well different GCMs predict the historical mean and slope of chill hours, and whether and to what extent projections differ based on model selection. We then compare our results with other climate-based evaluations of the region, to identify similarities and differences. For the model skill evaluation, historically observed chill hours were compared with simulations from 27 GCMs (and multiple ensembles). Model skill scores were generated based on a statistical hypothesis test of the comparative assessment. Future projections from RCP 8.5 runs were evaluated, and a simple bias correction was also conducted. Our analysis indicates that model skill in predicting chill hour slope is dependent on its skill in predicting mean chill hours, which results from the non-linear nature of the chill metric. However, there was no clear relationship between the models that performed well for the chill hour metric and those that performed well in other temperature-based evaluations (such winter minimum temperature or diurnal temperature range). Further, contrary to conclusions from other studies, we also found that the multi-model mean or large ensemble mean results may not always be most appropriate for this outcome metric. Our assessment sheds light on key differences between global versus local skill, and broad versus specific skill of climate models, highlighting that decision-relevant model evaluation may be crucial for providing practitioners with the best available climate information for their specific needs.

Producing More Actionable Science Isn't the Problem; It's Providing Decision-Makers with Access to Right Actionable Knowledge

NASA Astrophysics Data System (ADS)

Trexler, M.

2017-12-01

Policy-makers today have almost infinite climate-relevant scientific and other information available to them. The problem for climate change decision-making isn't missing science or inadequate knowledge of climate risks; the problem is that the "right" climate change actionable knowledge isn't getting to the right decision-maker, or is getting there too early or too late to effectively influence her decision-making. Actionable knowledge is not one-size-fit-all, and for a given decision-maker might involve scientific, economic, or risk-based information. Simply producing more and more information as we are today is not the solution, and actually makes it harder for individual decision-makers to access "their" actionable knowledge. The Climatographers began building the Climate Web five years ago to test the hypothesis that a knowledge management system could help navigate the gap between infinite information and individual actionable knowledge. Today the Climate Web's more than 1,500 index terms allow instant access to almost any climate change topic. It is a curated public-access knowledgebase of more than 1,000 books, 2,000 videos, 15,000 reports and articles, 25,000 news stories, and 3,000 websites. But it is also much more, linking together tens of thousands of individually extracted ideas and graphics, and providing Deep Dives into more than 100 key topics from changing probability distributions of extreme events to climate communications best practices to cognitive dissonance in climate change decision-making. The public-access Climate Web is uniquely able to support cross-silo learning, collaboration, and actionable knowledge dissemination. The presentation will use the Climate Web to demonstrate why knowledge management should be seen as a critical component of science and policy-making collaborations.

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

Negotiating the question: using science-manager communication to develop management-relevant science products

NASA Astrophysics Data System (ADS)

Beechie, T. J.; Snover, A. K.

2014-12-01

Natural resource managers often ask scientists to answer questions that cannot be answered, and scientists commonly offer research that is not useful to managers. To produce management-relevant science, managers and scientists must communicate clearly to identify research that is scientifically doable and will produce results that managers find useful. Scientists might also consider that journals with high impact scores are rarely used by managers, while managers might consider that publishing in top tier journals is important to maintain scientific credentials. We offer examples from climate change and river restoration research, in which agency scientists and managers worked together to identify key management questions that scientists could answer and which could inform management. In our first example, we describe how climate scientists worked with agency staff to develop guidance for selecting appropriate climate change scenarios for use in ecological impacts assessments and Endangered Species Act decision making. Within NOAA Fisheries, agency researchers provide science to guide agency managers, and a key question has been how to adapt river restoration efforts for climate change. Based on discussions with restoration practitioners and agency staff, we developed adaptation guidance that summarizes current science to lead managers to develop climate-resilient restoration plans, as well as maps of population vulnerability for endangered steelhead. From these experiences we have learned that collaborative definition of relevant and producible knowledge requires (1) iterative discussions that go beyond simply asking managers what they need or scientists what they can produce, and (2) candid conversation about the intended applications and potential limitations of the knowledge.

Climate change and the economics of biomass energy feedstocks in semi-arid agricultural landscapes: A spatially explicit real options analysis.

PubMed

Regan, Courtney M; Connor, Jeffery D; Raja Segaran, Ramesh; Meyer, Wayne S; Bryan, Brett A; Ostendorf, Bertram

2017-05-01

The economics of establishing perennial species as renewable energy feedstocks has been widely investigated as a climate change adapted diversification option for landholders, primarily using net present value (NPV) analysis. NPV does not account for key uncertainties likely to influence relevant landholder decision making. While real options analysis (ROA) is an alternative method that accounts for the uncertainty over future conditions and the large upfront irreversible investment involved in establishing perennials, there have been limited applications of ROA to evaluating land use change decision economics and even fewer applications considering climate change risks. Further, while the influence of spatially varying climate risk on biomass conversion economic has been widely evaluated using NPV methods, effects of spatial variability and climate on land use change have been scarcely assessed with ROA. In this study we applied a simulation-based ROA model to evaluate a landholder's decision to convert land from agriculture to biomass. This spatially explicit model considers price and yield risks under baseline climate and two climate change scenarios over a geographically diverse farming region. We found that underlying variability in primary productivity across the study area had a substantial effect on conversion thresholds required to trigger land use change when compared to results from NPV analysis. Areas traditionally thought of as being quite similar in average productive capacity can display large differences in response to the inclusion of production and price risks. The effects of climate change, broadly reduced returns required for land use change to biomass in low and medium rainfall zones and increased them in higher rainfall areas. Additionally, the risks posed by climate change can further exacerbate the tendency for NPV methods to underestimate true conversion thresholds. Our results show that even under severe drying and warming where crop yield variability is more affected than perennial biomass plantings, comparatively little of the study area is economically viable for conversion to biomass under $200/DM t, and it is not until prices exceed $200/DM t that significant areas become profitable for biomass plantings. We conclude that for biomass to become a valuable diversification option the synchronisation of products and services derived from biomass and the development of markets is vital. Copyright © 2017 Elsevier Ltd. All rights reserved.

The weather roulette: assessing the economic value of seasonal wind speed predictions

NASA Astrophysics Data System (ADS)

Christel, Isadora; Cortesi, Nicola; Torralba-Fernandez, Veronica; Soret, Albert; Gonzalez-Reviriego, Nube; Doblas-Reyes, Francisco

2016-04-01

Climate prediction is an emerging and highly innovative research area. For the wind energy sector, predicting the future variability of wind resources over the coming weeks or seasons is especially relevant to quantify operation and maintenance logistic costs or to inform energy trading decision with potential cost savings and/or economic benefits. Recent advances in climate predictions have already shown that probabilistic forecasting can improve the current prediction practices, which are based in the use of retrospective climatology and the assumption that what happened in the past is the best estimation of future conditions. Energy decision makers now have this new set of climate services but, are they willing to use them? Our aim is to properly explain the potential economic benefits of adopting probabilistic predictions, compared with the current practice, by using the weather roulette methodology (Hagedorn & Smith, 2009). This methodology is a diagnostic tool created to inform in a more intuitive and relevant way about the skill and usefulness of a forecast in the decision making process, by providing an economic and financial oriented assessment of the benefits of using a particular forecast system. We have selected a region relevant to the energy stakeholders where the predictions of the EUPORIAS climate service prototype for the energy sector (RESILIENCE) are skillful. In this region, we have applied the weather roulette to compare the overall prediction success of RESILIENCE's predictions and climatology illustrating it as an effective interest rate, an economic term that is easier to understand for energy stakeholders.

Climate Risk Informed Decision Analysis (CRIDA): A novel practical guidance for Climate Resilient Investments and Planning

NASA Astrophysics Data System (ADS)

Jeuken, Ad; Mendoza, Guillermo; Matthews, John; Ray, Patrick; Haasnoot, Marjolijn; Gilroy, Kristin; Olsen, Rolf; Kucharski, John; Stakhiv, Gene; Cushing, Janet; Brown, Casey

2016-04-01

Engineers and water managers have always incorporated uncertainty in water resources operations, design and planning. In recent years, concern has been growing concern that many of the fundamental principles to address uncertainty in planning and design are insufficient for coping with unprecedented shifts in climate, especially given the long lifetimes of water investments - spanning decades, even centuries. Can we design and operate new flood risk management, energy, water supply and sanitation, and agricultural projects that are robust to shifts over 20, 50, or more years? Since about 2009, better approaches to planning and designing under climate uncertainty have been gaining ground worldwide. The main challenge is to operationalize these approaches and bring them from science to practice, embed them within the existing decision-making processes of particular institutions, and shift from highly specialized "boutique" applications to methods that result in consistent, replicable outcomes accessible to water managers worldwide. With CRIDA a serious step is taken to achieve these goals. CRIDA is built on two innovative but complementary approaches that have developed in isolation across the Atlantic over the past seven years: diagnosing and assessing risk (decision scaling), and developing sequential decision steps to compensate for uncertainty within regulatory / performance standards (adaptation pathways). First, the decision scaling or "bottom up" framework to climate change adaptation was first conceptualized during the US/Canada Great Lakes regulation study and has recently been placed in a decision-making context for water-related investments published by the World Bank Second, the adaptation pathways approach was developed in the Netherlands to cope with the level of climate uncertainty we now face. Adaptation pathways is a tool for maintaining options and flexibility while meeting operational goals by envisioning how sequences of decisions can be navigated over time. They are part of the Dutch adaptive planning approach Adaptive Delta Management, executed and develop by the Dutch Delta program. Both decision scaling and adaptation pathways have been piloted in studies worldwide. The objective of CRIDA is to mainstream effective climate adaptation for professional water managers. The CRIDA publication, due in april 2016, follows the generic water design planning design cycle. At each step, CRIDA describes stepwise guidance for incorporating climate robustness: problem definition, stress test, alternatives formulation and recommendation, evaluation and selection. In the presentation the origin, goal, steps and practical tools available at each step of CRIDA will be explained. In two other abstracts ("Climate Risk Informed Decision Analysis: A Hypothetical Application to the Waas Region" by Gilroy et al., "The Application of Climate Risk Informed Decision Analysis to the Ioland Water Treatment Plant in Lusaka, Zambia, by Kucharski et al.), the application of CRIDA to cases is explained

Designing the Bridge: Perceptions and Use of Downscaled Climate Data by Climate Modelers and Resource Managers in Hawaii

NASA Astrophysics Data System (ADS)

Keener, V. W.; Brewington, L.; Jaspers, K.

2016-12-01

To build an effective bridge from the climate modeling community to natural resource managers, we assessed the existing landscape to see where different groups diverge in their perceptions of climate data and needs. An understanding of a given community's shared knowledge and differences can help design more actionable science. Resource managers in Hawaii are eager to have future climate projections at spatial scales relevant to the islands. National initiatives to downscale climate data often exclude US insular regions, so researchers in Hawaii have generated regional dynamically and statistically downscaled projections. Projections of precipitation diverge, however, leading to difficulties in communication and use. Recently, a two day workshop was held with scientists and managers to evaluate available models and determine a set of best practices for moving forward with decision-relevant downscaling in Hawaii. To seed the discussion, the Pacific Regional Integrated Sciences and Assessments (RISA) program conducted a pre-workshop survey (N=65) of climate modelers and freshwater, ecosystem, and wildfire managers working in Hawaii. Scientists reported spending less than half of their time on operational research, although the majority was eager to partner with managers on specific projects. Resource managers had varying levels of familiarity with downscaled climate projections, but reported needing more information about uncertainty for decision making, and were less interested in the technical model details. There were large differences between groups of managers, with 41.7% of freshwater managers reporting that they used climate projections regularly, while a majority of ecosystem and wildfire managers reported having "no familiarity". Scientists and managers rated which spatial and temporal scales were most relevant to decision making. Finally, when asked to compare how confident they were in projections of specific climate variables between the dynamical and statistical data, 80-90% of managers responded that they had no opinion. Workshop attendees were very interested in the survey results, adding to evidence of a need for sustained engagement between modeler and user groups, as well as different strategies for working with different types of resource managers.

The End-to-end Demonstrator for improved decision making in the water sector in Europe (EDgE)

NASA Astrophysics Data System (ADS)

Wood, Eric; Wanders, Niko; Pan, Ming; Sheffield, Justin; Samaniego, Luis; Thober, Stephan; Kumar, Rohinni; Prudhomme, Christel; Houghton-Carr, Helen

2017-04-01

High-resolution simulations of water resources from hydrological models are vital to supporting important climate services. Apart from a high level of detail, both spatially and temporally, it is important to provide simulations that consistently cover a range of timescales, from historical reanalysis to seasonal forecast and future projections. In the new EDgE project commissioned by the ECMWF (C3S) we try to fulfill these requirements. EDgE is a proof-of-concept project which combines climate data and state-of-the-art hydrological modelling to demonstrate a water-oriented information system implemented through a web application. EDgE is working with key European stakeholders representative of private and public sectors to jointly develop and tailor approaches and techniques. With these tools, stakeholders are assisted in using improved climate information in decision-making, and supported in the development of climate change adaptation and mitigation policies. Here, we present the first results of the EDgE modelling chain, which is divided into three main processes: 1) pre-processing and downscaling; 2) hydrological modelling; 3) post-processing. Consistent downscaling and bias corrections for historical simulations, seasonal forecasts and climate projections ensure that the results across scales are robust. The daily temporal resolution and 5km spatial resolution ensure locally relevant simulations. With the use of four hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), uncertainty between models is properly addressed, while consistency is guaranteed by using identical input data for static land surface parameterizations. The forecast results are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs) that have been created in collaboration with the end-user community of the EDgE project. The final product of this project is composed of 15 years of seasonal forecast and 10 climate change projections, all combined with four hydrological models. These unique high-resolution climate information simulations in the EDgE project provide an unprecedented information system for decision-making over Europe.

The Application of Climate Risk Informed Decision Analysis to the Ioland Water Treatment Plant in Lusaka, Zambia

NASA Astrophysics Data System (ADS)

Kucharski, John; Tkach, Mark; Olszewski, Jennifer; Chaudhry, Rabia; Mendoza, Guillermo

2016-04-01

This presentation demonstrates the application of Climate Risk Informed Decision Analysis (CRIDA) at Zambia's principal water treatment facility, The Iolanda Water Treatment Plant. The water treatment plant is prone to unacceptable failures during periods of low hydropower production at the Kafue Gorge Dam Hydroelectric Power Plant. The case study explores approaches of increasing the water treatment plant's ability to deliver acceptable levels of service under the range of current and potential future climate states. The objective of the study is to investigate alternative investments to build system resilience that might have been informed by the CRIDA process, and to evaluate the extra resource requirements by a bilateral donor agency to implement the CRIDA process. The case study begins with an assessment of the water treatment plant's vulnerability to climate change. It does so by following general principals described in "Confronting Climate Uncertainty in Water Resource Planning and Project Design: the Decision Tree Framework". By utilizing relatively simple bootstrapping methods a range of possible future climate states is generated while avoiding the use of more complex and costly downscaling methodologies; that are beyond the budget and technical capacity of many teams. The resulting climate vulnerabilities and uncertainty in the climate states that produce them are analyzed as part of a "Level of Concern" analysis. CRIDA principals are then applied to this Level of Concern analysis in order to arrive at a set of actionable water management decisions. The principal goals of water resource management is to transform variable, uncertain hydrology into dependable services (e.g. water supply, flood risk reduction, ecosystem benefits, hydropower production, etc…). Traditional approaches to climate adaptation require the generation of predicted future climate states but do little guide decision makers how this information should impact decision making. In this context it is not surprising that the increased hydrologic variability and uncertainty produced by many climate risk analyses bedevil water resource decision making. The Climate Risk Informed Decision Analysis (CRIDA) approach builds on work found in "Confronting Climate Uncertainty in Water Resource Planning and Project Design: the Decision Tree Framework" which provide guidance of vulnerability assessments. It guides practitioners through a "Level of Concern" analysis where climate vulnerabilities are analyzed to produce actionable alternatives and decisions.

Climate Modeling and Analysis with Decision Makers in Mind

NASA Astrophysics Data System (ADS)

Jones, A. D.; Jagannathan, K.; Calvin, K. V.; Lamarque, J. F.; Ullrich, P. A.

2016-12-01

There is a growing need for information about future climate conditions to support adaptation planning across a wide range of sectors and stakeholder communities. However, our principal tools for understanding future climate - global Earth system models - were not developed with these user needs in mind, nor have we developed transparent methods for evaluating and communicating the credibility of various climate information products with respect to the climate characteristics that matter most to decision-makers. Several recent community engagements have identified a need for "co-production" of knowledge among stakeholders and scientists. Here we highlight some of the barriers to communication and collaboration that must be overcome to improve the dialogue among researchers and climate adaptation practitioners in a meaningful way. Solutions to this challenge are two-fold: 1) new institutional arrangements and collaborative mechanisms designed to improve coordination and understanding among communities, and 2) a research agenda that explicitly incorporates stakeholder needs into model evaluation, development, and experimental design. We contrast the information content in global-scale model evaluation exercises with that required for in specific decision contexts, such as long-term agricultural management decisions. Finally, we present a vision for advancing the science of model evaluation in the context of predicting decision-relevant hydroclimate regime shifts in North America.

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

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

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

10 CFR 1003.26 - Decision and Order.

Code of Federal Regulations, 2010 CFR

2010-01-01

... § 1003.26 Decision and Order. (a) Upon consideration of the application and other relevant information... the relevant facts and the legal basis of the order. The Decision and Order shall provide that any...

Climate Engine - Monitoring Drought with Google Earth Engine

NASA Astrophysics Data System (ADS)

Hegewisch, K.; Daudert, B.; Morton, C.; McEvoy, D.; Huntington, J. L.; Abatzoglou, J. T.

2016-12-01

Drought has adverse effects on society through reduced water availability and agricultural production and increased wildfire risk. An abundance of remotely sensed imagery and climate data are being collected in near-real time that can provide place-based monitoring and early warning of drought and related hazards. However, in an era of increasing wealth of earth observations, tools that quickly access, compute, and visualize archives, and provide answers at relevant scales to better inform decision-making are lacking. We have developed ClimateEngine.org, a web application that uses Google's Earth Engine platform to enable users to quickly compute and visualize real-time observations. A suite of drought indices allow us to monitor and track drought from local (30-meters) to regional scales and contextualize current droughts within the historical record. Climate Engine is currently being used by U.S. federal agencies and researchers to develop baseline conditions and impact assessments related to agricultural, ecological, and hydrological drought. Climate Engine is also working with the Famine Early Warning Systems Network (FEWS NET) to expedite monitoring agricultural drought over broad areas at risk of food insecurity globally.

Psychological defense, ideological hideaway, or rational reckoning? The role of uncertainty in local adaptation to climate change

NASA Astrophysics Data System (ADS)

Moser, S. C.

2011-12-01

As adaptation planning is rising rapidly on the agenda of decision-makers, the need for adequate information to inform those decisions is growing. Locally relevant climate change (as well as related impacts and vulnerability) information, however, is difficult to obtain and that which can be obtained carries the burden of significant scientific uncertainty. This paper aims to assess how important such uncertainty is in adaptation planning, decision-making, and related stakeholder engagement. Does uncertainty actually hinder adaptation planning? Is scientific uncertainty used to postpone decisions reflecting ideologically agendas? Or is it a convenient defense against cognitive and affective engagement with the emerging and projected - and in some cases daunting - climate change risks? To whom does such uncertainty matter and how important is it relative to other challenges decision-makers and stakeholders face? The paper draws on four sources of information to answer these questions: (1) a statewide survey of California coastal managers conducted in summer 2011, (2) years of continual engagement with, and observation of, decision-makers in local adaptation efforts, (3) findings from focus groups with lay individuals in coastal California; and (4) a review of relevant adaptation literature to guide and contextualize the empirical research. The findings entail some "inconvenient truths" for those claiming critical technical or political importance. Rather, the insights suggest that some uncertainties matter more than others; they matter at certain times, but not at others; and they matter to some decision-makers, but not to others. Implications for scientists communicating and engaging with communities are discussed.

Climate services to improve public health.

PubMed

Jancloes, Michel; Thomson, Madeleine; Costa, María Mánez; Hewitt, Chris; Corvalan, Carlos; Dinku, Tufa; Lowe, Rachel; Hayden, Mary

2014-04-25

A high level expert panel discussed how climate and health services could best collaborate to improve public health. This was on the agenda of the recent Third International Climate Services Conference, held in Montego Bay, Jamaica, 4-6 December 2013. Issues and challenges concerning a demand led approach to serve the health sector needs, were identified and analysed. Important recommendations emerged to ensure that innovative collaboration between climate and health services assist decision-making processes and the management of climate-sensitive health risk. Key recommendations included: a move from risk assessment towards risk management; the engagement of the public health community with both the climate sector and development sectors, whose decisions impact on health, particularly the most vulnerable; to increase operational research on the use of policy-relevant climate information to manage climate- sensitive health risks; and to develop in-country capacities to improve local knowledge (including collection of epidemiological, climate and socio-economic data), along with institutional interaction with policy makers.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Structural Model Error and Decision Relevancy

NASA Astrophysics Data System (ADS)

Goldsby, M.; Lusk, G.

2017-12-01

The extent to which climate models can underwrite specific climate policies has long been a contentious issue. Skeptics frequently deny that climate models are trustworthy in an attempt to undermine climate action, whereas policy makers often desire information that exceeds the capabilities of extant models. While not skeptics, a group of mathematicians and philosophers [Frigg et al. (2014)] recently argued that even tiny differences between the structure of a complex dynamical model and its target system can lead to dramatic predictive errors, possibly resulting in disastrous consequences when policy decisions are based upon those predictions. They call this result the Hawkmoth effect (HME), and seemingly use it to rebuke rightwing proposals to forgo mitigation in favor of adaptation. However, a vigorous debate has emerged between Frigg et al. on one side and another philosopher-mathematician pair [Winsberg and Goodwin (2016)] on the other. On one hand, Frigg et al. argue that their result shifts the burden to climate scientists to demonstrate that their models do not fall prey to the HME. On the other hand, Winsberg and Goodwin suggest that arguments like those asserted by Frigg et al. can be, if taken seriously, "dangerous": they fail to consider the variety of purposes for which models can be used, and thus too hastily undermine large swaths of climate science. They put the burden back on Frigg et al. to show their result has any effect on climate science. This paper seeks to attenuate this debate by establishing an irenic middle position; we find that there is more agreement between sides than it first seems. We distinguish a `decision standard' from a `burden of proof', which helps clarify the contributions to the debate from both sides. In making this distinction, we argue that scientists bear the burden of assessing the consequences of HME, but that the standard Frigg et al. adopt for decision relevancy is too strict.

Selection of climate policies under the uncertainties in the Fifth Assessment Report of the IPCC

NASA Astrophysics Data System (ADS)

Drouet, L.; Bosetti, V.; Tavoni, M.

2015-10-01

Strategies for dealing with climate change must incorporate and quantify all the relevant uncertainties, and be designed to manage the resulting risks. Here we employ the best available knowledge so far, summarized by the three working groups of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5; refs , , ), to quantify the uncertainty of mitigation costs, climate change dynamics, and economic damage for alternative carbon budgets. We rank climate policies according to different decision-making criteria concerning uncertainty, risk aversion and intertemporal preferences. Our findings show that preferences over uncertainties are as important as the choice of the widely discussed time discount factor. Climate policies consistent with limiting warming to 2 °C above preindustrial levels are compatible with a subset of decision-making criteria and some model parametrizations, but not with the commonly adopted expected utility framework.

Motivators and Barriers to Incorporating Climate Change-Related Health Risks in Environmental Health Impact Assessment

PubMed Central

Turner, Lyle R.; Alderman, Katarzyna; Connell, Des; Tong, Shilu

2013-01-01

Climate change presents risks to health that must be addressed by both decision-makers and public health researchers. Within the application of Environmental Health Impact Assessment (EHIA), there have been few attempts to incorporate climate change-related health risks as an input to the framework. This study used a focus group design to examine the perceptions of government, industry and academic specialists about the suitability of assessing the health consequences of climate change within an EHIA framework. Practitioners expressed concern over a number of factors relating to the current EHIA methodology and the inclusion of climate change-related health risks. These concerns related to the broad scope of issues that would need to be considered, problems with identifying appropriate health indicators, the lack of relevant qualitative information that is currently incorporated in assessment and persistent issues surrounding stakeholder participation. It was suggested that improvements are needed in data collection processes, particularly in terms of adequate communication between environmental and health practitioners. Concerns were raised surrounding data privacy and usage, and how these could impact on the assessment process. These findings may provide guidance for government and industry bodies to improve the assessment of climate change-related health risks. PMID:23525029

Motivators and barriers to incorporating climate change-related health risks in environmental health impact assessment.

PubMed

Turner, Lyle R; Alderman, Katarzyna; Connell, Des; Tong, Shilu

2013-03-22

Climate change presents risks to health that must be addressed by both decision-makers and public health researchers. Within the application of Environmental Health Impact Assessment (EHIA), there have been few attempts to incorporate climate change-related health risks as an input to the framework. This study used a focus group design to examine the perceptions of government, industry and academic specialists about the suitability of assessing the health consequences of climate change within an EHIA framework. Practitioners expressed concern over a number of factors relating to the current EHIA methodology and the inclusion of climate change-related health risks. These concerns related to the broad scope of issues that would need to be considered, problems with identifying appropriate health indicators, the lack of relevant qualitative information that is currently incorporated in assessment and persistent issues surrounding stakeholder participation. It was suggested that improvements are needed in data collection processes, particularly in terms of adequate communication between environmental and health practitioners. Concerns were raised surrounding data privacy and usage, and how these could impact on the assessment process. These findings may provide guidance for government and industry bodies to improve the assessment of climate change-related health risks.

Climate change and public health policy: translating the science.

PubMed

Braks, Marieta; van Ginkel, Rijk; Wint, William; Sedda, Luigi; Sprong, Hein

2013-12-19

Public health authorities are required to prepare for future threats and need predictions of the likely impact of climate change on public health risks. They may get overwhelmed by the volume of heterogeneous information in scientific articles and risk relying purely on the public opinion articles which focus mainly on global warming trends, and leave out many other relevant factors. In the current paper, we discuss various scientific approaches investigating climate change and its possible impact on public health and discuss their different roles and functions in unraveling the complexity of the subject. It is not our objective to review the available literature or to make predictions for certain diseases or countries, but rather to evaluate the applicability of scientific research articles on climate change to evidence-based public health decisions. In the context of mosquito borne diseases, we identify common pitfalls to watch out for when assessing scientific research on the impact of climate change on human health. We aim to provide guidance through the plethora of scientific papers and views on the impact of climate change on human health to those new to the subject, as well as to remind public health experts of its multifactorial and multidisciplinary character.

Climate Change and Public Health Policy: Translating the Science

PubMed Central

Braks, Marieta; van Ginkel, Rijk; Wint, William; Sedda, Luigi; Sprong, Hein

2013-01-01

Public health authorities are required to prepare for future threats and need predictions of the likely impact of climate change on public health risks. They may get overwhelmed by the volume of heterogeneous information in scientific articles and risk relying purely on the public opinion articles which focus mainly on global warming trends, and leave out many other relevant factors. In the current paper, we discuss various scientific approaches investigating climate change and its possible impact on public health and discuss their different roles and functions in unraveling the complexity of the subject. It is not our objective to review the available literature or to make predictions for certain diseases or countries, but rather to evaluate the applicability of scientific research articles on climate change to evidence-based public health decisions. In the context of mosquito borne diseases, we identify common pitfalls to watch out for when assessing scientific research on the impact of climate change on human health. We aim to provide guidance through the plethora of scientific papers and views on the impact of climate change on human health to those new to the subject, as well as to remind public health experts of its multifactorial and multidisciplinary character. PMID:24452252

Developing Effective Communications about Extreme Weather Risks.

NASA Astrophysics Data System (ADS)

Bruine de Bruin, W.

2014-12-01

Members of the general public often face complex decisions about the risks that they face, including those associated with extreme weather and climate change adaptation. Scientific experts may be asked to develop communications with the goal of improving people's understanding of weather and climate risks, and informing people's decisions about how to protect against these risks. Unfortunately, scientific experts' communication efforts may fail if they lack information about what people need or want to know to make more informed decisions or what wording people prefer use to describe relevant concepts. This presentation provides general principles for developing effective risk communication materials that aim for widespread dissemination, such as brochures and websites. After a brief review of the social science evidence on how to design effective risk communication materials, examples will focus on communications about extreme weather events and climate change. Specifically, data will be presented from ongoing projects on flood risk perception, public preparedness for heat waves, and public perceptions of climate change. The presentation will end with specific recommendations about how to improve recipients' understanding about risks and inform decisions. These recommendations should be useful to scientific experts who aim to communicate about extreme weather, climate change, or other risks.

Climate services: Lessons learned and future prospects

NASA Astrophysics Data System (ADS)

Brasseur, Guy P.; Gallardo, Laura

2016-03-01

This perspective paper reviews progress made in the last decades to enhance the communication and use of climate information relevant to the political and economic decision process. It focuses, specifically, on the creation and development of climate services, and highlights a number of difficulties that have limited the success of these services. Among them are the insufficient awareness by societal actors of their vulnerability to climate change, the lack of relevant products and services offered by the scientific community, the inappropriate format in which the information is provided, and the inadequate business model adopted by climate services. The authors suggest that, to be effective, centers should host within the same center a diversity of staff including experts in climate science, specialists in impact, adaptation, and vulnerability, representatives of the corporate world, agents of the public service as well as social managers and communication specialists. The role and importance of environmental engineering is emphasized.

Enhancing the Value of the Federal Climate-Relevant Data Through the Climate Data Initiative

NASA Astrophysics Data System (ADS)

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

2016-12-01

The Climate Data Initiative (CDI), launched by the Obama Administration in March of 2014, is an effort to leverage the extensive open Federal data to spur innovation and private-sector entrepreneurship around climate resilience. As part of this initiative the federal agencies identified key climate-relevant datasets and made them discoverable through an online catalog at data.gov/climate. Although this was a critical and foundational step to improve the discoverability to these federal data, enhancements to its accessibility and usability require a deeper understanding of the data needs of the different user communities. More recently, the focus of the CDI project has evolved toward extended engagement with communities of resilience trough the identification of use-cases. This effort aims to guide the next steps of the CDI project to make the CDI resources more easily integrated into decision support systems

10 CFR 430.56 - Decision and order.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Exemptions § 430.56 Decision and order. (a) Upon consideration of the application and other relevant information received or obtained, the Secretary shall issue an order granting or denying the application. (b) The order shall include a written statement setting forth the relevant facts and the legal basis of...

Identifying Decision-Makers’ Science Needs for Adaptation to Climate-Related Impacts on Forest Ecosystem Services

NASA Astrophysics Data System (ADS)

Gordon, E.; Lukas, J.

2009-12-01

Through the Western Water Assessment RISA program, we are conducting a research project that will produce science synthesis information to help local, state, and federal decision-makers in Colorado and Wyoming develop adaptation strategies to deal with climate-related threats to forest ecosystem services, in particular bark beetle infestations and stand-replacing wildfires. We begin by using the problem orientation framework, a policy sciences methodology, to understand how decision-makers can most effectively address policy problems that threaten the attainment of socially accepted goals. By applying this framework to the challenges facing decision-makers, we more accurately identify specific areas where scientific research can improve decision-making. WWA researchers will next begin to connect decision-makers with relevant scientific literature and identify specific areas of future scientific research that will be most effective at addressing their needs.

Climate Information Needs for Financial Decision Making

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

Higgins, Paul

Climate Information Needs for Financial Decision Making (Final Report) This Department of Energy workshop award (grant #DE-SC0008480) provided primary support for the American Meteorological Society’s study on climate information needs for financial decision making. The goal of this study was to help advance societal decision making by examining the implications of climate variability and change on near-term financial investments. We explored four key topics: 1) the conditions and criteria that influence returns on investment of major financial decisions, 2) the climate sensitivity of financial decisions, 3) climate information needs of financial decision makers, and 4) potential new mechanisms to promotemore » collaboration between scientists and financial decision makers. Better understanding of these four topics will help scientists provide the most useful information and enable financial decision makers to use scientific information most effectively. As a result, this study will enable leaders in business and government to make well-informed choices that help maximize long-term economic success and social wellbeing in the United States The outcomes of the study include a workshop, which brought together leaders from the scientific and financial decision making communities, a publication of the study report, and a public briefing of the results to the policy community. In addition, we will present the results to the scientific community at the AMS Annual Meeting in February, 2014. The study results were covered well by the media including Bloomberg News and E&E News. Upon request, we also briefed the Office of Science Technology Policy (OSTP) and the Council on Environmental Quality (CEQ) on the outcomes. We presented the results to the policy community through a public briefing in December on Capitol Hill. The full report is publicly available at www.ametsoc.org/cin. Summary of Key Findings The United States invests roughly $1.5 trillion U.S. dollars (USD) in capital assets each year across the public and private sectors (Orszag 2008; United States Census Bureau 2013). Extreme weather events create and exacerbate risks to these financial investments by contributing to: • Direct physical impacts on the investments themselves • Degradation of critical supporting infrastructure • Changes in the availability of key natural resources • Changes to workforce availability or capacity • Changes in the customer base • Supply chain disruptions • Legal liability • Shifts in the regulatory environment • Reductions in credit ratings Even small changes in weather can impact operations in critical economic sectors. As a result, maximizing returns on financial investments depends on accurately understanding and effectively accounting for these risks. Climate variability and change can either exacerbate existing risks or cause new sources of risk to emerge. Managing these risks most effectively will depend on scientific advances and increases in the capacity of financial decision makers to use the scientific knowledge that results. Barriers to using climate information must also be overcome. This study proposes three predefined levels of certainty for communicating about weather and climate risks: 1) possible (i.e., unknown likelihood or less than 50% chance of occurrence), 2) probable (greater than 50% chance of occurrence), and 3) effectively certain (at least 95% chance of occurrence). For example, it is effectively certain that a change in climate will alter weather patterns. It is probable that climate warming will cause increases in the intensity of some extreme events. It is possible that climate change will cause major and widespread disruptions to key planetary life-support services. Key recommendations of this study: 1) Identify climate-related risks and opportunities for financial decision making. 2) Create a framework to translate scientific information in clear and actionable terms for financial decision makers. 3) Analyze existing climate assessments and translate projected impacts into possible, probable, and effectively certain impacts. 4) Improve climate projections with respect to precipitation (timing, amount, and intensity), extreme events, and tails of probability distributions (i.e., low-probability but high-consequence events). 5) Increase spatial resolution of climate projections in order to provide climate information at the scale most relevant to financial investments. 6) Improve projections of the societal consequences of climate impacts through integrated assessments of physical, natural, and social sciences. 7) Create a user-friendly information repository and portal that provides easy access to information relevant to financial decision making. 8) Create and maintain opportunities to bring together financial decision makers, scientists, and service providers. Near-term financial decisions have long-term implications for the United States’ social and economic well-being that depend, in part, on climate variability and change. Investments will be most successful, and will advance the interests of society most effectively, if they are grounded in the best available knowledge & understanding.« less

A Framework for Bridging Scientists, Knowledge Brokers and Local Decision Makers in State-level Climate Assessments

NASA Astrophysics Data System (ADS)

Galford, G. L.; Nash, J. L.

2016-12-01

Large-scale analyses like the National Climate Assessment (NCA) contain a wealth of information critical to national and regional responses to climate change but tend to be insufficiently detailed for action at state or local levels. Many states now develop assessments (SCAs) to provide relevant, actionable information to state and local authorities. These assessments generate new or additional primary information, build networks and inform stakeholders. Based on our experience in the Vermont Climate Assessment (VCA), we present a SCA framework to engage local decision makers, using a fluid network of scientific experts and knowledge brokers to conduct subject area prioritization, data analysis, and writing. Knowledge brokers bridged the scientific and stakeholder communities, providing a two-way flow of information by capitalizing on their existing networks. Rich citizen records of climate and climate change impacts associated a human voice, a memorable story, or personal observation with a climate record, improving climate information salience. This engagement process that created salient climate information perceived as credible and legitimate by local and state decision makers. We present this framework as an effective structure for SCAs to foster interaction among scientists, knowledge brokers and stakeholders. We include a qualitative impact evaluation and lessons learned for future SCAs.

Communicating the Needs of Climate Change Policy Makers to Scientists

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Escobar, Vanessa M.; Lovell, Heather

2012-01-01

This chapter will describe the challenges that earth scientists face in developing science data products relevant to decision maker and policy needs, and will describe strategies that can improve the two-way communication between the scientist and the policy maker. Climate change policy and decision making happens at a variety of scales - from local government implementing solar homes policies to international negotiations through the United Nations Framework Convention on Climate Change. Scientists can work to provide data at these different scales, but if they are not aware of the needs of decision makers or understand what challenges the policy maker is facing, they are likely to be less successful in influencing policy makers as they wished. This is because the science questions they are addressing may be compelling, but not relevant to the challenges that are at the forefront of policy concerns. In this chapter we examine case studies of science-policy partnerships, and the strategies each partnership uses to engage the scientist at a variety of scales. We examine three case studies: the global Carbon Monitoring System pilot project developed by NASA, a forest biomass mapping effort for Silvacarbon project, and a forest canopy cover project being conducted for forest management in Maryland. In each of these case studies, relationships between scientists and policy makers were critical for ensuring the focus of the science as well as the success of the decision-making.

Applications of geographic information systems (GIS) for transportation and climate change

DOT National Transportation Integrated Search

2011-08-31

This report describes the current practice and application of GIS technologies for integrating climate change into the transportation decision-making process. It examines how select state, regional, and local agencies are using GIS to analyze, mitiga...

Bridging the Gap with the Pacific Climate Impacts Consortium (PCIC)

NASA Astrophysics Data System (ADS)

Rodenhuis, D.; Kangasniemi, B.; Murdock, T. Q.

2008-12-01

The difficulty of translating scientific results into useful information defines the abyss that is addressed by a new PCIC consortium of academics-government-industry at the University of Victoria. The scope of the consortium is research applications of climate variability and change, including extreme weather events, for climate impacts and adaptation in Pacific North America. During the past 3 years traditional tools of collaboration have been utilized--both with the science community and with stakeholders. Some success in networking with Provinces, the States, and with national institutions has been achieved. Limitations of governance/management, resources, and cooperation have been identified. Input and statements of need from the climate stakeholders in government and industry has been achieved, but only in specific areas - water/power generation, forestry, communities. Three examples will be given of successful engagement of stakeholders. These examples demonstrate how difficult it is to summarize effectiveness, relevance, and capacity. This experience, and early decisions on scope, focus and priorities have taken us this far, but some exceptional challenges have arisen due to the stakeholder demand for new (geophysical) design conditions for the 21st century.

Enhancing the usability of seasonal to decadal (S2D) climate information - an evidence-based framework for the identification and assessment of sector-specific vulnerabilities

NASA Astrophysics Data System (ADS)

Funk, Daniel

2016-04-01

The successful provision of from seasonal to decadal (S2D) climate service products to sector-specific users is dependent on specific problem characteristics and individual user needs and decision-making processes. Climate information requires an impact on decision making to have any value (Rodwell and Doblas-Reyes, 2006). For that reason the knowledge of sector-specific vulnerabilities to S2D climate variability is very valuable information for both, climate service producers and users. In this context a concept for a vulnerability assessment framework was developed to (i) identify climate events (and especially their temporal scales) critical for sector-specific problems to assess the basic requirements for an appropriate climate-service product development; and to (ii) assess the potential impact or value of related climate information for decision-makers. The concept was developed within the EUPORIAS project (European Provision of Regional Impacts Assessments on Seasonal and Decadal Timescales) based on ten project-related case-studies from different sectors all over Europe. In the prevalent stage the framework may be useful as preliminary assessment or 'quick-scan' of the vulnerability of specific systems to climate variability in the context of S2D climate service provision. The assessment strategy of the framework is user-focused, using predominantly a bottom-up approach (vulnerability as state) but also a top-down approach (vulnerability as outcome) generally based on qualitative data (surveys, interviews, etc.) and literature research for system understanding. The starting point of analysis is a climate-sensitive 'critical situation' of the considered system which requires a decision and is defined by the user. From this basis the related 'critical climate conditions' are assessed and 'climate information needs' are derived. This mainly refers to the critical period of time of the climate event or sequence of events. The relevant period of time of problem-specific critical climate conditions may be assessed by the resilience of the system of concern, the response time of an interconnected system (i.e. top-down approach using a bottom-up methodology) or alternatively, by the critical time-frame of decision-making processes (bottom-up approach). This approach counters the challenges for a vulnerability assessment of economic sectors to S2D climate events which originate from the inherent role of climate for economic sectors: climate may affect economic sectors as hazard, resource, production- or regulation factor. This implies, that climate dependencies are often indirect and nonlinear. Consequently, climate events which are critical for affected systems do not necessarily correlate with common climatological extremes. One important output of the framework is a classification system of 'climate-impact types' which classifies sector-specific problems in a systemic way. This system proves to be promising because (i) it reflects and thus differentiates the cause for the climate relevance of a specific problem (compositions of buffer factors); (ii) it integrates decision-making processes which proved to be a significant factor; (iii) it indicates a potential usability of S2D climate service products and thus integrates coping options, and (vi) it is a systemic approach which goes beyond the established 'snap-shot' of vulnerability assessments.

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

PubMed

Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

2018-01-22

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

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.

Violation of Students' Legal Rights as Correlate of Organization Climate in Imo State Secondary Schools, in Nigeria

ERIC Educational Resources Information Center

Anuna, M. C.; Mbonu, F. O.; Amanchukwu, R. N.

2013-01-01

The purpose of this study is to determine whether violation of students' legal rights has relationship with organizational climate in secondary schools in Imo State, Nigeria. Three research questions and null hypothesis were put forward and tested in order to make one's decisions on the issues investigated. Relevant literature to the study was…

Geographic information systems applications for climate change decision-making : Peer exchange summary report, Atlanta, Georgia, September 26-27, 2011

DOT National Transportation Integrated Search

2011-09-30

On September 26-27, 2011, the FHWA's Office of Planning sponsored a 1.5 day peer exchange focusing on the use of GIS to support transportation related climate change decisions. This report provides overviews of the presentations given at the peer exc...

Heat and Health in a Changing Climate: Building a Decision Support Tool for California Public Health Officials

NASA Astrophysics Data System (ADS)

Steinberg, N.

2017-12-01

There is considerable interest in overlaying climate projections with social vulnerability maps as a mechanism for targeting community adaptation efforts. Yet the identification of relevant factors for adaptation- and resilience-based decisions remain a challenge. Our findings show that successful adaptation interventions are more likely when factors are grouped and spatially represented. By designing a decision-support tool that is focused on informing long-term planning to mitigate the public health impacts of extreme heat, communities can more easily integrate climate, land use, and population characteristics into local planning processes. The ability to compare risks and potential health impacts across census tracts may also position local practitioners to leverage scarce resources. This presentation will discuss the information gaps identified by planners and public health practitioners throughout California and illustrate the spatial variations of key health risk factors.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The application of system dynamics modelling to environmental health decision-making and policy - a scoping review.

PubMed

Currie, Danielle J; Smith, Carl; Jagals, Paul

2018-03-27

Policy and decision-making processes are routinely challenged by the complex and dynamic nature of environmental health problems. System dynamics modelling has demonstrated considerable value across a number of different fields to help decision-makers understand and predict the dynamic behaviour of complex systems in support the development of effective policy actions. In this scoping review we investigate if, and in what contexts, system dynamics modelling is being used to inform policy or decision-making processes related to environmental health. Four electronic databases and the grey literature were systematically searched to identify studies that intersect the areas environmental health, system dynamics modelling, and decision-making. Studies identified in the initial screening were further screened for their contextual, methodological and application-related relevancy. Studies deemed 'relevant' or 'highly relevant' according to all three criteria were included in this review. Key themes related to the rationale, impact and limitation of using system dynamics in the context of environmental health decision-making and policy were analysed. We identified a limited number of relevant studies (n = 15), two-thirds of which were conducted between 2011 and 2016. The majority of applications occurred in non-health related sectors (n = 9) including transportation, public utilities, water, housing, food, agriculture, and urban and regional planning. Applications were primarily targeted at micro-level (local, community or grassroots) decision-making processes (n = 9), with macro-level (national or international) decision-making to a lesser degree. There was significant heterogeneity in the stated rationales for using system dynamics and the intended impact of the system dynamics model on decision-making processes. A series of user-related, technical and application-related limitations and challenges were identified. None of the reported limitations or challenges appeared unique to the application of system dynamics within the context of environmental health problems, but rather to the use of system dynamics in general. This review reveals that while system dynamics modelling is increasingly being used to inform decision-making related to environmental health, applications are currently limited. Greater application of system dynamics within this context is needed before its benefits and limitations can be fully understood.

Water Resources Management and Hydrologic Design Under Uncertain Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Teegavarapu, R. S.

2008-05-01

The impact of climate change on hydrologic design and management of water resource systems could be one of the important challenges faced by future practicing hydrologists and water resources managers. Many water resources managers currently rely on the historical hydrological data and adaptive real-time operations without consideration of the impact of climate change on major inputs influencing the behavior of hydrologic systems and the operating rules. Issues such as risk, reliability and robustness of water resources systems under different climate change scenarios were addressed in the past. However, water resources management with the decision maker's preferences attached to climate change has never been dealt with. This presentation discusses issues related to impacts of climate change on water resources management and application of a soft-computing approach, fuzzy set theory, for climate-sensitive management of water resources systems. A real-life case study example is presented to illustrate the applicability of soft-computing approach for handling the decision maker's preferences in accepting or rejecting the magnitude and direction of climate change.

Financing Education in a Climate of Change. Third Edition.

ERIC Educational Resources Information Center

Burrup, Percy E.; Brimley, Vern, Jr.

Education is declared to be an investment in human capital. Reform in school finance systems is long overdue in many states, but much progress has been made, and will yet be made, due to far-reaching decisions in a number of relevant court cases in the 1970s. To provide practical guidelines and cost-effective decision-making techniques for…

Localizing drought monitoring products to support agricultural climate service advisories in South Asia

NASA Astrophysics Data System (ADS)

Qamer, F. M.; Matin, M. A.; Yadav, N. K.; Bajracharya, B.; Zaitchik, B. F.; Ellenburg, W. L.; Krupnik, T. J.; Hussain, G.

2017-12-01

The Fifth Assessment Report of the Intergovernmental Panel on Climate Change identifies drought as one of the major climate risks in South Asia. During past two decades, a large amount of climate data have been made available by the scientific community, but the deployment of climate information for local level and agricultural decision making remains less than optimal. The provisioning of locally calibrated, easily accessible, decision-relevant and user-oriented information, in the form of drought advisory service could help to prepare communities to reduce climate vulnerability and increase resilience. A collaborative effort is now underway to strengthen existing and/or establish new drought monitoring and early warning systems in Afghanistan, Bangladesh, Nepal and Pakistan by incorporating standard ground-based observations, earth observation datasets, and numerical forecast models. ICT-based agriculture drought monitoring platforms, hosted at national agricultural and meteorological institutions, are being developed and coupled with communications and information deployment strategies to enable the rapid and efficient deployment of information that farmers can understand, interpret, and act on to adapt to anticipated droughts. Particular emphasis is being placed on the calibration and validation of data products through retrospective analysis of time series data, in addition to the installation of automatic weather station networks. In order to contextualize monitoring products to that they may be relevant for farmers' primary cropping systems, district level farming practices calendars are being compiled and validated through focus groups and surveys to identify the most important times and situations during which farmers can adapt to drought. High-resolution satellite crop distribution maps are under development and validation to add value to these efforts. This programme also aims to enhance capacity of agricultural extension staff to better understand climate information, probabilistic forecasts, related technologies, and adaptation strategies, in addition to equipping them with increased capacity to convey drought risks to farmers and improve climate related decision making.

Forest climate change Vulnerability and Adaptation Assessment in Himalayas

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Shrestha, H. L.; Agarwal, N. K.; Choudhurya, D.; Gilani, H.; Dhonju, H. K.; Murthy, M. S. R.

2014-11-01

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

NASA Astrophysics Data System (ADS)

Lissner, T. K.; Reusser, D. E.; Schewe, J.; Lakes, T.; Kropp, J. P.

2014-10-01

Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models, as well as greenhouse gas scenarios, are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure what is referred to here as AHEAD (Adequate Human livelihood conditions for wEll-being And Development). Based on a trans-disciplinary sample of concepts addressing human well-being and livelihoods, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows for the uncertainty of climate and impact model projections to be identified and differentiated. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that livelihood conditions are compromised by water scarcity in 34 countries. However, more often, AHEAD fulfilment is limited through other elements. The analysis shows that the water-specific uncertainty ranges of the model output are outside relevant thresholds for AHEAD for 65 out of 111 countries, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. In 46 of the countries in the analysis, water-specific uncertainty is relevant to AHEAD. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy decisions.

The World Climate Project: Bringing the UN Climate Negotiations to Classrooms, Boardrooms, and Living Rooms Near You

NASA Astrophysics Data System (ADS)

Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

2015-12-01

As a simulation-based role-playing exercise, World Climate provides an opportunity for participants to have an immersive experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the geophysical dynamics of the climate system, through an interactive computer simulation. In June 2015, we launched the World Climate Project with the intent of bringing this powerful tool to students, citizens, and decision-makers across government, NGO, and private sectors around the world. Within a period of six weeks from the launch date, 440 educators from 36 states and 56 countries have enrolled in the initiative, offering the potential to reach tens of thousands of participants around the world. While this project is clearly in its infancy, we see several characteristics that may be contributing to widespread interest in it. These factors include the ease-of-use, real-world relevance, and scientific rigor of the decision-support simulation, C-ROADS, that frames the World Climate Exercise. Other characteristics of World Climate include its potential to evoke an emotional response that is arousing and inspirational and its use of positive framing and a call to action. Similarly, the World Climate Project takes a collaborative approach, enabling educators to be innovators and valued contributors and regularly communicating with people who join the initiative through webinars, social media, and resources.

Translational Environmental Research: Improving the Usefulness and Usability of Research Results

NASA Astrophysics Data System (ADS)

Garfin, G.

2008-12-01

In recent years, requests for proposals more frequently emphasize outreach to stakeholder communities, decision support, and science that serves societal needs. Reports from the National Academy of Sciences and Western States Water Council emphasize the need for science translation and outreach, in order to address societal concerns with climate extremes, such as drought, the use of climate predictions, and the growing challenges of climate change. In the 1990s, the NOAA Climate Program Office developed its Regional Integrated Sciences and Asssessments program to help bridge the gap between climate science (notably, seasonal predictions) and society, to improve the flow of information to stakeholders, and to increase the relevance of climate science to inform decisions. During the same time period, the National Science Foundation initiated multi-year Science and Technology Centers and Decision Making Under Uncertainty Centers, with similar goals, but different metrics of success. Moreover, the combination of population growth, climate change, and environmental degradation has prompted numerous research initiatives on linking knowledge and action for sustainable development. This presentation reviews various models and methodologies for translating science results from field, lab, or modeling work to use by society. Lessons and approaches from cooperative extension, boundary organizations, co-production of science and policy, and medical translational research are examined. In particular, multi-step translation as practiced within the health care community is examined. For example, so- called "T1" (translation 1) research moves insights from basic science to clinical research; T2 research evaluates the effectiveness of clinical practice, who benefits from promising care regimens, and develops tools for clinicians, patients, and policy makers. T3 activities test the implementation, delivery, and spread of research results and clinical practices in order to foster policy changes and improve general health. Parallels in environmental sciences might be TER1 (translational environmental research 1), basic insights regarding environmental processes and relationships between environmental changes and their causes. TER2, applied environmental research, development of best practices, and development of decision support tools. TER3, might include usability and impact evaluation, effective outreach and implementation of best practices, and application of research insights to public policy and institutional change. According to the medical literature, and in anecdotal evidence from end-to-end environmental science, decision-maker and public involvement in these various forms of engaged research decreases the lag between scientific discovery and implementation of discoveries in operational practices, information tools, and organizational and public policies.

Cal-Adapt: California's Climate Data Resource and Interactive Toolkit

NASA Astrophysics Data System (ADS)

Thomas, N.; Mukhtyar, S.; Wilhelm, S.; Galey, B.; Lehmer, E.

2016-12-01

Cal-Adapt is a web-based application that provides an interactive toolkit and information clearinghouse to help agencies, communities, local planners, resource managers, and the public understand climate change risks and impacts at the local level. The website offers interactive, visually compelling, and useful data visualization tools that show how climate change might affect California using downscaled continental climate data. Cal-Adapt is supporting California's Fourth Climate Change Assessment through providing access to the wealth of modeled and observed data and adaption-related information produced by California's scientific community. The site has been developed by UC Berkeley's Geospatial Innovation Facility (GIF) in collaboration with the California Energy Commission's (CEC) Research Program. The Cal-Adapt website allows decision makers, scientists and residents of California to turn research results and climate projections into effective adaptation decisions and policies. Since its release to the public in June 2011, Cal-Adapt has been visited by more than 94,000 unique visitors from over 180 countries, all 50 U.S. states, and 689 California localities. We will present several key visualizations that have been employed by Cal-Adapt's users to support their efforts to understand local impacts of climate change, indicate the breadth of data available, and delineate specific use cases. Recently, CEC and GIF have been developing and releasing Cal-Adapt 2.0, which includes updates and enhancements that are increasing its ease of use, information value, visualization tools, and data accessibility. We showcase how Cal-Adapt is evolving in response to feedback from a variety of sources to present finer-resolution downscaled data, and offer an open API that allows other organization to access Cal-Adapt climate data and build domain specific visualization and planning tools. Through a combination of locally relevant information, visualization tools, and access to primary data, Cal-Adapt allows users to investigate how the climate is projected to change in their areas of interest.

Coordinated Development and Deployment of Scenarios for Sustained Assessment

NASA Astrophysics Data System (ADS)

Lipschultz, F.; Weaver, C. P.; Leidner, A. K.; Delgado, A.; Grambsch, A.

2017-12-01

There has been a clear need for a more coordinated Federal government approach for authoritative, climate-relevant scenarios to support growing demands by decision-makers, to meet stakeholder needs for consistent approaches and guidance, and to better address the needs of the impacts, adaptation and vulnerability community. To begin to satisfy these decision-support needs, in early 2015 the U.S. Global Change Research Program (USGCRP) began coordinated production of scenario information for use across a suite of USGCRP activities. These have been implemented in the 4th National Climate Assessment (NCA4), the Climate Science Special Report and the Climate Resilience Toolkit (CRT), all of which are intended to help better organize, summarize, and communicate science to decision-makers as they think about our future. First, USGCRP introduced and implemented an explicit risk-framing approach across the entire scenario enterprise to encourage exploration of tail risks. A suite of scenario products was developed framed around three simplified storylines: `Lower', `Higher', and `Upper Bound' departures from current baselines. Second, USGCRP developed future climate information for the U.S. using Representative Concentration Pathway (RCP) 8.5 and RCP 4.5, including a weighted mean of Global Climate Models and adoption of an improved statistical downscaling approach across USGCRP products. Additional variables were derived from the downscaled parameters for use across USGCRP reports and in the CRT's Climate Explorer tool. Third, and given the need to address other tightly-coupled global changes in a more integrated way, a set of population, housing density, and impervious surface projections were developed based on global scenarios. In addition, USGCRP and the National Ocean Council developed scenarios of future sea-level rise and coastal-flood hazard for the U.S. and integrated them into existing Federal capabilities to support preparedness planning. To better convey these scenario components, next steps include capability for dynamic interaction between NCA4 products and CRT to permit users to explore and customize relevant information for their decision at spatial scales that matter to them, as well as links to more in-depth CRT content.

Phylogeny and source climate impact seed dormancy and germination of restoration-relevant forb species

PubMed Central

Williams, Evelyn; Bilge, Arman; Kramer, Andrea T.

2018-01-01

For many species and seed sources used in restoration activities, specific seed germination requirements are often unknown. Because seed dormancy and germination traits can be constrained by phylogenetic history, related species are often assumed to have similar traits. However, significant variation in these traits is also present within species as a result of adaptation to local climatic conditions. A growing number of studies have attempted to disentangle how phylogeny and climate influence seed dormancy and germination traits, but they have focused primarily on species-level effects, ignoring potential population-level variation. We examined the relationships between phylogeny, climate, and seed dormancy and germination traits for 24 populations of eight native, restoration-relevant forb species found in a wide range of climatic conditions in the Southwest United States. The seeds were exposed to eight temperature and stratification length regimes designed to mimic regional climatic conditions. Phylogenetic relatedness, overall climatic conditions, and temperature conditions at the site were all significantly correlated with final germination response, with significant among-population variation in germination response across incubation treatments for seven of our eight study species. Notably, germination during stratification was significantly predicted by precipitation seasonality and differed significantly among populations for seven species. While previous studies have not examined germination during stratification as a potential trait influencing overall germination response, our results suggest that this trait should be included in germination studies as well as seed sourcing decisions. Results of this study deepen our understanding of the relationships between source climate, species identity, and germination, leading to improved seed sourcing decisions for restorations. PMID:29401470

Are mobile health applications useful for supporting shared decision making in diagnostic and treatment decisions?

PubMed Central

Abbasgholizadeh Rahimi, Samira; Menear, Matthew; Robitaille, Hubert; Légaré, France

2017-01-01

ABSTRACT Mobile health (mHealth) applications intended to support shared decision making in diagnostic and treatment decisions are increasingly available. In this paper, we discuss some recent studies on mHealth applications with relevance to shared decision making. We discuss the potential advantages and disadvantages of using mHealth in shared decision making in various contexts, and suggest some directions for future research in this quickly expanding field. PMID:28838306

Scenario Planning Provides a Framework for Climate Change Adaptation in the National Park Service

NASA Astrophysics Data System (ADS)

Welling, L. A.

2012-12-01

Resource management decisions must be based on future expectations. Abundant evidence suggests climate change will have highly consequential effects on the Nation's natural and cultural resources, but specific impacts are difficult to accurately predict. This situation of too much information but not enough specificity can often lead to either paralysis or denial for decision makers. Scenario planning is an emerging tool for climate change adaptation that provides a structured framework for identifying and exploring critical drivers of change and their uncertain outcomes. Since 2007, the National Park Service (NPS) has been working with its partners to develop and apply a scenario-based approach for adaptation planning that integrates quantitative, model-driven, climate change projections with qualitative, participatory exercises to explore management and policy options under a range of future conditions. Major outcomes of this work are (1) increased understanding of key scientific results and uncertainties, (2) incorporation of alternative perspectives into park and landscape level planning, (3) identification of "no brainer" and "no gainer" actions, (4) strengthening of regional science-management partnerships, and (5) overall improved capacity for flexible decision making. The basic approach employed by NPS for scenario planning follows a typical adaptive management process: define the focal question, assess the relevant science, explore plausible futures, identify effective strategies, prioritize and implement actions, and monitor results. Many science and management partners contributed to the process, including NOAA Regional Integrated Science and Assessment teams (RISAs) and Regional Climate Centers (RCCs), USGS Research Centers, and other university and government scientists. The Global Business Network, an internationally recognized leader in scenario development, provided expert facilitation and training techniques. Climate science input is provided through global and regional circulation models and downscaling to arrive at climate driver information that is relevant for parks and the landscapes within which they are found. Considerable effort is necessary to synthesize the information and to effectively communicate uncertainties about both values and trend (e.g. scientists have higher confidence in the trend of temperature over a given time period than the value). Drivers that are determined to be highly consequential and uncertain are used to create management-relevant scenarios using various techniques, including a structured 2X2 matrix approach, a succession of rapid combinations using multiple variables, and the development of a base, "least change" scenario from which alternatives are then constructed. Socio-economic factors are also considered as essential factors that define the full decision environment within which management and policy decisions are made. Resulting scenarios incorporate information about impacts to natural and cultural resources as well as facilities and visitor experience. The NPS conducted prototypes for scenario planning in each of seven regions and has begun to incorporate elements of the process into all planning requirements. A significant outcome of this work is managers and scientists alike understand climate and ecosystem models provide tools for exploring the future rather than predicting it.

Developing a National Climate Indicators System to Track Climate Changes, Impacts, Vulnerabilities, and Preparedness

NASA Astrophysics Data System (ADS)

Kenney, M. A.; Janetos, A. C.; Arndt, D.; Chen, R. S.; Pouyat, R.; Anderson, S. M.

2013-12-01

The National Climate Assessment (NCA) is being conducted under the auspices of the U.S. Global Change Research Program (USGCRP), pursuant to the Global Change Research Act of 1990, Section 106, which requires a report to Congress every 4 years. Part of the vision, which is now under development, for the sustained National Climate Assessment (NCA) process is a system of physical, ecological, and societal indicators that communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness for the purpose of informing both decision makers and the public with scientifically valid information that is useful to inform decision-making processes such as the development and implementation of climate adaptation strategies in a particular sector or region. These indicators will be tracked as a part of ongoing assessment activities, with adjustments as necessary to adapt to changing conditions and understanding. The indicators will be reviewed and updated so that the system adapts to new information. The NCA indicator system is not intended to serve as a vehicle for documenting rigorous cause and effect relationships. It is reasonable, however, for it to serve as a guide to those factors that affect the evolution of variability and change in the climate system, the resources and sectors of concern that are affected by it, and how society chooses to respond. Different components of the end-to-end climate issue serve as categories within which to organize an end-to-end system of indicators: Greenhouse Gas Emissions and Sinks, Atmospheric Composition, Physical Climate Variability and Change, Sectors and Resources of Concern, and Adaptation and Mitigation Responses. This framing has several advantages. It can be used to identify the different components of the end-to-end climate issue that both decision-makers and researchers are interested in. It is independent of scale, and therefore allows the indicators themselves to be described at spatial scales that are the most relevant for their intended use. National decision-makers may find indicators of national greenhouse gas emissions to be informative; however, state or local decision-makers have the freedom in this framework to define indicators of state, regional, or local greenhouse emissions that are more relevant to their concerns. The framework is also independent of time scale and topics within the broad categories. It therefore allows indicators of different sectors to be developed, and allows the consideration of both indicators of current state, past trends, and leading indicators. In this talk we will discuss the general conceptual model for the system, the sector specific conceptual models, and indicators that will be included in the prototype end-to-end indicator system.

Developing a System of National Climate Assessment Indicators to Track Climate Change Impacts, Vulnerabilities, and Preparedness

NASA Astrophysics Data System (ADS)

Janetos, A. C.; Kenney, M. A.; Chen, R. S.; Arndt, D.

2012-12-01

The National Climate Assessment (NCA) is being conducted under the auspices of the U.S. Global Change Research Program (USGCRP), pursuant to the Global Change Research Act of 1990, Section 106, which requires a report to Congress every 4 years (http://globalchange.gov/what-we-do/assessment/). Part of the vision for the sustained National Climate Assessment (NCA) process is a system of physical, ecological, and societal indicators that communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness for the purpose of informing both decision makers and the public with scientifically valid information that is useful to inform decision-making processes such as the development and implementation of climate adaptation strategies in a particular sector or region. These indicators will be tracked as a part of ongoing assessment activities, with adjustments as necessary to adapt to changing conditions and understanding. The indicators will be reviewed and updated so that the system adapts to new information. The NCA indicator system is not intended to serve as a vehicle for documenting rigorous cause and effect relationships. It is reasonable, however, for it to serve as a guide to those factors that affect the evolution of variability and change in the climate system, the resources and sectors of concern that are affected by it, and how society chooses to respond. Different components of the end-to-end climate issue serve as categories within which to organize an end-to-end system of indicators: Greenhouse Gas Emissions and Sinks Atmospheric Composition Physical Climate Variability and Change Sectors and Resources of Concern Adaptation and Mitigation Responses This framing has several advantages. It can be used to identify the different components of the end-to-end climate issue that both decision-makers and researchers are interested in. It is independent of scale, and therefore allows the indicators themselves to be described at spatial scales that are the most relevant for their intended use. National decision-makers may find indicators of national greenhouse gas emissions to be informative; however, state or local decision-makers have the freedom in this framework to define indicators of state, regional, or local greenhouse emissions that are more relevant to their concerns. The framework is also independent of time scale and topics within the broad categories. It therefore allows indicators of different sectors to be developed, and allows the consideration of both indicators of current state, past trends, and leading indicators. In this talk we will discuss a number of existing candidate indicators that could be included in this framework as well as the research needed to fully develop an end-to-end indicator system.

The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB V1.0) Contribution to CMIP6

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Kovats, R. Sari;

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America

PubMed Central

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data. PMID:27275583

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America.

PubMed

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901-2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011-2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data.

Methane Leakage from Natural Gas Systems: Comparisons, Communication, and Policy Relevance (Invited)

NASA Astrophysics Data System (ADS)

Weber, C.; Clavin, C.; Mueller, K. L.

2013-12-01

Increases in domestic natural gas production from shale gas and tight oil resources have ignited a scientific and policy debate about the climate implications of increasing levels of natural gas utilization on a national and global scale. The debate has primarily centered on characterizing the life-cycle greenhouse gas emissions associated with natural gas electricity generation or transportation. As such, there has been significant recent attention to estimating upstream methane and CO2 emissions from natural gas production, processing, transmission, and distribution using either bottom-up inventory or top-down atmospheric methods ranging from regional to global scales. Due to the general scarcity of measured data, the highly variable production practices of the oil & gas industry, and the different geological conditions under which the industry operates, determining methane emissions (sometimes calculated as a 'leakage rate') and overall climate impact over a policy-relevant spatial and temporal scale has been highly challenging. This unsettled state of the science exists as energy and climate policy decisions are being made in tandem with scientific knowledge generation, while at the same time production practices continue to change in a quickly innovating industry. This research critically reviews the work to date on quantifying methane leakage and life-cycle greenhouse gas implications of unconventional onshore oil & gas compared to other fuels such as coal. We take the perspective of a national-level U.S. decision-maker and ask how different methods (inventories, device-level measurements, regional and national inversions) can contribute to the information needed to make informed energy and climate policy decision regarding unconventional resources. Different methods have different strengths, weaknesses, and uncertainties, and such differences must be accounted for properly to ensure usefulness. We find that most work to date has suffered from one or more of several flaws that decrease the policy applicability of scientific results. These include inconsistent metric definitions (particularly related to the 'methane leakage' metric), inconsistent comparisons between studies with different scopes and temporal and spatial boundaries, and a failure to properly distinguish between emissions associated with oil, gas, and other co-products. We conclude that in order for policy decisions to be made in the needed timeframe given the current speed of development, scientists from different communities must work together to develop common strategies for communicating results and interpreting differences between highly different methods. This represents a significant challenge but one that is imperative for atmospheric scientists, engineers, and policy analysts to jointly solve in order to better inform national energy policy needs.

Can Climate Information be relevant to decision making for Agriculture on the 1-10 year timescale? Case studies from southern Africa

NASA Astrophysics Data System (ADS)

Fujisawa, Mariko

2016-04-01

Climate forecasts have been developed to assist decision making in sectors averse to, and affected by, climate risks, and agriculture is one of those. In agriculture and food security, climate information is now used on a range of timescales, from days (weather), months (seasonal outlooks) to decades (climate change scenarios). Former researchers have shown that when seasonal climate forecast information was provided to farmers prior to decision making, farmers adapted by changing their choice of planting seeds and timing or area planted. However, it is not always clear that the end-users' needs for climate information are met and there might be a large gap between information supplied and needed. It has been pointed out that even when forecasts were available, they were often not utilized by farmers and extension services because of lack of trust in the forecast or the forecasts did not reach the targeted farmers. Many studies have focused on the use of either seasonal forecasts or longer term climate change prediction, but little research has been done on the medium term, that is, 1 to 10 year future climate information. The agriculture and food system sector is one potential user of medium term information, as land use policy and cropping systems selection may fall into this time scale and may affect farmers' decision making process. Assuming that reliable information is provided and it is utilized by farmers for decision making, it might contribute to resilient farming and indeed to longer term food security. To this end, we try to determine the effect of medium term climate information on farmers' strategic decision making process. We explored the end-users' needs for climate information and especially the possible role of medium term information in agricultural system, by conducting interview surveys with farmers and agricultural experts. In this study, the cases of apple production in South Africa, maize production in Malawi and rice production in Tanzania will be presented. With case studies of various crops, we also aim to identify what climatic factors and timescale of prediction may be critical to what crop types of farmers, which may be of value to climate prediction community to further develop climate prediction useful for agricultural system.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.; Hooten, Mevin B.; Dubovsky, James A.; Drewien, Roderick C.

2015-01-01

Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment.Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression.Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect.Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond.Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level

PubMed Central

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I.; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world. PMID:27227671

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level.

PubMed

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world.

The adventures of climate science in the sweet land of idle arguments

NASA Astrophysics Data System (ADS)

Winsberg, Eric; Goodwin, William Mark

2016-05-01

In a recent series of papers Roman Frigg, Leonard Smith, and several coauthors have developed a general epistemological argument designed to cast doubt on the capacity of a broad range of mathematical models to generate "decision relevant predictions." The presumptive targets of their argument are at least some of the modeling projects undertaken in contemporary climate science. In this paper, we trace and contrast two very different readings of the scope of their argument. We do this by considering the very different implications for climate science that these interpretations would have. Then, we lay out the structure of their argument-an argument by analogy-with an eye to identifying points at which certain epistemically significant distinctions might limit the force of the analogy. Finally, some of these epistemically significant distinctions are introduced and defended as relevant to a great many of the predictive mathematical modeling projects employed in contemporary climate science.

Decision fatigue: A conceptual analysis.

PubMed

Pignatiello, Grant A; Martin, Richard J; Hickman, Ronald L

2018-03-01

Decision fatigue is an applicable concept to healthcare psychology. Due to a lack of conceptual clarity, we present a concept analysis of decision fatigue. A search of the term "decision fatigue" was conducted across seven research databases, which yielded 17 relevant articles. The authors identified three antecedent themes (decisional, self-regulatory, and situational) and three attributional themes (behavioral, cognitive, and physiological) of decision fatigue. However, the extant literature failed to adequately describe consequences of decision fatigue. This concept analysis provides needed conceptual clarity for decision fatigue, a concept possessing relevance to nursing and allied health sciences.

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

PubMed

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

2012-09-01

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

New Methods for Crafting Locally Decision-Relevant Scenarios

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2015-12-01

Scenarios can play an important role in helping decision makers to imagine future worlds, both good and bad, different than the one with which we are familiar and to take concrete steps now to address the risks generated by climate change. At their best, scenarios can effectively represent deep uncertainty; integrate over multiple domains; and enable parties with different expectation and values to expand the range of futures they consider, to see the world from different points of view, and to grapple seriously with the potential implications of surprising or inconvenient futures. These attributes of scenario processes can prove crucial in helping craft effective responses to climate change. But traditional scenario methods can also fail to overcome difficulties related to choosing, communicating, and using scenarios to identify, evaluate, and reach consensus on appropriate policies. Such challenges can limit scenario's impact in broad public discourse. This talk will demonstrate how new decision support approaches can employ new quantitative tools that allow scenarios to emerge from a process of deliberation with analysis among stakeholders, rather than serve as inputs to it, thereby increasing the impacts of scenarios on decision making. This talk will demonstrate these methods in the design of a decision support tool to help residents of low lying coastal cities grapple with the long-term risks of sea level rise. In particular, this talk will show how information from the IPCC SSP's can be combined with local information to provide a rich set of locally decision-relevant information.

Invited review: Helping dairy farmers to improve economic performance utilizing data-driving decision support tools.

PubMed

Cabrera, V E

2018-01-01

The objective of this review paper is to describe the development and application of a suite of more than 40 computerized dairy farm decision support tools contained at the University of Wisconsin-Madison (UW) Dairy Management website http://DairyMGT.info. These data-driven decision support tools are aimed to help dairy farmers improve their decision-making, environmental stewardship and economic performance. Dairy farm systems are highly dynamic in which changing market conditions and prices, evolving policies and environmental restrictions together with every time more variable climate conditions determine performance. Dairy farm systems are also highly integrated with heavily interrelated components such as the dairy herd, soils, crops, weather and management. Under these premises, it is critical to evaluate a dairy farm following a dynamic integrated system approach. For this approach, it is crucial to use meaningful data records, which are every time more available. These data records should be used within decision support tools for optimal decision-making and economic performance. Decision support tools in the UW-Dairy Management website (http://DairyMGT.info) had been developed using combination and adaptation of multiple methods together with empirical techniques always with the primary goal for these tools to be: (1) highly user-friendly, (2) using the latest software and computer technologies, (3) farm and user specific, (4) grounded on the best scientific information available, (5) remaining relevant throughout time and (6) providing fast, concrete and simple answers to complex farmers' questions. DairyMGT.info is a translational innovative research website in various areas of dairy farm management that include nutrition, reproduction, calf and heifer management, replacement, price risk and environment. This paper discusses the development and application of 20 selected (http://DairyMGT.info) decision support tools.

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

Updating beliefs and combining evidence in adaptive forest management under climate change: a case study of Norway spruce (Picea abies L. Karst) in the Black Forest, Germany.

PubMed

Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald; Elkin, Che; Hanewinkel, Marc; Meilby, Henrik; Jacobsen, Jette Bredahl; Thorsen, Bo Jellesmark

2013-06-15

We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change. Copyright © 2013 Elsevier Ltd. All rights reserved.

Land Use, climate change and BIOdiversity in cultural landscapes (LUBIO): Assessing feedbacks and promoting land-use strategies towards a viable future

NASA Astrophysics Data System (ADS)

Dullinger, Iwona; Bohner, Andreas; Dullinger, Stefan; Essl, Franz; Gaube, Veronika; Haberl, Helmut; Mayer, Andreas; Plutzar, Christoph; Remesch, Alexander

2016-04-01

Land-use and climate change are important, pervasive drivers of global environmental change and pose major threats to global biodiversity. Research to date has mostly focused either on land-use change or on climate change, but rarely on the interactions between both drivers, even though it is expected that systemic feedbacks between changes in climate and land use will have important effects on biodiversity. In particular, climate change will not only alter the pool of plant and animal species capable of thriving in a specific area, it will also force land owners to reconsider their land use decisions. Such changes in land-use practices may have major additional effects on local and regional species composition and abundance. In LUBIO, we will explore the anticipated systemic feedbacks between (1) climate change, (2) land owner's decisions on land use, (3) land-use change, and (4) changes in biodiversity patterns during the coming decades in a regional context which integrates a broad range of land use practices and intensity gradients. To achieve this goal, an integrated socioecological model will be designed and implemented, consisting of three principal components: (1) an agent based model (ABM) that simulates decisions of important actors, (2) a spatially explicit GIS model that translates these decisions into changes in land cover and land use patterns, and (3) a species distribution model (SDM) that calculates changes in biodiversity patterns following from both changes in climate and the land use decisions as simulated in the ABM. Upon integration of these three components, the coupled socioecological model will be used to generate scenarios of future land-use decisions of landowners under climate change and, eventually, the combined effects of climate and land use changes on biodiversity. Model development of the ABM will be supported by a participatory process intended to collect regional and expert knowledge through a series of expert interviews, a series of transdisciplinary participatory modelling workshops, and a questionnaire-based survey targeted at regional farmers. Beside the integrated socioecological model a catalogue of recommended actions will be developed in order to distribute the insights of the research to the most relevant regional stakeholder groups.

Using decadal climate prediction to characterize and manage changing drought and flood risks in Colorado

NASA Astrophysics Data System (ADS)

Lazrus, H.; Done, J.; Morss, R. E.

2017-12-01

A new branch of climate science, known as decadal prediction, seeks to predict the time-varying trajectory of climate over the next 3-30 years and not just the longer-term trends. Decadal predictions bring climate information into the time horizon of decision makers, particularly those tasked with managing water resources and floods whose master planning is often on the timescale of decades. Information from decadal predictions may help alleviate some aspects of vulnerability by helping to inform decisions that reduce drought and flood exposure and increase adaptive capacities including preparedness, response, and recovery. This presentation will highlight an interdisciplinary project - involving atmospheric and social scientists - on the development of decadal climate information and its use in decision making. The presentation will explore the skill and utility of decadal drought and flood prediction along Colorado's Front Range, an area experiencing rapid population growth and uncertain climate variability and climate change impacts. Innovative statistical and dynamical atmospheric modeling techniques explore the extent to which Colorado precipitation can be predicted on decadal scales using remote Pacific Ocean surface temperature patterns. Concurrently, stakeholder interviews with flood managers in Colorado are being used to explore the potential utility of decadal climate information. Combining the modeling results with results from the stakeholder interviews shows that while there is still significant uncertainty surrounding precipitation on decadal time scales, relevant and well communicated decadal information has potential to be useful for drought and flood management.

ESA's Earth Observation Programmes in the Changing Anthropocene

NASA Astrophysics Data System (ADS)

Liebig, Volker

2016-07-01

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

An Efficient Workflow Environment to Support the Collaborative Development of Actionable Climate Information Using the NCAR Climate Risk Management Engine (CRMe)

NASA Astrophysics Data System (ADS)

Ammann, C. M.; Vigh, J. L.; Lee, J. A.

2016-12-01

Society's growing needs for robust and relevant climate information have fostered an explosion in tools and frameworks for processing climate projections. Many top-down workflows might be employed to generate sets of pre-computed data and plots, frequently served in a "loading-dock style" through a metadata-enabled search and discovery engine. Despite these increasing resources, the diverse needs of applications-driven projects often result in data processing workflow requirements that cannot be fully satisfied using past approaches. In parallel to the data processing challenges, the provision of climate information to users in a form that is also usable represents a formidable challenge of its own. Finally, many users do not have the time nor the desire to synthesize and distill massive volumes of climate information to find the relevant information for their particular application. All of these considerations call for new approaches to developing actionable climate information. CRMe seeks to bridge the gap between the diversity and richness of bottom-up needs of practitioners, with discrete, structured top-down workflows typically implemented for rapid delivery. Additionally, CRMe has implemented web-based data services capable of providing focused climate information in usable form for a given location, or as spatially aggregated information for entire regions or countries following the needs of users and sectors. Making climate data actionable also involves summarizing and presenting it in concise and approachable ways. CRMe is developing the concept of dashboards, co-developed with the users, to condense the key information into a quick summary of the most relevant, curated climate data for a given discipline, application, or location, while still enabling users to efficiently conduct deeper discovery into rich datasets on an as-needed basis.

Can we expect to predict climate if we cannot shadow weather?

NASA Astrophysics Data System (ADS)

Smith, Leonard

2010-05-01

What limits our ability to predict (or project) useful statistics of future climate? And how might we quantify those limits? In the early 1960s, Ed Lorenz illustrated one constraint on point forecasts of the weather (chaos) while noting another (model imperfections). In the mid-sixties he went on to discuss climate prediction, noting that chaos, per se, need not limit accurate forecasts of averages and the distributions that define climate. In short, chaos might place draconian limits on what we can say about a particular summer day in 2010 (or 2040), but it need not limit our ability to make accurate and informative statements about the weather over this summer as a whole, or climate distributions of the 2040's. If not chaos, what limits our ability to produce decision relevant probability distribution functions (PDFs)? Is this just a question of technology (raw computer power) and uncertain boundary conditions (emission scenarios)? Arguably, current model simulations of the Earth's climate are limited by model inadequacy: not that the initial or boundary conditions are unknown but that state-of-the-art models would not yield decision-relevant probability distributions even if they were known. Or to place this statement in an empirically falsifiable format: that in 2100 when the boundary conditions are known and computer power is (hopefully) sufficient to allow exhaustive exploration of today's state-of-the-art models: we will find today's models do not admit a trajectory consistent with our knowledge of the state of the earth in 2009 which would prove of decision support relevance for, say, 25 km, hourly resolution. In short: today's models cannot shadow the weather of this century even after the fact. Restating this conjecture in a more positive frame: a 2100 historian of science will be able to determine the highest space and time scales on which 2009 models could have (i) produced trajectories plausibly consistent with the (by then) observed twenty-first century and (ii) produced probability distributions useful as such for decision support. As it will be some time until such conjectures can be refuted, how might we best advise decision makers of the detail (specifically, space and time resolution of a quantity of interest as a function of lead-time) that it is rational to interpret model-based PDFs as decision-relevant probability distributions? Given the nonlinearities already incorporated in our models, how far into the future can one expect a simulation to get the temperature "right" given the simulation has precipitation badly "wrong"? When can biases in local temperature which melt model-ice no longer be dismissed, and neglected by presenting model-anomalies? At what lead times will feedbacks due to model inadequacies cause the 2007 model simulations to drift away from what today's basic science (and 2100 computer power) would suggest? How might one justify quantitative claims regarding "extreme events" (or NUMB weather)? Models are unlikely to forecast things they cannot shadow, or at least track. There is no constraint on rational scientists to take model distributions as their subjective probabilities, unless they believe the model is empirically adequate. How then are we to use today's simulations to inform today's decisions? Two approaches are considered. The first augments the model-based PDF with an explicit subjective-probability of a "Big Surprise". The second is to look not for a PDF but, following Solvency II, consider the risk from any event that cannot be ruled out at, say, the one in 200 level. The fact that neither approach provides the simplicity and apparent confidence of interpreting model-based PDFs as if they were objective probabilities does not contradict the claim that either might lead to better decision-making.

[Study on eco-climatic applicability of Angelica sinensis].

PubMed

Deng, Zhen-Yong; Yin, Xian-Zhi; Yin, Dong; Yang, Qi-Guo; Zhu, Guo-Qing; Liu, Ming-Chun

2005-06-01

In the interest of establish planting base of Angelica sinensis on a large scale, enhance economic benefit, and improve decision-making reasons, the eco-climatic applicability of A. sinensis was studied. Using integral regression, eco-climatic applicability and the effect of meteorological conditions for the yield of A. sinensis' were analysed by field experimental data. Selected > or =0 degrees C accumulated temperature and annual precipitation as leading index, altitude as assistant index, yield and rate of finished products as reference index, the integrated eco-climatic division index and the planting division applicability of A. sinensis was confirmed. Accordancing to theory of climate similitude and leading index summarisation, combining with assistant index and reference index, the integrated division index of eco-climate was confirmed. The planting division of co-climate applicability was divided into 5 grades as best suitable, suitable hypo-suitable, just suitable and no suitable regions. At the same time,the way to enhanced utilizing efficiency of eco-climate resources was brought forward.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Leveraging a Community Participatory Framework to Move Climate Survey Data into Action at a Small College

ERIC Educational Resources Information Center

Peters, C. Ellen; Benitez, Michael, Jr.

2017-01-01

A participatory framework in conducting research and implementing decisions can engage multiple constituents throughout a college community. At a small college, it is especially relevant, because nonmajority groups are especially vulnerable because of a smaller critical mass.

Farmers' Options to Address Water Scarcity in a Changing Climate: Case Studies from two Basins in Mediterranean Chile.

PubMed

Roco, Lisandro; Poblete, David; Meza, Francisco; Kerrigan, George

2016-12-01

Irrigated agriculture in Mediterranean areas faces tremendous challenges because of its exposure to hydroclimatic variability, increasing competition for water from different sectors, and the possibility of a climatic change. In this context, efficient management of water resources emerges as a critical issue. This requires the adoption of technological innovations, investment in infrastructure, adequate institutional arrangements, and informed decision makers. To understand farmers' perceptions and their implementation of climate change adaptation strategies with regards to water management, primary information was captured in the Limarí and Maule river basins in Chile. Farmers identified stressors for agriculture; climate change, droughts, and lack of water appeared as the most relevant stressors compared to others productive, economic, and institutional factors; revealing a rising relevance of climate related factors. While most producers perceived climate changes in recent years (92.9 %), a significant proportion (61.1 %) claim to have experienced drought, whereas only a fraction (31.9 %) have implemented a strategy to deal with this situation. Identified actions were classified in four groups: investments for water accumulation, modernization of irrigation systems, rationalization of water use, and partnership activities. Using a multinomial logit model these strategies were related to socioeconomic and productive characteristics. Results show that gender and farm size are relevant for investments, implementation and improvement of irrigation systems. For all the strategies described, access to weather information was a relevant element. The study provides empirical evidence of a recent increase in the importance assigned to climate factors by producers and adaptation options that can be supported by agricultural policy.

Farmers' Options to Address Water Scarcity in a Changing Climate: Case Studies from two Basins in Mediterranean Chile

NASA Astrophysics Data System (ADS)

Roco, Lisandro; Poblete, David; Meza, Francisco; Kerrigan, George

2016-12-01

Irrigated agriculture in Mediterranean areas faces tremendous challenges because of its exposure to hydroclimatic variability, increasing competition for water from different sectors, and the possibility of a climatic change. In this context, efficient management of water resources emerges as a critical issue. This requires the adoption of technological innovations, investment in infrastructure, adequate institutional arrangements, and informed decision makers. To understand farmers' perceptions and their implementation of climate change adaptation strategies with regards to water management, primary information was captured in the Limarí and Maule river basins in Chile. Farmers identified stressors for agriculture; climate change, droughts, and lack of water appeared as the most relevant stressors compared to others productive, economic, and institutional factors; revealing a rising relevance of climate related factors. While most producers perceived climate changes in recent years (92.9 %), a significant proportion (61.1 %) claim to have experienced drought, whereas only a fraction (31.9 %) have implemented a strategy to deal with this situation. Identified actions were classified in four groups: investments for water accumulation, modernization of irrigation systems, rationalization of water use, and partnership activities. Using a multinomial logit model these strategies were related to socioeconomic and productive characteristics. Results show that gender and farm size are relevant for investments, implementation and improvement of irrigation systems. For all the strategies described, access to weather information was a relevant element. The study provides empirical evidence of a recent increase in the importance assigned to climate factors by producers and adaptation options that can be supported by agricultural policy.

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.

Moving toward climate-informed agricultural decision support - can we use PRISM data for more than just monthly averages?

USDA-ARS?s Scientific Manuscript database

Decision support systems/models for agriculture are varied in target application and complexity, ranging from simple worksheets to near real-time forecast systems requiring significant computational and manpower resources. Until recently, most such decision support systems have been constructed with...

NADE Accreditation: The Right Decision for the Current Time

ERIC Educational Resources Information Center

NADE Digest, 2018

2018-01-01

The National Association for Developmental Education (NADE) Accreditation process is more relevant and important than ever to the discussion of students' success and completion of meaningful credentials. In the current politically-charged climate, NADE Accreditation helps programs demonstrate not only to themselves and their administrations, but…

Development of an Online Climate and Fisheries Data Dashboard for Stakeholders in the Northeast Shelf Large Marine Ecosystem

NASA Astrophysics Data System (ADS)

Young Morse, R.

2016-12-01

Fisheries managers make decisions that shape the future of ecosystems and the communities that depend on them. These decisions are often made without reference to environmental conditions, or are made assuming that past conditions (physical conditions, productivity, and species distributions) will persist. The rapid changes experienced in the Northeast Shelf Large Marine Ecosystem (NES LME), as well as the high degree of natural variability in this system, are prompting new discussions about how to incorporate environmental information into fisheries policy and management and into the industry. Through this project, we are facilitating access to fisheries and climate data for fisheries stakeholders in the Northeast through the creation of an online dynamic data dashboard. The primary goal is to make complex climate-relevant data accessible and easy to understand. Information on past, present, and future environmental conditions in the NES LME are presented in the context of fisheries dependent data. Working with marine fisheries stakeholders, including fisheries management council members, industry leaders and non-profits, we have developed a suite of open source processes and tools to acquire and subset climate relevant data from a variety of sources (satellites, sensors, models), develop long range climatologies, and display through dynamically updated interactive data visualizations. The resulting dashboard allows users to quickly assess conditions in the ocean and evaluate them in the context of past and projected change.

A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity

PubMed Central

Brousset, Jean Marie; Abbal, Philippe; Guillemin, Hervé; Perret, Bruno; Goulet, Etienne; Guerin, Laurence; Barbeau, Gérard; Picque, Daniel

2015-01-01

Agri-food is one of the most important sectors of the industry and a major contributor to the global warming potential in Europe. Sustainability issues pose a huge challenge for this sector. In this context, a big issue is to be able to predict the multiscale dynamics of those systems using computing science. A robust predictive mathematical tool is implemented for this sector and applied to the wine industry being easily able to be generalized to other applications. Grape berry maturation relies on complex and coupled physicochemical and biochemical reactions which are climate dependent. Moreover one experiment represents one year and the climate variability could not be covered exclusively by the experiments. Consequently, harvest mostly relies on expert predictions. A big challenge for the wine industry is nevertheless to be able to anticipate the reactions for sustainability purposes. We propose to implement a decision support system so called FGRAPEDBN able to (1) capitalize the heterogeneous fragmented knowledge available including data and expertise and (2) predict the sugar (resp. the acidity) concentrations with a relevant RMSE of 7 g/l (resp. 0.44 g/l and 0.11 g/kg). FGRAPEDBN is based on a coupling between a probabilistic graphical approach and a fuzzy expert system. PMID:26230334

Analysing urban resilience through alternative stormwater management options: application of the conceptual Spatial Decision Support System model at the neighbourhood scale.

PubMed

Balsells, M; Barroca, B; Amdal, J R; Diab, Y; Becue, V; Serre, D

2013-01-01

Recent changes in cities and their environments, caused by rapid urbanisation and climate change, have increased both flood probability and the severity of flooding. Consequently, there is a need for all cities to adapt to climate and socio-economic changes by developing new strategies for flood risk management. Following a risk paradigm shift from traditional to more integrated approaches, and considering the uncertainties of future urban development, one of the main emerging tasks for city managers becomes the development of resilient cities. However, the meaning of the resilience concept and its operability is still not clear. The goal of this research is to study how urban engineering and design disciplines can improve resilience to floods in urban neighbourhoods. This paper presents the conceptual Spatial Decision Support System (DS3) model which we consider a relevant tool to analyse and then implement resilience into neighbourhood design. Using this model, we analyse and discuss alternative stormwater management options at the neighbourhood scale in two specific areas: Rotterdam and New Orleans. The results obtained demonstrate that the DS3 model confirmed in its framework analysis that stormwater management systems can positively contribute to the improved flood resilience of a neighbourhood.

Data Mashups: Potential Contribution to Decision Support on Climate Change and Health

PubMed Central

Fleming, Lora E.; Haines, Andy; Golding, Brian; Kessel, Anthony; Cichowska, Anna; Sabel, Clive E.; Depledge, Michael H.; Sarran, Christophe; Osborne, Nicholas J.; Whitmore, Ceri; Cocksedge, Nicola; Bloomfield, Daniel

2014-01-01

Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on “data mashups”. These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers. PMID:24499879

Data mashups: potential contribution to decision support on climate change and health.

PubMed

Fleming, Lora E; Haines, Andy; Golding, Brian; Kessel, Anthony; Cichowska, Anna; Sabel, Clive E; Depledge, Michael H; Sarran, Christophe; Osborne, Nicholas J; Whitmore, Ceri; Cocksedge, Nicola; Bloomfield, Daniel

2014-02-04

Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on "data mashups". These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers.

Assessing Climate Risk on Agricultural Production: Insights Using Retrospective Analysis of Crop Insurance and Climatic Trends

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Elias, E.; Eischens, A.; Shilts, M.; Rango, A.; Steele, R.

2017-12-01

The collaborative synthesis of existing datasets, such as long-term climate observations and farmers' crop insurance payments, can increase their overall collective value and societal application. The U.S. Department of Agriculture (USDA) Climate Hubs were created to develop and deliver science-based information and technologies to agricultural and natural resource managers to enable climate-informed decision-making. As part of this mission, Hubs work across USDA and other climate service agencies to synthesize existing information. The USDA Risk Management Agency (RMA) is responsible for overseeing the Federal crop insurance program which currently insures over $100 billion in crops annually. RMA hosts data describing the cause for loss (e.g. drought, wind, irrigation failure) and indemnity amount (i.e. total cost of loss) at multiple spatio-temporal scales (i.e. state, county, year, month). The objective of this paper is to link climate information with indemnities, and their associated cause of loss, to assess climate risk on agricultural production and provide regionally-relevant information to stakeholders to promote resilient working landscapes. We performed a retrospective trend analysis at the state-level for the American Southwest (SW). First, we assessed indemnity-only trends by cause of loss and crop type at varying temporal scales. Historical monthly weather data (i.e. precipitation and temperature) and long-term drought indices (e.g. Palmer Drought Severity Index) were then linked with indemnities and grouped by different causes of loss. Climatological ranks were used to integrate historical comparative intensity of acute and long-term climatic events. Heat and drought as causes of loss were most correlated with temperature and drought indicators, respectively. Across all SW states increasing indemnities were correlated with warmer conditions. Multiple statistical trend analyses suggest a framework is necessary to appropriately measure the biophysical signals in crop insurance trends taking into account spatio-temporal characteristics. Based on stakeholder feedback, we also developed a web-based information browser to visualize and assess indemnity trends providing useful and usable knowledge to support informed land management decisions and ecosystem resilience.

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.

Taxonomies of Higher Educational Institutions Predicted from Organizational Climate.

ERIC Educational Resources Information Center

Lysons, Art

1990-01-01

Application of the Perceived Climate Questionnaire involving senior-level staff from Australian institutions used climate factors as the basis for testing hypothesized taxonomies of the institutions. Results reinforce the relevance of contemporary management theories and demonstrate the importance of leadership styles in organizational…

Information Needs Assessment for Coastal and Marine Management and Policy: Ecosystem Services Under Changing Climatic, Land Use, and Demographic Conditions.

PubMed

Goldsmith, Kaitlin A; Granek, Elise F; Lubitow, Amy

2015-12-01

Changing climatic, demographic, and land use conditions are projected to alter the provisioning of ecosystem services in estuarine, coastal, and nearshore marine ecosystems, necessitating mitigation and adaptation policies and management. The current paradigm of research efforts occurring in parallel to, rather than in collaboration with, decision makers will be insufficient for the rapid responses required to adapt to and mitigate for projected changing conditions. Here, we suggest a different paradigm: one where research begins by engaging decision makers in the identification of priority data needs (biophysical, economic, and social). This paper uses synthesized interview data to provide insight into the varied demands for scientific research as described by decision makers working on coastal issues in Oregon, USA. The findings highlight the need to recognize (1) the differing framing of ecosystem services by decision makers versus scientists; and (2) the differing data priorities relevant to inland versus coastal decision makers. The findings further serve to highlight the need for decision makers, scientists, and funders to engage in increased communication. This research is an important first step in advancing efforts toward evidence-based decision making in Oregon and provides a template for further research across the US.

From Ice Sheets to Main Streets: Intermediaries Connect Climate Scientists to Coastal Adaptation

NASA Astrophysics Data System (ADS)

Ultee, Lizz; Arnott, James C.; Bassis, Jeremy; Lemos, Maria Carmen

2018-03-01

Despite the societal relevance of sea-level research, a knowledge-to-action gap remains between researchers and coastal communities. In the agricultural and water-management sectors, intermediaries such as consultants and extension agencies have a long and well-documented history of helping to facilitate the application of scientific knowledge on the ground. However, the role of such intermediaries in adaptation to sea-level rise, though potentially of vital importance, has been less thoroughly explored. In this commentary, we describe three styles of science intermediation that can connect researchers working on sea-level projections with decision-makers relying on those projections. We illustrate these styles with examples of recent and ongoing contexts for the application of sea-level research, at different spatial scales and political levels ranging from urban development projects to international organizations. Our examples highlight opportunities and drawbacks for the researchers involved and communities adapting to rising seas.

Forecasting wildlife response to rapid warming in the Alaskan Arctic

USGS Publications Warehouse

Van Hemert, Caroline R.; Flint, Paul L.; Udevitz, Mark S.; Koch, Joshua C.; Atwood, Todd C.; Oakley, Karen L.; Pearce, John M.

2015-01-01

Arctic wildlife species face a dynamic and increasingly novel environment because of climate warming and the associated increase in human activity. Both marine and terrestrial environments are undergoing rapid environmental shifts, including loss of sea ice, permafrost degradation, and altered biogeochemical fluxes. Forecasting wildlife responses to climate change can facilitate proactive decisions that balance stewardship with resource development. In this article, we discuss the primary and secondary responses to physical climate-related drivers in the Arctic, associated wildlife responses, and additional sources of complexity in forecasting wildlife population outcomes. Although the effects of warming on wildlife populations are becoming increasingly well documented in the scientific literature, clear mechanistic links are often difficult to establish. An integrated science approach and robust modeling tools are necessary to make predictions and determine resiliency to change. We provide a conceptual framework and introduce examples relevant for developing wildlife forecasts useful to management decisions.

Urban Climate Resilience - Connecting climate models with decision support cyberinfrastructure using open standards

NASA Astrophysics Data System (ADS)

Bermudez, L. E.; Percivall, G.; Idol, T. A.

2015-12-01

Experts in climate modeling, remote sensing of the Earth, and cyber infrastructure must work together in order to make climate predictions available to decision makers. Such experts and decision makers worked together in the Open Geospatial Consortium's (OGC) Testbed 11 to address a scenario of population displacement by coastal inundation due to the predicted sea level rise. In a Policy Fact Sheet "Harnessing Climate Data to Boost Ecosystem & Water Resilience", issued by White House Office of Science and Technology (OSTP) in December 2014, OGC committed to increase access to climate change information using open standards. In July 2015, the OGC Testbed 11 Urban Climate Resilience activity delivered on that commitment with open standards based support for climate-change preparedness. Using open standards such as the OGC Web Coverage Service and Web Processing Service and the NetCDF and GMLJP2 encoding standards, Testbed 11 deployed an interoperable high-resolution flood model to bring climate model outputs together with global change assessment models and other remote sensing data for decision support. Methods to confirm model predictions and to allow "what-if-scenarios" included in-situ sensor webs and crowdsourcing. A scenario was in two locations: San Francisco Bay Area and Mozambique. The scenarios demonstrated interoperation and capabilities of open geospatial specifications in supporting data services and processing services. The resultant High Resolution Flood Information System addressed access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios examined the feasibility and capability of existing OGC geospatial Web service specifications in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Results of this testbed included identification of standards and best practices that help researchers and cities deal with climate-related issues. Results of the testbeds will now be deployed in pilot applications. The testbed also identified areas of additional development needed to help identify scientific investments and cyberinfrastructure approaches needed to improve the application of climate science research results to urban climate resilence.

Tracking Expected Improvements of Decadal Prediction in Climate Services

NASA Astrophysics Data System (ADS)

Suckling, E.; Thompson, E.; Smith, L. A.

2013-12-01

Physics-based simulation models are ultimately expected to provide the best available (decision-relevant) probabilistic climate predictions, as they can capture the dynamics of the Earth System across a range of situations, situations for which observations for the construction of empirical models are scant if not nonexistent. This fact in itself provides neither evidence that predictions from today's Earth Systems Models will outperform today's empirical models, nor a guide to the space and time scales on which today's model predictions are adequate for a given purpose. Empirical (data-based) models are employed to make probability forecasts on decadal timescales. The skill of these forecasts is contrasted with that of state-of-the-art climate models, and the challenges faced by each approach are discussed. The focus is on providing decision-relevant probability forecasts for decision support. An empirical model, known as Dynamic Climatology is shown to be competitive with CMIP5 climate models on decadal scale probability forecasts. Contrasting the skill of simulation models not only with each other but also with empirical models can reveal the space and time scales on which a generation of simulation models exploits their physical basis effectively. It can also quantify their ability to add information in the formation of operational forecasts. Difficulties (i) of information contamination (ii) of the interpretation of probabilistic skill and (iii) of artificial skill complicate each modelling approach, and are discussed. "Physics free" empirical models provide fixed, quantitative benchmarks for the evaluation of ever more complex climate models, that is not available from (inter)comparisons restricted to only complex models. At present, empirical models can also provide a background term for blending in the formation of probability forecasts from ensembles of simulation models. In weather forecasting this role is filled by the climatological distribution, and can significantly enhance the value of longer lead-time weather forecasts to those who use them. It is suggested that the direct comparison of simulation models with empirical models become a regular component of large model forecast intercomparison and evaluation. This would clarify the extent to which a given generation of state-of-the-art simulation models provide information beyond that available from simpler empirical models. It would also clarify current limitations in using simulation forecasting for decision support. No model-based probability forecast is complete without a quantitative estimate if its own irrelevance; this estimate is likely to increase as a function of lead time. A lack of decision-relevant quantitative skill would not bring the science-based foundation of anthropogenic warming into doubt. Similar levels of skill with empirical models does suggest a clear quantification of limits, as a function of lead time, for spatial and temporal scales on which decisions based on such model output are expected to prove maladaptive. Failing to clearly state such weaknesses of a given generation of simulation models, while clearly stating their strength and their foundation, risks the credibility of science in support of policy in the long term.

Water Planning in Phoenix: Managing Risk in the Face of Climatic Uncertainty

NASA Astrophysics Data System (ADS)

Gober, P.

2009-12-01

The Decision Center for a Desert City (DCDC) was founded in 2004 to develop scientifically-credible support tools to improve water management decisions in the face of growing climatic uncertainty and rapid urbanization in metropolitan Phoenix. At the center of DCDC's effort is WaterSim, a model that integrates information about water supply from groundwater, the Colorado River, and upstream watersheds and water demand from land use change and population growth. Decision levers enable users to manipulate model outcomes in response to climate change scenarios, drought conditions, population growth rates, technology innovations, lifestyle changes, and policy decisions. WaterSim allows users to examine the risks of water shortage from global climate change, the tradeoffs between groundwater sustainability and lifestyle choices, the effects of various policy decisions, and the consequences of delaying policy for the exposure to risk. WaterSim is an important point of contact for DCDC’s relationships with local decision makers. Knowledge, tools, and visualizations are co-produced—by scientists and policy makers, and the Center’s social scientists mine this co-production process for new insights about model development and application. WaterSim is less a static scientific product and more a dynamic process of engagement between decision makers and scientists.

Informing Drought Preparedness and Response with the South Asia Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Ghatak, D.; Matin, M. A.; Qamer, F. M.; Adhikary, B.; Bajracharya, B.; Nelson, J.; Pulla, S. T.; Ellenburg, W. L.

2017-12-01

Decision-relevant drought monitoring in South Asia is a challenge from both a scientific and an institutional perspective. Scientifically, climatic diversity, inconsistent in situ monitoring, complex hydrology, and incomplete knowledge of atmospheric processes mean that monitoring and prediction are fraught with uncertainty. Institutionally, drought monitoring efforts need to align with the information needs and decision-making processes of relevant agencies at national and subnational levels. Here we present first results from an emerging operational drought monitoring and forecast system developed and supported by the NASA SERVIR Hindu-Kush Himalaya hub. The system has been designed in consultation with end users from multiple sectors in South Asian countries to maximize decision-relevant information content in the monitoring and forecast products. Monitoring of meteorological, agricultural, and hydrological drought is accomplished using the South Asia Land Data Assimilation System, a platform that supports multiple land surface models and meteorological forcing datasets to characterize uncertainty, and subseasonal to seasonal hydrological forecasts are produced by driving South Asia LDAS with downscaled meteorological fields drawn from an ensemble of global dynamically-based forecast systems. Results are disseminated to end users through a Tethys online visualization platform and custom communications that provide user oriented, easily accessible, timely, and decision-relevant scientific information.

Defining ecohydrological function to support low impact development in coastal South Carolina

Treesearch

Daniel Hitchcock; A.D. Jayakaran; T. H. Epps; J.A. Palazzolo; T.M. Williams; D.M. Amatya

2016-01-01

In the face of dual pressures in coastal South Carolina - residential and commercial development, along with potential climate change impacts - stakeholders need clear, accurate, relevant, and easily-accessible information for effective decision-making for watershed management and natural resource protection.

Recent Challenges Facing US Government Climate Science Access and Application

NASA Astrophysics Data System (ADS)

Goldman, G. T.; Carter, J. M.; Licker, R.

2017-12-01

Climate scientists have long faced politicization of their work, especially those working within the US federal government. However, political interference in federal government climate change science has escalated in the current political era with efforts by political actors to undermine and disrupt infrastructure supporting climate science. This has included funding changes, decreased access to climate science information on federal agency websites, restrictions on media access to scientific experts within the government, and rolling back of science-based policies designed to incorporate and respond to climate science findings. What are the impacts of such changes for both the climate science community and the broader public? What can be done to ensure that access to and application of climate change-related research to policy decisions continues? We will summarize and analyze the state of climate change research and application in the US government. The impacts of political interference in climate change science as well as opportunities the scientific community has to support climate science in the US government, will be discussed.

An integrated assessment of climate change impacts for Athens- relevance to stakeholders and policy makers

NASA Astrophysics Data System (ADS)

Giannakopoulos, C.; Hatzaki, M.; Kostopoulou, E.; Varotsos, K.

2010-09-01

Analysing climate change and its impact needs a production of relevant elements for policy making that can be very different from the parameters considered by climate experts. In the framework of EU project CIRCE, a more realistic approach to match stakeholders and policy-makers demands is attempted. For this reason, within CIRCE selected case studies have been chosen that will provide assessments that can be integrated in practical decision making. In this work, an integrated assessment of climate change impacts on several sectors for the urban site of Athens in Greece is presented. The Athens urban case study has been chosen since it provides excellent opportunities for using an integrated approach across multiple temporal and spatial scales and sectors. In the spatial dimension, work extends from the inner city boundaries to the surrounding mountains and forests. In the temporal dimension, research ranges from the current observed time period (using available meteorological and sector data) to future time periods using data from several climate change projections. In addition, a multi-sector approach to climate change impacts is adopted. Impacts sectors covered range from direct climate impacts on natural ecosystems (such as flash floods, air pollution and forest fire risk) to indirect impacts resulting from combined climate-social-economic linkages (such as energy demand, tourism and health). Discussion of impact sector risks and adaptation measures are also exploited. Case-study work on impact sector risk to climate change is of particular interest to relevant policy makers and stakeholders, communication with who is ensured through a series of briefing notes and information sheets and through regional workshops.

Lessons Learned from Applications of a Climate Change Decision Tree toWater System Projects in Kenya and Nepal

NASA Astrophysics Data System (ADS)

Ray, P. A.; Bonzanigo, L.; Taner, M. U.; Wi, S.; Yang, Y. C. E.; Brown, C.

2015-12-01

The Decision Tree Framework developed for the World Bank's Water Partnership Program provides resource-limited project planners and program managers with a cost-effective and effort-efficient, scientifically defensible, repeatable, and clear method for demonstrating the robustness of a project to climate change. At the conclusion of this process, the project planner is empowered to confidently communicate the method by which the vulnerabilities of the project have been assessed, and how the adjustments that were made (if any were necessary) improved the project's feasibility and profitability. The framework adopts a "bottom-up" approach to risk assessment that aims at a thorough understanding of a project's vulnerabilities to climate change in the context of other nonclimate uncertainties (e.g., economic, environmental, demographic, political). It helps identify projects that perform well across a wide range of potential future climate conditions, as opposed to seeking solutions that are optimal in expected conditions but fragile to conditions deviating from the expected. Lessons learned through application of the Decision Tree to case studies in Kenya and Nepal will be presented, and aspects of the framework requiring further refinement will be described.

CEOS SEO and GISS Meeting

NASA Technical Reports Server (NTRS)

Killough, Brian; Stover, Shelley

2008-01-01

The Committee on Earth Observation Satellites (CEOS) provides a brief to the Goddard Institute for Space Studies (GISS) regarding the CEOS Systems Engineering Office (SEO) and current work on climate requirements and analysis. A "system framework" is provided for the Global Earth Observation System of Systems (GEOSS). SEO climate-related tasks are outlined including the assessment of essential climate variable (ECV) parameters, use of the "systems framework" to determine relevant informational products and science models and the performance of assessments and gap analyses of measurements and missions for each ECV. Climate requirements, including instruments and missions, measurements, knowledge and models, and decision makers, are also outlined. These requirements would establish traceability from instruments to products and services allowing for benefit evaluation of instruments and measurements. Additionally, traceable climate requirements would provide a better understanding of global climate models.

Development of climate risk services under climate change scenarios in the North Adriatic coast (Italy).

NASA Astrophysics Data System (ADS)

Valentina, Gallina; Silvia, Torresan; Anna, Sperotto; Elisa, Furlan; Andrea, Critto; Antonio, Marcomini

2014-05-01

Nowadays, the challenge for coastal stakeholders and decision makers is to incorporate climate change in land and policy planning in order to ensure a sustainable integrated coastal zone management aimed at preserve coastal environments and socio-economic activities. Consequently, an increasing amount of information on climate variability and its impact on human and natural ecosystem is requested. Climate risk services allows to bridge the gap between climate experts and decision makers communicating timely science-based information about impacts and risks related to climate change that could be incorporated into land planning, policy and practice. Within the CLIM-RUN project (FP7), a participatory Regional Risk Assessment (RRA) methodology was applied for the evaluation of water-related hazards in coastal areas (i.e. pluvial flood and sea-level rise inundation risks) taking into consideration future climate change scenarios in the case study of the North Adriatic Sea for the period 2040-2050. Specifically, through the analysis of hazard, exposure, vulnerability and risk and the application of Multi-Criteria Decision Analysis (MCDA), the RRA methodology allowed to identify and prioritize targets (i.e. residential and commercial-industrial areas, beaches, infrastructures, wetlands, agricultural typology) and sub-areas that are more likely to be affected by pluvial flood and sea-level rise impacts in the same region. From the early stages of the climate risk services development and application, the RRA followed a bottom-up approach taking into account the needs, knowledge and perspectives of local stakeholders dealing with the Integrated Coastal Zone Management (ICZM), by means of questionnaires, workshops and focus groups organized within the project. Specifically, stakeholders were asked to provide their needs in terms of time scenarios, geographical scale and resolution, choice of receptors, vulnerability factors and thresholds that were considered in the implementation of the RRA methodology. The main output of the analysis are climate risk products produced with the DEcision support SYstem for COastal climate change impact assessment (DESYCO) and represented by GIS-based maps and statistics of hazard, exposure, physical and environmental vulnerability, risk and damage. These maps are useful to transfer information about climate change impacts to stakeholders and decision makers, to allow the classification and prioritization of areas that are likely to be affected by climate change impacts more severely than others in the same region, and therefore to support the identification of suitable areas for infrastructure, economic activities and human settlements toward the development of regional adaptation plans. The climate risk products and the results of North Adriatic case study will be here presented and discussed.

Climate Generation: Advancing Climate Action through Education, Public Engagement and Youth Leadership

NASA Astrophysics Data System (ADS)

Poppleton, K. L. I.

2017-12-01

Climate Generation: A Will Steger Legacy empowers youth, educators, decision-makers and the public to foster climate literacy and action with the goal of building a more equitable and resilient future. We have over eleven years of experience delivering high-quality K-12 education, public engagement and youth leadership programming, reaching over 75,000 people, 35,000 students and 17,000 educators since 2006. By engaging educators, youth, and the public, we believe that communities can be better positioned to build a resilient and equitable future. For this reason we strive to engage with all these sectors through innovative programming and policy initiatives. Communities are resilient when individuals are connected to each other, resources, and decision-makers. Sharing personal narratives, and highlighting locally relevant solutions are all tools that Climate Generation employs to engage the public. We do this through community wide convenings, as well as sector specific events including at breweries, art fairs, and businesses. Education is also an integral piece for sustained action on climate change. We support educators with a science-based, interdisciplinary model of climate change education that engages all learners, and fosters climate literacy and action. We develop curriculum and offer professional development, encouraging teachers to develop today's students into action-competent citizens. Finally, Climate Generation recognizes the importance of empowering high school youth as a key strategy in transitioning to a just and sustainable future for all. We believe in the inherent genius of youth and know from experience that mentorship fosters powerful youth leadership at the community level, inspiring peers, family members, and local decision-makers to take critical action on climate change solutions. In order to accelerate and implement action on climate change we must take a multi-faceted approach: we are building public will for strong climate action at the local and state level; preparing educators and their students to understand the problem and implement clean energy solutions; and pushing our decision-makers to do the right thing via pressure from their constituents, including youth, who can effectively articulate equitable policy solutions and hold officials accountable.

Opportunities and Challenges for the Contribution of Citizen Science to High-Quality, Traceable Indicators of Biodiversity in the Context of Climate Change

NASA Astrophysics Data System (ADS)

Weltzin, J. F.

2014-12-01

Indicators of climate change are designed to communicate key aspects of the status and trends of the physical climate, climate impacts, vulnerabilities, and preparedness to inform both decision makers and the public. The US Environmental Protection Agency (EPA) provides a suite of "Indicators of Climate Change" and the US Global Change Research Program delivers indicators via its "Global Change Information System" (GCIS). The process of research, development and delivery of appropriate indicators of linked to climate change faces challenges including but not limited to (1) lack of data for relevant variables across longitudinal time scales with a defined relationship to climate variation or change, (2) sufficient density and distribution of data across spatial scales to support indicator development for researchers, natural resource managers and decision-makers, and (3) limited engagement of intended stakeholders who may not understand how the data were derived or the potential application of the indicator to their domain. Recent advances in the field of public participation in scientific research (PPSR), also known as "citizen science," represents a potential innovation in monitoring, research, information management and public engagement that can address several of these challenges. Citizen science datasets already available can be decades long and collected at many sites across broad spatial scales; by their nature, they create direct engagement with stakeholders and the public. For example, bird distribution data collected by citizen scientists participating in the continental-scale Christmas Bird Count since 1900 are used in EPA's indicator for "Bird Wintering Ranges." Similarly, plant leafing data collected across the nation since 1956 are combined with meteorological data to create a modeled indicator of plant leafing dates for the GCIS. This presentation will focus on (1) challenges to the development of ecological indicators of biodiversity linked to environmental variation and climate change, (2) how citizen science can address these challenges within suitable domains or disciplines, and (3) minimal requirements for citizen science projects to maximize their contribution to the production of high-quality, traceable indicators of biodiversity.

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations.

PubMed

Gerber, Brian D; Kendall, William L; Hooten, Mevin B; Dubovsky, James A; Drewien, Roderick C

2015-09-01

1. Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. 2. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. 3. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring-summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. 4. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. 5. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Engage, discover, apply, learn, repeat: Implementing a Sustained National Climate Assessment within the United States

NASA Astrophysics Data System (ADS)

Moss, R. H.

2017-12-01

Assessment of potential impacts and adaptations to global environmental change evaluate the continuously evolving state of science through the lens of relevance to challenges such as planning long-lived infrastructure and managing risks to property, ecosystems, public health, and other valued assets or objectives. These planning and decision contexts present varied challenges, including: multiple attributes at risk from interacting environmental and socioeconomic trends; uncertainties (scientific and otherwise); partial solutions with indefinite costs and benefits; and tradeoffs across stakeholder groups. Research and evaluation of assessments indicate they convey information that is more usable and relevant to decision makers if they are designed as sustained interactions of pertinent scientific and user communities and result in products beyond written reports. This talk will report on the work of a Federal Advisory Committee for the Sustained National Climate Assessment (SNCA) to develop recommendations to increase the SNCA's relevance and usability. The recommendations build on the conclusions of a 2013 report by the predecessor SNCA advisory committee and suggest next steps for (1) engagement, (2) provision of core scientific products, (3) tailoring of information and tools to provide insights under uncertainty, and (4) evaluation of products and outcomes. The recommended process focuses on providing insights relevant to consideration of risks and solutions. While resulting in a wide range of products and outcomes on an ongoing basis, aggregation and assessment of emerging insights and good practice for supporting decision making under uncertainty would recur over a four-year adaptive management cycle in the context of the preparation of the US national assessment report mandated under the Global Change Research Act. Uncertainty about the future role of Federal agencies in the assessment process and opportunities for increased engagement by non-Federal actors will be considered.

Exploring Challenges and Opportunities of Coproduction: USDA Climate Hub Efforts to Integrate Coproduction with Applied Research and Decision Support Tool Development in the Northwest

NASA Astrophysics Data System (ADS)

Roesch-McNally, G.; Prendeville, H. R.

2017-12-01

A lack of coproduction, the joint production of new technologies or knowledge among technical experts and other groups, is arguably one of the reasons why much scientific information and resulting decision support systems are not very usable. Increasingly, public agencies and academic institutions are emphasizing the importance of coproduction of scientific knowledge and decision support systems in order to facilitate greater engagement between the scientific community and key stakeholder groups. Coproduction has been embraced as a way for the scientific community to develop actionable scientific information that will assist end users in solving real-world problems. Increasing the level of engagement and stakeholder buy-in to the scientific process is increasingly necessary, particularly in the context of growing politicization of science and the scientific process. Coproduction can be an effective way to build trust and can build-on and integrate local and traditional knowledge. Employing coproduction strategies may enable the development of more relevant and useful information and decision support tools that address stakeholder challenges at relevant scales. The USDA Northwest Climate Hub has increasingly sought ways to integrate coproduction in the development of both applied research projects and the development of decision support systems. Integrating coproduction, however, within existing institutions is not always simple, given that coproduction is often more focused on process than products and products are, for better or worse, often the primary focus of applied research and tool development projects. The USDA Northwest Climate Hub sought to integrate coproduction into our FY2017 call for proposal process. As a result we have a set of proposals and fledgling projects that fall along the engagement continuum (see Figure 1- attached). We will share the challenges and opportunities that emerged from this purposeful integration of coproduction into the work that we prioritized for funding. This effort highlights strategies for how federal agencies might consider how and whether to codify coproduction tenets into their collaborations and agenda setting.

ClimatePipes: User-Friendly Data Access, Manipulation, Analysis & Visualization of Community Climate Models

NASA Astrophysics Data System (ADS)

Chaudhary, A.; DeMarle, D.; Burnett, B.; Harris, C.; Silva, W.; Osmari, D.; Geveci, B.; Silva, C.; Doutriaux, C.; Williams, D. N.

2013-12-01

The impact of climate change will resonate through a broad range of fields including public health, infrastructure, water resources, and many others. Long-term coordinated planning, funding, and action are required for climate change adaptation and mitigation. Unfortunately, widespread use of climate data (simulated and observed) in non-climate science communities is impeded by factors such as large data size, lack of adequate metadata, poor documentation, and lack of sufficient computational and visualization resources. We present ClimatePipes to address many of these challenges by creating an open source platform that provides state-of-the-art, user-friendly data access, analysis, and visualization for climate and other relevant geospatial datasets, making the climate data available to non-researchers, decision-makers, and other stakeholders. The overarching goals of ClimatePipes are: - Enable users to explore real-world questions related to climate change. - Provide tools for data access, analysis, and visualization. - Facilitate collaboration by enabling users to share datasets, workflows, and visualization. ClimatePipes uses a web-based application platform for its widespread support on mainstream operating systems, ease-of-use, and inherent collaboration support. The front-end of ClimatePipes uses HTML5 (WebGL, Canvas2D, CSS3) to deliver state-of-the-art visualization and to provide a best-in-class user experience. The back-end of the ClimatePipes is built around Python using the Visualization Toolkit (VTK, http://vtk.org), Climate Data Analysis Tools (CDAT, http://uv-cdat.llnl.gov), and other climate and geospatial data processing tools such as GDAL and PROJ4. ClimatePipes web-interface to query and access data from remote sources (such as ESGF). Shown in the figure is climate data layer from ESGF on top of map data layer from OpenStreetMap. The ClimatePipes workflow editor provides flexibility and fine grained control, and uses the VisTrails (http://www.vistrails.org) workflow engine in the backend.

Stakeholder-based evaluation categories for regional climate services - a case study at the German Baltic Sea coast

NASA Astrophysics Data System (ADS)

Meinke, Insa

2017-08-01

In this study, categories, dimensions, and criteria for evaluating regional climate services are derived by a participatory approach with potential service users at the German Baltic Sea coast. The development is carried out within nine face-to-face interviews conducted with decision makers, working in climate sensitive sectors at the German Baltic Sea coast. Three main groups of categories were localized which seem to matter most to the considered stakeholders and which seem to be crucial evaluation categories for regional climate services: (1) credibility, (2) relevance, and (3) appropriateness. For each of these evaluation categories several dimensions emerged, indicating certain perspectives of stakeholder demands. When summarizing these evaluation categories and their dimensions, 13 evaluation criteria for regional climate services can be derived (see Table 1). The results show that stakeholders do mainly address components other than those found in the literature (e.g. inputs, process, outputs, outcomes, and impacts). This might indicate that an evaluation, following solely literature-based (non-participative) components, is not sufficient to localize deficiencies or efficiencies within a regional climate service, since it might lead to results which are not relevant for potential users.

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.

Climate Risk Informed Decision Analysis: A Hypothetical Application to the Waas Region

NASA Astrophysics Data System (ADS)

Gilroy, Kristin; Mens, Marjolein; Haasnoot, Marjolijn; Jeuken, Ad

2016-04-01

More frequent and intense hydrologic events under climate change are expected to enhance water security and flood risk management challenges worldwide. Traditional planning approaches must be adapted to address climate change and develop solutions with an appropriate level of robustness and flexibility. The Climate Risk Informed Decision Analysis (CRIDA) method is a novel planning approach embodying a suite of complementary methods, including decision scaling and adaptation pathways. Decision scaling offers a bottom-up approach to assess risk and tailors the complexity of the analysis to the problem at hand and the available capacity. Through adaptation pathway,s an array of future strategies towards climate robustness are developed, ranging in flexibility and immediacy of investments. Flexible pathways include transfer points to other strategies to ensure that the system can be adapted if future conditions vary from those expected. CRIDA combines these two approaches in a stakeholder driven process which guides decision makers through the planning and decision process, taking into account how the confidence in the available science, the consequences in the system, and the capacity of institutions should influence strategy selection. In this presentation, we will explain the CRIDA method and compare it to existing planning processes, such as the US Army Corps of Engineers Principles and Guidelines as well as Integrated Water Resources Management Planning. Then, we will apply the approach to a hypothetical case study for the Waas Region, a large downstream river basin facing rapid development threatened by increased flood risks. Through the case study, we will demonstrate how a stakeholder driven process can be used to evaluate system robustness to climate change; develop adaptation pathways for multiple objectives and criteria; and illustrate how varying levels of confidence, consequences, and capacity would play a role in the decision making process, specifically in regards to the level of robustness and flexibility in the selected strategy. This work will equip practitioners and decision makers with an example of a structured process for decision making under climate uncertainty that can be scaled as needed to the problem at hand. This presentation builds further on another submitted abstract "Climate Risk Informed Decision Analysis (CRIDA): A novel practical guidance for Climate Resilient Investments and Planning" by Jeuken et al.

The World Climate Exercise: Is (Simulated) Experience Our Best Teacher?

NASA Astrophysics Data System (ADS)

Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

2015-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

Climate Literacy in the Classroom: Supporting Teachers in the Transition to NGSS

NASA Astrophysics Data System (ADS)

Rogers, M. J. B.; Merrill, J.; Harcourt, P.; Petrone, C.; Shea, N.; Mead, H.

2014-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

NASA Astrophysics Data System (ADS)

Lissner, T. K.; Reusser, D. E.; Schewe, J.; Lakes, T.; Kropp, J. P.

2014-03-01

Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target-measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models as well as greenhouse gas scenarios are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure Adequate Human livelihood conditions for wEll-being And Development (AHEAD). Based on a transdisciplinary sample of influential concepts addressing human well-being, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows identifying and differentiating uncertainty of climate and impact model projections. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that in many countries today, livelihood conditions are compromised by water scarcity. However, more often, AHEAD fulfilment is limited through other elements. Moreover, the analysis shows that for 44 out of 111 countries, the water-specific uncertainty ranges are outside relevant thresholds for AHEAD, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy-decisions.

Climate Change Information Dashboards for Water Resource Managers

NASA Astrophysics Data System (ADS)

Buja, Lawrence

2016-04-01

It is in the context of its application that one needs to determine if climate information is of high quality and ultimately useful. Therefore, it is important that the intersection between data providers and data consumers is structured in form of an iterative and collaborative exchange where science and application viewpoints can be brought together. A traditional "loading dock"-style hand-off of data fails to optimally inform decisions. It is now broadly recognized that a collaborative, open exchange is better suited to generate credible and salient products and knowledge that can be more confidently used in decisions. But in order for this exchange to be successful in practice, it needs to be sufficiently efficient to actually facilitate an exploratory process that is inherently iterative to determine the most informative products. It also requires a transparent approach that is easily understood and communicated. We will present prototypes of Climate Information Dashboards that collect on a single page to integrate a suite of key climate information for resource managers. The content of dashboards is based on standardized products that can be assembled to meet specific needs. They were co-designed with the water resource managers and are tailored to selected management and decision topics. The visualizations are tuned to quickly provide the basic information, yet below individual diagnostics are more detailed analyses that can be consulted. These dashboards offer a flexible way to connect decision-makers to climate model output. Conversely, such dashboards can also be applied to inform model development by providing insight into a suite of key characteristics of model performance that have been identified as critical by a sector.

Transportation planning, climate change, and decision making under uncertainty

DOT National Transportation Integrated Search

2008-01-01

Case studies are presented that illustrate the application of methods which incorporate : decisionmaking under uncertainty. The applications of these methods that are summarized in : this paper deal with cases outside of transportation, including mil...

Reconciling justice and attribution research to advance climate policy

NASA Astrophysics Data System (ADS)

Huggel, Christian; Wallimann-Helmer, Ivo; Stone, Dáithí; Cramer, Wolfgang

2016-10-01

The Paris Climate Agreement is an important step for international climate policy, but the compensation for negative effects of climate change based on clear assignment of responsibilities remains highly debated. From both a policy and a science perspective, it is unclear how responsibilities should be defined and on what evidence base. We explore different normative principles of justice relevant to climate change impacts, and ask how different forms of causal evidence of impacts drawn from detection and attribution research could inform policy approaches in accordance with justice considerations. We reveal a procedural injustice based on the imbalance of observations and knowledge of impacts between developed and developing countries. This type of injustice needs to be considered in policy negotiations and decisions, and efforts strengthened to reduce it.

Assessing climate-change risks to cultural and natural resources in the Yakima River Basin, Washington, USA

USGS Publications Warehouse

Hatten, James R.; Waste, Stephen M.; Maule, Alec G.

2014-01-01

We provide an overview of an interdisciplinary special issue that examines the influence of climate change on people and fish in the Yakima River Basin, USA. Jenni et al. (2013) addresses stakeholder-relevant climate change issues, such as water availability and uncertainty, with decision analysis tools. Montag et al. (2014) explores Yakama Tribal cultural values and well-being and their incorporation into the decision-making process. Graves and Maule (2012) simulates effects of climate change on stream temperatures under baseline conditions (1981–2005) and two future climate scenarios (increased air temperature of 1 °C and 2 °C). Hardiman and Mesa (2013) looks at the effects of increased stream temperatures on juvenile steelhead growth with a bioenergetics model. Finally, Hatten et al. (2013) examines how changes in stream flow will affect salmonids with a rule-based fish habitat model. Our simulations indicate that future summer will be a very challenging season for salmonids when low flows and high water temperatures can restrict movement, inhibit or alter growth, and decrease habitat. While some of our simulations indicate salmonids may benefit from warmer water temperatures and increased winter flows, the majority of simulations produced less habitat. The floodplain and tributary habitats we sampled are representative of the larger landscape, so it is likely that climate change will reduce salmonid habitat potential throughout particular areas of the basin. Management strategies are needed to minimize potential salmonid habitat bottlenecks that may result from climate change, such as keeping streams cool through riparian protection, stream restoration, and the reduction of water diversions. An investment in decision analysis and support technologies can help managers understand tradeoffs under different climate scenarios and possibly improve water and fish conservation over the next century.

Do quantitative decadal forecasts from GCMs provide decision relevant skill?

NASA Astrophysics Data System (ADS)

Suckling, E. B.; Smith, L. A.

2012-04-01

It is widely held that only physics-based simulation models can capture the dynamics required to provide decision-relevant probabilistic climate predictions. This fact in itself provides no evidence that predictions from today's GCMs are fit for purpose. Empirical (data-based) models are employed to make probability forecasts on decadal timescales, where it is argued that these 'physics free' forecasts provide a quantitative 'zero skill' target for the evaluation of forecasts based on more complicated models. It is demonstrated that these zero skill models are competitive with GCMs on decadal scales for probability forecasts evaluated over the last 50 years. Complications of statistical interpretation due to the 'hindcast' nature of this experiment, and the likely relevance of arguments that the lack of hindcast skill is irrelevant as the signal will soon 'come out of the noise' are discussed. A lack of decision relevant quantiative skill does not bring the science-based insights of anthropogenic warming into doubt, but it does call for a clear quantification of limits, as a function of lead time, for spatial and temporal scales on which decisions based on such model output are expected to prove maladaptive. Failing to do so may risk the credibility of science in support of policy in the long term. The performance amongst a collection of simulation models is evaluated, having transformed ensembles of point forecasts into probability distributions through the kernel dressing procedure [1], according to a selection of proper skill scores [2] and contrasted with purely data-based empirical models. Data-based models are unlikely to yield realistic forecasts for future climate change if the Earth system moves away from the conditions observed in the past, upon which the models are constructed; in this sense the empirical model defines zero skill. When should a decision relevant simulation model be expected to significantly outperform such empirical models? Probability forecasts up to ten years ahead (decadal forecasts) are considered, both on global and regional spatial scales for surface air temperature. Such decadal forecasts are not only important in terms of providing information on the impacts of near-term climate change, but also from the perspective of climate model validation, as hindcast experiments and a sufficient database of historical observations allow standard forecast verification methods to be used. Simulation models from the ENSEMBLES hindcast experiment [3] are evaluated and contrasted with static forecasts of the observed climatology, persistence forecasts and against simple statistical models, called dynamic climatology (DC). It is argued that DC is a more apropriate benchmark in the case of a non-stationary climate. It is found that the ENSEMBLES models do not demonstrate a significant increase in skill relative to the empirical models even at global scales over any lead time up to a decade ahead. It is suggested that the contsruction and co-evaluation with the data-based models become a regular component of the reporting of large simulation model forecasts. The methodology presented may easily be adapted to other forecasting experiments and is expected to influence the design of future experiments. The inclusion of comparisons with dynamic climatology and other data-based approaches provide important information to both scientists and decision makers on which aspects of state-of-the-art simulation forecasts are likely to be fit for purpose. [1] J. Bröcker and L. A. Smith. From ensemble forecasts to predictive distributions, Tellus A, 60(4), 663-678 (2007). [2] J. Bröcker and L. A. Smith. Scoring probabilistic forecasts: The importance of being proper, Weather and Forecasting, 22, 382-388 (2006). [3] F. J. Doblas-Reyes, A. Weisheimer, T. N. Palmer, J. M. Murphy and D. Smith. Forecast quality asessment of the ENSEMBLES seasonal-to-decadal stream 2 hindcasts, ECMWF Technical Memorandum, 621 (2010).

How to Reach Decision Makers: Build a network of educators and practitioners with common goals

NASA Astrophysics Data System (ADS)

Boudrias, M. A.; Estrada, M.; Anders, S.; Silva-Send, N. J.; Gershunov, A.

2013-12-01

In San Diego County, the Climate Education Partners (CEP) includes climate scientists, science educators, behavioral scientists, environmental practitioners and community organizations that are dedicated to providing local decision makers (elected officials, business leaders, community leaders) with sound climate science learning opportunities and resources that promote informed decision making. Their work over the past three years has found that effective climate education programs are designed for specific audiences with tailored information that is relevant to them, while simultaneously building community efficacy, identity and values. An integrated approach that blends rigorous scientific facts, local climate change impact, and social science education theory is contributing towards the development of a cadre of engaged leaders and communities. To track project progress and to inform the project strategy, local Key Influentials are being interviewed to gauge their current understanding of climate change and their interest in either becoming messengers to their community or becoming the portal to their constituency. Innovation comes from productive collaboration. For this reason, CEP has been working with leading scientists (climatologists, hydrologists, meteorologists, ecologists), environmental groups, museums and zoos, media experts and government agencies (Water Authority, CalFire) to develop and refine a program of learning activities and resources geared specifically for Key Influentials. For example, a water tour has been designed to bring 25 key influential leaders in San Diego County to a dam, a pumping station and a reservoir and provide climate change facts, impacts and potential solutions to the critical issue of water supply for the San Diego Region. While learning local facts about the causes and impacts of climate change, participants also learn about what they can do (increasing efficacy), that they can be a part of a solution centered community (building identity), and that everything - the education and the use of this knowledge to promote informed decisions - is connected to doing what is best for the next generation (tying learning to values). In addition, CEP developed locally focused videos, one on heat waves and one on water resources, which are being experimentally tested for their impact on informed decision-making and utilized with various KI audiences. Climate Education Partners is finding that linking excellent science with healthy community partnerships is resulting in San Diego leaders and their communities making more informed decisions on how to adapt to climate change and preserve the quality of life enjoyed in San Diego for all future generations.

Interagency collaboration in the Rocky Mountains and Great Plains: Federal-university climate service networks for producing actionable information for climate change adaptation

NASA Astrophysics Data System (ADS)

Ray, A. J.; McNie, E.; Averyt, K.; Morisette, J. T.; Derner, J. D.; Ojima, D. S.; Dilling, L.; Barsugli, J. J.

2014-12-01

Several federal agencies in north-central United States are each working to develop and disseminate useful climate information to enhance resilience to climate change. This talk will discuss how the U.S. Geological Survey (USGS) the North Central Climate Science Center, the National Oceanic and Atmospheric Administration Western Water Assessment RISA, and the U.S. Department of Agriculture Climate Hub, are building and managing a collaborative research and climate-service network in the Rocky Mountains and Great Plains. This presentation will describe the evolution of the interagency collaboration and the partnership with universities to build a climate service network. Such collaboration takes time and intention and must include the right people and organizations to effectively bridge the gap between use-inspired research and application. In particular, we will discuss a focus on the Upper Missouri Basin, developing research to meet needs in a basin that has had relatively less attention on risks of climate change and adaptation to those risks. Each organization has its own mission, stakeholders, and priorities, but there are many commonalities and potential synergies. Together, these organizations, and their agency scientists and university partners, are fostering cross-agency collaboration at the regional scale to optimize efficient allocation of resources while simultaneously enabling information to be generated at a scale that is relevant to decision makers. By each organization knowing the others needs and priorities, there are opportunities to craft research agendas and strategies for providing services that take advantage of the strengths and skills of the different organizations. University partners are key components of each organization, and of the collaboration, who bring in expertise beyond that in the agencies, in particular connections to social scientists, extension services.

Atmospheric Aerosol Properties and Climate Impacts

NASA Technical Reports Server (NTRS)

Chin, Mian; Kahn, Ralph A.; Remer, Lorraine A.; Yu, Hongbin; Rind, David; Feingold, Graham; Quinn, Patricia K.; Schwartz, Stephen E.; Streets, David G.; DeCola, Phillip;

Regional climate response collaboratives: Multi-institutional support for climate resilience

USGS Publications Warehouse

Averyt, Kristen; Derner, Justin D.; Dilling, Lisa; Guerrero, Rafael; Joyce, Linda A.; McNeeley, Shannon; McNie, Elizabeth; Morisette, Jeffrey T.; Ojima, Dennis; O'Malley, Robin; Peck, Dannele; Ray, Andrea J.; Reeves, Matt; Travis, William

2018-01-01

Federal investments by U.S. agencies to enhance climate resilience at regional scales grew over the past decade (2010s). To maximize efficiency and effectiveness in serving multiple sectors and scales, it has become critical to leverage existing agency-specific research, infrastructure, and capacity while avoiding redundancy. We discuss lessons learned from a multi-institutional “regional climate response collaborative” that comprises three different federally-supported climate service entities in the Rocky Mountain west and northern plains region. These lessons include leveraging different strengths of each partner, creating deliberate mechanisms to increase cross-entity communication and joint ownership of projects, and placing a common priority on stakeholder-relevant research and outcomes. We share the conditions that fostered successful collaboration, which can be transferred elsewhere, and suggest mechanisms for overcoming potential barriers. Synergies are essential for producing actionable research that informs climate-related decisions for stakeholders and ultimately enhances climate resilience at regional scales.

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

USGS Publications Warehouse

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

2010-01-01

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

Problems, Prescriptions and Potential in Actionable Climate Change Science - A Case Study from California Coastal Marsh Research

NASA Astrophysics Data System (ADS)

MacDonald, G. M.; Ambrose, R. F.; Thorne, K.; Takekawa, J.; Brown, L. N.; Fejtek, S.; Gold, M.; Rosencranz, J.

2015-12-01

Frustrations regarding the provision of actionable science extend to both producers and consumers. Scientists decry the lack of application of their research in shaping policy and practices while decision makers bemoan the lack of applicability of scientific research to the specific problems at hand or its narrow focus relative to the plethora of engineering, economic and social considerations that they must also consider. Incorporating climate change adds additional complexity due to uncertainties in estimating many facets of future climate, the inherent variability of climate and the decadal scales over which significant changes will develop. Recently a set of guidelines for successful science-policy interaction was derived from the analysis of transboundary water management. These are; 1 recognizing that science is a crucial but bounded input into the decision-making processes, 2 early establishment of conditions for collaboration and shared commitment among participants, 3 understanding that science-policy interactions are enhanced through greater collaboration and social or group-learning processes, 4 accepting that the collaborative production of knowledge is essential to build legitimate decision-making processes, and 5 engaging boundary organizations and informal networks as well as formal stakeholders. Here we present as a case study research on California coastal marshes, climate change and sea-level that is being conducted by university and USGS scientists under the auspices of the Southwest Climate Science Center. We also present research needs identified by a seperate analysis of best practices for coastal marsh restoration in the face of climate change that was conducted in extensive consultation with planners and managers. The initial communication, scientific research and outreach-dissemination of the marsh scientfic study are outlined and compared to best practices needs identified by planners and the science-policy guidelines outlined above. Matches, mismatches, early-stage evidence of applicability and potential improvements of program development and design are considered.

Analysis and Lessons Learned from an Online, Consultative Dialogue between Community Leaders and Climate Experts

NASA Astrophysics Data System (ADS)

Sylak-Glassman, E.; Clavin, C.

2016-12-01

Common approaches to climate resilience planning in the United States rely upon participatory planning approaches and dialogues between decision-makers, science translators, and subject matter experts. In an effort to explore alternative approaches support community climate resilience planning, a pilot of a public-private collaboration called the Resilience Dialogues was held in February and March of 2016. The Resilience Dialogues pilot was an online, asynchronous conversation between community leaders and climate experts, designed to help communities begin the process of climate resilience planning. In order to identify lessons learned from the pilot, we analyzed the discourse of the facilitated dialogues, administered surveys and conducted interviews with participants. Our analysis of the pilot suggests that participating community leaders found value in the consultative dialogue with climate experts, despite limited community-originated requests for climate information. Community leaders most often asked for advice regarding adaptation planning, including specific engineering guidance and advice on how to engage community members around the topic of resilience. Community leaders that had access to downscaled climate data asked experts about how to incorporate the data into their existing planning processes. The guidance sought by community leaders during the pilot shows a large range of hurdles that communities face in using climate information to inform their decision-making processes. Having a forum that connects community leaders with relevant experts and other community leaders who have familiarity with both climate impacts and municipal planning processes would likely help communities accelerate their resilience efforts.

Resource management and operations in central North Dakota: Climate change scenario planning workshop summary November 12-13, 2015, Bismarck, ND

USGS Publications Warehouse

Fisichelli, Nicholas A.; Schuurman, Gregor; Symstad, Amy J.; Ray, Andrea; Friedman, Jonathan M.; Miller, Brian; Rowland, Erika

2016-01-01

The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties.This report summarizes project work for public and tribal lands in the central North Dakota focal area, with an emphasis on Knife River Indian Villages National Historic Site. The report explainsscenario planning as an adaptation tool in general, then describes how it was applied to the central North Dakota focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held November 12-13, 2015 in Bismarck, ND, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.

Resource management and operations in southwest South Dakota: Climate change scenario planning workshop summary January 20-21, 2016, Rapid City, SD

USGS Publications Warehouse

Fisichelli, Nicholas A.; Schuurman, Gregor W.; Symstad, Amy J.; Ray, Andrea; Miller, Brian; Cross, Molly; Rowland, Erika

2016-01-01

The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties.This report summarizes project work for public and tribal lands in the southwest South Dakota grasslands focal area, with an emphasis on Badlands National Park and Buffalo Gap National Grassland. The report explains scenario planning as an adaptation tool in general, then describes how it was applied to the focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held January 20-21, 2016 in Rapid City, South Dakota, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.

Decision strategies for handling the uncertainty of future extreme rainfall under the influence of climate change.

PubMed

Gregersen, I B; Arnbjerg-Nielsen, K

2012-01-01

Several extraordinary rainfall events have occurred in Denmark within the last few years. For each event, problems in urban areas occurred as the capacity of the existing drainage systems were exceeded. Adaptation to climate change is necessary but also very challenging as urban drainage systems are characterized by long technical lifetimes and high, unrecoverable construction costs. One of the most important barriers for the initiation and implementation of the adaptation strategies is therefore the uncertainty when predicting the magnitude of the extreme rainfall in the future. This challenge is explored through the application and discussion of three different theoretical decision support strategies: the precautionary principle, the minimax strategy and Bayesian decision support. The reviewed decision support strategies all proved valuable for addressing the identified uncertainties, at best applied together as they all yield information that improved decision making and thus enabled more robust decisions.

Climate sensitivity uncertainty: when is good news bad?

PubMed

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

2015-11-28

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

Ecohydrology of agroecosystems: probabilistic description of yield reduction risk under limited water availability

NASA Astrophysics Data System (ADS)

Vico, Giulia; Porporato, Amilcare

2013-04-01

Supplemental irrigation represents one of the main strategies to mitigate the effects of climate variability and stabilize yields. Irrigated agriculture currently provides 40% of food production and its relevance is expected to further increase in the near future, in face of the projected alterations of rainfall patterns and increase in food, fiber, and biofuel demand. Because of the significant investments and water requirements involved in irrigation, strategic choices are needed to preserve productivity and profitability, while maintaining a sustainable water management - a nontrivial task given the unpredictability of the rainfall forcing. To facilitate decision making under uncertainty, a widely applicable probabilistic framework is proposed. The occurrence of rainfall events and irrigation applications are linked probabilistically to crop development during the growing season and yields at harvest. Based on these linkages, the probability density function of yields and corresponding probability density function of required irrigation volumes, as well as the probability density function of yields under the most common case of limited water availability are obtained analytically, as a function of irrigation strategy, climate, soil and crop parameters. The full probabilistic description of the frequency of occurrence of yields and water requirements is a crucial tool for decision making under uncertainty, e.g., via expected utility analysis. Furthermore, the knowledge of the probability density function of yield allows us to quantify the yield reduction hydrologic risk. Two risk indices are defined and quantified: the long-term risk index, suitable for long-term irrigation strategy assessment and investment planning, and the real-time risk index, providing a rigorous probabilistic quantification of the emergence of drought conditions during a single growing season in an agricultural setting. Our approach employs relatively few parameters and is thus easily and broadly applicable to different crops and sites, under current and future climate scenarios. Hence, the proposed probabilistic framework provides a quantitative tool to assess the impact of irrigation strategy and water allocation on the risk of not meeting a certain target yield, thus guiding the optimal allocation of water resources for human and environmental needs.

32 CFR 724.802 - Applicant's responsibilities.

Code of Federal Regulations, 2012 CFR

2012-07-01

... shall identify the page, paragraph, and sentence incorporated. Because it is to the applicant's benefit... Reading Room), applicants must provide the NDRB with copies of such decisions or of the relevant portion...

32 CFR 724.802 - Applicant's responsibilities.

Code of Federal Regulations, 2014 CFR

2014-07-01

... shall identify the page, paragraph, and sentence incorporated. Because it is to the applicant's benefit... Reading Room), applicants must provide the NDRB with copies of such decisions or of the relevant portion...

32 CFR 724.802 - Applicant's responsibilities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... shall identify the page, paragraph, and sentence incorporated. Because it is to the applicant's benefit... Reading Room), applicants must provide the NDRB with copies of such decisions or of the relevant portion...

Near-Term Actions to Address Long-Term Climate Risk

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2014-12-01

Addressing climate change requires effective long-term policy making, which occurs when reflecting on potential events decades or more in the future causes policy makers to choose near-term actions different than those they would otherwise pursue. Contrary to some expectations, policy makers do sometimes make such long-term decisions, but not as commonly and successfully as climate change may require. In recent years however, the new capabilities of analytic decision support tools, combined with improved understanding of cognitive and organizational behaviors, has significantly improved the methods available for organizations to manage longer-term climate risks. In particular, these tools allow decision makers to understand what near-term actions consistently contribute to achieving both short- and long-term societal goals, even in the face of deep uncertainty regarding the long-term future. This talk will describe applications of these approaches for infrastructure, water, and flood risk management planning, as well as studies of how near-term choices about policy architectures can affect long-term greenhouse gas emission reduction pathways.

Regional Integrated Assessments in Support of Decision-making: Process, Product, and Policy

NASA Astrophysics Data System (ADS)

Luers, A. L.; Hayhoe, K.

2006-12-01

Regional integrated climate assessments are increasingly viewed as critical for informing sound climate policy. Yet, the scientific information in many assessments often is not effectively transformed in to policies to protect the environment. Why are some assessments more effective at informing policies than others? We will provide some insight into this question by describing the lessons learned from a series of regional assessments organized by the Union of Concerned Scientists (UCS). Working with independent experts in the global change research community, UCS has produced assessments in three regions of the US California, the Great Lakes, and the Gulf Coast. The reports from each of these assessments continue to be used by local, state and regional decision-makers in related management and policy initiatives. We attribute the success of these assessments in motivating and supporting climate-related decisions to four factors: (1) credibility, attained both through scientific peer-review and by engaging local scientific and community leaders; (2) regional relevance of assessment focus areas; (3) accessible presentation of the results to non-technical audiences; and (4) wide communication and distribution of the report to the media, the public, civic groups, and public officials.

Leveraging modern climatology to increase adaptive capacity across protected area networks

USGS Publications Warehouse

Davison, J.E.; Graumlich, L.J.; Rowland, E.L.; Pederson, G.T.; Breshears, D.D.

2012-01-01

Human-driven changes in the global environment pose an increasingly urgent challenge for the management of ecosystems that is made all the more difficult by the uncertain future of both environmental conditions and ecological responses. Land managers need strategies to increase regional adaptive capacity, but relevant and rapid assessment approaches are lacking. To address this need, we developed a method to assess regional protected area networks across biophysically important climatic gradients often linked to biodiversity and ecosystem function. We plot the land of the southwestern United States across axes of historical climate space, and identify landscapes that may serve as strategic additions to current protected area portfolios. Considering climate space is straightforward, and it can be applied using a variety of relevant climate parameters across differing levels of land protection status. The resulting maps identify lands that are climatically distinct from existing protected areas, and may be utilized in combination with other ecological and socio-economic information essential to collaborative landscape-scale decision-making. Alongside other strategies intended to protect species of special concern, natural resources, and other ecosystem services, the methods presented herein provide another important hedging strategy intended to increase the adaptive capacity of protected area networks. ?? 2011 Elsevier Ltd.

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

ECOLOGICAL RISK ASSESSMENT IN THE CONTEXT OF GLOBAL CLIMATE CHANGE

PubMed Central

Landis, Wayne G; Durda, Judi L; Brooks, Marjorie L; Chapman, Peter M; Menzie, Charles A; Stahl, Ralph G; Stauber, Jennifer L

2013-01-01

Changes to sources, stressors, habitats, and geographic ranges; toxicological effects; end points; and uncertainty estimation require significant changes in the implementation of ecological risk assessment (ERA). Because of the lack of analog systems and circumstances in historically studied sites, there is a likelihood of type III error. As a first step, the authors propose a decision key to aid managers and risk assessors in determining when and to what extent climate change should be incorporated. Next, when global climate change is an important factor, the authors recommend seven critical changes to ERA. First, develop conceptual cause–effect diagrams that consider relevant management decisions as well as appropriate spatial and temporal scales to include both direct and indirect effects of climate change and the stressor of management interest. Second, develop assessment end points that are expressed as ecosystem services. Third, evaluate multiple stressors and nonlinear responses—include the chemicals and the stressors related to climate change. Fourth, estimate how climate change will affect or modify management options as the impacts become manifest. Fifth, consider the direction and rate of change relative to management objectives, recognizing that both positive and negative outcomes can occur. Sixth, determine the major drivers of uncertainty, estimating and bounding stochastic uncertainty spatially, temporally, and progressively. Seventh, plan for adaptive management to account for changing environmental conditions and consequent changes to ecosystem services. Good communication is essential for making risk-related information understandable and useful for managers and stakeholders to implement a successful risk-assessment and decision-making process. Environ. Toxicol. Chem. 2013;32:79–92. © 2012 SETAC PMID:23161373

Ecological risk assessment in the context of global climate change.

PubMed

Landis, Wayne G; Durda, Judi L; Brooks, Marjorie L; Chapman, Peter M; Menzie, Charles A; Stahl, Ralph G; Stauber, Jennifer L

2013-01-01

Changes to sources, stressors, habitats, and geographic ranges; toxicological effects; end points; and uncertainty estimation require significant changes in the implementation of ecological risk assessment (ERA). Because of the lack of analog systems and circumstances in historically studied sites, there is a likelihood of type III error. As a first step, the authors propose a decision key to aid managers and risk assessors in determining when and to what extent climate change should be incorporated. Next, when global climate change is an important factor, the authors recommend seven critical changes to ERA. First, develop conceptual cause-effect diagrams that consider relevant management decisions as well as appropriate spatial and temporal scales to include both direct and indirect effects of climate change and the stressor of management interest. Second, develop assessment end points that are expressed as ecosystem services. Third, evaluate multiple stressors and nonlinear responses-include the chemicals and the stressors related to climate change. Fourth, estimate how climate change will affect or modify management options as the impacts become manifest. Fifth, consider the direction and rate of change relative to management objectives, recognizing that both positive and negative outcomes can occur. Sixth, determine the major drivers of uncertainty, estimating and bounding stochastic uncertainty spatially, temporally, and progressively. Seventh, plan for adaptive management to account for changing environmental conditions and consequent changes to ecosystem services. Good communication is essential for making risk-related information understandable and useful for managers and stakeholders to implement a successful risk-assessment and decision-making process. Copyright © 2012 SETAC.

Do We Need Better Climate Predictions to Adapt to a Changing Climate? (Invited)

NASA Astrophysics Data System (ADS)

Dessai, S.; Hulme, M.; Lempert, R.; Pielke, R., Jr.

2009-12-01

Based on a series of international scientific assessments, climate change has been presented to society as a major problem that needs urgently to be tackled. The science that underpins these assessments has been pre-dominantly from the realm of the natural sciences and central to this framing have been ‘projections’ of future climate change (and its impacts on environment and society) under various greenhouse gas emissions scenarios and using a variety of climate model predictions with embedded assumptions. Central to much of the discussion surrounding adaptation to climate change is the claim - explicit or implicit - that decision makers need accurate and increasingly precise assessments of future impacts of climate change in order to adapt successfully. If true, this claim places a high premium on accurate and precise climate predictions at a range of geographical and temporal scales; such predictions therefore become indispensable, and indeed a prerequisite for, effective adaptation decision-making. But is effective adaptation tied to the ability of the scientific enterprise to predict future climate with accuracy and precision? If so, this may impose a serious and intractable limit on adaptation. This paper proceeds in three sections. It first gathers evidence of claims that climate prediction is necessary for adaptation decision-making. This evidence is drawn from peer-reviewed literature and from published science funding strategies and government policy in a number of different countries. The second part discusses the challenges of climate prediction and why science will consistently be unable to provide accurate and precise predictions of future climate relevant for adaptation (usually at the local/regional level). Section three discusses whether these limits to future foresight represent a limit to adaptation, arguing that effective adaptation need not be limited by a general inability to predict future climate. Given the deep uncertainties involved in climate prediction (and even more so in the prediction of climate impacts) and given that climate is usually only one factor in decisions aimed at climate adaptation, we conclude that the ‘predict and provide’ approach to science in support of climate change adaptation is largely flawed. We consider other important areas of public policy fraught with uncertainty - e.g. earthquake risk, national security, public health - where such a ‘predict and provide’ approach is not attempted. Instead of relying on an approach which has climate prediction (and consequent risk assessment) at its heart - which because of the associated epistemological limits to prediction will consequently act as an apparent limit to adaptation - we need to view adaptation differently, in a manner that opens up options for decision making under uncertainty. We suggest an approach which examines the robustness of adaptation strategies/policies/activities to the myriad of uncertainties that face us in the future, only one of which is the state of climate.

Climate Change, Public Health, and Decision Support: The New Threat of Vector-borne Disease

NASA Astrophysics Data System (ADS)

Grant, F.; Kumar, S.

2011-12-01

Climate change and vector-borne diseases constitute a massive threat to human development. It will not be enough to cut emissions of greenhouse gases-the tide of the future has already been established. Climate change and vector-borne diseases are already undermining the world's efforts to reduce extreme poverty. It is in the best interests of the world leaders to think in terms of concerted global actions, but adaptation and mitigation must be accomplished within the context of local community conditions, resources, and needs. Failure to act will continue to consign developed countries to completely avoidable health risks and significant expense. Failure to act will also reduce poorest of the world's population-some 2.6 billion people-to a future of diminished opportunity. Northrop Grumman has taken significant steps forward to develop the tools needed to assess climate change impacts on public health, collect relevant data for decision making, model projections at regional and local levels; and, deliver information and knowledge to local and regional stakeholders. Supporting these tools is an advanced enterprise architecture consisting of high performance computing, GIS visualization, and standards-based architecture. To address current deficiencies in local planning and decision making with respect to regional climate change and its effect on human health, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model to develop decision aids that translate the regional climate data into actionable information for users. For the present climate WRF was forced with the Max Planck Institute European Center/Hamburg Model version 5 (ECHAM5) General Circulation Model 20th century simulation. For the 21th century climate, we used an ECHAM5 simulation with the Special Report on Emissions (SRES) A1B emissions scenario. WRF was run in nested mode at spatial resolution of 108 km, 36 km and 12 km and 28 vertical levels. This model was examined relative to two mosquito vectors, both competent carriers of dengue fever, a viral, vector-borne disease. Models which incorporate public health considerations can enable decision makers to take proactive steps to mitigate the impacts and adapt to the changing environmental conditions. In this paper we provide a snapshot of our climate initiative and some examples relative to our public health practice work in vector-borne diseases to illustrate how integrated decision support could be of assistance to regional and local communities worldwide.

KNOW ESSENTIALS: a tool for informed decisions in the absence of formal HTA systems.

PubMed

Mathew, Joseph L

2011-04-01

Most developing countries and resource-limited settings lack robust health technology assessment (HTA) systems. Because the development of locally relevant HTA is not immediately viable, and the extrapolation of external HTA is inappropriate, a new model for evaluating health technologies is required. The aim of this study was to describe the development and application of KNOW ESSENTIALS, a tool facilitating evidence-based decisions on health technologies by stakeholders in settings lacking formal HTA systems. Current HTA methodology was examined through literature search. Additional issues relevant to resource-limited settings, but not adequately addressed in current methodology, were identified through further literature search, appraisal of contextually relevant issues, discussion with healthcare professionals familiar with the local context, and personal experience. A set of thirteen elements important for evidence-based decisions was identified, selected and combined into a tool with the mnemonic KNOW ESSENTIALS. Detailed definitions for each element, coding for the elements, and a system to evaluate a given health technology using the tool were developed. Developing countries and resource-limited settings face several challenges to informed decision making. Models that are relevant and applicable in high-income countries are unlikely in such settings. KNOW ESSENTIALS is an alternative that facilitates evidence-based decision making by stakeholders without formal expertise in HTA. The tool could be particularly useful, as an interim measure, in healthcare systems that are developing HTA capacity. It could also be useful anywhere when rapid evidence-based decisions on health technologies are required.

Climate sensitivity estimated from temperature reconstructions of the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Schmittner, A.; Urban, N.; Shakun, J. D.; Mahowald, N. M.; Clark, P. U.; Bartlein, P. J.; Mix, A. C.; Rosell-Melé, A.

2011-12-01

In 1959 IJ Good published the discussion "Kinds of Probability" in Science. Good identified (at least) five kinds. The need for (at least) a sixth kind of probability when quantifying uncertainty in the context of climate science is discussed. This discussion brings out the differences in weather-like forecasting tasks and climate-links tasks, with a focus on the effective use both of science and of modelling in support of decision making. Good also introduced the idea of a "Dynamic probability" a probability one expects to change without any additional empirical evidence; the probabilities assigned by a chess playing program when it is only half thorough its analysis being an example. This case is contrasted with the case of "Mature probabilities" where a forecast algorithm (or model) has converged on its asymptotic probabilities and the question hinges in whether or not those probabilities are expected to change significantly before the event in question occurs, even in the absence of new empirical evidence. If so, then how might one report and deploy such immature probabilities in scientific-support of decision-making rationally? Mature Probability is suggested as a useful sixth kind, although Good would doubtlessly argue that we can get by with just one, effective communication with decision makers may be enhanced by speaking as if the others existed. This again highlights the distinction between weather-like contexts and climate-like contexts. In the former context one has access to a relevant climatology (a relevant, arguably informative distribution prior to any model simulations), in the latter context that information is not available although one can fall back on the scientific basis upon which the model itself rests, and estimate the probability that the model output is in fact misinformative. This subjective "probability of a big surprise" is one way to communicate the probability of model-based information holding in practice, the probability that the information the model-based probability is conditioned on holds. It is argued that no model-based climate-like probability forecast is complete without a quantitative estimate of its own irrelevance, and that the clear identification of model-based probability forecasts as mature or immature, are critical elements for maintaining the credibility of science-based decision support, and can shape uncertainty quantification more widely.

Wetlands as large-scale nature-based solutions: status and future challenges for research and management

NASA Astrophysics Data System (ADS)

Thorslund, Josefin; Jarsjö, Jerker; Destouni, Georgia

2017-04-01

Wetlands are often considered as nature-based solutions that can provide a multitude of services of great social, economic and environmental value to humankind. The services may include recreation, greenhouse gas sequestration, contaminant retention, coastal protection, groundwater level and soil moisture regulation, flood regulation and biodiversity support. Changes in land-use, water use and climate can all impact wetland functions and occur at scales extending well beyond the local scale of an individual wetland. However, in practical applications, management decisions usually regard and focus on individual wetland sites and local conditions. To understand the potential usefulness and services of wetlands as larger-scale nature-based solutions, e.g. for mitigating negative impacts from large-scale change pressures, one needs to understand the combined function multiple wetlands at the relevant large scales. We here systematically investigate if and to what extent research so far has addressed the large-scale dynamics of landscape systems with multiple wetlands, which are likely to be relevant for understanding impacts of regional to global change. Our investigation regards key changes and impacts of relevance for nature-based solutions, such as large-scale nutrient and pollution retention, flow regulation and coastal protection. Although such large-scale knowledge is still limited, evidence suggests that the aggregated functions and effects of multiple wetlands in the landscape can differ considerably from those observed at individual wetlands. Such scale differences may have important implications for wetland function-effect predictability and management under large-scale change pressures and impacts, such as those of climate change.

From vision to action: roadmapping as a strategic method and tool to implement climate change adaptation - the example of the roadmap 'water sensitive urban design 2020'.

PubMed

Hasse, J U; Weingaertner, D E

2016-01-01

As the central product of the BMBF-KLIMZUG-funded Joint Network and Research Project (JNRP) 'dynaklim - Dynamic adaptation of regional planning and development processes to the effects of climate change in the Emscher-Lippe region (North Rhine Westphalia, Germany)', the Roadmap 2020 'Regional Climate Adaptation' has been developed by the various regional stakeholders and institutions containing specific regional scenarios, strategies and adaptation measures applicable throughout the region. This paper presents the method, elements and main results of this regional roadmap process by using the example of the thematic sub-roadmap 'Water Sensitive Urban Design 2020'. With a focus on the process support tool 'KlimaFLEX', one of the main adaptation measures of the WSUD 2020 roadmap, typical challenges for integrated climate change adaptation like scattered knowledge, knowledge gaps and divided responsibilities but also potential solutions and promising chances for urban development and urban water management are discussed. With the roadmap and the related tool, the relevant stakeholders of the Emscher-Lippe region have jointly developed important prerequisites to integrate their knowledge, to clarify vulnerabilities, adaptation goals, responsibilities and interests, and to foresightedly coordinate measures, resources, priorities and schedules for an efficient joint urban planning, well-grounded decision-making in times of continued uncertainties and step-by-step implementation of adaptation measures from now on.

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.

UQ for Decision Making: How (at least five) Kinds of Probability Might Come Into Play

NASA Astrophysics Data System (ADS)

Smith, L. A.

2013-12-01

In 1959 IJ Good published the discussion "Kinds of Probability" in Science. Good identified (at least) five kinds. The need for (at least) a sixth kind of probability when quantifying uncertainty in the context of climate science is discussed. This discussion brings out the differences in weather-like forecasting tasks and climate-links tasks, with a focus on the effective use both of science and of modelling in support of decision making. Good also introduced the idea of a "Dynamic probability" a probability one expects to change without any additional empirical evidence; the probabilities assigned by a chess playing program when it is only half thorough its analysis being an example. This case is contrasted with the case of "Mature probabilities" where a forecast algorithm (or model) has converged on its asymptotic probabilities and the question hinges in whether or not those probabilities are expected to change significantly before the event in question occurs, even in the absence of new empirical evidence. If so, then how might one report and deploy such immature probabilities in scientific-support of decision-making rationally? Mature Probability is suggested as a useful sixth kind, although Good would doubtlessly argue that we can get by with just one, effective communication with decision makers may be enhanced by speaking as if the others existed. This again highlights the distinction between weather-like contexts and climate-like contexts. In the former context one has access to a relevant climatology (a relevant, arguably informative distribution prior to any model simulations), in the latter context that information is not available although one can fall back on the scientific basis upon which the model itself rests, and estimate the probability that the model output is in fact misinformative. This subjective "probability of a big surprise" is one way to communicate the probability of model-based information holding in practice, the probability that the information the model-based probability is conditioned on holds. It is argued that no model-based climate-like probability forecast is complete without a quantitative estimate of its own irrelevance, and that the clear identification of model-based probability forecasts as mature or immature, are critical elements for maintaining the credibility of science-based decision support, and can shape uncertainty quantification more widely.

Impact of Seasonal Forecasts on Agriculture

NASA Astrophysics Data System (ADS)

Aldor-Noiman, S. C.

2014-12-01

More extreme and volatile weather conditions are a threat to U.S. agricultural productivity today, as multiple environmental conditions during the growing season impact crop yields. That's why farmers' agronomic management decisions are dominated by consideration for near, medium and seasonal forecasts of climate. The Climate Corporation aims to help farmers around the world protect and improve their farming operations by providing agronomic decision support tools that leverage forecasts on multiple timescales to provide valuable insights directly to farmers. In this talk, we will discuss the impact of accurate seasonal forecasts on major decisions growers face each season. We will also discuss assessment and evaluation of seasonal forecasts in the context of agricultural applications.

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

Ernst, Kathleen M; Van Riemsdijk, Dr. Micheline

This article studies the participation of stakeholders in climate change decision-making in Alaska s National Parks. We place stakeholder participation within literatures on environmental and climate change decision-making. We conducted participant observation and interviews in two planning workshops to investigate the decision-making process, and our findings are three-fold. First, the inclusion of diverse stakeholders expanded climate change decision-making beyond National Park Service (NPS) institutional constraints. Second, workshops of the Climate Change Scenario Planning Project (CCSPP) enhanced institutional understandings of participants attitudes towards climate change and climate change decision-making. Third, the geographical context of climate change influences the decision-making process. Asmore » the first regional approach to climate change decision-making within the NPS, the CCSPP serves as a model for future climate change planning in public land agencies. This study shows how the participation of stakeholders can contribute to robust decisions, may move climate change decision-making beyond institutional barriers, and can provide information about attitudes towards climate change decision-making.« less

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.

Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

NASA Astrophysics Data System (ADS)

Samaras, C.; Cook, L.

2015-12-01

Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.

Engaging science in a climate of values: tools for animal scientists tasked with addressing ethical problems.

PubMed

Croney, C C; Anthony, R

2010-04-01

In the United States, escalating concerns about current farm animal science and production methods have resulted not only in increased food animal protection policies, but also in animal welfare legislation. Animal scientists and industry leaders are apprehensive that such policies may be driven primarily by emotion and a lack of scientific understanding, and thus may have unforeseen consequences. However, decisions about animal care, and particularly animal welfare, cannot be made solely on the basis of science because the potential effects on producers, animals, and concerned citizens and the implications for the environment and on food prices must also be considered. Balancing the interests and values of all stakeholders in regard to animal welfare problems has presented a considerable challenge. Ethical accounting processes, such as the Ethical Matrix and the ethics assessment process by Campbell, offer models to combine socioethical concerns with relevant factual information, thereby facilitating decision making that is ethically responsible and that offers viable solutions. A case study is used to illustrate application of the ethics assessment process by Campbell that includes identification of the ethical problems, the embedded values, the relevant facts, and moral tests that can be applied. Awareness of these emerging ways of examining ethics that offer real solutions to conflicts of interests and not merely "one size fits all" answers should be an asset to animal and poultry scientists.

Identifying climate risk perceptions, information needs, and barriers to information exchange among public land managers.

PubMed

Peters, Casey B; Schwartz, Mark W; Lubell, Mark N

2018-03-01

Meeting ecosystem management challenges posed by climate change requires building effective communication channels among researchers, planners and practitioners to focus research on management issues requiring new knowledge. We surveyed resource managers within two regions of the western United States regions to better understand perceived risks and vulnerabilities associated with climate change and barriers to obtaining and using relevant climate science information in making ecosystem management decisions. We sought to understand what types of climate science information resource managers find most valuable, and the formats in which they prefer to receive climate science information. We found broad concern among natural resource managers in federal agencies that climate change will make it more difficult for them to achieve their management goals. Primary barriers to incorporating climate science into planning are distributed among challenges identifying, receiving, and interpreting appropriate science and a lack of direction provided by agency leadership needed to meaningfully use this emerging science in resource planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Producing regionally-relevant multiobjective tradeoffs to engage with Colorado water managers

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Basdekas, L.; Dilling, L.

2016-12-01

Disseminating results from water resources systems analysis research can be challenging when there are political or regulatory barriers associated with real-world models, or when a research model does not incorporate management context to which practitioners can relate. As part of a larger transdisciplinary study, we developed a broadly-applicable case study in collaboration with our partners at six diverse water utilities in the Front Range of Colorado, USA. Our model, called the "Eldorado Utility Planning Model", incorporates realistic water management decisions and objectives and achieves a pragmatic balance between system complexity and simplicity. Using the sophisticated modeling platform RiverWare, we modeled a spatially distributed regional network in which, under varying climate scenarios, the Eldorado Utility can meet growing demand from its variety of sources and by interacting with other users in the network. In accordance with complicated Front Range water laws, ownership, priority of use, and restricted uses of water are tracked through RiverWare's accounting functionality. To achieve good system performance, Eldorado can make decisions such as expand/build a reservoir, purchase rights from one or more actors, and enact conservation. This presentation introduces the model, and motivates how it can be used to aid researchers in developing multi-objective evolutionary algorithm (MOEA)-based optimization for similar multi-reservoir systems in Colorado and the Western US. Within the optimization, system performance is quantified by 5 objectives: minimizing time in restrictions; new storage capacity; newly developed supply; and uncaptured water; and maximizing year-end storage. Our results demonstrate critical tradeoffs between the objectives and show how these tradeoffs are affected by several realistic climate change scenarios. These results were used within an interactive workshop that helped demonstrate the application of MOEA-based optimization for water management in the western US.

Phenology for science, resource management, decision making, and education

USGS Publications Warehouse

Nolan, V.P.; Weltzin, J.F.

2011-01-01

Fourth USA National Phenology Network (USA-NPN) Research Coordination Network (RCN) Annual Meeting and Stakeholders Workshop; Milwaukee, Wisconsin, 21-22 September 2010; Phenology, the study of recurring plant and animal life cycle events, is rapidly emerging as a fundamental approach for understanding how ecological systems respond to environmental variation and climate change. The USA National Phenology Network (USA-NPN; http://www.usanpn.org) is a large-scale network of governmental and nongovernmental organizations, academic institutions, resource management agencies, and tribes. The network is dedicated to conducting and promoting repeated and integrated plant and animal phenological observations, identifying linkages with other relevant biological and physical data sources, and developing and distributing the tools to analyze these data at local to national scales. The primary goal of the USA-NPN is to improve the ability of decision makers to design strategies for climate adaptation.

Phenology for Science, Resource Management, Decision Making, and Education

NASA Astrophysics Data System (ADS)

Nolan, Vivian P.; Weltzin, Jake F.

2011-01-01

Fourth USA National Phenology Network (USA-NPN) Research Coordination Network (RCN) Annual Meeting and Stakeholders Workshop; Milwaukee, Wisconsin, 21-22 September 2010; Phenology, the study of recurring plant and animal life cycle events, is rapidly emerging as a fundamental approach for understanding how ecological systems respond to environmental variation and climate change. The USA National Phenology Network (USA-NPN; http://www.usanpn.org) is a large-scale network of governmental and nongovernmental organizations, academic institutions, resource management agencies, and tribes. The network is dedicated to conducting and promoting repeated and integrated plant and animal phenological observations, identifying linkages with other relevant biological and physical data sources, and developing and distributing the tools to analyze these data at local to national scales. The primary goal of the USA-NPN is to improve the ability of decision makers to design strategies for climate adaptation.

Community-level climate change vulnerability research: trends, progress, and future directions

NASA Astrophysics Data System (ADS)

McDowell, Graham; Ford, James; Jones, Julie

2016-03-01

This study systematically identifies, characterizes, and critically evaluates community-level climate change vulnerability assessments published over the last 25 years (n = 274). We find that while the field has advanced considerably in terms of conceptual framing and methodological approaches, key shortcomings remain in how vulnerability is being studied at the community-level. We argue that vulnerability research needs to more critically engage with the following: methods for evaluating future vulnerability, the relevance of vulnerability research for decision-making, interdependencies between social and ecological systems, attention to researcher / subject power dynamics, critical interpretation of key terms, and consideration of the potentially positive opportunities presented by a changing climate. Addressing these research needs is necessary for generating knowledge that supports climate-affected communities in navigating the challenges and opportunities ahead.

Understanding Optimal Military Decision Making: Year 2 Progress Report

DTIC Science & Technology

2014-01-01

measures. ARMY RELEVANCY AND MILITARY APPLICATION AREAS Objectively defining, measuring, and developing a means to assess military optimal decision making...has the potential to enhance training and refine procedures supporting more efficient learning and task accomplishment. Through the application of...26.79 (12.39) 7.94 (62.38) N/A = Not applicable ; as it is not possible to calculate this particular variable. Table 2. Descriptive statistics of

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.

Exploring regional stakeholder needs and requirements in terms of Extreme Weather Event Attribution

NASA Astrophysics Data System (ADS)

Schwab, M.; Meinke, I.; Vanderlinden, J. P.; Touili, N.; Von Storch, H.

2015-12-01

Extreme event attribution has increasingly received attention in the scientific community. It may also serve decision-making at the regional level where much of the climate change impact mitigation takes place. Nevertheless, there is, to date, little known about the requirements of regional actors in terms of extreme event attribution. We have therefore analysed these at the example of regional decision-makers for climate change-related activities and/or concerned with storm surge risks at the German Baltic Sea and heat wave risks in the Greater Paris area. In order to explore if stakeholders find scientific knowledge from extreme event attribution useful and how this information might be relevant to their decision-making, we consulted a diverse set of actors engaged in the assessment, mitigation and communication of storm surge, heat wave, and climate change-related risks. Extreme event attribution knowledge was perceived to be most useful to public and political awareness-raising, but was of little or no relevance for the consulted stakeholders themselves. It was not acknowledged that it would support adaptation planning as sometimes argued in the literature. The consulted coastal protection, health, and urban adaptation planners rather needed reliable statements about possible future changes in extreme events than causal statements about past events. To enhance salience, a suitable product of event attribution should be linked to regional problems, vulnerabilities, and impacts of climate change. Given that the tolerance of uncertainty is rather low, most of the stakeholders also claimed that a suitable product of event attribution is to be received from a trusted "honest broker" and published rather later, but with smaller uncertainties than vice versa. Institutional mechanisms, like regional climate services, which enable and foster communication, translation and mediation across the boundaries between knowledge and action can help fulfill such requirements. This is of particular importance for extreme event attribution which is often understood as science producing complex and abstract information attached to large uncertainties. They can serve as an interface for creating the necessary mutual understanding by being in a continuous dialogue with both science and stakeholders.

Useful global-change scenarios: current issues and challenges

NASA Astrophysics Data System (ADS)

Parson, E. A.

2008-10-01

Scenarios are increasingly used to inform global-change debates, but their connection to decisions has been weak and indirect. This reflects the greater number and variety of potential users and scenario needs, relative to other decision domains where scenario use is more established. Global-change scenario needs include common elements, e.g., model-generated projections of emissions and climate change, needed by many users but in different ways and with different assumptions. For these common elements, the limited ability to engage diverse global-change users in scenario development requires extreme transparency in communicating underlying reasoning and assumptions, including probability judgments. Other scenario needs are specific to users, requiring a decentralized network of scenario and assessment organizations to disseminate and interpret common elements and add elements requiring local context or expertise. Such an approach will make global-change scenarios more useful for decisions, but not less controversial. Despite predictable attacks, scenario-based reasoning is necessary for responsible global-change decisions because decision-relevant uncertainties cannot be specified scientifically. The purpose of scenarios is not to avoid speculation, but to make the required speculation more disciplined, more anchored in relevant scientific knowledge when available, and more transparent.

Introduction to health economics and decision-making: Is economics relevant for the frontline clinician?

PubMed

Goeree, Ron; Diaby, Vakaramoko

2013-12-01

In a climate of escalating demands for new health care services and significant constraints on new resources, the disciplines of health economics and health technology assessment (HTA) have increasingly been turned to as explicit evidence-based frameworks to help make tough health care access and reimbursement decisions. Health economics is the discipline of economics concerned with the efficient allocation of health care resources, essentially trying to maximize health benefits to society contingent upon available resources. HTA is a broader field drawing upon several disciplines, but which relies heavily upon the tools of health economics and economic evaluation. Traditionally, health economics and economic evaluation have been widely used at the political (macro) and local (meso) decision-making levels, and have progressively had an important role even at informing individual clinical decisions (micro level). The aim of this paper is to introduce readers to health economics and discuss its relevance to frontline clinicians. Particularly, the content of the paper will facilitate clinicians' understanding of the link between economics and their medical practice, and how clinical decision-making reflects on health care resource allocation. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Ernst, Kathleen M; Van Riemsdijk, Dr. Micheline

This article studies the participation of stakeholders in climate change decision-making in Alaska s National Parks. We place stakeholder participation within literatures on environmental and climate change decision-making. We conducted participant observation and interviews in two planning workshops to investigate the decision-making process, and our findings are three-fold. First, the inclusion of diverse stakeholders expanded climate change decision-making beyond National Park Service (NPS) institutional constraints. Second, workshops of the Climate Change Scenario Planning Project (CCSPP) enhanced institutional understandings of participants attitudes towards climate change and climate change decision-making. Third, the geographical context of climate change influences the decisionmaking process. Asmore » the first regional approach to climate change decision-making within the NPS, the CCSPP serves as a model for future climate change planning in public land agencies. This study shows how the participation of stakeholders can contribute to robust decisions, may move climate change decision-making beyond institutional barriers, and can provide information about attitudes towards climate change decision-making.« less

Lessons and challenges from adaptation pathways planning applications

NASA Astrophysics Data System (ADS)

Haasnoot, M.; Lawrence, J.; Kwakkel, J. H.; Walker, W.; Timmermans, J.; Bloemen, P.; Thissen, W.

2015-12-01

Planning for adaptation to dynamic risks (e.g., because of climate change) is a critical need. The concept of 'adaptive policies' is receiving increasing attention as a way of performing strategic planning that is able to address many of the inherent challenges of uncertainty and dynamic change. Several approaches for developing adaptive policies are available in the literature. One approach, for which several applications already exist, is Dynamic Adaptive Policy Pathways (DAPP). Pathway maps enable policy analysts, decision makers, and stakeholders to recognize potential 'locked-in' situations and to assess the flexibility, robustness, and efficacy of decision alternatives. Most of the applications of DAPP have been in deltas, coastal cities, or floodplains, often within the context of climate change adaptation. In this talk, we describe the DAPP approach and present a framework for designing signposts as adaptation signals, together with an illustrative application for the Rhine River in the Netherlands. We also draw lessons and challenges from pathways applications that differ in environment, culture, and institutional context. For example, the Dutch Delta Programme has used pathways to identify short-term decisions and long-term policy options. In Bangladesh, an application is in its early phase. Steps before generating pathways - such as long- term thinking in multiple possible futures and acknowledging uncertainties - are already a big challenge there. In New Zealand, the 'Sustainable Delta Game' has been used as the catalyst for pathways thinking by two local councils. This has led to its application in decision making for coastal and flood risk management and economic analysis of policy options.

Building Capacity to Use Earth Observations in Decision Making for Climate, Health, Agriculture and Natural Disasters

NASA Astrophysics Data System (ADS)

Robertson, A. W.; Ceccato, P.

2015-12-01

In order to fill the gaps existing in climate and public health, agriculture, natural disasters knowledge and practices, the International Research Institute for Climate and Society (IRI) has developed a Curriculum for Best Practices in Climate Information. This Curriculum builds on the experience of 10 years courses on 'Climate Information' and captures lessons and experiences from different tailored trainings that have been implemented in many countries in Africa, Asia and Latin America. In this presentation, we will provide examples of training activities we have developed to bring remote sensing products to monitor climatic and environmental information into decision processes that benefited users such as the World Health Organization, Ministries of Health, Ministries of Agriculture, Universities, Research Centers such as CIFOR and FIOCRUZ. The framework developed by IRI to provide capacity building is based on the IDEAS framework: Innovation (research) Around climate impacts, evaluation of interventions, and the value of climate information in reducing risks and maximizing opportunities Demonstration E.g. in-country GFCS projects in Tanzania and Malawi - or El Nino work in Ethiopia Education Academic and professional training efforts Advocacy This might focus on communication of variability and change? We are WHO collaborating center so are engaged through RBM/Global Malaria Programme Service ENACTS and Data library key to this. Country data better quality than NASA as incorporates all relevant station data and NASA products. This presentation will demonstrate how the IDEAS framework has been implemented and lessons learned.

How Five Master Teachers Teach about Climate Chang

NASA Astrophysics Data System (ADS)

Bloch, L.

2015-12-01

The AGU Position Statement, "Human-Induced Climate Change Requires Urgent Action," calls on scientists to "[work] with stakeholders to identify relevant information, and [to convey] understanding clearly and accurately, both to decision makers and to the general public". Everyday, K-12 teachers communicate with an important segment of the general public, and they represent important stakeholders with unique needs. The terms 'global warming', 'greenhouse effect', and 'climate change' appear nowhere in the 1996 National Science Education Standards, but under the Next Generation Science Standards, millions of teachers- most of whom have little to no experience teaching about climate change- will be required to cover the topic. This presentation discusses research conducted with five veteran public school teachers, each of whom has been teaching about climate change for many years. The group comprises three high school teachers, a middle school teacher, and an elementary school teacher. The study examined: 1) What these teachers teach about climate change; 2) How they teach about climate change; 3) What resources they use in teaching and learning about climate change; and 4) How they think the scientific community can support teachers in their efforts to teach about climate change. The teachers varied in their teaching practices and in their conceptions of 'climate change', but they all said that the academic community can support climate change education by developing locally relevant educational resources. Scientists working with K-12 teachers can build on the work of these master teachers, and attendees can access detailed descriptions of all of the lessons and the associated learning materials.

Adaptive Regulation of the Northern California Reservoir System for Water, Energy, and Environmental Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.; Kistenmacher, M.; Yao, H.; Georgakakos, K. P.

2014-12-01

The 2014 National Climate Assessment of the US Global Change Research Program emphasizes that water resources managers and planners in most US regions will have to cope with new risks, vulnerabilities, and opportunities, and recommends the development of adaptive capacity to effectively respond to the new water resources planning and management challenges. In the face of these challenges, adaptive reservoir regulation is becoming all the more ncessary. Water resources management in Northern California relies on the coordinated operation of several multi-objective reservoirs on the Trinity, Sacramento, American, Feather, and San Joaquin Rivers. To be effective, reservoir regulation must be able to (a) account for forecast uncertainty; (b) assess changing tradeoffs among water uses and regions; and (c) adjust management policies as conditions change; and (d) evaluate the socio-economic and environmental benefits and risks of forecasts and policies for each region and for the system as a whole. The Integrated Forecast and Reservoir Management (INFORM) prototype demonstration project operated in Northern California through the collaboration of several forecast and management agencies has shown that decision support systems (DSS) with these attributes add value to stakeholder decision processes compared to current, less flexible management practices. Key features of the INFORM DSS include: (a) dynamically downscaled operational forecasts and climate projections that maintain the spatio-temporal coherence of the downscaled land surface forcing fields within synoptic scales; (b) use of ensemble forecast methodologies for reservoir inflows; (c) assessment of relevant tradeoffs among water uses on regional and local scales; (d) development and evaluation of dynamic reservoir policies with explicit consideration of hydro-climatic forecast uncertainties; and (e) focus on stakeholder information needs.This article discusses the INFORM integrated design concept, underlying methodologies, and selected applications with the California water resources system.

Climate Change and Agriculture in the U.S.: Effects and Adaptation (Invited)

NASA Astrophysics Data System (ADS)

Walsh, M. K.; Rippey, B.; Walthall, C. L.; Hatfield, J.; Backlund, P. W.; Lengnick, L.; Marshall, E.

2013-12-01

Agriculture in the United States has followed a path of continual adaptation to a wide range of factors throughout its history. However, observational evidence, supported by an understanding of the physical climate system, shows that human-induced climate change is underway in the U.S. and even now causing changes for which there is no historical reference for producers. Temperatures have increased and precipitation patterns have changed; the incidence, frequency, and extent of pest infestations have been altered, as well as the natural resource base (water, air, and soils) upon which production depends. Each factor challenges agricultural management as atmospheric concentrations of greenhouse gases rise. These trends are likely to continue over the next century. Importantly, a gap exists between U.S. agricultural producers and managers' needs related to climate-driven problems and the information that research currently offers them. In the past, agricultural research into climate change effects has largely focused on mean values of precipitation and temperature. Today's management requirements, however, often demand immediate response on shorter time scales to address abrupt, often novel needs. Further complicating this reality, future decisions will likely require even greater emphasis on managing under increasing levels of uncertainty, and planning for and adjusting to the extremes. Research is moving to better address these emerging issues for the relevant timescales and parameters in order to allow the formulation of improved and resilient management strategies that apply to a future in which past experience has become less applicable. A climate-ready U.S. agricultural system requires easy access to useable climate knowledge and technical resources, improved climate risk management strategies, new processes to support effective adaptive actions, and the development of sustainable production systems resilient to climate effects. Mainstreaming climate knowledge improves adaptive capacity of the agricultural system by ensuring that land managers, technical advisors, researchers, private businesspeople, government program managers, and policymakers are aware of current and projected climate impacts and can access best management practices to reduce risks and capture opportunities.

Reaching a Consensus on the Definition of Genetic Literacy that Is Required from a Twenty-First-Century Citizen

NASA Astrophysics Data System (ADS)

Boerwinkel, Dirk Jan; Yarden, Anat; Waarlo, Arend Jan

2017-12-01

To determine what knowledge of genetics is needed for decision-making on genetic-related issues, a consensus-reaching approach was used. An international group of 57 experts, involved in teaching, studying, or developing genetic education and communication or working with genetic applications in medicine, agriculture, or forensics, answered the questions: "What knowledge of genetics is relevant to those individuals not professionally involved in science?" and "Why is this knowledge relevant?" The answers were classified in different knowledge components following the PISA 2015 science framework. During a workshop with the participants, the results were discussed and applied to seven cases in which genetic knowledge is relevant for decision-making. The analysis of these discussions resulted in a revised framework consisting of nine conceptual knowledge components, three sociocultural components, and four epistemic components. The framework can be used in curricular decisions; its open character allows for including new technologies and applications and facilitates comparisons of different cases.

From climate model ensembles to climate change impacts and adaptation: A case study of water resource management in the southwest of England

NASA Astrophysics Data System (ADS)

Lopez, Ana; Fung, Fai; New, Mark; Watts, Glenn; Weston, Alan; Wilby, Robert L.

2009-08-01

The majority of climate change impacts and adaptation studies so far have been based on at most a few deterministic realizations of future climate, usually representing different emissions scenarios. Large ensembles of climate models are increasingly available either as ensembles of opportunity or perturbed physics ensembles, providing a wealth of additional data that is potentially useful for improving adaptation strategies to climate change. Because of the novelty of this ensemble information, there is little previous experience of practical applications or of the added value of this information for impacts and adaptation decision making. This paper evaluates the value of perturbed physics ensembles of climate models for understanding and planning public water supply under climate change. We deliberately select water resource models that are already used by water supply companies and regulators on the assumption that uptake of information from large ensembles of climate models will be more likely if it does not involve significant investment in new modeling tools and methods. We illustrate the methods with a case study on the Wimbleball water resource zone in the southwest of England. This zone is sufficiently simple to demonstrate the utility of the approach but with enough complexity to allow a variety of different decisions to be made. Our research shows that the additional information contained in the climate model ensemble provides a better understanding of the possible ranges of future conditions, compared to the use of single-model scenarios. Furthermore, with careful presentation, decision makers will find the results from large ensembles of models more accessible and be able to more easily compare the merits of different management options and the timing of different adaptation. The overhead in additional time and expertise for carrying out the impacts analysis will be justified by the increased quality of the decision-making process. We remark that even though we have focused our study on a water resource system in the United Kingdom, our conclusions about the added value of climate model ensembles in guiding adaptation decisions can be generalized to other sectors and geographical regions.

Lessons learned from a rigorous peer-review process for building the Climate Literacy and Energy Awareness (CLEAN) collection of high-quality digital teaching materials

NASA Astrophysics Data System (ADS)

Gold, A. U.; Ledley, T. S.; McCaffrey, M. S.; Buhr, S. M.; Manduca, C. A.; Niepold, F.; Fox, S.; Howell, C. D.; Lynds, S. E.

2010-12-01

The topic of climate change permeates all aspects of our society: the news, household debates, scientific conferences, etc. To provide students with accurate information about climate science and energy awareness, educators require scientifically and pedagogically robust teaching materials. To address this need, the NSF-funded Climate Literacy & Energy Awareness Network (CLEAN) Pathway has assembled a new peer-reviewed digital collection as part of the National Science Digital Library (NSDL) featuring teaching materials centered on climate and energy science for grades 6 through 16. The scope and framework of the collection is defined by the Essential Principles of Climate Science (CCSP 2009) and a set of energy awareness principles developed in the project. The collection provides trustworthy teaching materials on these socially relevant topics and prepares students to become responsible decision-makers. While a peer-review process is desirable for curriculum developer as well as collection builder to ensure quality, its implementation is non-trivial. We have designed a rigorous and transparent peer-review process for the CLEAN collection, and our experiences provide general guidelines that can be used to judge the quality of digital teaching materials across disciplines. Our multi-stage review process ensures that only resources with teaching goals relevant to developing climate literacy and energy awareness are considered. Each relevant resource is reviewed by two individuals to assess the i) scientific accuracy, ii) pedagogic effectiveness, and iii) usability/technical quality. A science review by an expert ensures the scientific quality and accuracy. Resources that pass all review steps are forwarded to a review panel of educators and scientists who make a final decision regarding inclusion of the materials in the CLEAN collection. Results from the first panel review show that about 20% (~100) of the resources that were initially considered for inclusion passed final review. Reviewer comments are recorded as annotations to enhance the resources in the collection and help educators with the implementation in their curriculum. CLEAN launched the first collection of digital educational resources about climate science and energy awareness in November 2010. The final CLEAN collection will include ≥500 resources and will also provide the alignment with the Benchmarks for Science Literacy and the NAAEE Excellence in Environmental Education Guidelines for Learning through the interactive NSDL strandmaps. We will present the first user feedback to this new collection.

Science and Systems in Support of Multi-hazard Early Warnings and Decisions

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2015-12-01

The demand for improved climate knowledge and information is well documented. As noted in the IPCC (SREX, AR5), the UNISDR Global Assessment Reports and other assessments, this demand has increased pressure for information to support planning under changing rates and emergence of multiple hazards including climate extremes (drought, heat waves, floods). "Decision support" is now a popular term in the climate applications research community. While existing decision support activities can be identified in many disparate settings (e.g. federal, academic, private), the challenge of changing environments (coupled physical and social) is actually one of crafting implementation strategies for improving decision quality (not just meeting "user needs"). This includes overcoming weaknesses in co-production models, moving beyond DSSs as simply "software", coordinating innovation mapping and diffusion, and providing fora and gaming tools to identify common interests and differences in the way risks are perceived and managed among the affected groups. We outline the development and evolution of multi-hazard early warning systems in the United States and elsewhere, focusing on climate-related hazards. In particular, the presentation will focus on the climate science and information needed for (1) improved monitoring and modeling, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds, (4) the net benefits of using new information (5) characterizing and bridging the "last mile" in the context of longer-term risk management.

What lies behind crop decisions?Coming to terms with revealing farmers' preferences

NASA Astrophysics Data System (ADS)

Gomez, C.; Gutierrez, C.; Pulido-Velazquez, M.; López Nicolás, A.

2016-12-01

The paper offers a fully-fledged applied revealed preference methodology to screen and represent farmers' choices as the solution of an optimal program involving trade-offs among the alternative welfare outcomes of crop decisions such as profits, income security and management easiness. The recursive two-stage method is proposed as an alternative to cope with the methodological problems inherent to common practice positive mathematical program methodologies (PMP). Differently from PMP, in the model proposed in this paper, the non-linear costs that are required for both calibration and smooth adjustment are not at odds with the assumptions of linear Leontief technologies and fixed crop prices and input costs. The method frees the model from ad-hoc assumptions about costs and then recovers the potential of economic analysis as a means to understand the rationale behind observed and forecasted farmers' decisions and then to enhance the potential of the model to support policy making in relevant domains such as agricultural policy, water management, risk management and climate change adaptation. After the introduction, where the methodological drawbacks and challenges are set up, section two presents the theoretical model, section three develops its empirical application and presents its implementation to a Spanish irrigation district and finally section four concludes and makes suggestions for further research.

How seasonal forecast could help a decision maker: an example of climate service for water resource management

NASA Astrophysics Data System (ADS)

Viel, Christian; Beaulant, Anne-Lise; Soubeyroux, Jean-Michel; Céron, Jean-Pierre

2016-04-01

The FP7 project EUPORIAS was a great opportunity for the climate community to co-design with stakeholders some original and innovative climate services at seasonal time scales. In this framework, Météo-France proposed a prototype that aimed to provide to water resource managers some tailored information to better anticipate the coming season. It is based on a forecasting system, built on a refined hydrological suite, forced by a coupled seasonal forecast model. It particularly delivers probabilistic river flow prediction on river basins all over the French territory. This paper presents the work we have done with "EPTB Seine Grands Lacs" (EPTB SGL), an institutional stakeholder in charge of the management of 4 great reservoirs on the upper Seine Basin. First, we present the co-design phase, which means the translation of classical climate outputs into several indices, relevant to influence the stakeholder's decision making process (DMP). And second, we detail the evaluation of the impact of the forecast on the DMP. This evaluation is based on an experiment realised in collaboration with the stakeholder. Concretely EPTB SGL has replayed some past decisions, in three different contexts: without any forecast, with a forecast A and with a forecast B. One of forecast A and B really contained seasonal forecast, the other only contained random forecasts taken from past climate. This placebo experiment, realised in a blind test, allowed us to calculate promising skill scores of the DMP based on seasonal forecast in comparison to a classical approach based on climatology, and to EPTG SGL current practice.

NASA Earth Observations Informing Renewable Energy Management and Policy Decision Making

NASA Technical Reports Server (NTRS)

Eckman, Richard S.; Stackhouse, Paul W., Jr.

2008-01-01

The NASA Applied Sciences Program partners with domestic and international governmental organizations, universities, and private entities to improve their decisions and assessments. These improvements are enabled by using the knowledge generated from research resulting from spacecraft observations and model predictions conducted by NASA and providing these as inputs to the decision support and scenario assessment tools used by partner organizations. The Program is divided into eight societal benefit areas, aligned in general with the Global Earth Observation System of Systems (GEOSS) themes. The Climate Application of the Applied Sciences Program has as one of its focuses, efforts to provide for improved decisions and assessments in the areas of renewable energy technologies, energy efficiency, and climate change impacts. The goals of the Applied Sciences Program are aligned with national initiatives such as the U.S. Climate Change Science and Technology Programs and with those of international organizations including the Group on Earth Observations (GEO) and the Committee on Earth Observation Satellites (CEOS). Activities within the Program are funded principally through proposals submitted in response to annual solicitations and reviewed by peers.

Reply to Comment on ‘The climate mitigation gap: education and government recommendations miss the most effective individual actions’

NASA Astrophysics Data System (ADS)

Wynes, Seth; Nicholas, Kimberly A.

2018-04-01

In their comment piece, van Basshuysen and Brandstedt raise three main issues: first, whether population at the global scale, or individual family planning decisions, are relevant for climate change mitigation; second, they offer useful critiques of the methodologies to attribute greenhouse gas emissions for the choice to have a child; and third, they question the appropriate ethical responsibility for emissions resulting from personal choices. Here we reply that first, we consider choices regarding family size to meet the authors’ criteria for actions ‘under the control of the individual agent and which, with a significant probability, contribute to’ (increased greenhouse gas emissions), and therefore are relevant to consider for climate mitigation. Second, we acknowledge both methodological issues inherent in allocating responsibility for emissions, and encourage more research on this topic especially for the climate impact of reproductive choices. Third, we address ethical questions about responsibility for emissions, and conclude that while such discussions are important, and individual choices are only one part of necessary emissions reductions, people alive today are the last to have a chance at remaining within the carbon budget to meet international climate targets, and therefore do have a special responsibility to reduce emissions.

Types of Forecast and Weather-Related Information Used among Tourism Businesses in Coastal North Carolina

NASA Astrophysics Data System (ADS)

Ayscue, Emily P.

This study profiles the coastal tourism sector, a large and diverse consumer of climate and weather information. It is crucial to provide reliable, accurate and relevant resources for the climate and weather-sensitive portions of this stakeholder group in order to guide them in capitalizing on current climate and weather conditions and to prepare them for potential changes. An online survey of tourism business owners, managers and support specialists was conducted within the eight North Carolina oceanfront counties asking respondents about forecasts they use and for what purposes as well as why certain forecasts are not used. Respondents were also asked about their perceived dependency of their business on climate and weather as well as how valuable different forecasts are to their decision-making. Business types represented include: Agriculture, Outdoor Recreation, Accommodations, Food Services, Parks and Heritage, and Other. Weekly forecasts were the most popular forecasts with Monthly and Seasonal being the least used. MANOVA and ANOVA analyses revealed outdoor-oriented businesses (Agriculture and Outdoor Recreation) as perceiving themselves significantly more dependent on climate and weather than indoor-oriented ones (Food Services and Accommodations). Outdoor businesses also valued short-range forecasts significantly more than indoor businesses. This suggests a positive relationship between perceived climate and weather dependency and forecast value. The low perceived dependency and value of short-range forecasts of indoor businesses presents an opportunity to create climate and weather information resources directed at how they can capitalize on positive climate and weather forecasts and how to counter negative effects with forecasted adverse conditions. The low use of long-range forecasts among all business types can be related to the low value placed on these forecasts. However, these forecasts are still important in that they are used to make more financially risky decisions such as investment decisions.

An Agenda for Climate Impacts Science

NASA Astrophysics Data System (ADS)

Kaye, J. A.

2009-12-01

The report Global Change Impacts in the United States released by the US Global Change Research Program in June 2009 identifies a number of areas in which inadequate information or understanding hampers our ability to estimate likely future climate change and its impacts. In this section of the report, the focus is on those areas of climate science that could contribute most towards advancing our knowledge of climate change impacts and those aspects of climate change responsible for these impacts in order to continue to guide decision making. The Report identifies the six most important gaps in knowledge and offers some thoughts on how to address those gaps: 1. Expand our understanding of climate change impacts. There is a clear need to increase understanding of how ecosystems, social and economic systems, human health, and the built environment will be affected by climate change in the context of other stresses. 2. Refine ability to project climate change, including extreme events, at local scales. While climate change is a global issue, it has a great deal of regional variability. There is an indisputable need to improve understanding of climate system effects at these smaller scales, because these are often the scales of decision-making in society. This includes advances in modeling capability and observations needed to address local scales and high-impact extreme events. 3. Expand capacity to provide decision makers and the public with relevant information on climate change and its impacts. Significant potential exists in the US to create more comprehensive measurement, archive, and data-access systems that could provide great benefit to society, which requires defining needed information, gathering it, expanding capacity to deliver it, and improving tools by which decision makers use it to best advantage. 4. Improve understanding of thresholds likely to lead to abrupt changes in climate or ecosystems. Potential areas of research include thresholds that could lead to rapid changes in ice-sheet dynamics that could impact future sea-level rise and tipping points in biological systems (including those that may be associated with ocean acidification). 5. Improve understanding of the most effective ways to reduce the rate and magnitude of climate change, as well as unintended consequences of such actions. Research will help to identify the desired mix of mitigation options necessary to control the rate and magnitude of climate change, and to examine possible unintended consequences of mitigation options. 6. Enhance understanding of how society can adapt to climate change. There is currently limited knowledge about the ability of communities, regions, and sectors to adapt to future climate change. It is important to improve understanding of how to enhance society’s capacity to adapt to a changing climate in the context of other environmental stresses.

Communicating climate change adaptation information using web-based platforms

NASA Astrophysics Data System (ADS)

Karali, Eleni; Mattern, Kati

2017-07-01

To facilitate progress in climate change adaptation policy and practice, it is important not only to ensure the production of accurate, comprehensive and relevant information, but also the easy, timely and affordable access to it. This can contribute to better-informed decisions and improve the design and implementation of adaptation policies and other relevant initiatives. Web-based platforms can play an important role in communicating and distributing data, information and knowledge that become constantly available, reaching out to a large group of potential users. Indeed in the last decade there has been an extensive increase in the number of platforms developed for this purpose in many fields including climate change adaptation. This short paper concentrates on the web-based adaptation platforms developed in Europe. It provides an overview of the recently emerged landscape, examines the basic characteristics of a set of platforms that operate at national, transnational and European level, and discusses some of the key challenges related to their development, maintenance and overall management. Findings presented in this short paper are discussed in greater detailed in the Technical Report of the European Environment Agency Overview of climate change adaptation platforms in Europe.

Large rainfall changes consistently projected over substantial areas of tropical land

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Good, Peter; Martin, Gill; Rowell, David P.

2016-02-01

Many tropical countries are exceptionally vulnerable to changes in rainfall patterns, with floods or droughts often severely affecting human life and health, food and water supplies, ecosystems and infrastructure. There is widespread disagreement among climate model projections of how and where rainfall will change over tropical land at the regional scales relevant to impacts, with different models predicting the position of current tropical wet and dry regions to shift in different ways. Here we show that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century. The area of semi-arid land affected by large changes under a higher emissions scenario is likely to be greater than during even the most extreme regional wet or dry periods of the twentieth century, such as the Sahel drought of the late 1960s to 1990s. Substantial changes are projected to occur by mid-century--earlier than previously expected--and to intensify in line with global temperature rise. Therefore, current climate projections contain quantitative, decision-relevant information on future regional rainfall changes, particularly with regard to climate change mitigation policy.

Urbanism, climate change and health: systems approaches to governance.

PubMed

Capon, Anthony G; Synnott, Emma S; Holliday, Sue

2009-01-01

Effective action on climate change health impacts and vulnerability will require systems approaches and integrated policy and planning responses from a range of government agencies. Similar responses are needed to address other complex problems, such as the obesity epidemic. Local government, with its focus on the governance of place, will have a key role in responding to these convergent agendas. Industry can also be part of the solution - indeed it must be, because it has a lead role in relevant sectors. Understanding the co-benefits for health of climate mitigation actions will strengthen the case for early action. There is a need for improved decision support tools to inform urban governance. These tools should be based on a systems approach and should incorporate a spatial perspective.

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.

Responding to climate change in New York State: the ClimAID integrated assessment for effective climate change adaptation in New York State. Final report.

PubMed

2011-12-01

Climate change is already beginning to affect New York State, and these impacts are projected to grow. At the same time, the state has the ability to develop adaptation strategies to prepare for and respond to climate risks now and in the future. The ClimAID assessment provides information on climate change impacts and adaptation for eight sectors in New York State: water resources, coastal zones, ecosystems, agriculture, energy, transportation,telecommunications, and public health. Observed climate trends and future climate projections were developed for seven regions across the state. Within each of the sectors, climate risks, vulnerabilities, and adaptation strategies are identified. Integrating themes across all of the sectors are equity and environmental justice and economics.Case studies are used to examine specific vulnerabilities and potential adaptation strategies in each of the eight sectors. These case studies also illustrate the linkages among climate vulnerabilities, risks, and adaptation, and demonstrate specific monitoring needs. Stakeholder participation was critical to the ClimAID assessment process to ensure relevance to decision makers across the state.

CREAT Risk Assessment Application for Water Utilities

EPA Pesticide Factsheets

CREAT allows users to evaluate potential impacts of climate change on their utility and to evaluate adaptation options to address them using both traditional risk assessment and scenario-based decision making.

Tele-Epidemiology and Public Health in the Canadian Context

NASA Astrophysics Data System (ADS)

Brazeau, Stephanie; Kotchi, Serge Olivier; Ludwig, Antoinette; Turgeon, Patricia; Pelcat, Yann; Aube, Guy; Ogden, Nicholas H.

2016-08-01

The management of key public health issues requires solid evidence-based knowledge for the prevention and control of various emerging or re-emerging vector borne diseases (e.g. Lyme disease, West Nile virus, etc.) and environmentally-linked diseases (e.g. enteric infections from recreational water contamination). Earth observation (EO) images enhance knowledge and capacity to characterize risk of illness across the vast Canadian territory by deriving new and up-to-date data from population, climatic and environmental determinants of health relevant to public health actions such as risk mapping, risk communication and identification of vulnerable populations.Modeling of infectious disease transmission has made possible the identification of risk areas and the underlying factors (human activities, ecology, environment and climate) that may explain this emergence. New data products derived from Earth observation satellites pertaining to climate, land cover and land use, and distribution and density of animal and human populations have greatly improved the resolution and the specificity of explanatory and predictive models.This article focuses on the scope of tele-epidemiology activities of the Canadian public health community as well as current and potential future fields of application for Earth observation data. It will demonstrate the strength, sustainability and innovative character of these approaches to improve scale-dependent decision- making at different levels of government in Canada (federal, provincial/territorial and regional) and increase the efficiency of many preventive, preparedness and response actions.Examples of tele-epidemiology applications will be presented such as the risk assessment of microbial contamination of recreational waters and modelling the risk of vector borne diseases in the Canadian context.

Emotional and Motivational Outcomes of Lab Work in the Secondary Intermediate Track: The Contribution of a Science Center Outreach Lab

ERIC Educational Resources Information Center

Itzek-Greulich, Heike; Vollmer, Christian

2017-01-01

Students' interest in science declines in secondary school. Therefore, motivating students to become competent and engaged in science topics that are relevant for their everyday lives is an important goal, so they can be better citizens and decision makers with socioscientific issues (e.g., climate change and waste disposal). The present study…

Lessons learned from Applications of a Decision Tree for Confronting Climate Change Uncertainty - the Short Term and the Long Term

NASA Astrophysics Data System (ADS)

Ray, P. A.; Wi, S.; Bonzanigo, L.; Taner, M. U.; Rodriguez, D.; Garcia, L.; Brown, C.

2016-12-01

The Decision Tree for Confronting Climate Change Uncertainty is a hierarchical, staged framework for accomplishing climate change risk management in water resources system investments. Since its development for the World Bank Water Group two years ago, the framework has been applied to pilot demonstration projects in Nepal (hydropower generation), Mexico (water supply), Kenya (multipurpose reservoir operation), and Indonesia (flood risks to dam infrastructure). An important finding of the Decision Tree demonstration projects has been the need to present the risks/opportunities of climate change to stakeholders and investors in proportion to risks/opportunities and hazards of other kinds. This presentation will provide an overview of tools and techniques used to quantify risks/opportunities to each of the project types listed above, with special attention to those found most useful for exploration of the risk space. Careful exploration of the risk/opportunity space shows that some interventions would be better taken now, whereas risks/opportunities of other types would be better instituted incrementally in order to maintain reversibility and flexibility. A number of factors contribute to the robustness/flexibility tradeoff: available capital, magnitude and imminence of potential risk/opportunity, modular (or not) character of investment, and risk aversion of the decision maker, among others. Finally, in each case, nuance was required in the translation of Decision Tree findings into actionable policy recommendations. Though the narrative of stakeholder solicitation, engagement, and ultimate partnership is unique to each case, summary lessons are available from the portfolio that can serve as a guideline to the community of climate change risk managers.

Chasing a changing climate: Reproductive and dispersal traits predict how sessile species respond to global warming

USGS Publications Warehouse

Archambault, Jennifer M.; Cope, W. Gregory; Kwak, Thomas J.

2018-01-01

AimStudies of species' range shifts have become increasingly relevant for understanding ecology and biogeography in the face of accelerated global change. The combination of limited mobility and imperilled status places some species at a potentially greater risk of range loss, extirpation or extinction due to climate change. To assess the ability of organisms with limited movement and dispersal capabilities to track shifts associated with climate change, we evaluated reproductive and dispersal traits of freshwater mussels (Unionida), sessile invertebrates that require species‐specific fish for larval dispersal.LocationNorth American Atlantic Slope rivers.MethodsTo understand how unionid mussels may cope with and adapt to current and future warming trends, we identified mechanisms that facilitated their colonization of the northern Atlantic Slope river basins in North America after the Last Glacial Maximum. We compiled species occurrence and life history trait information for each of 55 species, and then selected life history traits for which ample data were available (larval brooding duration, host fish specificity, host infection strategy, and body size) and analysed whether the trait state for each was related to mussel distribution in Atlantic Slope rivers.ResultsBrooding duration (p < .01) and host fish specificity (p = .02) were significantly related to mussel species distribution. Long‐term brooders were more likely than short‐term brooders to colonize formerly glaciated rivers, as were host generalists compared to specialists. Body size and host infection strategy were not predictive of movement into formerly glaciated rivers (p > .10).Main conclusionsOur results are potentially applicable to many species for which life history traits have not been well‐documented, because reproductive and dispersal traits in unionid mussels typically follow phylogenetic relationships. These findings may help resource managers prioritize species according to climate change vulnerability and predict which species might become further imperilled with climate warming. Finally, we suggest that similar trait‐based decision support frameworks may be applicable for other movement limited taxa.

Development and Application of Climate Services for Water Resources Planning and Management within the Department of Interior Bureau of Reclamation

NASA Astrophysics Data System (ADS)

Raff, D. A.; Morgan, A.; Brekke, L. D.

2014-12-01

The Bureau of Reclamation is the nation's largest wholesale water supplier and the second largest producer of hydropower. Reclamation operates 337 reservoirs with a total storage capacity of 245 million acre-feet and operates 53 hydroelectric powerplants that annually produce, on average for the past 10 years, 40 billion kilowatt-hours. Reclamation is adapting to the impacts and future challenges posed by the changing climate through the development of new climate services as well as through cooperation with Federal, state, local, tribal, academic, and non-governmental partners in the use of climate and water resource information that may be available. Reclamation is utilizing this information within a strategy that has four goals: 1) Increase Water Management Flexibility, 2) Enhance Climate Adaptation Planning, 3) Improve Infrastructure Resiliency, and 4) Expand Information Sharing. Within this presentation we will focus on the utilization of climate services within each of these key goals of Reclamation's strategy. This includes the utilization of climate information to track and potentially improve reservoir management to increase water management flexibility, the development of climate informed hydrology that supports climate adaptation planning, use of climate information to inform decisions of infrastructure resilience, and climate services use for jointly informed water management decisions through education and web based services.

14 CFR 414.9 - Pre-application consultation.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 4 2014-01-01 2014-01-01 false Pre-application consultation. 414.9 Section 414.9 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... application process and the potential issues relevant to the FAA's safety approval decision. ...

14 CFR 414.9 - Pre-application consultation.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 4 2011-01-01 2011-01-01 false Pre-application consultation. 414.9 Section 414.9 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... application process and the potential issues relevant to the FAA's safety approval decision. ...

14 CFR 414.9 - Pre-application consultation.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 4 2012-01-01 2012-01-01 false Pre-application consultation. 414.9 Section 414.9 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... application process and the potential issues relevant to the FAA's safety approval decision. ...

14 CFR 414.9 - Pre-application consultation.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 4 2013-01-01 2013-01-01 false Pre-application consultation. 414.9 Section 414.9 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... application process and the potential issues relevant to the FAA's safety approval decision. ...

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Risk based adaptation of infrastructures to floods and storm surges induced by climate change.

NASA Astrophysics Data System (ADS)

Luna, Byron Quan; Garrè, Luca; Hansen, Peter Friis

2014-05-01

Coastal natural hazards are changing in frequency and intensity associated to climate change. These extreme events combined with an increase in the extent of vulnerable societies will lead to an increase of substantial monetary losses. For this reason, adaptive measures are required to identify the effective and adequate measures to withstand the impacts of climate change. Decision strategies are needed for the timing of investments and for the allocation of resources to safeguard the future in a sustainable manner. Adapting structures to climate change requires decision making under uncertainties. Therefore, it is vital that risk assessments are generated on a reliable and appropriate evaluation of the involved uncertainties. Linking a Bayesian network (BN) to a Geographic Information System (GIS) for a risk assessment enables to model all the relevant parameters, their causal relations and the involved uncertainties. The integration of the probabilistic approach into a GIS allows quantifying and visualizing uncertainties in a spatial manner. By addressing these uncertainties, the Bayesian Network approach allows quantifying their effects; and facilitates the identification of future model improvements and where other efforts should be concentrated. The final results can be applied as a supportive tool for presenting reliable risk assessments to decision-makers. Based on this premises, a case study was performed to assess how the storm surge magnitude and flooding extent of an event with similar characteristics to the Sandy Super storm will occur in 2050 and 2090.

Embedding climate change risk assessment within a governance context

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

Preston, Benjamin L

Climate change adaptation is increasingly being framed in the context of climate risk management. This has contributed to the proliferation of climate change vulnerability and/or risk assessments as means of supporting institutional decision-making regarding adaptation policies and measures. To date, however, little consideration has been given to how such assessment projects and programs interact with governance systems to facilitate or hinder the implementation of adaptive responses. An examination of recent case studies involving Australian local governments reveals two key linkages between risk assessment and the governance of adaptation. First, governance systems influence how risk assessment processes are conducted, by whommore » they are conducted, and whom they are meant to inform. Australia s governance system emphasizes evidence-based decision-making that reinforces a knowledge deficit model of decision support. Assessments are often carried out by external experts on behalf of local government, with limited participation by relevant stakeholders and/or civil society. Second, governance systems influence the extent to which the outputs from risk assessment activities are translated into adaptive responses and outcomes. Technical information regarding risk is often stranded by institutional barriers to adaptation including poor uptake of information, competition on the policy agenda, and lack of sufficient entitlements. Yet, risk assessments can assist in bringing such barriers to the surface, where they can be debated and resolved. In fact, well-designed risk assessments can contribute to multi-loop learning by institutions, and that reflexive problem orientation may be one of the more valuable benefits of assessment.« less

Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture

NASA Astrophysics Data System (ADS)

Kim, K. H.; Lee, S.; Han, E.; Ines, A. V. M.

2017-12-01

Climate-Agriculture-Modeling and Decision Tool (CAMDT) is a decision support system (DSS) tool that aims to facilitate translations of probabilistic seasonal climate forecasts (SCF) to crop responses such as yield and water stress. Since CAMDT is a software framework connecting different models and algorithms with SCF information, it can be easily customized for different types of agriculture models. In this study, we replaced the DSSAT-CSM-Rice model originally incorporated in CAMDT with a generic epidemiological model, EPIRICE, to generate a seasonal pest outlook. The resulting CAMDT-Disease generates potential risks for selected fungal, viral, and bacterial diseases of rice over the next months by translating SCFs into agriculturally-relevant risk information. The integrated modeling procedure of CAMDT-Disease first disaggregates a given SCF using temporal downscaling methods (predictWTD or FResampler1), runs EPIRICE with the downscaled weather inputs, and finally visualizes the EPIRICE outputs as disease risk compared to that of the previous year and the 30-year-climatological average. In addition, the easy-to-use graphical user interface adopted from CAMDT allows users to simulate "what-if" scenarios of disease risks over different planting dates with given SCFs. Our future work includes the simulation of the effect of crop disease on yields through the disease simulation models with the DSSAT-CSM-Rice model, as disease remains one of the most critical yield-reducing factors in the field.

Capturing Data Connections within the Climate Data Initiative to Support Resiliency

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Bugbee, K.; Weigel, A. M.; Tilmes, C.

2015-12-01

The Climate Data Initiative (CDI) focuses on preparing the United States for the impacts of climate change by leveraging existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship supporting national climate-change preparedness. To achieve these goals, relevant data was curated around seven thematic areas relevant to climate change resiliency. Data for each theme was selected by subject matter experts from various Federal agencies and collected in Data.gov at http://climate.data.gov. While the curation effort for each theme has been immensely valuable on its own, in the end, the themes essentially become a long directory or a list. Establishing valuable connections between datasets and their intended use is lost. Therefore, the user understands that the datasets in the list have been approved by the CDI subject matter experts but has less certainty when making connections between the various datasets and their possible applications. Additionally, the intended use of the curated list is overwhelming and can be difficult to interpret. In order to better address the needs of the CDI data end users, the CDI team has been developing a new controlled vocabulary that will assist in capturing connections between datasets. This new vocabulary will be implemented in the Global Change Information System (GCIS), which has the capability to link individual items within the system. This presentation will highlight the methodology used to develop the controlled vocabulary that will aid end users in both understanding and locating relevant datasets for their intended use.

Toward a categorical drought prediction system based on U.S. Drought Monitor (USDM) and climate forecast

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Xia, Youlong; Luo, Lifeng; Singh, Vijay P.; Ouyang, Wei; Hao, Fanghua

2017-08-01

Disastrous impacts of recent drought events around the world have led to extensive efforts in drought monitoring and prediction. Various drought information systems have been developed with different indicators to provide early drought warning. The climate forecast from North American Multimodel Ensemble (NMME) has been among the most salient progress in climate prediction and its application for drought prediction has been considerably growing. Since its development in 1999, the U.S. Drought Monitor (USDM) has played a critical role in drought monitoring with different drought categories to characterize drought severity, which has been employed to aid decision making by a wealth of users such as natural resource managers and authorities. Due to wide applications of USDM, the development of drought prediction with USDM drought categories would greatly aid decision making. This study presented a categorical drought prediction system for predicting USDM drought categories in the U.S., based on the initial conditions from USDM and seasonal climate forecasts from NMME. Results of USDM drought categories predictions in the U.S. demonstrate the potential of the prediction system, which is expected to contribute to operational early drought warning in the U.S.

Short-term Forecasting Tools for Agricultural Nutrient Management.

PubMed

Easton, Zachary M; Kleinman, Peter J A; Buda, Anthony R; Goering, Dustin; Emberston, Nichole; Reed, Seann; Drohan, Patrick J; Walter, M Todd; Guinan, Pat; Lory, John A; Sommerlot, Andrew R; Sharpley, Andrew

2017-11-01

The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Integrating Indigenous Traditional, Local and Scientific Knowledge for Improved Management, Policy and Decision-Making in Reindeer Husbandry in the Russian Arctic

NASA Technical Reports Server (NTRS)

Maynard, Nancy G.; Yurchak, Boris; Turi, Johan Mathis; Mathiesen, Svein D.; Aissi-Wespi, Rita L.

2004-01-01

As scientists and policy-makers from both indigenous and non-indigenous communities begin to build closer partnerships to address common sustainability issues such as the health impacts of climate change and anthropogenic activities, it becomes increasingly important to create shared information management systems which integrate all relevant factors for optimal information sharing and decision-making. This paper describes a new GIs-based system being designed to bring local and indigenous traditional knowledge together with scientific data and information, remote sensing, and information technologies to address health-related environment, weather, climate, pollution and land use change issues for improved decision/policy-making for reindeer husbandry. The system is building an easily-accessible archive of relevant current and historical, traditional, local and remotely-sensed and other data and observations for shared analysis, measuring, and monitoring parameters of interest. Protection of indigenous culturally sensitive information will be respected through appropriate data protocols. A mechanism which enables easy information sharing among all participants, which is real time and geo-referenced and which allows interconnectivity with remote sites is also being designed into the system for maximum communication among partners. A preliminary version of our system will be described for a Russian reindeer test site, which will include a combination of indigenous knowledge about local conditions and issues, remote sensing and ground-based data on such parameters as the vegetation state and distribution, snow cover, temperature, ice condition, and infrastructure.

Assessing climate change impacts on fruit plant and pest phenology and their synchrony: the case of apple and codling moth

NASA Astrophysics Data System (ADS)

Felber, Raphael; Stöckli, Sibylle; Calanca, Pierluigi

2017-04-01

Temperature is a main climatic driver of plant phenology and the dominant abiotic factor directly affecting insect pests. Global warming is therefore expected to accelerate the development of plants and insects. Moreover, in the case of multivoltine pest species higher temperatures are expected to lead to the appearance of additional generations toward the end of the warm season. These changes could entail higher pest pressure and hence require an adaptation of pest management, but ultimately this would depend on whether plant and pest phenology remain synchronized or not. In this contribution we present an analysis of potential impacts of climate change on the phenology of the apple tree (Malus pumila L.), a fruit crop of economic relevance worldwide, and the codling moth (Cydia pomonella L.), one of its main pests. Key developmental stages of the apple and the codling moth were simulated by means of two heat summation models. The models were calibrated with lab and field data from Switzerland and subsequently run with observed weather data and various climate change scenarios. The time period between flowering termination and the harvest of the apples was compared to the appearance of the second and third generation of codling moth larvae to study the interlinkage between host and pest. To illustrate the potential for practical applications of the phenology models, we used spatial temperature data of Switzerland to produce risk maps that can serve as a basis for further studies and decision support.

Extreme Events and Energy Providers: Science and Innovation

NASA Astrophysics Data System (ADS)

Yiou, P.; Vautard, R.

2012-04-01

Most socio-economic regulations related to the resilience to climate extremes, from infrastructure or network design to insurance premiums, are based on a present-day climate with an assumption of stationarity. Climate extremes (heat waves, cold spells, droughts, storms and wind stilling) affect in particular energy production, supply, demand and security in several ways. While national, European or international projects have generated vast amounts of climate projections for the 21st century, their practical use in long-term planning remains limited. Estimating probabilistic diagnostics of energy user relevant variables from those multi-model projections will help the energy sector to elaborate medium to long-term plans, and will allow the assessment of climate risks associated to those plans. The project "Extreme Events for Energy Providers" (E3P) aims at filling a gap between climate science and its practical use in the energy sector and creating in turn favourable conditions for new business opportunities. The value chain ranges from addressing research questions directly related to energy-significant climate extremes to providing innovative tools of information and decision making (including methodologies, best practices and software) and climate science training for the energy sector, with a focus on extreme events. Those tools will integrate the scientific knowledge that is developed by scientific communities, and translate it into a usable probabilistic framework. The project will deliver projection tools assessing the probabilities of future energy-relevant climate extremes at a range of spatial scales varying from pan-European to local scales. The E3P project is funded by the Knowledge and Innovation Community (KIC Climate). We will present the mechanisms of interactions between academic partners, SMEs and industrial partners for this project. Those mechanisms are elementary bricks of a climate service.

Limitations and opportunities for the social cost of carbon (Invited)

NASA Astrophysics Data System (ADS)

Rose, S. K.

2010-12-01

Estimates of the marginal value of carbon dioxide-the social cost of carbon (SCC)-were recently adopted by the U.S. Government in order to satisfy requirements to value estimated GHG changes of new federal regulations. However, the development and use of SCC estimates of avoided climate change impacts comes with significant challenges and controversial decisions. Fortunately, economics can provide some guidance for conceptually appropriate estimates. At the same time, economics defaults to a benefit-cost decision framework to identify socially optimal policies. However, not all current policy decisions are benefit-cost based, nor depend on monetized information, or even have the same threshold for information. While a conceptually appropriate SCC is a useful metric, how far can we take it? This talk discusses potential applications of the SCC, limitations based on the state of research and methods, as well as opportunities for among other things consistency with climate risk management and research and decision-making tools.

Supporting UK adaptation: building services for the next set of UK climate projections

NASA Astrophysics Data System (ADS)

Fung, Fai; Lowe, Jason

2016-04-01

As part of the Climate Change Act 2008, the UK Government sets out a national adaptation programme to address the risks and opportunities identified in a national climate change risk assessment (CCRA) every five years. The last risk assessment in 2012 was based on the probabilistic projections for the UK published in 2009 (UKCP09). The second risk assessment will also use information from UKCP09 alongside other evidence on climate projections. However, developments in the science of climate projeciton, and evolving user needs (based partly on what has been learnt about the diverse user requirements of the UK adaptation community from the seven years of delivering and managing UKCP09 products, market research and the peer-reviewed literature) suggest now is an appropriate time to update the projections and how they are delivered. A new set of UK climate projections are now being produced to upgrade UKCP09 to reflect the latest developments in climate science, the first phase of which will be delivered in 2018 to support the third CCRA. A major component of the work is the building of a tailored service to support users of the new projections during their development and to involve users in key decisions so that the projections are of most use. We will set out the plan for the new climate projections that seek to address the evolving user need. We will also present a framework which aims to (i) facilitate the dialogue between users, boundary organisations and producers, reflecting their different decision-making roles (ii) produce scientifically robust, user-relevant climate information (iii) provide the building blocks for developing further climate services to support adaptation activities in the UK.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Sustainable water management under future uncertainty with eco-engineering decision scaling

NASA Astrophysics Data System (ADS)

Poff, N. Leroy; Brown, Casey M.; Grantham, Theodore E.; Matthews, John H.; Palmer, Margaret A.; Spence, Caitlin M.; Wilby, Robert L.; Haasnoot, Marjolijn; Mendoza, Guillermo F.; Dominique, Kathleen C.; Baeza, Andres

2016-01-01

Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stakeholder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrological uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.

Sustainable water management under future uncertainty with eco-engineering decision scaling

USGS Publications Warehouse

Poff, N LeRoy; Brown, Casey M; Grantham, Theodore E.; Matthews, John H; Palmer, Margaret A.; Spence, Caitlin M; Wilby, Robert L.; Haasnoot, Marjolijn; Mendoza, Guillermo F; Dominique, Kathleen C; Baeza, Andres

2015-01-01

Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stakeholder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrological uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.

Supporting Private Sector Decision-Making with NOAA's Interim Climate Data Records (ICDRs)

NASA Astrophysics Data System (ADS)

Privette, J. L.; Glance, W. J.; Cecil, D.; Bates, J. J.

2012-12-01

NOAA initiated its Climate Data Record Program (CDRP) in 2009 to operationally provide authoritative satellite Climate Data Records (CDRs) to the government and the private sector. The CDRs are based primarily on 35+ years of meteorological satellite and in situ data collected by NOAA and the Department of Defense. To date, the Program has transitioned 14 CDRs from research to initial operations. In the past year, the CDRP developed and implemented a framework to continuously extend historical CDRs using Interim Climate Data Records (ICDRs). ICDRs are "first batch" CDRs generated within several days of observation using official CDR algorithms and processes. ICDRs are required by decision support systems and other near-term applications which need current data that are fully consistent with homogeneous historical records. For example, an electrical power utility may need temperature and precipitation ICDRs to optimally identify, in both time and space, the "nearest" historical analog period to recent weather. The utility could then use the contemporaneous business data from that period to inform current decision-making. In addition to their homogeneity and consistency, ICDRs are more complete than operational weather products since ICDR processing can await upstream data delays that can negate data value for weather forecasting. However, the operational nature of ICDRs means their uncertainties typically can be improved through reprocessing once better sensor calibration and characterization data become available. Therefore, ICDRs may be considered valuable but temporary placeholders. However, the "trigger" for electing to update a given record involves many considerations, including cost, latency, downstream dependencies and scientific significance. This presentation provides an update on NOAA's CDR Program, focusing on the new CDRs transitioned to operations in 2012 and the ICDR framework -- including update decision criteria -- used to extend CDRs and meet the needs of near-term applications as well as climate monitoring and indicators activities.

An Urban Resilience to Extreme Weather Events Framework for Development of Post Event Learning and Transformative Adaptation in Cities

NASA Astrophysics Data System (ADS)

Solecki, W. D.; Friedman, E. S.; Breitzer, R.

2016-12-01

Increasingly frequent extreme weather events are becoming an immediate priority for urban coastal practitioners and stakeholders, adding complexity to decisions concerning risk management for short-term action and long-term needs of city climate stakeholders. The conflict between the prioritization of short versus long-term events by decision-makers creates disconnect between climate science and its applications. The Consortium for Climate Risk in the Urban Northeast (CCRUN), a NOAA RISA team, is developing a set of mechanisms to help bridge this gap. The mechanisms are designed to promote the application of climate science on extreme weather events and their aftermath. It is in the post event policy window where significant opportunities for science-policy linkages exist. In particular, CCRUN is interested in producing actionable and useful information for city managers to use in decision-making processes surrounding extreme weather events and climate change. These processes include a sector specific needs assessment survey instrument and two tools for urban coastal practitioners and stakeholders. The tools focus on post event learning and connections between resilience and transformative adaptation. Elements of the two tools are presented. Post extreme event learning supports urban coastal practitioners and decision-makers concerned about maximizing opportunities for knowledge transfer and assimilation, and policy initiation and development following an extreme weather event. For the urban U.S. Northeast, post event learning helps coastal stakeholders build the capacity to adapt to extreme weather events, and inform and develop their planning capacity through analysis of past actions and steps taken in response to Hurricane Sandy. Connecting resilience with transformative adaptation is intended to promote resilience in urban Northeast coastal settings to the long-term negative consequences of extreme weather events. This is done through a knowledge co-production engagement process that links innovative and flexible adaptation pathways that can address requirements for short-term action and long-term needs.

Time series of Essential Climate Variables from Satellite Data

NASA Astrophysics Data System (ADS)

Werscheck, M.

2010-09-01

Climate change is a fact. We need to know how the climate system will develop in future and how this will affect workaday life. To do this we need climate models for prediction of the future on all time scales, and models to assess the impact of the prediction results to the various sectors of social and economic life. With this knowledge we can take measures to mitigate the causes and adapt to changes. Prerequisite for this is a careful and thorough monitoring of the climate systems. Satellite data are an increasing & valuable source of information to observe the climate system. For many decades now satellite data are available to derive information about our planet earth. EUMETSAT is the European Organisation in charge of the exploitation of satellite data for meteorology and (since the year 2000) climatology. Within the EUMETSAT Satellite Application Facility (SAF) Network, comprising 8 initiatives to derive geophysical parameters from satellite, the Satellite Application Facility on Climate Monitoring (CM SAF) is especially dedicated to provide climate relevant information from satellite data. Many products as e.g. water vapour, radiation at surface and top of atmosphere, cloud properties are available, some of these for more then 2 decades. Just recently the European Space Agency (ESA) launched the Climate Change Initiative (CCI) to derive Essential Climate Variables (ECVs) from satellite data, including e.g. cloud properties, aerosol, ozone, sea surface temperature etc.. The presentation will give an overview on some relevant European activities to derive Essential Climate Variables from satellite data and the links to Global Climate Observing System (GCOS), the Global Satellite Intercalibration System (GSICS) as well as the Sustained Co-ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE CM).

Making better decisions in uncertain times (Invited)

NASA Astrophysics Data System (ADS)

St John, C.

2013-12-01

Scientific information about climate change and other human impacts on the environment are increasingly available and sought after (often in the form of probabilistic forecasts or technical information related to engineering solutions). However, it is increasingly apparent that there are barriers to the use of this information by decision makers - either from its lack of application altogether, its usability for people without scientific backgrounds, or its ability to inform sound decisions and widespread behavior change. While the argument has been made that an information deficit is to blame, we argue that there is also a motivation deficit contributing to a lack of understanding of information about climate change impacts and solutions. Utilizing insight from over thirty years of research in social and cognitive psychology, in addition to other social sciences, the Center for Research on Environmental Decisions (CRED) seeks to understand how people make environmental decisions under conditions of uncertainty, and how these decisions can be improved. This presentation will focus specifically on recent research that has come forth since the 2009 publication of CRED's popular guide 'The Psychology of Climate Change Communication: A Guide for Scientists, Journalists, Educators, Political Aides, and the Interested Public.' Utilizing case studies from real world examples, this talk will explore how decision making can be improved through a better understanding of how people perceive and process uncertainty and risk. It will explore techniques such as choice architecture and 'nudging' behavior change, how social goals and group participation affect decision making, and how framing of environmental information influences mitigative behavior.

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

32 CFR 724.802 - Applicant's responsibilities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... to bring such issues to the NDRB's attention as early as possible in the review, applicants who... basis for a change in discharge. If the applicant wishes to bring the NDRB's attention to a prior... Reading Room), applicants must provide the NDRB with copies of such decisions or of the relevant portion...

Revisiting the generation and interpretation of climate models experiments for adaptation decision-making (Invited)

NASA Astrophysics Data System (ADS)

Ranger, N.; Millner, A.; Niehoerster, F.

2010-12-01

Traditionally, climate change risk assessments have taken a roughly four-stage linear ‘chain’ of moving from socioeconomic projections, to climate projections, to primary impacts and then finally onto economic and social impact assessment. Adaptation decisions are then made on the basis of these outputs. The escalation of uncertainty through this chain is well known; resulting in an ‘explosion’ of uncertainties in the final risk and adaptation assessment. The space of plausible future risk scenarios is growing ever wider with the application of new techniques which aim to explore uncertainty ever more deeply; such as those used in the recent ‘probabilistic’ UK Climate Projections 2009, and the stochastic integrated assessment models, for example PAGE2002. This explosion of uncertainty can make decision-making problematic, particularly given that the uncertainty information communicated can not be treated as strictly probabilistic and therefore, is not an easy fit with standard decision-making under uncertainty approaches. Additional problems can arise from the fact that the uncertainty estimated for different components of the ‘chain’ is rarely directly comparable or combinable. Here, we explore the challenges and limitations of using current projections for adaptation decision-making. We report the findings of a recent report completed for the UK Adaptation Sub-Committee on approaches to deal with these challenges and make robust adaptation decisions today. To illustrate these approaches, we take a number of illustrative case studies, including a case of adaptation to hurricane risk on the US Gulf Coast. This is a particularly interesting case as it involves urgent adaptation of long-lived infrastructure but requires interpreting highly uncertain climate change science and modelling; i.e. projections of Atlantic basin hurricane activity. An approach we outline is reversing the linear chain of assessments to put the economics and decision-making first. Such an approach forces one to focus on the information of greatest value for the specific decision. We suggest that such an approach will help to accommodate the uncertainties in the chain and facilitate robust decision-making. Initial findings of these case studies will be presented with the aim of raising open questions and promoting discussion of the methodology. Finally, we reflect on the implications for the design of climate model experiments.

HEALTH TECHNOLOGY ASSESSMENT FOR DECISION MAKING IN LATIN AMERICA: GOOD PRACTICE PRINCIPLES.

PubMed

Pichon-Riviere, Andrés; Soto, Natalie C; Augustovski, Federico Ariel; García Martí, Sebastián; Sampietro-Colom, Laura

2018-06-11

The aim of this study was to identify good practice principles for health technology assessment (HTA) that are the most relevant and of highest priority for application in Latin America and to identify potential barriers to their implementation in the region. HTA good practice principles proposed at the international level were identified and then explored during a deliberative process in a forum of assessors, funders, and product manufacturers. Forty-two representatives from ten Latin American countries participated. Good practice principles proposed at the international level were considered valid and potentially relevant to Latin America. Five principles were identified as priority and with the greatest potential to be strengthened at this time: transparency in the production of HTA, involvement of relevant stakeholders in the HTA process, mechanisms to appeal decisions, clear priority-setting processes in HTA, and a clear link between HTA and decision making. The main challenge identified was to find a balance between the application of these principles and the available resources in a way that would not detract from the production of reports and adaptation to the needs of decision makers. The main recommendation was to progress gradually in strengthening HTA and its link to decision making by developing appropriate processes for each country, without trying to impose, in the short-term, standards taken from examples at the international level without adequate adaptation of these to local contexts.

Co-production of science for regional integrated assessment and management of climate change impacts: The case study of Aspen, CO

NASA Astrophysics Data System (ADS)

Arnott, J. C.; Katzenberger, J.

2015-12-01

The impacts of global climate change to regional scales are complex and cut across sectorial and jurisdictional boundaries, and therefore, a unique enterprise of collaboration between scientists, resource managers, and other stakeholders for development of adequate response strategies is required. Such collaboration has been exhibited between stakeholders, researchers, and a boundary organization—the Aspen Global Change Institute—since 2005 in assessing impacts and crafting policies in response with regard to climate change impacts in the mountain watershed surrounding Aspen, CO. A series of structured stakeholder interviews and town hall sessions, impact assessment reports, and intensive collaboration between various information providers and user groups has set the stage for development of both mitigation of and adaptation to climate change impacts. The most recent example of this has included the use of global scale climate model output to inform the development of resiliency strategies in response to extreme precipitation projections. The use of this kind of resource has been considered in a variety of decision-making contexts and has included the development of region- and decision-relevant qualitative scenarios that make use of quantitative model-based information. Results from this line of work that include feedback from actual users', a boundary organization, and researchers' perspectives will be reported along with examples of policy and implementation results.

"The first step is admitting you have a problem…": the process of advancing science communication in Landscape Conservation Cooperatives in Alaska

NASA Astrophysics Data System (ADS)

Buxbaum, T. M.; Trainor, S.; Warner, N.; Timm, K.

2015-12-01

Climate change is impacting ecological systems, coastal processes, and environmental disturbance regimes in Alaska, leading to a pressing need to communicate reliable scientific information about climate change, its impacts, and future projections for land and resource management and decision-making. However, little research has been done to dissect and analyze the process of making the results of scientific inquiry directly relevant and usable in resource management. Based within the Science Application division of the US Fish and Wildlife Service, Landscape Conservation Cooperatives (LCCs) are regional conservation science partnerships that provide scientific and technical expertise needed to support conservation planning at landscape scales and promote collaboration in defining shared conservation goals. The five LCCs with jurisdiction in Alaska recently held a training workshop with the goals of advancing staff understanding and skills related to science communication and translation. We report here preliminary results from analysis of workshop discussions and pre- and post- workshop interviews and surveys revealing expectations, assumptions, and mental models regarding science communication and the process of conducting use-inspired science. Generalizable conclusions can assist scientists and boundary organizations bridge knowledge gaps between science and resource management.

Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

PubMed

Salinger, J; Hobday, A J; Matear, R J; O'Kane, T J; Risbey, J S; Dunstan, P; Eveson, J P; Fulton, E A; Feng, M; Plagányi, É E; Poloczanska, E S; Marshall, A G; Thompson, P A

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales. © 2016 Elsevier Ltd. All rights reserved.

Comparative risk assessment of the burden of disease from climate change.

PubMed

Campbell-Lendrum, Diarmid; Woodruff, Rosalie

2006-12-01

The World Health Organization has developed standardized comparative risk assessment methods for estimating aggregate disease burdens attributable to different risk factors. These have been applied to existing and new models for a range of climate-sensitive diseases in order to estimate the effect of global climate change on current disease burdens and likely proportional changes in the future. The comparative risk assessment approach has been used to assess the health consequences of climate change worldwide, to inform decisions on mitigating greenhouse gas emissions, and in a regional assessment of the Oceania region in the Pacific Ocean to provide more location-specific information relevant to local mitigation and adaptation decisions. The approach places climate change within the same criteria for epidemiologic assessment as other health risks and accounts for the size of the burden of climate-sensitive diseases rather than just proportional change, which highlights the importance of small proportional changes in diseases such as diarrhea and malnutrition that cause a large burden. These exercises help clarify important knowledge gaps such as a relatively poor understanding of the role of nonclimatic factors (socioeconomic and other) that may modify future climatic influences and a lack of empiric evidence and methods for quantifying more complex climate-health relationships, which consequently are often excluded from consideration. These exercises highlight the need for risk assessment frameworks that make the best use of traditional epidemiologic methods and that also fully consider the specific characteristics of climate change. These include the longterm and uncertain nature of the exposure and the effects on multiple physical and biotic systems that have the potential for diverse and widespread effects, including high-impact events.

Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

PubMed

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

NASA Astrophysics Data System (ADS)

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Developing a robust methodology for assessing the value of weather/climate services

NASA Astrophysics Data System (ADS)

Krijnen, Justin; Golding, Nicola; Buontempo, Carlo

2016-04-01

Increasingly, scientists involved in providing weather and climate services are expected to demonstrate the value of their work for end users in order to justify the costs of developing and delivering these services. This talk will outline different approaches that can be used to assess the socio-economic benefits of weather and climate services, including, among others, willingness to pay and avoided costs. The advantages and limitations of these methods will be discussed and relevant case-studies will be used to illustrate each approach. The choice of valuation method may be influenced by different factors, such as resource and time constraints and the end purposes of the study. In addition, there are important methodological differences which will affect the value assessed. For instance the ultimate value of a weather/climate forecast to a decision-maker will not only depend on forecast accuracy but also on other factors, such as how the forecast is communicated to and consequently interpreted by the end-user. Thus, excluding these additional factors may result in inaccurate socio-economic value estimates. In order to reduce the inaccuracies in this valuation process we propose an approach that assesses how the initial weather/climate forecast information can be incorporated within the value chain of a given sector, taking into account value gains and losses at each stage of the delivery process. By this we aim to more accurately depict the socio-economic benefits of a weather/climate forecast to decision-makers.

Using simple chaotic models to interpret climate under climate change: Implications for probabilistic climate prediction

NASA Astrophysics Data System (ADS)

Daron, Joseph

2010-05-01

Exploring the reliability of model based projections is an important pre-cursor to evaluating their societal relevance. In order to better inform decisions concerning adaptation (and mitigation) to climate change, we must investigate whether or not our models are capable of replicating the dynamic nature of the climate system. Whilst uncertainty is inherent within climate prediction, establishing and communicating what is plausible as opposed to what is likely is the first step to ensuring that climate sensitive systems are robust to climate change. Climate prediction centers are moving towards probabilistic projections of climate change at regional and local scales (Murphy et al., 2009). It is therefore important to understand what a probabilistic forecast means for a chaotic nonlinear dynamic system that is subject to changing forcings. It is in this context that we present the results of experiments using simple models that can be considered analogous to the more complex climate system, namely the Lorenz 1963 and Lorenz 1984 models (Lorenz, 1963; Lorenz, 1984). Whilst the search for a low-dimensional climate attractor remains illusive (Fraedrich, 1986; Sahay and Sreenivasan, 1996) the characterization of the climate system in such terms can be useful for conceptual and computational simplicity. Recognising that a change in climate is manifest in a change in the distribution of a particular climate variable (Stainforth et al., 2007), we first establish the equilibrium distributions of the Lorenz systems for certain parameter settings. Allowing the parameters to vary in time, we investigate the dependency of such distributions to initial conditions and discuss the implications for climate prediction. We argue that the role of chaos and nonlinear dynamic behaviour ought to have more prominence in the discussion of the forecasting capabilities in climate prediction. References: Fraedrich, K. Estimating the dimensions of weather and climate attractors. J. Atmos. Sci, 43, 419-432, 1986. Lorenz, E. N. Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130-141, 1963. Lorenz, E. N. Irregularity: a fundamental property of the atmosphere. Tellus, 36A, 98-110, 1984. Murphy, J. M., D. M. H. Sexton, G. J. Jenkins, B. B. B. Booth, C. C. Brown, R. T. Clark, M. Collins, G. R. Harris, E. J. Kendon, R. A. Betts, S. J. Brown, P. Boorman, T. P. Howard, K. A. Humphrey, M. P. McCarthy, R. E. McDonald, A. Stephens, C. Wallace, R. Warren, R. Wilby, and R. A. Wood. Uk climate projections science report: Climate change projections. 2009. Sahay, A. and K. R. Sreenivasan. The search for a low-dimensional characterization of a local climate system. Phil. Trans. R. Soc. A., 354, 1715-1750, 1996. Stainforth, D. A., M. R. Allen, E. R. Tredger, and L. A. Smith. Confidence, uncertainty and decision-support relevance in climate predictions. Phil. Trans. R. Soc. A, 365, 2145-2161, 2007.

Agricultural climate impacts assessment for economic modeling and decision support

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

2013-12-01

A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a mitigation level of 3.7 W/m2, as well as consideration of different levels of climate sensitivity (2, 3, 4.5 and 6oC) and different initial conditions for addressing uncertainty. Since the CMIP 3 and CMIP5 protocols did not include this mitigation level or consider alternative levels of climate sensitivity, additional climate projections were required. These two cases will be discussed to illustrate some of the trade-offs made in development of methodologies for climate impact assessments that are intended for a specific user or audience, and oriented towards addressing a specific topic of interest and providing useable results. This involvement of stakeholders from the design phase of climate impacts methodology serves to both define the appropriate method for the question at hand and also to engage and inform the stakeholders of the myriad options and uncertainties associated with different methodology choices. This type of engagement should benefit decision making in the long run through greater stakeholder understanding of the science of future climate model projections, scenarios, the climate impacts sector models and the types of outputs that can be generated by each along with the respective uncertainties at each step of the climate impacts assessment process.

Climate change and the health of older people in Australia: A scoping review on the role of mobile applications (apps) in ameliorating impact.

PubMed

Black, Deborah A; O'Loughlin, Kate; Wilson, Leigh A

2018-06-01

Due to the impact of climate change, mobile applications (apps) providing information about the external environment have the potential to improve the health of older people. The purpose of this research was to undertake a scoping review of the evidence on the usability, feasibility and effectiveness of mobile apps to encourage access to activities outside the home in older people. A search of databases was undertaken with relevant keywords. Selected manuscripts were judged for relevance to the inclusion criteria and assessed for quality. Very few published studies examined mobile apps specifically designed to prevent, or to treat, chronic disease in ageing populations, and fewer had rigorous designs. No study addressed accessing the external environment in the context of climate change. This study demonstrates that there is a gap in the evidence about the mobile apps designed for healthy ageing and, more specifically, to improve access to the external environment. © 2018 AJA Inc.

Report from the workshop on climate downscaling and its application in high Hawaiian Islands, September 16–17, 2015

USGS Publications Warehouse

Helweg, David A.; Keener, Victoria; Burgett, Jeff M.

2016-07-14

In the subtropical and tropical Pacific islands, changing climate is predicted to influence precipitation and freshwater availability, and thus is predicted to impact ecosystems goods and services available to ecosystems and human communities. The small size of high Hawaiian Islands, plus their complex microlandscapes, require downscaling of global climate models to provide future projections of greater skill and spatial resolution. Two different climate modeling approaches (physics-based dynamical downscaling and statistics-based downscaling) have produced dissimilar projections. Because of these disparities, natural resource managers and decision makers have low confidence in using the modeling results and are therefore are unwilling to include climate-related projections in their decisions. In September 2015, the Pacific Islands Climate Science Center (PICSC), the Pacific Islands Climate Change Cooperative (PICCC), and the Pacific Regional Integrated Sciences and Assessments (Pacific RISA) program convened a 2-day facilitated workshop in which the two modeling teams, plus key model users and resource managers, were brought together for a comparison of the two approaches, culminating with a discussion of how to provide predictions that are useable by resource managers. The proceedings, discussions, and outcomes of this Workshop are summarized in this Open-File Report.

An index-based robust decision making framework for watershed management in a changing climate.

PubMed

Kim, Yeonjoo; Chung, Eun-Sung

2014-03-01

This study developed an index-based robust decision making framework for watershed management dealing with water quantity and quality issues in a changing climate. It consists of two parts of management alternative development and analysis. The first part for alternative development consists of six steps: 1) to understand the watershed components and process using HSPF model, 2) to identify the spatial vulnerability ranking using two indices: potential streamflow depletion (PSD) and potential water quality deterioration (PWQD), 3) to quantify the residents' preferences on water management demands and calculate the watershed evaluation index which is the weighted combinations of PSD and PWQD, 4) to set the quantitative targets for water quantity and quality, 5) to develop a list of feasible alternatives and 6) to eliminate the unacceptable alternatives. The second part for alternative analysis has three steps: 7) to analyze all selected alternatives with a hydrologic simulation model considering various climate change scenarios, 8) to quantify the alternative evaluation index including social and hydrologic criteria with utilizing multi-criteria decision analysis methods and 9) to prioritize all options based on a minimax regret strategy for robust decision. This framework considers the uncertainty inherent in climate models and climate change scenarios with utilizing the minimax regret strategy, a decision making strategy under deep uncertainty and thus this procedure derives the robust prioritization based on the multiple utilities of alternatives from various scenarios. In this study, the proposed procedure was applied to the Korean urban watershed, which has suffered from streamflow depletion and water quality deterioration. Our application shows that the framework provides a useful watershed management tool for incorporating quantitative and qualitative information into the evaluation of various policies with regard to water resource planning and management. Copyright © 2013 Elsevier B.V. All rights reserved.

The Climate Response to the Astronomical Forcing

NASA Astrophysics Data System (ADS)

Crucifix, M.; Loutre, M. F.; Berger, A.

2006-08-01

Links between climate and Earth’s orbit have been proposed for about 160 years. Two decisive advances towards an astronomical theory of palæoclimates were Milankovitch’s theory of insolation (1941) and independent findings, in 1976, of a double precession frequency peak in marine sediment data and from celestial mechanics calculations. The present chapter reviews three essential elements of any astronomical theory of climate: (1) to calculate the orbital elements, (2) to infer insolation changes from climatic precession, obliquity and eccentricity, and (3) to estimate the impact of these variations on climate. The Louvain-la-Neuve climate-ice sheet model has been an important instrument for confirming the relevance of Milankovitch’s theory, but it also evidences the critical role played by greenhouse gases during periods of low eccentricity. It is recognised today that climatic interactions at the global scale were involved in the processes of glacial inception and deglaciation. Three examples are given, related to the responses of the carbon cycle, hydrological cycle, and the terrestrial biosphere, respectively. The chapter concludes on an outlook on future research directions on this topic.

Adaptation by Stealth: Understanding climate information use across scales and decision spaces in water management in the United States

NASA Astrophysics Data System (ADS)

Kirchhoff, C.; Vang Rasmussen, L.; Lemos, M. C.

2016-12-01

While there has been considerable focus on understanding how factors related to the creation of climate knowledge affect its uptake and use, less attention has been paid to the actors, decisions, and processes through which climate information supports, or fails to support, action. This is particularly the case concerning how different scales of decision-making influence information uptake. In this study, we seek to understand how water and resource managers' decision space influences climate information use in two Great Lakes watersheds. We find that despite the availability of tailored climate information, actual use of information in decision making remains low. Reasons include: a) lack of willingness to place climate on agendas because local managers perceive climate change as politically risky and a difficult and intangible problem; b) lack of formal mandate or authority at the city and county scale to translate climate information into on-the-ground action, c) problems with the information itself, and d) perceived lack of demand for climate information by those managers who have the mandate and authority (e.g. at the state level) to use (or help others use) climate information. Our findings suggest that 1) climate scientists and information brokers should produce information that meets a range of decision needs and reserve intensive tailoring efforts for decision makers who have authority and willingness to employ climate information, 2) without support from higher levels of decision-making (e.g. state) it is unlikely that climate information use for adaptation decisions will accelerate significantly in the next few years, and 3) the trend towards adopting more sustainability and resilience practices over climate-specific actions should be supported as an important component of the climate adaptation repertoire.

The Relevance of Theories of the Policy Process to Educational Decision-Making.

ERIC Educational Resources Information Center

Ryan, R. J.

1985-01-01

Two case studies of educational decision making are used to test the utility of some current theories of the policy-formation process; a framework for the application of these theories is proposed; and the merits of applying existing theories before seeking new paradigms are stressed. (MSE)

The Federal Geospatial Platform a shared infrastructure for publishing, discovering and exploiting public data and spatial applications.

NASA Astrophysics Data System (ADS)

Dabolt, T. O.

2016-12-01

The proliferation of open data and data services continues to thrive and is creating new challenges on how researchers, policy analysts and other decision makes can quickly discover and use relevant data. While traditional metadata catalog approaches used by applications such as data.gov prove to be useful starting points for data search they can quickly frustrate end users who are seeking ways to quickly find and then use data in machine to machine environs. The Geospatial Platform is overcoming these obstacles and providing end users and applications developers a richer more productive user experience. The Geospatial Platform leverages a collection of open source and commercial technology hosted on Amazon Web Services providing an ecosystem of services delivering trusted, consistent data in open formats to all users as well as a shared infrastructure for federal partners to serve their spatial data assets. It supports a diverse array of communities of practice ranging on topics from the 16 National Geospatial Data Assets Themes, to homeland security and climate adaptation. Come learn how you can contribute your data and leverage others or check it out on your own at https://www.geoplatform.gov/

Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions

USGS Publications Warehouse

Amy K. Snover,; Nathan J. Mantua,; Littell, Jeremy; Michael A. Alexander,; Michelle M. McClure,; Janet Nye,

2013-01-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

2016-04-01

The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.

Advancing coupled human-earth system models: The integrated Earth System Model Project

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems. While these initial experiments have relied on offline coupling methodologies, current and future experiments are utilizing a single model code developed to integrate GCAM into CESM as a component of the land model. This unique capability facilitates many new applications to scientific questions arising from human and biogeophysical systems interaction. Future developments will further integrate the energy system decisions and greenhouse gas emissions as simulated in GCAM with the appropriate climate and land system components of CESM.

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

PubMed

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

Decision Support System for an efficient irrigation water management in semi arid environment

NASA Astrophysics Data System (ADS)

Khan, M. A.; Islam, M.; Hafeez, M. M.; Flugel, W. A.

2009-12-01

A significant increase in agricultural productivity over the last few decades has protected the world from episodes of hunger and food shortages. Water management in irrigated agriculture was instrumental in achieving those gains. Water resources are under high pressure due to rapid population growth and increased competition among various sectors. Access to reliable data on water availability, quantity and quality can provide the necessary foundation for sound management of water resources. There are many traditional methods for matching water demand and supply, however imbalances between demand and supply remain inevitable. It is possible to reduce the imbalances considerably through development of appropriate irrigation water management tool that take into account various factors such as soil type, irrigation water supply, and crop water demand. All components of water balance need to be understood and quantified for efficient and sustainable management of water resources. Application of an intelligent Decision Support System (DSS) is becoming significant. A DSS incorporates knowledge and expertise within the decision support framework. It is an integrated set of data, functions, models and other relevant information that efficiently processes input data, simulates models and displays the results in a user friendly format. It helps in decision-making process, to analyse the problem and explore various scenarios to make the most appropriate decision for water management. This paper deals with the Coleambally Irrigation Area (CIA) located in Murrumbidgee catchment, NSW, Australia. An Integrated River Information System called Coleambally IRIS has been developed to improve the irrigation water management ranging from farm to sub-system and system level. It is a web-based information management system with a focus on time series and geospatial hydrological, climatic and remote sensing data including land cover class, surface temperature, soil moisture, Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI) and Evapotranspiration (ET). Coleambally IRIS provides user friendly environment for data input and output, and an adaptable set of functions for data analysis, management and decision making to develops strategies for sustainable irrigation water management. Coleambally IRIS is used to assist the managers of irrigation service provider and the farmers in their decision making by providing relevant information over the web. The developed DSS has been practically used in managing irrigation water under the current drought conditions. The DSS will be further extended for forecasting irrigation water demand in the future.

A scenario neutral approach to assess low flow sensitivity to climate change

NASA Astrophysics Data System (ADS)

Sauquet, Eric; Prudhomme, Christel

2015-04-01

Most impact studies of climate change on river flow regime are performed following top-down approaches, where changes in hydrological characteristics are obtained from rainfall-runoff models forced by downscaled projections provided by GCMs. However, such approaches are not always considered robust enough to bridge the gap between climate research and stake holders needs to develop relevant adaptation strategy (Wilby et al., 2014). Alternatively, 'bottom-up' approaches can be applied to climate change impact studies on water resources to assess the intrinsic vulnerability of the catchments and ultimately help to prioritize adaptation actions for areas highly sensitive to small deviations from the present-day climate conditions. A general framework combining the scenario-neutral methodology developed by Prudhomme et al. (2010) and climate elasticity analyses (Sankarasubramanian et al., 2001) is presented and applied to measure the vulnerability of low flows and droughts on a large dataset of more than 400 French gauged basins. The different steps involved in the suggested framework are: - Calibration of the GR5J rainfall runoff model (Pushpalatha et al., 2011) against observations, - Identification of the main climate factors influencing low flows, - Definition of the sensitivity domain for precipitation (P), temperature (T) and potential evapotranspiration (PE) scenarios consistent with most recent climate change projections, - Derivation of the response surface describing changes in low flow and drought regime in terms of severity, duration and seasonality (Catalogne, 2012), - Uncertainty assessment. Results are the basis for a classification of river basins according to their sensitivity at national scale and for discussions on adaptation requirements with stakeholders. Catalogne C (2012) Amélioration des méthodes de prédétermination des débits de référence d'étiage en sites peu ou pas jaugés. PHD thesis, Université Joseph Fourier, Grenoble, 285 pp. Pushpalatha R, Perrin C, Le Moine N, Mathevet T, Andreassian V (2011) A downward structural sensitivity analysis of hydrological models to improve low-flow simulation. Journal of Hydrology 411.1-2. Prudhomme C, Wilby LR, Crooks SM, Kay AL, Reynard NS (2010) Scenario-neutral approach to climate change impact studies: application to flood risk. Journal of Hydrology, 390:198-209. Sankarasubramanian A, Vogel RM, Limbrunner JF (2001) Climate elasticity of streamflow in the United States. Water Resources Research, 3(6):1771-1781. Wilby R, Dawson C, Murphy C, O'Connor P., Hawkins E. (2014) The Statistical DownScaling Model - Decision Centric (SDSM-DC): conceptual basis and applications. Climate Research, 61(3):259-276.

The Upper Midwest Aerospace Consortium Environmental Information Network: Building ‘Learning Communities’ in the Northern Great Plains

USGS Publications Warehouse

Welling, Leigh; Seielstad, George; McClurg, Pat; Fagre, Daniel B.

2000-01-01

In the last two decades alone, the U.S. and large portions of the world have witnessed what can be aptly be described as an explosion of scientific information and technological innovations that has permeated almost every aspect of our lives. Given these trends, it is clear that science and the understanding of science are becoming increasingly more relevant and essential to decision-makers and the decision-making process. Every environmental issue confronting society has an undisputed scientific underpinning. Understanding the implications of the science underpinning issues of particular importance to the health and well being of society constitutes the basis for making more informed and enlightened decisions. However obvious this linkage may be, many factors continue to serve as impediments to the broader understanding and incorporation of science into policy- and decision-making processes, as perhaps is best exemplified by the case of climate science.

14 CFR 413.5 - Pre-application consultation.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 413.5 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... process and possible issues relevant to the FAA's licensing or permitting decision. Early consultation helps an applicant to identify possible regulatory issues at the planning stage when changes to an...

14 CFR 413.5 - Pre-application consultation.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 413.5 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... process and possible issues relevant to the FAA's licensing or permitting decision. Early consultation helps an applicant to identify possible regulatory issues at the planning stage when changes to an...

14 CFR 413.5 - Pre-application consultation.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 413.5 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... process and possible issues relevant to the FAA's licensing or permitting decision. Early consultation helps an applicant to identify possible regulatory issues at the planning stage when changes to an...

Health risks of climate change: an assessment of uncertainties and its implications for adaptation policies.

PubMed

Wardekker, J Arjan; de Jong, Arie; van Bree, Leendert; Turkenburg, Wim C; van der Sluijs, Jeroen P

2012-09-19

Projections of health risks of climate change are surrounded with uncertainties in knowledge. Understanding of these uncertainties will help the selection of appropriate adaptation policies. We made an inventory of conceivable health impacts of climate change, explored the type and level of uncertainty for each impact, and discussed its implications for adaptation policy. A questionnaire-based expert elicitation was performed using an ordinal scoring scale. Experts were asked to indicate the level of precision with which health risks can be estimated, given the present state of knowledge. We assessed the individual scores, the expertise-weighted descriptive statistics, and the argumentation given for each score. Suggestions were made for how dealing with uncertainties could be taken into account in climate change adaptation policy strategies. The results showed that the direction of change could be indicated for most anticipated health effects. For several potential effects, too little knowledge exists to indicate whether any impact will occur, or whether the impact will be positive or negative. For several effects, rough 'order-of-magnitude' estimates were considered possible. Factors limiting health impact quantification include: lack of data, multi-causality, unknown impacts considering a high-quality health system, complex cause-effect relations leading to multi-directional impacts, possible changes of present-day response-relations, and difficulties in predicting local climate impacts. Participants considered heat-related mortality and non-endemic vector-borne diseases particularly relevant for climate change adaptation. For possible climate related health impacts characterised by ignorance, adaptation policies that focus on enhancing the health system's and society's capability of dealing with possible future changes, uncertainties and surprises (e.g. through resilience, flexibility, and adaptive capacity) are most appropriate. For climate related health effects for which rough risk estimates are available, 'robust decision-making' is recommended. For health effects with limited societal and policy relevance, we recommend focusing on no-regret measures. For highly relevant health effects, precautionary measures can be considered. This study indicated that analysing and characterising uncertainty by means of a typology can be a very useful approach for selection and prioritization of preferred adaptation policies to reduce future climate related health risks.

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

2016-03-01

Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

Decision- rather than scenario-centred downscaling: Towards smarter use of climate model outputs

NASA Astrophysics Data System (ADS)

Wilby, Robert L.

2013-04-01

Climate model output has been used for hydrological impact assessments for at least 25 years. Scenario-led methods raise awareness about risks posed by climate variability and change to the security of supplies, performance of water infrastructure, and health of freshwater ecosystems. However, it is less clear how these analyses translate into actionable information for adaptation. One reason is that scenario-led methods typically yield very large uncertainty bounds in projected impacts at regional and river catchment scales. Consequently, there is growing interest in vulnerability-based frameworks and strategies for employing climate model output in decision-making contexts. This talk begins by summarising contrasting perspectives on climate models and principles for testing their utility for water sector applications. Using selected examples it is then shown how water resource systems may be adapted with varying levels of reliance on climate model information. These approaches include the conventional scenario-led risk assessment, scenario-neutral strategies, safety margins and sensitivity testing, and adaptive management of water systems. The strengths and weaknesses of each approach are outlined and linked to selected water management activities. These cases show that much progress can be made in managing water systems without dependence on climate models. Low-regret measures such as improved forecasting, better inter-agency co-operation, and contingency planning, yield benefits regardless of the climate outlook. Nonetheless, climate model scenarios are useful for evaluating adaptation portfolios, identifying system thresholds and fixing weak links, exploring the timing of investments, improving operating rules, or developing smarter licensing regimes. The most problematic application remains the climate change safety margin because of the very low confidence in extreme precipitation and river flows generated by climate models. In such cases, it is necessary to understand the trade-offs that exist between the additional costs of a scheme and the level of risk that is accommodated.

Value of information analysis in healthcare: a review of principles and applications.

PubMed

Tuffaha, Haitham W; Gordon, Louisa G; Scuffham, Paul A

2014-06-01

Economic evaluations are increasingly utilized to inform decisions in healthcare; however, decisions remain uncertain when they are not based on adequate evidence. Value of information (VOI) analysis has been proposed as a systematic approach to measure decision uncertainty and assess whether there is sufficient evidence to support new technologies. The objective of this paper is to review the principles and applications of VOI analysis in healthcare. Relevant databases were systematically searched to identify VOI articles. The findings from the selected articles were summarized and narratively presented. Various VOI methods have been developed and applied to inform decision-making, optimally designing research studies and setting research priorities. However, the application of this approach in healthcare remains limited due to technical and policy challenges. There is a need to create more awareness about VOI analysis, simplify its current methods, and align them with the needs of decision-making organizations.

A Review of Legal Decisions Relevant to Technical Standards Used in Pharmacy School Admissions

PubMed Central

2017-01-01

The implementation of an effective and legally sound technical standards procedure for pharmacy schools requires a proactive approach by admissions officers. Applicants with disabilities are accorded significant rights that must not be infringed during the admissions process in order to ensure compliance with applicable law. This article provides a review of applicable state cases, federal cases, and OCR decisions and guidance to help pharmacy schools identify procedures and implement technical standards into their admissions processes as required by ACPE Standards 2016. PMID:28381897

Incorporating uncertainty regarding applicability of evidence from meta-analyses into clinical decision making.

PubMed

Kriston, Levente; Meister, Ramona

2014-03-01

Judging applicability (relevance) of meta-analytical findings to particular clinical decision-making situations remains challenging. We aimed to describe an evidence synthesis method that accounts for possible uncertainty regarding applicability of the evidence. We conceptualized uncertainty regarding applicability of the meta-analytical estimates to a decision-making situation as the result of uncertainty regarding applicability of the findings of the trials that were included in the meta-analysis. This trial-level applicability uncertainty can be directly assessed by the decision maker and allows for the definition of trial inclusion probabilities, which can be used to perform a probabilistic meta-analysis with unequal probability resampling of trials (adaptive meta-analysis). A case study with several fictitious decision-making scenarios was performed to demonstrate the method in practice. We present options to elicit trial inclusion probabilities and perform the calculations. The result of an adaptive meta-analysis is a frequency distribution of the estimated parameters from traditional meta-analysis that provides individually tailored information according to the specific needs and uncertainty of the decision maker. The proposed method offers a direct and formalized combination of research evidence with individual clinical expertise and may aid clinicians in specific decision-making situations. Copyright © 2014 Elsevier Inc. All rights reserved.

Facilitating access to pre-processed research evidence in public health

PubMed Central

2010-01-01

Background Evidence-informed decision making is accepted in Canada and worldwide as necessary for the provision of effective health services. This process involves: 1) clearly articulating a practice-based issue; 2) searching for and accessing relevant evidence; 3) appraising methodological rigor and choosing the most synthesized evidence of the highest quality and relevance to the practice issue and setting that is available; and 4) extracting, interpreting, and translating knowledge, in light of the local context and resources, into practice, program and policy decisions. While the public health sector in Canada is working toward evidence-informed decision making, considerable barriers, including efficient access to synthesized resources, exist. Methods In this paper we map to a previously developed 6 level pyramid of pre-processed research evidence, relevant resources that include public health-related effectiveness evidence. The resources were identified through extensive searches of both the published and unpublished domains. Results Many resources with public health-related evidence were identified. While there were very few resources dedicated solely to public health evidence, many clinically focused resources include public health-related evidence, making tools such as the pyramid, that identify these resources, particularly helpful for public health decisions makers. A practical example illustrates the application of this model and highlights its potential to reduce the time and effort that would be required by public health decision makers to address their practice-based issues. Conclusions This paper describes an existing hierarchy of pre-processed evidence and its adaptation to the public health setting. A number of resources with public health-relevant content that are either freely accessible or requiring a subscription are identified. This will facilitate easier and faster access to pre-processed, public health-relevant evidence, with the intent of promoting evidence-informed decision making. Access to such resources addresses several barriers identified by public health decision makers to evidence-informed decision making, most importantly time, as well as lack of knowledge of resources that house public health-relevant evidence. PMID:20181270

Building Training Curricula for Accelerating the Use of NOAA Climate Products and Tools

NASA Astrophysics Data System (ADS)

Timofeyeva-Livezey, M. M.; Meyers, J. C.; Stevermer, A.; Abshire, W. E.; Beller-Simms, N.; Herring, D.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) plays a leading role in U.S. intergovernmental efforts on the Climate Data Initiative and the Climate Resilience Toolkit (CRT). CRT (http://toolkit.climate.gov/) is a valuable resource that provides tools, information, and subject matter expertise to decision makers in various sectors, such as agriculture, water resources and transportation, to help them build resilience to our changing climate. In order to make best use of the toolkit and all the resources within it, a training component is critical. The training section helps building users' understanding of the data, science, and impacts of climate variability and change. CRT identifies five steps in building resilience that includes use of appropriate tools to support decision makers depending on their needs. One tool that can be potentially integrated into CRT is NOAA's Local Climate Analysis Tool (LCAT), which provides access to trusted NOAA data and scientifically-sound analysis techniques for doing regional and local climate studies on climate variability and climate change. However, in order for LCAT to be used effectively, we have found an iterative learning approach using specific examples to train users. For example, for LCAT application in analysis of water resources, we use existing CRT case studies for Arizona and Florida water supply users. The Florida example demonstrates primary sensitivity to climate variability impacts, whereas the Arizona example takes into account longer- term climate change. The types of analyses included in LCAT are time series analysis of local climate and the estimated rate of change in the local climate. It also provides a composite analysis to evaluate the relationship between local climate and climate variability events such as El Niño Southern Oscillation, the Pacific North American Index, and other modes of climate variability. This paper will describe the development of a training module for use of LCAT and its integration into CRT. An iterative approach was used that incorporates specific examples of decision making while working with subject matter experts within the water supply community. The recommended strategy is to use a "stepping stone" learning structure to build users knowledge of best practices for use of LCAT.

The Colorado Climate Preparedness Project: A Systematic Approach to Assessing Efforts Supporting State-Level Adaptation

NASA Astrophysics Data System (ADS)

Klein, R.; Gordon, E.

2010-12-01

Scholars and policy analysts often contend that an effective climate adaptation strategy must entail "mainstreaming," or incorporating responses to possible climate impacts into existing planning and management decision frameworks. Such an approach, however, makes it difficult to assess the degree to which decisionmaking entities are engaging in adaptive activities that may or may not be explicitly framed around a changing climate. For example, a drought management plan may not explicitly address climate change, but the activities and strategies outlined in it may reduce vulnerabilities posed by a variable and changing climate. Consequently, to generate a strategic climate adaptation plan requires identifying the entire suite of activities that are implicitly linked to climate and may affect adaptive capacity within the system. Here we outline a novel, two-pronged approach, leveraging social science methods, to understanding adaptation throughout state government in Colorado. First, we conducted a series of interviews with key actors in state and federal government agencies, non-governmental organizations, universities, and other entities engaged in state issues. The purpose of these interviews was to elicit information about current activities that may affect the state’s adaptive capacity and to identify future climate-related needs across the state. Second, we have developed an interactive database cataloging organizations, products, projects, and people actively engaged in adaptive planning and policymaking that are relevant to the state of Colorado. The database includes a wiki interface, helping create a dynamic component that will enable frequent updating as climate-relevant information emerges. The results of this project are intended to paint a clear picture of sectors and agencies with higher and lower levels of adaptation awareness and to provide a roadmap for the next gubernatorial administration to pursue a more sophisticated climate adaptation agenda. Project results can also inform numerous other ongoing database efforts connected to the U.S. National Assessment of Climate Change.

Examining Challenges Related to the Production of Actionable Climate Knowledge for Adaptation Decision-Making: A Focus on Climate Knowledge System Producers

NASA Astrophysics Data System (ADS)

Ernst, K.; Preston, B. L.; Tenggren, S.; Klein, R.; Gerger-Swartling, Å.

2017-12-01

Many challenges to adaptation decision-making and action have been identified across peer-reviewed and gray literature. These challenges have primarily focused on the use of climate knowledge for adaptation decision-making, the process of adaptation decision-making, and the needs of the decision-maker. Studies on climate change knowledge systems often discuss the imperative role of climate knowledge producers in adaptation decision-making processes and stress the need for producers to engage in knowledge co-production activities and to more effectively meet decision-maker needs. While the influence of climate knowledge producers on the co-production of science for adaptation decision-making is well-recognized, hardly any research has taken a direct approach to analyzing the challenges that climate knowledge producers face when undertaking science co-production. Those challenges can influence the process of knowledge production and may hinder the creation, utilization, and dissemination of actionable knowledge for adaptation decision-making. This study involves semi-structured interviews, focus groups, and participant observations to analyze, identify, and contextualize the challenges that climate knowledge producers in Sweden face as they endeavor to create effective climate knowledge systems for multiple contexts, scales, and levels across the European Union. Preliminary findings identify complex challenges related to education, training, and support; motivation, willingness, and culture; varying levels of prioritization; professional roles and responsibilities; the type and amount of resources available; and professional incentive structures. These challenges exist at varying scales and levels across individuals, organizations, networks, institutions, and disciplines. This study suggests that the creation of actionable knowledge for adaptation decision-making is not supported across scales and levels in the climate knowledge production landscape. Additionally, enabling the production of actionable knowledge for adaptation decision-making requires multi-level effort beyond the individual level.

Climate Proxies: An Inquiry-Based Approach to Discovering Climate Change on Antarctica

NASA Astrophysics Data System (ADS)

Wishart, D. N.

2016-12-01

An attractive way to advance climate literacy in higher education is to emphasize its relevance while teaching climate change across the curriculum to science majors and non-science majors. An inquiry-based pedagogical approach was used to engage five groups of students on a "Polar Discovery Project" aimed at interpreting the paleoclimate history of ice cores from Antarctica. Learning objectives and student learning outcomes were clearly defined. Students were assigned several exercises ranging from examination of Antarctic topography to the application of physical and chemical measurements as proxies for climate change. Required materials included base and topographic maps of Antarctica; graph sheets for construction of topographic cross-sectional profiles from profile lines of the Western Antarctica Ice Sheet (WAIS) Divide and East Antarctica; high-resolution photographs of Antarctic ice cores; stratigraphic columns of ice cores; borehole and glaciochemical data (i.e. anions, actions, δ18O, δD etc.); and isotope data on greenhouse gases (CH4, O2, N2) extracted from gas bubbles in ice cores. The methodology was to engage students in (2) construction of topographic profiles; (2) suggest directions for ice flow based on simple physics; (3) formulate decisions on suitable locations for drilling ice cores; (4) visual ice stratigraphy including ice layer counting; (5) observation of any insoluble particles (i.e. meteoritic and volcanic material); (6) analysis of borehole temperature profiles; and (7) the interpretation of several datasets to derive a paleoclimate history of these areas of the continent. The overall goal of the project was to improve the students analytical and quantitative skills; their ability to evaluate relationships between physical and chemical properties in ice cores, and to advance the understanding the impending consequences of climate change while engaging science, technology, engineering and mathematics (STEM). Student learning outcomes were assessed at the completion of the `Polar Discovery Project' for their curiosity, analytical strength, creativity, group collaboration, problem-solving, innovation, and interest in level climate change and the implications of the its effects on polar regions.

Climate Change Impacts and Adaptation on Southwestern DoD Facilities

DTIC Science & Technology

2017-03-03

integrating climate change risks into decision priorities. 15. SUBJECT TERMS adaptation, baseline sensitivity, climate change, climate exposure...four bases we found that integrating climate change risks into the current decision matrix, by linking projected risks to current or past impacts...data and decision tools and methods. Bases have some capacity to integrate climate-related information, but they have limited resources to undertake

WWOSC 2014: research needs for better health resilience to weather hazards.

PubMed

Jancloes, Michel; Anderson, Vidya; Gosselin, Pierre; Mee, Carol; Chong, Nicholas J

2015-03-05

The first World Weather Open Science Conference (WWOSC, held from 17-21 August 2014 in Montreal, Québec), provided an open forum where the experience and perspective of a variety of weather information providers and users was combined with the latest application advances in social sciences. A special session devoted to health focused on how best the most recent weather information and communication technologies (ICT) could improve the health emergency responses to disasters resulting from natural hazards. Speakers from a plenary presentation and its corresponding panel shared lessons learnt from different international multidisciplinary initiatives against weather-related epidemics, such as malaria, leptospirosis and meningitis and from public health responses to floods and heat waves such as in Ontario and Quebec, Canada. Participants could bear witness to recent progress made in the use of forecasting tools and in the application of increased spatiotemporal resolutions in the management of weather related health risks through anticipative interventions, early alert and warning and early responses especially by vulnerable groups. There was an agreement that resilience to weather hazards is best developed based on evidence of their health impact and when, at local level, there is a close interaction between health care providers, epidemiologists, climate services, public health authorities and communities. Using near real time health data (such as hospital admission, disease incidence monitoring…) combined with weather information has been recommended to appraise the relevance of decisions and the effectiveness of interventions and to make adjustments when needed. It also helps appraising how people may be more or less vulnerable to a particular hazard depending on the resilience infrastructures and services. This session was mainly attended by climate, environment and social scientists from North American and European countries. Producing a commentary appears to be an effective way to share this session's conclusions to research institutions and public health experts worldwide. It also advocates for better linking operational research and decision making and for appraising the impact of ICT and public health interventions on health.

Web based visualization of large climate data sets

USGS Publications Warehouse

Alder, Jay R.; Hostetler, Steven W.

2015-01-01

We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.

Assessment of diffuse radiation models in Azores

NASA Astrophysics Data System (ADS)

Magarreiro, Clarisse; Brito, Miguel; Soares, Pedro; Azevedo, Eduardo

2014-05-01

Measured irradiance databases usually consist of global solar radiation data with limited spatial coverage. Hence, solar radiation models have been developed to estimate the diffuse fraction from the measured global irradiation. This information is critical for the assessment of the potential of solar energy technologies; for example, the decision to use photovoltaic systems with tracking system. The different solar radiation models for this purpose differ on the parameters used as input. The simplest, and most common, are models which use global radiation information only. More sophisticated models require meteorological parameters such as information from clouds, atmospheric turbidity, temperature or precipitable water content. Most of these models comprise correlations with the clearness index, kt (portion of horizontal extra-terrestrial radiation reaching the Earth's surface) to obtain the diffuse fraction kd (portion of diffuse component from global radiation). The applicability of these different models is related to the local atmospheric conditions and its climatic characteristics. The models are not of general validity and can only be applicable to locations where the albedo of the surrounding terrain and the atmospheric contamination by dust are not significantly different from those where the corresponding methods were developed. Thus, models of diffuse fraction exhibit a relevant degree of location dependence: e.g. models developed considering data acquired in Europe are mainly linked to Northern, Central or, more recently, Mediterranean areas. The Azores Archipelago, with its particular climate and cloud cover characteristics, different from mainland Europe, has not yet been considered for the development of testing of such models. The Azorean climate reveals large amounts of cloud cover in its annual cycle, with spatial and temporal variabilities more complex than the common Summer/Winter pattern. This study explores the applicability of different existing correlation models of diffuse fraction and clearness index or other plain parameters to the Azorean region. Reliable data provided by the Atmospheric Radiation Measurements (ARM) Climate Research Facility from the Graciosa Island deployment of the ARM Mobile Facility (http://www.arm.gov/sites/amf/grw) was used to perform the analysis. Model results showed a tendency to underestimate higher values of diffuse radiation. From the performance results of the correlation models reviewed it was clear that there is room for improvement.

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

NASA Astrophysics Data System (ADS)

Lucio, Filipe

2015-04-01

The World Climate Conference-3 (Geneva 2009) unanimously decided to establish the Global Framework for Climate Services (GFCS), a UN-led initiative spearheaded by WMO to guide the development and application of science-based climate information and services in support of decision-making in climate sensitive sectors. By promoting science-based decision-making, the GFCS is empowering governments, communities and companies to build climate resilience, reduce vulnerabilities and adapt to impacts. The initial priority areas of GFCS are Agriculture and Food Security; Disaster Risk Reduction; Health; and Water Resources. The implementation of GFCS is well underway with a governance structure now fully established. The governance structure of GFCS includes the Partner Advisory Committee (PAC), which is GFCS's stakeholder engagement mechanism. The membership of the PAC allows for a broad participation of stakeholders. The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), the European Commission (EC), the Food and Agriculture Organization of the UN (FAO), the Global Water Partnership (GWP), the International Federation of Red Cross and Red Crescent Societies (IFRC), the International Union of Geodesy and Geophysics (IUGG), United Nations Environment Programme (UNEP), the United Nations Institute for Training and Research (UNITAR), the World Business Council for Sustainable Development (WBCSD), the World Food Programme (WFP) and WMO have already joined the PAC. Activities are being implemented in various countries in Africa, the Caribbean, Asia and Pacific Small Islands Developing States through flagship projects and activities in the four priority areas of GFCS to enable the development of a Proof of Concept. The focus at national level is on strengthening institutional capacities needed for development of capacities for co-design and co-production of climate services and their application in support of decision-making in climate sensitive sectors. Establishment of regional capacities through climate centres to support national institutional capacities is a major focus. The Proof of Concept will be replicated in other parts of the world to ensure worldwide improvements in climate services for the four priority areas to facilitate the reduction of society's vulnerability to climate-related hazards and the advancement of the key global development goals. To streamline and harness climate research and knowledge in support of GFCS implementation, regional research plans or agendas are being shaped in different regions. For example, a Climate Research for Development Agenda for Africa (CR4D) is being developed under the leadership of the World Climate Research Programme (WCRP) and in cooperation with the African Union Commission and other partners. Similarly, regional climate research priorities are being developed for Latin America and the Caribbean, following the WCRP Conference for Latin America and the Caribbean (Montevideo, March 2014). Availability of regional research plans or agendas would ensure more effective research and involvement of national experts in climate research activities.

Choosing and using climate-change scenarios for ecological-impact assessments and conservation decisions.

PubMed

Snover, Amy K; Mantua, Nathan J; Littell, Jeremy S; Alexander, Michael A; McClure, Michelle M; Nye, Janet

2013-12-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación. © 2013 Society for Conservation Biology.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Quantifying conditional risks for water and energy systems using climate information

NASA Astrophysics Data System (ADS)

Lall, U.

2016-12-01

There has been a growing recognition of the multi-scale spatio-temporal organization of climate dynamics, and its implications for predictable, structured risk exposure to populations and infrastructure systems. At the most base level is an understanding that there are some identifiable climate modes, such as ENSO, that are associated with such outcomes. This has led to the emergence of a small cottage industry of analysts who relate different "climate indices" to specific regional outcomes. Such efforts and the associated media interest in these simplified "stories" have led to an increasing appreciation of the phenomenon, and some formal and informal efforts at decision making using such information. However, as was demonstrated through the 2014-16 El Nino forecasting season, many climate scientists over-emphasized the potential risks, while others cautioned the media as to the caveats and uncertainties associated with assuming that the forecasts of ENSO and the expected teleconnections may pan out. At least in certain sectors and regions, significant efforts or expectations as to outcomes were put in place, and some were beneficial, while others failed to manifest. Climate informed predictions for water and energy systems can be thought of as efforts to infer conditional distributions of specific outcomes given information on climate state. Invariably, the climate state may be presented as a very high dimensional spatial set of variables, with limited temporal sampling, while the water and energy attributes may be regional and constitute a much smaller dimension. One may, of course, be interested in the fact that the same climate state may lead to synchronous positive and negative effects across many locations, as may be expected under mid-latitude stationary and transient wave interaction. In this talk, I will provide examples of a few modern statistical and machine learning tools that allow a decomposition of the high dimensional climate state and its relation to specific regional or hemispheric outcomes that inform terrestrial water and energy (wind as well as hydropower) futures. The focus will be on how one can frame the mathematical problem of robustly estimating relevant conditional distributions and their uncertainty, to inform risk management applications in these sectors.

The role of paleoecology in restoration and resource management—The past as a guide to future decision-making: Review and example from the Greater Everglades Ecosystem, U.S.A

USGS Publications Warehouse

Wingard, G. Lynn; Bernhardt, Christopher E.; Wachnicka, Anna

2017-01-01

Resource managers around the world are challenged to develop feasible plans for sustainable conservation and/or restoration of the lands, waters, and wildlife they administer—a challenge made greater by anticipated climate change and associated effects over the next century. Increasingly, paleoecologic and geologic archives are being used to extend the period of record of observed data and provide information on centennial to millennial scale responses to long-term drivers of ecosystem change. The development of paleoecology from an emerging field investigating past environments to a highly relevant applied science is reviewed and general examples of the application of paleoecologic research to resource management questions in diverse habitats and regions are provided. Specific examples of the application of paleoecologic research to the restoration of the Greater Everglades Ecosystem of south Florida (U.S.A) are presented. Conducting valuable scientific research that would benefit resource management decisions, however, is not enough. Scientists and resource managers need to be engaged in collaborative discussions from the beginning of the research process to ensure that management questions are being addressed and that the science reaches the people who will benefit from the information. Paleoecology and related disciplines provide an understanding of how ecosystems and individual species function and change over time in response to both natural and anthropogenic drivers. Information on pre-anthropogenic baseline conditions is provided by paleoecologic research, but it is the detection of long-term trends and cycles that allow resource managers to set realistic goals and targets by moving away from the fixed-point baseline concept to one of dynamic landscapes that anticipates and incorporates an expectation of change into decision-making.

Connecting Climate Science to Policy: from Global Food Production to the US Supreme Court

NASA Astrophysics Data System (ADS)

Battisti, D. S.

2016-12-01

There are myriad ways climate science has been used to inform on global food security, and to affect law and policy. In this talk, I will summarize examples that include the application of the El Nino - Southern Oscillation science to improve food security in Indonesia and provide water forecasts for agriculture in northwest Mexico, as well as the application of climate change science to project changes in global grain production. In the latter case, reliable information on the impact of increasing greenhouse gases on growing season temperature is applied to assess the impact of climate change on average crop yields, on the volatility in crop yields, and on the loss of yield due to increasing pest pressure - all of which have acute implications for agricultural policy. In the US, climate change science was of paramount importance for the Supreme Court decision in the case "Massachusetts vs. EPA," which to this day greatly shapes US policy related to climate change - most notably in setting emission standards for vehicles. My colleagues and I have learned several lessons from our experiences in these applications of climate science that I will share, including some thoughts on the nature of interdisciplinary teams for producing reliable and effective products, and the on the professional pros and cons of pursuing applied work.

Development of a Climate Resilience Screening Index (CRSI) ...

EPA Pesticide Factsheets

A Climate Resilience Screening Index is being developed that is applicable at multiple scales for the United States. Those scales include national, state, county and community. The index will be applied at the first three scales and at selected communities. The index was developed in order to explicitly include domains, indicators and metrics addressing environmental, economic and societal aspects of climate resilience. In addition, the index uses indicators and metrics that assess ecosystem, economic, governance and social services at these scales. Finally, we are developing forecasting approaches that can relate intended changes in services and governance to likely levels of changes in the resiliency of communities to climate change impacts. The present challenge is the incorporation of the index, its relationships to governance and the developing forecasting tools into Federal decision-making across US government and into state/county/community decision-making across the US. Governmental acceptance of changes to policies often can be just as challenging as the initial technical acceptance of the index and its relation to climate change. Climate Resilience Index is a requested product by ORD AA and EPA Administrator through SHC Program. Index needed to assess states', counties', and communities' abilities of recovery from climate events. Audience: Internal EPA (Administrator, IO, OLEM, OW and OAR) and external (states, counties and communities). Product

29 CFR 18.302 - Applicability of state law.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 1 2014-07-01 2013-07-01 true Applicability of state law. 18.302 Section 18.302 Labor... OFFICE OF ADMINISTRATIVE LAW JUDGES Rules of Evidence Presumptions § 18.302 Applicability of state law... State law supplies the rule of decision is determined in accordance with State law. Relevancy and Its...

Data Management Guidance in the Context of Climate Risk-Management

NASA Astrophysics Data System (ADS)

Sylak-Glassman, E.

2016-12-01

Climate risk-management, while a national issue, often occurs at a local level. To prepare for the effects of climate change, community decision-makers require a diverse set of data from historical records, social science, observations, and models, much of which is collected and curated by Federal agencies. The President's Climate Action Plan calls for building stronger and safer communities and infrastructure to prepare the United States for the impacts of climate change, and the Obama Administration has prioritized making Federal data more discoverable, accessible, and usable to inform both climate risk-management, and other data-informed decisions. In order to understand the state of guidance for data provision for climate risk-management, we analyzed Federal, agency, and interagency documents such as the Common Framework for Earth-Observation Data, related to open data, climate data, and data management in general. We examined guidance related to the principles of data discovery, access, and ease of use, as well as the data management categories of application programming interfaces, controlled vocabularies and ontologies, metadata, persistent dataset identifiers, preservation, and usage metrics. This analysis showed both the extent of guidance provided, as well as gaps in guidance. Following the literature review, we held structured conversations with Federal climate data managers and tool developers to identify areas where further efforts could enhance provision of agency data for climate risk-management. Our analysis can be used by data managers to understand how various data management practices can help improve climate risk-management and where to find further guidance.

Sea Surface Temperature for Climate Applications: A New Dataset from the European Space Agency Climate Change Initiative

NASA Astrophysics Data System (ADS)

Merchant, C. J.; Hulley, G. C.

2013-12-01

There are many datasets describing the evolution of global sea surface temperature (SST) over recent decades -- so why make another one? Answer: to provide observations of SST that have particular qualities relevant to climate applications: independence, accuracy and stability. This has been done within the European Space Agency (ESA) Climate Change Initative (CCI) project on SST. Independence refers to the fact that the new SST CCI dataset is not derived from or tuned to in situ observations. This matters for climate because the in situ observing network used to assess marine climate change (1) was not designed to monitor small changes over decadal timescales, and (2) has evolved significantly in its technology and mix of types of observation, even during the past 40 years. The potential for significant artefacts in our picture of global ocean surface warming is clear. Only by having an independent record can we confirm (or refute) that the work done to remove biases/trend artefacts in in-situ datasets has been successful. Accuracy is the degree to which SSTs are unbiased. For climate applications, a common accuracy target is 0.1 K for all regions of the ocean. Stability is the degree to which the bias, if any, in a dataset is constant over time. Long-term instability introduces trend artefacts. To observe trends of the magnitude of 'global warming', SST datasets need to be stable to <5 mK/year. The SST CCI project has produced a satellite-based dataset that addresses these characteristics relevant to climate applications. Satellite radiances (brightness temperatures) have been harmonised exploiting periods of overlapping observations between sensors. Less well-characterised sensors have had their calibration tuned to that of better characterised sensors (at radiance level). Non-conventional retrieval methods (optimal estimation) have been employed to reduce regional biases to the 0.1 K level, a target violated in most satellite SST datasets. Models for quantifying uncertainty have been developed to attach uncertainty to SST across a range of space-time scales. The stability of the data has been validated.

Effective Decision Maker-Scientist Engagement:Climate Change Vulnerability Analysis of California's Water System to Using Decision Scaling.

NASA Astrophysics Data System (ADS)

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

2016-12-01

For nearly 2 years the California Department of Water Resources (CDWR) has been working with the University of Massachusetts Amherst (UMass) to evaluate climate change vulnerabilities to the California State Water Project. Working cooperatively, the team has developed tools and methods to employ a decision scaling approach to CDWR's existing water system model (CalSim-II/CalLite 3.0). This presentation will discuss how and why this partnership came to be, the co-production model the team has developed to share expertise, the new understanding of the system that has been gained through the process, and current and future efforts to influence planning and investments based on the findings of the work. This cooperative decision-maker-with-scientist engagement is unique in that CDWR has not outsourced the application of the science to their systems, and instead has worked directly with UMass researchers to develop the process, produce results, and interpret findings. Further, CDWR staff has worked with UMass researchers to present results in ways that are more useable and actionable for decision-makers. As will be shown, many of these graphics allow the team to use the science differently to improve decision making.

Operational seasonal forecasting of crop performance.

PubMed

Stone, Roger C; Meinke, Holger

2005-11-29

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.

Operational seasonal forecasting of crop performance

PubMed Central

Stone, Roger C; Meinke, Holger

2005-01-01

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production. PMID:16433097

An approach to designing a national climate service

PubMed Central

Miles, E. L.; Snover, A. K.; Whitely Binder, L. C.; Sarachik, E. S.; Mote, P. W.; Mantua, N.

2006-01-01

Climate variability and change are considerably important for a wide range of human activities and natural ecosystems. Climate science has made major advances during the last two decades, yet climate information is neither routinely useful for nor used in planning. What is needed is a mechanism, a national climate service (NCS), to connect climate science to decision-relevant questions and support building capacity to anticipate, plan for, and adapt to climate fluctuations. This article contributes to the national debate for an NCS by describing the rationale for building an NCS, the functions and services it would provide, and how it should be designed and evaluated. The NCS is most effectively achieved as a federal interagency partnership with critically important participation by regional climate centers, state climatologists, the emerging National Integrated Drought Information System, and the National Oceanic and Atmospheric Administration (NOAA) Regional Integrated Sciences Assessment (RISA) teams in a sustained relationship with a wide variety of stakeholders. Because the NCS is a service, and because evidence indicates that the regional spatial scale is most important for delivering climate services, given subnational geographical/geophysical complexity, attention is focused on lessons learned from the University of Washington Climate Impacts Group's 10 years of experience, the first of the NOAA RISA teams. PMID:17158218

An approach to designing a national climate service.

PubMed

Miles, E L; Snover, A K; Whitely Binder, L C; Sarachik, E S; Mote, P W; Mantua, N

2006-12-26

Climate variability and change are considerably important for a wide range of human activities and natural ecosystems. Climate science has made major advances during the last two decades, yet climate information is neither routinely useful for nor used in planning. What is needed is a mechanism, a national climate service (NCS), to connect climate science to decision-relevant questions and support building capacity to anticipate, plan for, and adapt to climate fluctuations. This article contributes to the national debate for an NCS by describing the rationale for building an NCS, the functions and services it would provide, and how it should be designed and evaluated. The NCS is most effectively achieved as a federal interagency partnership with critically important participation by regional climate centers, state climatologists, the emerging National Integrated Drought Information System, and the National Oceanic and Atmospheric Administration (NOAA) Regional Integrated Sciences Assessment (RISA) teams in a sustained relationship with a wide variety of stakeholders. Because the NCS is a service, and because evidence indicates that the regional spatial scale is most important for delivering climate services, given subnational geographical/geophysical complexity, attention is focused on lessons learned from the University of Washington Climate Impacts Group's 10 years of experience, the first of the NOAA RISA teams.

Climate Scenarios for the NASA / USAID SERVIR Project: Challenges for Multiple Planning Horizons

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Roberts, J. B.; Lyon, B.; Funk, C.; Bosilovich, M. G.

2014-01-01

SERVIR, an acronym meaning "to serve" in Spanish, is a joint venture between NASA and the U.S. Agency for International Development (USAID) which provides satellite-based Earth observation data, modeling, and science applications to help developing nations in Central America, East Africa and the Himalayas improve environmental decision making. Anticipating climate variability / climate change impacts has now become an important component of the SERVIR efforts to build capacity in these regions. Uncertainty in hydrometeorological components of climate variations and exposure to extreme events across scales from weather to climate are of particular concern. We report here on work to construct scenarios or outlooks that are being developed as input drivers for decision support systems (DSSs) in a variety of settings. These DSSs are being developed jointly by a broad array NASA Applied Science Team (AST) Investigations and user communities in the three SERVIR Hub Regions, Central America, East Africa and the Himalayas. Issues span hydrologic / water resources modeling, agricultural productivity, and forest carbon reserves. The scenarios needed for these efforts encompass seasonal forecasts, interannual outlooks, and likely decadal / multi-decadal trends. Providing these scenarios across the different AST efforts enables some level of integration in considering regional responses to climate events. We will discuss a number of challenges in developing this continuum of scenarios including the identification and "mining" of predictability, addressing multiple continental regions, issues of downscaling global model integrations to regional / local applications (i.e. hydrologic and crop modeling). We compare / contrast the role of the U.S. National Multi- Model Experiment initiative in seasonal forecasts and the CMIP-5 climate model experiments in supporting these efforts. Examples of these scenarios, their use, and an assessment of their utility as well as limitations will be presented.

Tools to support evidence-informed public health decision making

PubMed Central

2014-01-01

Background Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. Methods As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Results Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the ‘actionable message(s)’ from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing and sustaining evidence-informed decision making. Conclusion Tools are available to support the process of evidence-informed decision making among public health professionals. The usability and usefulness of these tools for advancing and sustaining evidence-informed decision making are discussed, including recommendations for the tools’ application in other public health settings beyond this study. Knowledge and awareness of these tools may assist other health professionals in their efforts to implement evidence-informed practice. PMID:25034534

Tools to support evidence-informed public health decision making.

PubMed

Yost, Jennifer; Dobbins, Maureen; Traynor, Robyn; DeCorby, Kara; Workentine, Stephanie; Greco, Lori

2014-07-18

Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the 'actionable message(s)' from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing and sustaining evidence-informed decision making. Tools are available to support the process of evidence-informed decision making among public health professionals. The usability and usefulness of these tools for advancing and sustaining evidence-informed decision making are discussed, including recommendations for the tools' application in other public health settings beyond this study. Knowledge and awareness of these tools may assist other health professionals in their efforts to implement evidence-informed practice.

Successful Coproduction in Water Management and Climate Science

NASA Astrophysics Data System (ADS)

Kaatz, L.

2017-12-01

Frequently described as the "canary in the coal mine," the water sector has been one of the first to experience and begin preparing for the impacts of climate change. Water utilities have lead the way in developing and testing climate information in practice with the end goal of building resiliency and avoiding catastrophic disasters. A key aspect of this leadership is strong, collaborative partnerships resulting in the coproduction of knowledge and actionable science. In this session we will hear from the decision-maker perspective regarding what effective partnerships in real-world applications look like using examples from the Water Utility Climate Alliances (WUCA), and the experience and outcomes of a unique decade-long partnership between Denver Water and the National Center for Atmospheric Research. The lessons learned and challenges encountered in these examples of coproduction are not unique to WUCA, Denver Water nor the water sector, rather they are applicable across sectors and may inform future coproduction efforts.

Affordances and Challenges of Using Argument as a Connective Discourse for Scientific Practices to Teach Climate Science

NASA Astrophysics Data System (ADS)

Sezen-Barrie, A.; Wolfson, J.

2015-12-01

An important goal of science education is to support development of citizens to participate in public debate and make informed decisions relevant to their lives and their worlds. The NGSS (Next Generation Science Standards) suggest engaging students in science classrooms in argumentation as a practice to help enhance the quality of evidence based decision making. In this multi-case study, we explored the use of written argumentation in eight secondary school science classrooms during a lesson on the relationship between ocean temperature and its CO2 holding capacity. All teachers of these classrooms were trained during a day long NSF funded Climate Literacy Workshop on the basic concepts of climate science, scientific practices and implementation of an activity called "It's a Gassy World". The data of the current study involved students' written arguments, teachers' written reflections on the implementation of the activity as well as field notes from the Climate Literacy Workshop. A qualitative discourse analysis of the data was used to find common themes around affordances and challenges of argument as a connective discourse for scientific practices to teach climate change. The findings show that participating in written argumentation process encouraged students to discuss their experimental design and use data interpretation for their evidences. However, the results also indicated the following challenges: a) teachers themselves need support in connecting their evidence to their claims, b) arguing a socioscientific issue creates a sensitive environment c) conceptual quality of an argument needs to be strengthen through background in courses other than science, and d) graphing skills (or lack of) can interfere with constructing scientifically accurate claims. This study has implications in effectively teaching climate change through argumentation, and thus creating opportunities for practicing authentic climate science research in K-12 classrooms.

Beyond climate-smart agriculture: toward safe operating spaces for global food systems

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

Gulledge, Jay; Neufeldt, Heinrich; Jahn, Margaret M

Agriculture is considered to be climate-smart when it contributes to increasing food security, adaptation and mitigation in a sustainable way. This new concept now dominates current discussions in agricultural development because of its capacity to unite the agendas of the agriculture, development and climate change communities under one brand. In this opinion piece authored by scientists from a variety of international agricultural and climate research communities, we argue that the concept needs to be evaluated critically because the relationship between the three dimensions is poorly understood, such that practically any improved agricultural practice can be considered climate-smart. This lack ofmore » clarity may have contributed to the broad appeal of the concept. From the understanding that we must hold ourselves accountable to demonstrably better meet human needs in the short and long term within foreseeable local and planetary limits, we develop a conceptualization of climate-smart agriculture as agriculture that can be shown to bring us closer to safe operating spaces for agricultural and food systems across spatial and temporal scales. Improvements in the management of agricultural systems that bring us significantly closer to safe operating spaces will require transformations in governance and use of our natural resources, underpinned by enabling political, social and economic conditions beyond incremental changes. Establishing scientifically credible indicators and metrics of long-term safe operating spaces in the context of a changing climate and growing social-ecological challenges is critical to creating the societal demand and political will required to motivate deep transformations. Answering questions on how the needed transformational change can be achieved will require actively setting and testing hypotheses to refine and characterize our concepts of safer spaces for social-ecological systems across scales. This effort will demand prioritizing key areas of innovation, such as (1) improved adaptive management and governance of social-ecological systems; (2) development of meaningful and relevant integrated indicators of social-ecological systems; (3) gathering of quality integrated data, information, knowledge and analytical tools for improved models and scenarios in time frames and at scales relevant for decision-making; and (4) establishment of legitimate and empowered science policy dialogues on local to international scales to facilitate decision making informed by metrics and indicators of safe operating spaces.« less

Easier surveillance of climate-related health vulnerabilities through a Web-based spatial OLAP application.

PubMed

Bernier, Eveline; Gosselin, Pierre; Badard, Thierry; Bédard, Yvan

2009-04-03

Climate change has a significant impact on population health. Population vulnerabilities depend on several determinants of different types, including biological, psychological, environmental, social and economic ones. Surveillance of climate-related health vulnerabilities must take into account these different factors, their interdependence, as well as their inherent spatial and temporal aspects on several scales, for informed analyses. Currently used technology includes commercial off-the-shelf Geographic Information Systems (GIS) and Database Management Systems with spatial extensions. It has been widely recognized that such OLTP (On-Line Transaction Processing) systems were not designed to support complex, multi-temporal and multi-scale analysis as required above. On-Line Analytical Processing (OLAP) is central to the field known as BI (Business Intelligence), a key field for such decision-support systems. In the last few years, we have seen a few projects that combine OLAP and GIS to improve spatio-temporal analysis and geographic knowledge discovery. This has given rise to SOLAP (Spatial OLAP) and a new research area. This paper presents how SOLAP and climate-related health vulnerability data were investigated and combined to facilitate surveillance. Based on recent spatial decision-support technologies, this paper presents a spatio-temporal web-based application that goes beyond GIS applications with regard to speed, ease of use, and interactive analysis capabilities. It supports the multi-scale exploration and analysis of integrated socio-economic, health and environmental geospatial data over several periods. This project was meant to validate the potential of recent technologies to contribute to a better understanding of the interactions between public health and climate change, and to facilitate future decision-making by public health agencies and municipalities in Canada and elsewhere. The project also aimed at integrating an initial collection of geo-referenced multi-scale indicators that were identified by Canadian specialists and end-users as relevant for the surveillance of the public health impacts of climate change. This system was developed in a multidisciplinary context involving researchers, policy makers and practitioners, using BI and web-mapping concepts (more particularly SOLAP technologies), while exploring new solutions for frequent automatic updating of data and for providing contextual warnings for users (to minimize the risk of data misinterpretation). According to the project participants, the final system succeeds in facilitating surveillance activities in a way not achievable with today's GIS. Regarding the experiments on frequent automatic updating and contextual user warnings, the results obtained indicate that these are meaningful and achievable goals but they still require research and development for their successful implementation in the context of surveillance and multiple organizations. Surveillance of climate-related health vulnerabilities may be more efficiently supported using a combination of BI and GIS concepts, and more specifically, SOLAP technologies (in that it facilitates and accelerates multi-scale spatial and temporal analysis to a point where a user can maintain an uninterrupted train of thought by focussing on "what" she/he wants (not on "how" to get it) and always obtain instant answers, including to the most complex queries that take minutes or hours with OLTP systems (e.g., aggregated, temporal, comparative)). The developed system respects Newell's cognitive band of 10 seconds when performing knowledge discovery (exploring data, looking for hypotheses, validating models). The developed system provides new operators for easily and rapidly exploring multidimensional data at different levels of granularity, for different regions and epochs, and for visualizing the results in synchronized maps, tables and charts. It is naturally adapted to deal with multiscale indicators such as those used in the surveillance community, as confirmed by this project's end-users.

Forecasting Distributional Responses of Limber Pine to Climate Change at Management-Relevant Scales in Rocky Mountain National Park

PubMed Central

Monahan, William B.; Cook, Tammy; Melton, Forrest; Connor, Jeff; Bobowski, Ben

2013-01-01

Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species' physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m2) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species' climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management. PMID:24391742

Tales from the Jungle: The Evolving Climate Services Ecosystem

NASA Astrophysics Data System (ADS)

Redmond, K. T.

2015-12-01

In 2001 the NRC Report "A Climate Services Vision: First Steps Toward the Future" examined the state and trends of climate services. That report included a definition of this term that has lost no relevance: "The timely production and delivery of useful climate data, information, and knowledge to decision makers." The original entities delivering such services, at the state level, are represented by the American Association of State Climatologists (AASC). In 1986 the NOAA Regional Climate Center program was initiated, followed in 1994 by the NOAA Regional Climate Sciences and Assessments. Since 2010 we have seen the establishment of the USDI Climate Science Centers and the Landscape Conservation Cooperatives, the NOAA Regional Climate Service Directors, and the USDA Regional Climate Hubs. The recent expansion of formal programs has essentially filled out the agency "niche space." Other non-governmental and private entities are also expanding into this space. The present profusion runs a risk of creating a perception of excessive duplication in some quarters, including those funding these enterprises. Collectively these activities form what can be thought of as an ecosystem of climate services. A certain amount of replication is desirable, healthy, and necessary, but beyond some point can be excessive unless the total capacity remains insufficient. Each component has come into existence for a different set of reasons. Since these components were invented by human beings, their subsequent evolution can in theory be guided by humans. The history and purpose of each component needs to be borne in mind, with capsule descriptions suitable for rapid delivery to the decision-makers who approve the support for the various components. Good communication among the components is therefore essential for a healthy and functional overall system. This in turn calls for the ability to adequately represent the role of each of those components, a purpose best informed through actual participation in multiple components, to obtain the necessary familiarity.

Varying geospatial analyses to assess climate risk and adaptive capacity in a hotter, drier Southwestern United States

NASA Astrophysics Data System (ADS)

Elias, E.; Reyes, J. J.; Steele, C. M.; Rango, A.

2017-12-01

Assessing vulnerability of agricultural systems to climate variability and change is vital in securing food systems and sustaining rural livelihoods. Farmers, ranchers, and forest landowners rely on science-based, decision-relevant, and localized information to maintain production, ecological viability, and economic returns. This contribution synthesizes a collection of research on the future of agricultural production in the American Southwest (SW). Research was based on a variety of geospatial methodologies and datasets to assess the vulnerability of rangelands and livestock, field crops, specialty crops, and forests in the SW to climate-risk and change. This collection emerged from the development of regional vulnerability assessments for agricultural climate-risk by the U.S. Department of Agriculture (USDA) Climate Hub Network, established to deliver science-based information and technologies to enable climate-informed decision-making. Authors defined vulnerability differently based on their agricultural system of interest, although each primarily focuses on biophysical systems. We found that an inconsistent framework for vulnerability and climate risk was necessary to adequately capture the diversity, variability, and heterogeneity of SW landscapes, peoples, and agriculture. Through the diversity of research questions and methodologies, this collection of articles provides valuable information on various aspects of SW vulnerability. All articles relied on geographic information systems technology, with highly variable levels of complexity. Agricultural articles used National Agricultural Statistics Service data, either as tabular county level summaries or through the CropScape cropland raster datasets. Most relied on modeled historic and future climate information, but with differing assumptions regarding spatial resolution and temporal framework. We assert that it is essential to evaluate climate risk using a variety of complementary methodologies and perspectives. In addition, we found that spatial analysis supports informed adaptation, within and outside the SW United States. The persistence and adaptive capacity of agriculture in the water-limited Southwest serves as an instructive example and may offer solutions to reduce future climate risk.

Forecasting distributional responses of limber pine to climate change at management-relevant scales in Rocky Mountain National Park.

PubMed

Monahan, William B; Cook, Tammy; Melton, Forrest; Connor, Jeff; Bobowski, Ben

2013-01-01

Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species' physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m(2)) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species' climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management.

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

PubMed

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

2012-10-01

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

RECOVERY ACT - Methods for Decision under Technological Change Uncertainty and Risk Assessment for Integrated Assessment of Climate Change

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

Webster, Mort David

2015-03-10

This report presents the final outcomes and products of the project as performed at the Massachusetts Institute of Technology. The research project consists of three main components: methodology development for decision-making under uncertainty, improving the resolution of the electricity sector to improve integrated assessment, and application of these methods to integrated assessment. Results in each area is described in the report.

Ontology development for provenance tracing in National Climate Assessment of the US Global Change Research Program

NASA Astrophysics Data System (ADS)

Ma, X.; Zheng, J. G.; Goldstein, J.; Duggan, B.; Xu, J.; Du, C.; Akkiraju, A.; Aulenbach, S.; Tilmes, C.; Fox, P. A.

2013-12-01

The periodical National Climate Assessment (NCA) of the US Global Change Research Program (USGCRP) [1] produces reports about findings of global climate change and the impacts of climate change on the United States. Those findings are of great public and academic concerns and are used in policy and management decisions, which make the provenance information of findings in those reports especially important. The USGCRP is developing a Global Change Information System (GCIS), in which the NCA reports and associated provenance information are the primary records. We were modeling and developing Semantic Web applications for the GCIS. By applying a use case-driven iterative methodology [2], we developed an ontology [3] to represent the content structure of a report and the associated provenance information. We also mapped the classes and properties in our ontology into the W3C PROV-O ontology [4] to realize the formal presentation of provenance. We successfully implemented the ontology in several pilot systems for a recent National Climate Assessment report (i.e., the NCA3). They provide users the functionalities to browse and search provenance information with topics of interest. Provenance information of the NCA3 has been made structured and interoperable by applying the developed ontology. Besides the pilot systems we developed, other tools and services are also able to interact with the data in the context of the 'Web of data' and thus create added values. Our research shows that the use case-driven iterative method bridges the gap between Semantic Web researchers and earth and environmental scientists and is able to be deployed rapidly for developing Semantic Web applications. Our work also provides first-hand experience for re-using the W3C PROV-O ontology in the field of earth and environmental sciences, as the PROV-O ontology is recently ratified (on 04/30/2013) by the W3C as a recommendation and relevant applications are still rare. [1] http://www.globalchange.gov [2] Fox, P., McGuinness, D.L., 2008. TWC Semantic Web Methodology. Accessible at: http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology [3] https://scm.escience.rpi.edu/svn/public/projects/gcis/trunk/rdf/schema/GCISOntology.ttl [4] http://www.w3.org/TR/prov-o/

The Key Political Decisions of the Military Government in Turkey, September 1980-November 1983 and the Impact on Those Decisions.

DTIC Science & Technology

1985-05-01

I-would argue that there is a relevant application of Professor Giovanni Sartoris theory of party systems to the Turkish case, especially in the 1979...1980 time frame. G. Sartori , Parties and Party Systems A Framework for Analysis (Cambridge Eng: Cambridge University Press, 1976). 7

An application programming interface for extreme precipitation and hazard products

NASA Astrophysics Data System (ADS)

Kirschbaum, D.; Stanley, T.; Cappelaere, P. G.; Reed, J.; Lammers, M.

2016-12-01

Remote sensing data provides situational awareness of extreme events and hazards over large areas in a way that is impossible to achieve with in situ data. However, more valuable than raw data is actionable information based on user needs. This information can take the form of derived products, extraction of a subset of variables in a larger data matrix, or data processing for a specific goal. These products can then stream to the end users, who can use these data to improve local to global decision making. This presentation will outline both the science and methodology of two new data products and tools that can provide relevant climate and hazard data for response and support. The Global Precipitation Measurement (GPM) mission provides near real-time information on rain and snow around the world every thirty minutes. Through a new applications programing interface (API), this data can be freely accessed by consumers to visualize, analyze, and communicate where, when and how much rain is falling worldwide. The second tool is a global landslide model that provides situational awareness of potential landslide activity in near real-time, utilizing several remotely sensed data products. This hazard information is also provided through an API and is being ingested by the emergency response community, international aid organizations, and others around the world. This presentation will highlight lessons learned through the development, implementation, and communication of these products and tools with the goal of enabling better and more effective decision making.

Towards process-informed bias correction of climate change simulations

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Shepherd, Theodore G.; Widmann, Martin; Zappa, Giuseppe; Walton, Daniel; Gutiérrez, José M.; Hagemann, Stefan; Richter, Ingo; Soares, Pedro M. M.; Hall, Alex; Mearns, Linda O.

2017-11-01

Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases.

Using expert judgments to explore robust alternatives for forest management under climate change.

PubMed

McDaniels, Timothy; Mills, Tamsin; Gregory, Robin; Ohlson, Dan

2012-12-01

We develop and apply a judgment-based approach to selecting robust alternatives, which are defined here as reasonably likely to achieve objectives, over a range of uncertainties. The intent is to develop an approach that is more practical in terms of data and analysis requirements than current approaches, informed by the literature and experience with probability elicitation and judgmental forecasting. The context involves decisions about managing forest lands that have been severely affected by mountain pine beetles in British Columbia, a pest infestation that is climate-exacerbated. A forest management decision was developed as the basis for the context, objectives, and alternatives for land management actions, to frame and condition the judgments. A wide range of climate forecasts, taken to represent the 10-90% levels on cumulative distributions for future climate, were developed to condition judgments. An elicitation instrument was developed, tested, and revised to serve as the basis for eliciting probabilistic three-point distributions regarding the performance of selected alternatives, over a set of relevant objectives, in the short and long term. The elicitations were conducted in a workshop comprising 14 regional forest management specialists. We employed the concept of stochastic dominance to help identify robust alternatives. We used extensive sensitivity analysis to explore the patterns in the judgments, and also considered the preferred alternatives for each individual expert. The results show that two alternatives that are more flexible than the current policies are judged more likely to perform better than the current alternatives on average in terms of stochastic dominance. The results suggest judgmental approaches to robust decision making deserve greater attention and testing. © 2012 Society for Risk Analysis.

Modeling human-climate interaction

NASA Astrophysics Data System (ADS)

Jacoby, Henry D.

If policymakers and the public are to be adequately informed about the climate change threat, climate modeling needs to include components far outside its conventional boundaries. An integration of climate chemistry and meteorology, oceanography, and terrestrial biology has been achieved over the past few decades. More recently the scope of these studies has been expanded to include the human systems that influence the planet, the social and ecological consequences of potential change, and the political processes that lead to attempts at mitigation and adaptation. For example, key issues—like the relative seriousness of climate change risk, the choice of long-term goals for policy, and the analysis of today's decisions when uncertainty may be reduced tomorrow—cannot be correctly understood without joint application of the natural science of the climate system and social and behavioral science aspects of human response. Though integration efforts have made significant contributions to understanding of the climate issue, daunting intellectual and institutional barriers stand in the way of needed progress. Deciding appropriate policies will be a continuing task over the long term, however, so efforts to extend the boundaries of climate modeling and assessment merit long-term attention as well. Components of the effort include development of a variety of approaches to analysis, the maintenance of a clear a division between close-in decision support and science/policy research, and the development of funding institutions that can sustain integrated research over the long haul.

Beyond misdiagnosis, misunderstanding and mistrust: relevance of the historical perspective in the medical and mental health treatment of people of color.

PubMed Central

Suite, Derek H.; La Bril, Robert; Primm, Annelle; Harrison-Ross, Phyllis

2007-01-01

In this article, we discuss the relationship and relevance of the historical interaction primarily between African-American culture and the medical and mental health communities, and explore the role of historical experience in contributing to mistrust and underutilization of services by people of color. We conclude that failure on the part of practitioners to go beyond clinical history gathering to recognize and acknowledge the larger historical perspectives from which they and their patients of color draw conclusions and make decisions contributes to the mistrust of the medical and mental health communities and to perpetuation of the current climate of healthcare disparities. PMID:17722664

Intra-seasonal risk of agriculturally-relevant weather extremes in West African Sudan Savanna

NASA Astrophysics Data System (ADS)

Boansi, David; Tambo, Justice A.; Müller, Marc

2018-01-01

Using household survey data and historical daily climate data for 29 communities across Upper East Ghana and Southwest Burkina Faso, we document climatic conditions deemed major threat to farming in the West African Sudan Savanna and assess risks posed by such conditions over the period 1997-2014. Based on farmers' perception, it is found that drought, low rainfall, intense precipitation, flooding, erratic rainfall pattern, extremely high temperatures, delayed rains, and early cessation of rains are the major threats farmers face. Using first-order Markov chain model and relevant indices for monitoring weather extremes, it is discovered that climatic risk is a general inherent attribute of the rainy season in the study area. Due to recent changes in onset of rains and length of the rainy season, some farmers have either resorted to early planting of drought-hardy crops, late planting of drought-sensitive crops, or spreading of planting across the first 3 months of the season to moderate harm. Each of these planting decisions however has some risk implications. The months of May, June, and October are found to be more susceptible to relatively longer duration of dry and hot spells, while July, August, and September are found to be more susceptible to intense precipitation and flooding. To moderate harm from anticipated weather extremes, farmers need to adjust their cropping calendar, adopt appropriate crop varieties, and implement soil and water management practices. For policy makers and other stakeholders, we recommend the supply of timely and accurate weather forecasts to guide farmers in their seasonal cropping decisions and investment in/installation of low cost irrigation facilities to enhance the practice of supplemental irrigation.

Community Resilience Education: Lessons Learned from an Emerging Community of Practice - NOAA's Environmental Literacy Grantees

NASA Astrophysics Data System (ADS)

Schoedinger, S. E.; McDougall, C.

2017-12-01

NOAA supports community resilience to extreme weather events, climate change and other environmental hazards by preparing communities through Weather Ready Nation and through programs addressing coastal community needs. These programs primarily target adult decisions makers in a professional capacity (emergency managers, city planners, et al.), leaving non-professional audiences without opportunities to understand and develop the skills to prepare for the threats and vulnerabilities that their communities face. As a result, resilience became the focus of NOAA's Environmental Literacy Grants in 2015. The goal of these investments is to strengthen the public's and/or K-12 students' environmental literacy to enable informed decision-making necessary for community resilience to extreme weather events and other environmental hazards. Funded projects build an understanding of Earth systems and the threats and vulnerabilities that are associated with a community's location, are aligned with existing adaptation/resilience plans, and connect audiences to relevant tools and resources to prepare for and respond to these hazards. These first few years of investment will create new models for how education can improve community resilience. Although these projects incorporate a variety of approaches, a few common themes stand out: empowering youth and adults to increase their understanding of locally relevant natural hazards and stresses; giving youth a voice in resilience planning; and student-led vulnerability assessments of their schools and communities. In this session we will report on the first convening of the principal investigators of our 13 funded projects, which represents the beginning of a new community of practice focused on resilience education. We will specifically share lessons learned about: engaging youth and adults about climate change and resiliency; working with local resilience/adaptation planners; and case studies on the use of NOAA's Digital Coast and the US Climate Resilience Toolkit.

Scientist-Practitioner Engagement to Inform Regional Hydroclimate Model Evaluation

NASA Astrophysics Data System (ADS)

Jones, A. D.; Jagannathan, K. A.; Ullrich, P. A.

2017-12-01

Water mangers face significant challenges in planning for the coming decades as previously stationary aspects of the regional hydroclimate shift in response to global climate change. Providing scientific insights that enable appropriate use of regional hydroclimate projections for planning is a non-trivial problem. The system of data, models, and methods used to produce regional hydroclimate projections is subject to multiple interacting uncertainties and biases, including uncertainties that arise from general circulation models, re-analysis data products, regional climate models, hydrologic models, and statistical downscaling methods. Moreover, many components of this system were not designed with the information needs of water managers in mind. To address this problem and provide actionable insights into the sources of uncertainty present in regional hydroclimate data products, Project Hyperion has undertaken a stakeholder engagement process in four case study water basins across the US. Teams of water managers and scientists are interacting in a structured manner to identify decision-relevant metrics of model performance. These metrics are in turn being used to drive scientific investigations to uncover the sources of uncertainty in these quantities. Thus far, we have found that identification of climate phenomena of interest to stakeholders is relatively easy, but translating these into specific quantifiable metrics and prioritizing metrics is more challenging. Iterative feedback among scientists and stakeholders has proven critical in resolving these challenges, as has the roles played by boundary spanners who understand and can speak to the perspectives of multiple professional communities. Here we describe the structured format of our engagement process and the lessons learned so far, as we aim to improve the decision-relevance of hydroclimate projections through a collaborative process.

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.

PAVICS: A platform for the Analysis and Visualization of Climate Science - adopting a workflow-based analysis method for dealing with a multitude of climate data sources

NASA Astrophysics Data System (ADS)

Gauvin St-Denis, B.; Landry, T.; Huard, D. B.; Byrns, D.; Chaumont, D.; Foucher, S.

2017-12-01

As the number of scientific studies and policy decisions requiring tailored climate information continues to increase, the demand for support from climate service centers to provide the latest information in the format most helpful for the end-user is also on the rise. Ouranos, being one such organization based in Montreal, has partnered with the Centre de recherche informatique de Montreal (CRIM) to develop a platform that will offer climate data products that have been identified as most useful for users through years of consultation. The platform is built as modular components that target the various requirements of climate data analysis. The data components host and catalog NetCDF data as well as geographical and political delimitations. The analysis components are made available as atomic operations through Web Processing Service (WPS) or as workflows, whereby the operations are chained through a simple JSON structure and executed on a distributed network of computing resources. The visualization components range from Web Map Service (WMS) to a complete frontend for searching the data, launching workflows and interacting with maps of the results. Each component can easily be deployed and executed as an independent service through the use of Docker technology and a proxy is available to regulate user workspaces and access permissions. PAVICS includes various components from birdhouse, a collection of WPS initially developed by the German Climate Research Center (DKRZ) and Institut Pierre Simon Laplace (IPSL) and is designed to be highly interoperable with other WPS as well as many Open Geospatial Consortium (OGC) standards. Further connectivity is made with the Earth System Grid Federation (ESGF) nodes and local results are made searchable using the same API terminology. Other projects conducted by CRIM that integrate with PAVICS include the OGC Testbed 13 Innovation Program (IP) initiative that will enhance advanced cloud capabilities, application packaging deployment processes, as well as enabling Earth Observation (EO) processes relevant to climate. As part of its experimental agenda, working implementations of scalable machine learning on big climate data with Spark and SciSpark were delivered.

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

Treesearch

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

2013-01-01

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

Traditional climate knowledge: a case study in a peasant community of Tlaxcala, Mexico.

PubMed

Rivero-Romero, Alexis D; Moreno-Calles, Ana I; Casas, Alejandro; Castillo, Alicia; Camou-Guerrero, Andrés

2016-08-18

Traditional climate knowledge is a comprehensive system of insights, experiences and practices used by peasant communities to deal with the uncertainties of climate conditions affecting their livelihood. This knowledge is today as relevant in the Mesoamerican and Andean regions as it is in Europe and Asia. Our research sought to analyze the traditional knowledge about the weather and climate in a rural village of the state of Tlaxcala, Mexico, and its importance in decision-making in agriculture. Through 30 interviews and participant observation in the community during 2013, information was gathered about traditional climate and weather indicators and prediction tools, as well as rituals and agronomic and agroforestry strategies. This information allowed for the reconstruction of the community's agro-festive calendar. Data analysis was carried out with the help of the qualitative analysis software Atlas.ti (version 7). The socio-ecological importance of traditional knowledge about the climate lies in its ability to forecast local weather conditions and recognize climate variations, so vital to the food security of rural families. Knowledge about climate predictors is exchanged and passed on from generation to generation, contributing to the preservation and promotion of biodiversity. By observing the behavior of 16 animals and 12 plant species (both domestic and wild) as well as seven astronomical indicators, villagers are able to predict rain, dry weather and frosts. However, the continuity of this traditional knowledge in the community under study is now compromised by the little interest in agriculture characteristic of the younger generations, the ensuing abandonment of the countryside, the widespread economic crisis and the disappearance of animal and plant species. Traditional climate knowledge includes the understanding of weather events and weather changes at different time scales (hours, days, weeks, and seasons). The ability to interpret weather events thanks to the accumulated knowledge about the climate through generations may prove today a relevant tool for improving agricultural practices and dealing with local and global socio-ecological changes.

Examining the Effects of Stress and Campus Climate on the Persistence of Students of Color and White Students: An Application of Bean and Eaton's Psychological Model of Retention

ERIC Educational Resources Information Center

Johnson, Dawn R.; Wasserman, Timothy H.; Yildirim, Nilay; Yonai, Barbara A.

2014-01-01

The current study examined the effects of stress and campus climate perceptions on the persistence decisions of students of color and White students using Bean and Eaton's (2000) Psychological Model of College Student Retention. A sample of first-year students (N = 1,491) at a predominantly White research university were survey enduring their…

Application of a hybrid association rules/decision tree model for drought monitoring

NASA Astrophysics Data System (ADS)

Nourani, Vahid; Molajou, Amir

2017-12-01

The previous researches have shown that the incorporation of the oceanic-atmospheric climate phenomena such as Sea Surface Temperature (SST) into hydro-climatic models could provide important predictive information about hydro-climatic variability. In this paper, the hybrid application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between drought of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend SSTs of the Black, Mediterranean and Red Seas. Two major steps of the proposed model were the classification of de-trend SST data and selecting the most effective groups and extracting hidden information involved in the data. The techniques of decision tree which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and Heidke Skill Score (HSS) measures were calculated and compared for different considering lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast drought and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and drought of Tabriz and Kermanshah synoptic stations so that the confidence between the monthly Standardized Precipitation Index (SPI) values and the de-trend SST of seas is higher than 70 and 80% respectively for Tabriz and Kermanshah synoptic stations.

Experimental climate information services in support of risk management

NASA Astrophysics Data System (ADS)

Webb, R. S.; Pulwarty, R. S.; Davidson, M. A.; Shea, E. E.; Nierenberg, C.; Dole, R. M.

2009-12-01

Climate variability and change impact national and local economies and environments. Developing and communicating climate and climate impacts information to inform decision making requires an understanding of context, societal objectives, and identification of factors important to the management of risk. Information sensitive to changing baselines or extremes is a critical emergent need. Meeting this need requires timely production and delivery of useful climate data, information and knowledge within familiar pathways. We identify key attributes for a climate service , and the network and infrastructure to develop and coordinate the resulting services based on lessons learned in experimental implementations of climate services. "Service-type" activities already exist in many settings within federal, state, academic, and private sectors. The challenge for a climate service is to find effective implementation strategies for improving decision quality (not just meeting user needs). These strategies include upfront infrastructure investments, learning from event to event, coordinated innovation and diffusion, and highlighting common adaptation interests. Common to these strategies is the production of reliable and accessible data, analyses of emergent conditions and needs, and deliberative processes to identify appropriate entry points and uses for improved knowledge. Experimental climate services show that the development of well-structured paths among observations, projections, risk assessments and usable information requires sustained participation in “knowledge management systems” for early warning across temporal and spatial scales. Central to these systems is a collaborative framework between research and management to ensure anticipatory coordination between decision makers and information providers, allowing for emerging research findings and their attendant uncertainties to be considered. Early warnings in this context are not simply forecasts or predictions but information on potential “futures” derived from past records, expert judgments, scenarios, and availability of mechanisms and capacity to use such information. Effective experimental climate services facilitate ongoing appraisals of knowledge needs for informing adaptation and mitigation options across sectors and across scenarios of near and longer-term future climates. Analyses show that climate service experiments drawing on data, applied research and prototyping functions of activities such as RISAs and RCCs are critical to developing the learning needed to inform and structure the flow of knowledge and understanding from problem definition and applications research to information delivery, use and evaluation. These activities effectively serve to inform services implementation when overarching cross-agency coordination, knowledge management, and innovation diffusion mechanisms such as afforded by NIDIS and the Coastal Services Center are engaged. We also demonstrate the importance of positioning climate research to engage and inform the decision-making process as society anticipates and responds to climate and its impacts.

State-and-transition models: Conceptual versus simulation perspectives, usefulness and breadth of use, and land management applications

USGS Publications Warehouse

Provencher, Louis; Frid, Leonardo; Czembor, Christina; Morisette, Jeffrey T.

2016-01-01

State-and-Transition Simulation Modeling (STSM) is a quantitative analysis method that can consolidate a wide array of resource management issues under a “what-if” scenario exercise. STSM can be seen as an ensemble of models, such as climate models, ecological models, and economic models that incorporate human dimensions and management options. This chapter presents STSM as a tool to help synthesize information on social–ecological systems and to investigate some of the management issues associated with exotic annual Bromus species, which have been described elsewhere in this book. Definitions, terminology, and perspectives on conceptual and computer-simulated stochastic state-and-transition models are given first, followed by a brief review of past STSM studies relevant to the management of Bromus species. A detailed case study illustrates the usefulness of STSM for land management. As a whole, this chapter is intended to demonstrate how STSM can help both managers and scientists: (a) determine efficient resource allocation for monitoring nonnative grasses; (b) evaluate sources of uncertainty in model simulation results involving expert opinion, and their consequences for management decisions; and (c) provide insight into the consequences of predicted local climate change effects on ecological systems invaded by exotic annual Bromus species.

Computer Applications in Science Education. The Illinois Series on Educational Application of Computers, No. 17e.

ERIC Educational Resources Information Center

Gaede, Owen F.; Singletary, Ted J.

This paper provides a summary of information and ideas relevant to the use of computers in science education, describes a variety of uses and strategies, discusses advantages and disadvantages of specific applications, and explores the decision-making process surrounding computer instruction implementation. Uses and strategies which are described…

Assessing and Synthesizing the Last Decade of Research on the Major Pools and Fluxes of the Carbon Cycle in the US and North America: An Interagency Governmental Perspective

NASA Astrophysics Data System (ADS)

Cavallaro, N.; Shrestha, G.; Stover, D. B.; Zhu, Z.; Ombres, E. H.; Deangelo, B.

2015-12-01

The 2nd State of the Carbon Cycle Report (SOCCR-2) is focused on US and North American carbon stocks and fluxes in managed and unmanaged systems, including relevant carbon management science perspectives and tools for supporting and informing decisions. SOCCR-2 is inspired by the US Carbon Cycle Science Plan (2011) which emphasizes global scale research on long-lived, carbon-based greenhouse gases, carbon dioxide and methane, and the major pools and fluxes of the global carbon cycle. Accordingly, the questions framing the Plan inform this report's topical roadmap, with a focus on US and North America in the global context: 1) How have natural processes and human actions affected the global carbon cycle on land, in the atmosphere, in the oceans and in the ecosystem interfaces (e.g. coastal, wetlands, urban-rural)? 2) How have socio-economic trends affected the levels of the primary carbon-containing gases, carbon dioxide and methane, in the atmosphere? 3) How have species, ecosystems, natural resources and human systems been impacted by increasing greenhouse gas concentrations, the associated changes in climate, and by carbon management decisions and practices? To address these aspects, SOCCR-2 will encompass the following broad assessment framework: 1) Carbon Cycle at Scales (Global Perspective, North American Perspective, US Perspective, Regional Perspective); 2) Role of carbon in systems (Soils; Water, Oceans, Vegetation; Terrestrial-aquatic Interfaces); 3) Interactions/Disturbance/Impacts from/on the carbon cycle. 4) Carbon Management Science Perspective and Decision Support (measurements, observations and monitoring for research and policy relevant decision-support etc.). In this presentation, the Carbon Cycle Interagency Working Group and the U.S. Global Change Research Program's U.S. Carbon Cycle Science Program Office will highlight the scientific context, strategy, structure, team and production process of the report, which is part of the USGCRP's Sustained National Climate Assessment process.

Assessing the influence of knowledge translation platforms on health system policy processes to achieve the health millennium development goals in Cameroon and Uganda: a comparative case study.

PubMed

Ongolo-Zogo, Pierre; Lavis, John N; Tomson, Goran; Sewankambo, Nelson K

2018-05-01

There is a scarcity of empirical data on the influence of initiatives supporting evidence-informed health system policy-making (EIHSP), such as the knowledge translation platforms (KTPs) operating in Africa. To assess whether and how two KTPs housed in government-affiliated institutions in Cameroon and Uganda have influenced: (1) health system policy-making processes and decisions aiming at supporting achievement of the health millennium development goals (MDGs); and (2) the general climate for EIHSP. We conducted an embedded comparative case study of four policy processes in which Evidence Informed Policy Network (EVIPNet) Cameroon and Regional East African Community Health Policy Initiative (REACH-PI) Uganda were involved between 2009 and 2011. We combined a documentary review and semi structured interviews of 54 stakeholders. A framework-guided thematic analysis, inspired by scholarship in health policy analysis and knowledge utilization was used. EVIPNet Cameroon and REACH-PI Uganda have had direct influence on health system policy decisions. The coproduction of evidence briefs combined with tacit knowledge gathered during inclusive evidence-informed stakeholder dialogues helped to reframe health system problems, unveil sources of conflicts, open grounds for consensus and align viable and affordable options for achieving the health MDGs thus leading to decisions. New policy issue networks have emerged. The KTPs indirectly influenced health policy processes by changing how interests interact with one another and by introducing safe-harbour deliberations and intersected with contextual ideational factors by improving access to policy-relevant evidence. KTPs were perceived as change agents with positive impact on the understanding, acceptance and adoption of EIHSP because of their complementary work in relation to capacity building, rapid evidence syntheses and clearinghouse of policy-relevant evidence. This embedded case study illustrates how two KTPs influenced policy decisions through pathways involving policy issue networks, interest groups interaction and evidence-supported ideas and how they influenced the general climate for EIHSP.

Assessing the influence of knowledge translation platforms on health system policy processes to achieve the health millennium development goals in Cameroon and Uganda: a comparative case study

PubMed Central

Lavis, John N; Tomson, Goran; Sewankambo, Nelson K

2018-01-01

Abstract There is a scarcity of empirical data on the influence of initiatives supporting evidence-informed health system policy-making (EIHSP), such as the knowledge translation platforms (KTPs) operating in Africa. To assess whether and how two KTPs housed in government-affiliated institutions in Cameroon and Uganda have influenced: (1) health system policy-making processes and decisions aiming at supporting achievement of the health millennium development goals (MDGs); and (2) the general climate for EIHSP. We conducted an embedded comparative case study of four policy processes in which Evidence Informed Policy Network (EVIPNet) Cameroon and Regional East African Community Health Policy Initiative (REACH-PI) Uganda were involved between 2009 and 2011. We combined a documentary review and semi structured interviews of 54 stakeholders. A framework-guided thematic analysis, inspired by scholarship in health policy analysis and knowledge utilization was used. EVIPNet Cameroon and REACH-PI Uganda have had direct influence on health system policy decisions. The coproduction of evidence briefs combined with tacit knowledge gathered during inclusive evidence-informed stakeholder dialogues helped to reframe health system problems, unveil sources of conflicts, open grounds for consensus and align viable and affordable options for achieving the health MDGs thus leading to decisions. New policy issue networks have emerged. The KTPs indirectly influenced health policy processes by changing how interests interact with one another and by introducing safe-harbour deliberations and intersected with contextual ideational factors by improving access to policy-relevant evidence. KTPs were perceived as change agents with positive impact on the understanding, acceptance and adoption of EIHSP because of their complementary work in relation to capacity building, rapid evidence syntheses and clearinghouse of policy-relevant evidence. This embedded case study illustrates how two KTPs influenced policy decisions through pathways involving policy issue networks, interest groups interaction and evidence-supported ideas and how they influenced the general climate for EIHSP. PMID:29506146

Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

NASA Astrophysics Data System (ADS)

Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

2016-04-01

Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing agricultural water demand significantly affect downstream water availability. Water demand options demonstrate potential to improve environmental flow conditions and satisfy legal water supply requirements for downstream riparian states. On the other hand, currently planned large scale infrastructural projects demonstrate reduced value in certain scenarios, illustrating the impacts of lock-in effects of large scale infrastructure. From a methodological perspective, we find that while the stakeholder-driven approach revealed robust options in a resource-light manner and helped initiate much needed interaction amongst stakeholders, the modelling approach provides complementary quantitative information. The study reveals robust adaptation options for this important basin and provides a strong methodological basis for carrying out future studies that support adaptation decision making.

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

PubMed

Hopkins, Debbie

2015-03-01

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

INVENTORY AND ASSESSMENT OF CLIMATE SENSITIVE DECISIONS

EPA Science Inventory

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

New institutional mechanisms to bridge the information gap between climate science and public policy decisions

NASA Astrophysics Data System (ADS)

Rogers, W.; Gulledge, J. M.

2010-12-01

Many decision makers lack actionable scientific information needed to prepare for future challenges associated with climate change. Although the scope and quality of available scientific information has increased dramatically in recent years, this information does not always reach - or is not presented in a form that is useful to - decision makers who need it. The producer (i.e. scientists) community tends to be stovepiped, even though consumers (i.e. decision makers) often need interdisciplinary science and analysis. Consumers, who may also be stovepiped in various agencies or subject areas, may lack familiarity with or access to these separate communities, as well as the tools or time to navigate scientific information and disciplines. Closing the communication gap between these communities could be facilitated by institutionalizing processes designed for this purpose. We recommend a variety of mainstreaming policies within the consumer community, as well as mechanisms to generate a strong demand signal that will resonate more strongly with the producer community. We also recommend institutional reforms and methods of incentivizing policy-oriented scientific analysis within the producer community. Our recommendations focus on improving information flow to national security and foreign policy decision makers, but many are relevant to public policy writ large. Recommendations for Producers 1. The scientific community should formally encourage collaborations between natural and social scientists and reward publications in interdisciplinary outlets Incentives could include research funding and honorary awards recognizing service to public policy. 2. Academic merit review should reward research grants and publications targeted at interdisciplinary and/or policy-oriented audiences. Reforms of merit review may require new policies and engaged institutional leadership. Recommendations for Consumers 1. Congress should amend Title VI of the National Defense Education Act to encourage the development of multidisciplinary educational programs on the national security implications of climate change. 2. Federal agencies should establish funding programs to encourage producers to provide scientific information tailored to consumer needs. 3. The Department of State should appoint climate advisors to serve within the regional bureaus and on the policy and planning staff. 4. Federal agencies, the Department of Education, and the National Science Foundation should develop programs to stimulate new interdisciplinary research partnerships and training of a new generation of interdisciplinary climate change risk thinkers, assessors and managers. 5. Federal agencies should encourage Senior Executive Service decision makers to participate in science policy certi¬fication workshops and include science and technology policy as a core curricu¬lum component of the SES Federal Candidate Development Program. These recommendations are described in detail in a report published by the Center for a New American Security: Rogers, W. and J. Gulledge (2010) Lost in Translation: Closing the Gap Between Climate Science and National Security Policy (available online: http://cnas.org/node/4391)

The Urban Climate Change Research Network (UCCRN) Second Assessment Report on Climate Change and Cities (ARC3-2), and the UCCRN Hubs

NASA Astrophysics Data System (ADS)

Rosenzweig, C.; Ali Ibrahim, S.

2015-12-01

The objective of this session is to foster a dialogue between experts working on global-scale, climate change and cities assessments in order to simultaneously present state-of-the-art knowledge on how cities are responding to climate change and to define emerging opportunities and challenges to the effective placement of this knowledge in the hands of local stakeholders and decision-makers. We will present the UCCRN and the Second UCCRN Assessment Report on Climate Change and Cities (ARC3-2), the second in an ongoing series of global, interdisciplinary, cross-regional, science-based assessments to address climate risks, adaptation, mitigation, and policy mechanisms relevant to cities. This is an especially important time to examine these issues. Cities continue to act as world leaders in climate action. Several major climate change assessment efforts are in full swing, at a crucial stage where significant opportunities for the co-production of knowledge between researchers and stakeholders exist. The IPCC AR5 Working Group II and III Reports have placed unprecedented attention on cities and urbanization and their connection to the issue of climate change. Concurrently several major, explicitly city-focused efforts have emerged from the Urban Climate Change Research Network (UCCRN), ICLEI, the Durban Adaptation Charter (DAC), C40, Future Earth, and the Urbanization and Global Environmental Change (UGEC) Project, among others. The underlying rationale for the discussion will be to identify methods and approaches to further foster the development and dissemination of new climate change knowledge and information that will be useful for cities, especially in small and medium-sized cities and in the developing country context where the demand is particularly acute. Participants will leave this session with: · The latest scientific data and state-of-the-knowledge on how cities are responding to climate change · Emerging opportunities and challenges to the effective placement of this knowledge in the hands of local stakeholders and decision-makers and for urban resilience and adaptation action · How practitioner-scientist interactions can work best · Synergies between the IPCC, ARC3, and other climate and cities assessments

Bridging the Gap between Climate Research and Policy

NASA Astrophysics Data System (ADS)

Weiss, M.; Lambert, K. F.; Buonocore, J.; Driscoll, C. T.

2016-12-01

The weak link between science and policy jeopardizes the wellbeing of people and the planet. Climate change is a pressing example of this disconnect. Policies are not keeping pace with the best of our knowledge from climate change research. We are working to bridge the science-policy divide and advance climate solutions by focusing on the positive health, ecosystem, and economic benefits of policy action. In 2013, we brought together an interdisciplinary team to estimate the co-benefits of U.S. power plant carbon standards for air quality and health, plus the economic value of the benefits. The results demonstrate that strong carbon standards with flexible compliance options can change the power sector, yielding substantial air quality and health benefits nationwide. The results also show that the economic value of these benefits outweighs the costs nationally and regionally. We advanced the policy applications of this research through a strategic campaign with three key elements: media communication, targeted outreach, and information for policymakers. Our strategy was to build widespread awareness of the research outcomes via media engagement, amplify our message via targeted outreach to citizens groups, and inform policy solutions by sharing research results with decision makers. The research was reported in more than 600 unique news stories in mainstream media outlets and received social media posts by members of Congress and senior White House officials. We amplified the messages via 14 webinars for citizens groups. We also held 16 briefings for policymakers and the public, in addition to meetings with relevant policy staff. Regional, state and federal policy leaders have used the research to understand air quality and health benefits of power plant carbon standards. This model of pairing research with media communication, targeted outreach, and information for policymakers is effective for bridging the gap between climate research and policy, and can be applied to other climate research projects.

Applying Cases to Solve Ethical Problems: The Significance of Positive and Process-Oriented Reflection

PubMed Central

Antes, Alison L.; Thiel, Chase E.; Martin, Laura E.; Stenmark, Cheryl K.; Connelly, Shane; Devenport, Lynn D.; Mumford, Michael D.

2015-01-01

This study examined the role of reflection on personal cases for making ethical decisions with regard to new ethical problems. Participants assumed the position of a business manager in a hypothetical organization and solved ethical problems that might be encountered. Prior to making a decision for the business problems, participants reflected on a relevant ethical experience. The findings revealed that application of material garnered from reflection on a personal experience was associated with decisions of higher ethicality. However, whether the case was viewed as positive or negative, and whether the outcomes, process, or outcomes and processes embedded in the experience were examined, influenced the application of case material to the new problem. As expected, examining positive experiences and the processes involved in those positive experiences resulted in greater application of case material to new problems. Future directions and implications for understanding ethical decision-making are discussed. PMID:26257506

Clinical cognition and diagnostic error: applications of a dual process model of reasoning.

PubMed

Croskerry, Pat

2009-09-01

Both systemic and individual factors contribute to missed or delayed diagnoses. Among the multiple factors that impact clinical performance of the individual, the caliber of cognition is perhaps the most relevant and deserves our attention and understanding. In the last few decades, cognitive psychologists have gained substantial insights into the processes that underlie cognition, and a new, universal model of reasoning and decision making has emerged, Dual Process Theory. The theory has immediate application to medical decision making and provides an overall schema for understanding the variety of theoretical approaches that have been taken in the past. The model has important practical applications for decision making across the multiple domains of healthcare, and may be used as a template for teaching decision theory, as well as a platform for future research. Importantly, specific operating characteristics of the model explain how diagnostic failure occurs.

CIRUN: Climate Information Responding to User Needs

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2009-12-01

The Earth System will experience real climate change over the next 50 years, exceeding the scope of natural climate variability. A paramount question facing society is how to adapt to this certainty of climate variability and change. In response, OSTP and NOAA are considering how comprehensive climate services would best inform decisions about adaptation. Similarly, NASA is considering the optimal configuration of the next generation of Earth, environmental, and climate observations to be deployed over the coming 10-20 years. Moreover, much of the added-value information for specific climate-related decisions will be provided by private, academic and non-governmental organizations. In this context, over the past several years the University of Maryland has established the CIRUN (Climate Information: Responding to User Needs) initiative to identify the nature of national needs for climate information and services from a decision support perspective. To date, CIRUN has brought together decisionmakers in a number of sectors to help understand their perspectives on climate with the goal of improving the usefulness of climate information, observations and prediction products to specific user communities. CIRUN began with a major workshop in October 2007 that convened 430 participants in agriculture, parks and recreation, terrestrial ecosystems, insurance/investment, energy, national security, state/local/municipal, water, human health, commerce and manufacturing, transportation, and coastal/marine sectors. Plenary speakers such as Norman Augustine, R. James Woolsey, James Mahoney, and former Senator Joseph Tydings, breakout panel sessions, and participants provided input based on the following: - How would you characterize the exposure or vulnerability to climate variability or change impacting your organization? - Does climate variability and/or change currently factor into your organization's objectives or operations? - Are any of your existing plans being affected by climate or projections of climate change? - Is your organization developing a plan for adapting to climate change? - What are your needs for climate observations, predictions, and services? Please cite one or more specific examples when possible. - Do you currently have access to the climate information your organization needs? - What next steps are needed to assure effective use of climate services in your decision making? As a result, a dialogue with various user communities and a subsequent series of more sector specific workshops has been established regarding how significantly enhanced climate observations, data management, modeling, and predictions can provide valuable decision support for business and policy decisions. In particular, CIRUN has helped - To identify how users, stakeholders, and decision makers are influenced by climate on time scales from seasons to decades - To identify the needs and requirements of users, stakeholders, and decision makers for climate information, observations, predictions, and services from global to local scales - To identify what adaptation measures are being considered in the private and public sectors, and how this might result in new classes of information for decision support - To recommend principal elements of the path forward toward more effective use of climate services in decision making.

Climate Assessment for Army Enterprise Planning Fact Sheet

DTIC Science & Technology

2017-11-30

decision metric values that affect Army enterprise planning decisions . The payoff of this research improved planning processes for...portions of the processes . 1D. Approach The research approach identified and developed advanced decision metrics that quantified climate...fundamental physical and ecological processes to climate change for each of the decision metrics. Where there is significant interaction among

Learning the Rhythm of the Seasons in the Face of Global Change: Phenological Research in the 21st Century

NASA Technical Reports Server (NTRS)

Morisette, Jeffrey T.; Richardson, Andrew D.; Knapp, Alan K.; Fisher, Jeremy I.; Graham, Eric A.; Abatzoglou, John; Wilson, Bruce E.; Breshears, David D.; Hanebry, Geoffrey M.; Hanes, Jonathan M.;

Translating Extreme Precipitation Data from Climate Change Projections into Resilient Engineering Applications

NASA Astrophysics Data System (ADS)

Cook, L. M.; Samaras, C.; Anderson, C.

2016-12-01

Engineers generally use historical precipitation trends to inform assumptions and parameters for long-lived infrastructure designs. However, resilient design calls for the adjustment of current engineering practice to incorporate a range of future climate conditions that are likely to be different than the past. Despite the availability of future projections from downscaled climate models, there remains a considerable mismatch between climate model outputs and the inputs needed in the engineering community to incorporate climate resiliency. These factors include differences in temporal and spatial scales, model uncertainties, and a lack of criteria for selection of an ensemble of models. This research addresses the limitations to working with climate data by providing a framework for the use of publicly available downscaled climate projections to inform engineering resiliency. The framework consists of five steps: 1) selecting the data source based on the engineering application, 2) extracting the data at a specific location, 3) validating for performance against observed data, 4) post-processing for bias or scale, and 5) selecting the ensemble and calculating statistics. The framework is illustrated with an example application to extreme precipitation-frequency statistics, the 25-year daily precipitation depth, using four publically available climate data sources: NARCCAP, USGS, Reclamation, and MACA. The attached figure presents the results for step 5 from the framework, analyzing how the 24H25Y depth changes when the model ensemble is culled based on model performance against observed data, for both post-processing techniques: bias-correction and change factor. Culling the model ensemble increases both the mean and median values for all data sources, and reduces range for NARCCAP and MACA ensembles due to elimination of poorer performing models, and in some cases, those that predict a decrease in future 24H25Y precipitation volumes. This result is especially relevant to engineers who wish to reduce the range of the ensemble and remove contradicting models; however, this result is not generalizable for all cases. Finally, this research highlights the need for the formation of an intermediate entity that is able to translate climate projections into relevant engineering information.

Institutionalizing telemedicine applications: the challenge of legitimizing decision-making.

PubMed

Zanaboni, Paolo; Lettieri, Emanuele

2011-09-28

During the last decades a variety of telemedicine applications have been trialed worldwide. However, telemedicine is still an example of major potential benefits that have not been fully attained. Health care regulators are still debating why institutionalizing telemedicine applications on a large scale has been so difficult and why health care professionals are often averse or indifferent to telemedicine applications, thus preventing them from becoming part of everyday clinical routines. We believe that the lack of consolidated procedures for supporting decision making by health care regulators is a major weakness. We aim to further the current debate on how to legitimize decision making about the institutionalization of telemedicine applications on a large scale. We discuss (1) three main requirements--rationality, fairness, and efficiency--that should underpin decision making so that the relevant stakeholders perceive them as being legitimate, and (2) the domains and criteria for comparing and assessing telemedicine applications--benefits and sustainability. According to these requirements and criteria, we illustrate a possible reference process for legitimate decision making about which telemedicine applications to implement on a large scale. This process adopts the health care regulators' perspective and is made up of 2 subsequent stages, in which a preliminary proposal and then a full proposal are reviewed.

Scalable methodology for large scale building energy improvement: Relevance of calibration in model-based retrofit analysis

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

Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane

2015-05-01

The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less

Bioclimatic Classification of Northeast Asia for climate change response

NASA Astrophysics Data System (ADS)

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

2016-12-01

As climate change has been getting worse, we should monitor the change of biodiversity, and distribution of species to handle the crisis and take advantage of climate change. The development of bioclimatic map which classifies land into homogenous zones by similar environment properties is the first step to establish a strategy. Statistically derived classifications of land provide useful spatial frameworks to support ecosystem research, monitoring and policy decisions. Many countries are trying to make this kind of map and actively utilize it to ecosystem conservation and management. However, the Northeast Asia including North Korea doesn't have detailed environmental information, and has not built environmental classification map. Therefore, this study presents a bioclimatic map of Northeast Asia based on statistical clustering of bioclimate data. Bioclim data ver1.4 which provided by WorldClim were considered for inclusion in a model. Eight of the most relevant climate variables were selected by correlation analysis, based on previous studies. Principal Components Analysis (PCA) was used to explain 86% of the variation into three independent dimensions, which were subsequently clustered using an ISODATA clustering. The bioclimatic zone of Northeast Asia could consist of 29, 35, and 50 zones. This bioclimatic map has a 30' resolution. To assess the accuracy, the correlation coefficient was calculated between the first principal component values of the classification variables and the vegetation index, Gross Primary Production (GPP). It shows about 0.5 Pearson correlation coefficient. This study constructed Northeast Asia bioclimatic map by statistical method with high resolution, but in order to better reflect the realities, the variety of climate variables should be considered. Also, further studies should do more quantitative and qualitative validation in various ways. Then, this could be used more effectively to support decision making on climate change adaptation.

Climate Change Impacts and Responses: Societal Indicators for the National Climate Assessment

NASA Technical Reports Server (NTRS)

Kenney, Melissa A.; Chen, Robert S.; Maldonado, Julie; Quattrochi, Dale

2011-01-01

The Climate Change Impacts and Responses: Societal Indicators for the National Climate Assessment workshop, sponsored by the National Aeronautics and Space Administration (NASA) for the National Climate Assessment (NCA), was held on April 28-29, 2011 at The Madison Hotel in Washington, DC. A group of 56 experts (see list in Appendix B) convened to share their experiences. Participants brought to bear a wide range of disciplinary expertise in the social and natural sciences, sector experience, and knowledge about developing and implementing indicators for a range of purposes. Participants included representatives from federal and state government, non-governmental organizations, tribes, universities, and communities. The purpose of the workshop was to assist the NCA in developing a strategic framework for climate-related physical, ecological, and socioeconomic indicators that can be easily communicated with the U.S. population and that will support monitoring, assessment, prediction, evaluation, and decision-making. The NCA indicators are envisioned as a relatively small number of policy-relevant integrated indicators designed to provide a consistent, objective, and transparent overview of major variations in climate impacts, vulnerabilities, adaptation, and mitigation activities across sectors, regions, and timeframes. The workshop participants were asked to provide input on a number of topics, including: (1) categories of societal indicators for the NCA; (2) alternative approaches to constructing indicators and the better approaches for NCA to consider; (3) specific requirements and criteria for implementing the indicators; and (4) sources of data for and creators of such indicators. Socioeconomic indicators could include demographic, cultural, behavioral, economic, public health, and policy components relevant to impacts, vulnerabilities, and adaptation to climate change as well as both proactive and reactive responses to climate change. Participants provided inputs through in-depth discussion in breakout sessions, plenary sessions on break-out results, and several panels that provided key insights about indicators, lessons learned through experience with developing and implementing indicators, and thoughts on how the NCA could proceed to develop indicators for the NCA.

Decision making in cancer primary prevention and chemoprevention.

PubMed

Gorin, Sherri Sheinfeld; Wang, Catharine; Raich, Peter; Bowen, Deborah J; Hay, Jennifer

2006-12-01

We know very little about how individuals decide to undertake, maintain, or discontinue cancer primary prevention or chemoprevention. The aims of this article are to (a) examine whether and, if so, how traditional health behavior change models are relevant for decision making in this area; (b) review the application of decision aids to forming specific, personal choices between options; and (c) identify the challenges of evaluating these decision processes to suggest areas for future research. Theoretical models and frameworks derived from the health behavior change and decision-making fields were applied to cancer primary prevention choices. Decision aids for the human papillomavirus (HPV) vaccine, Hormone Replacement Therapy (HRT), and tamoxifen were systematically examined. Traditional concepts such as decisional balance and cues to action are relevant to understanding cancer primary prevention choices; Motivational Interviewing, Self-Determination Theory, and the Preventive Health Model may also explain the facilitators of decision making. There are no well-tested HPV vaccine decision aids, although there have been some studies on aids for HPV testing. There are several effective decision aids for HRT and tamoxifen; evidence-based decision aid components have also been identified. Additional theory-based empirical research on decision making in cancer primary prevention and chemoprevention, particularly at the interface of psychology and behavioral economics, is suggested.

Developing Flexible, Integrated Hydrologic Modeling Systems for Multiscale Analysis in the Midwest and Great Lakes Region

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Chiu, C. M.; Sharma, A.; Byun, K.; Hanson, Z.

2016-12-01

Physically based hydrologic modeling of surface and groundwater resources that can be flexibly and efficiently applied to support water resources policy/planning/management decisions at a wide range of spatial and temporal scales are greatly needed in the Midwest, where stakeholder access to such tools is currently a fundamental barrier to basic climate change assessment and adaptation efforts, and also the co-production of useful products to support detailed decision making. Based on earlier pilot studies in the Pacific Northwest Region, we are currently assembling a suite of end-to-end tools and resources to support various kinds of water resources planning and management applications across the region. One of the key aspects of these integrated tools is that the user community can access gridded products at any point along the end-to-end chain of models, looking backwards in time about 100 years (1915-2015), and forwards in time about 85 years using CMIP5 climate model projections. The integrated model is composed of historical and projected future meteorological data based on station observations and statistical and dynamically downscaled climate model output respectively. These gridded meteorological data sets serve as forcing data for the macro-scale VIC hydrologic model implemented over the Midwest at 1/16 degree resolution. High-resolution climate model (4km WRF) output provides inputs for the analyses of urban impacts, hydrologic extremes, agricultural impacts, and impacts to the Great Lakes. Groundwater recharge estimated by the surface water model provides input data for fine-scale and macro-scale groundwater models needed for specific applications. To highlight the multi-scale use of the integrated models in support of co-production of scientific information for decision making, we briefly describe three current case studies addressing different spatial scales of analysis: 1) Effects of climate change on the water balance of the Great Lakes, 2) Future hydropower resources in the St. Joseph River basin, 3) Effects of climate change on carbon cycling in small lakes in the Northern Highland Lakes District.

Challenges for continuity of L-Band observations over land

USDA-ARS?s Scientific Manuscript database

Over land, L-band observations are primarily used for the detection of soil freeze/thaw events and the quantification of surface soil moisture content. Both products have important science, climate and decision support applications and would benefit from longer historical data records derived from s...

Spatially explicit watershed modeling: tracking water, mercury and nitrogen in multiple systems under diverse conditions

EPA Science Inventory

Environmental decision-making and the influences of various stressors, such as landscape and climate changes on water quantity and quality, requires the application of environmental modeling. Spatially explicit environmental and watershed-scale models using GIS as a base framewor...

Using Weather Types to Understand and Communicate Weather and Climate Impacts

NASA Astrophysics Data System (ADS)

Prein, A. F.; Hale, B.; Holland, G. J.; Bruyere, C. L.; Done, J.; Mearns, L.

2017-12-01

A common challenge in atmospheric research is the translation of scientific advancements and breakthroughs to decision relevant and actionable information. This challenge is central to the mission of NCAR's Capacity Center for Climate and Weather Extremes (C3WE, www.c3we.ucar.edu). C3WE advances our understanding of weather and climate impacts and integrates these advances with distributed information technology to create tools that promote a global culture of resilience to weather and climate extremes. Here we will present an interactive web-based tool that connects historic U.S. losses and fatalities from extreme weather and climate events to 12 large-scale weather types. Weather types are dominant weather situations such as winter high-pressure systems over the U.S. leading to very cold temperatures or summertime moist humid air masses over the central U.S. leading to severe thunderstorms. Each weather type has a specific fingerprint of economic losses and fatalities in a region that is quantified. Therefore, weather types enable a direct connection of observed or forecasted weather situation to loss of life and property. The presented tool allows the user to explore these connections, raise awareness of existing vulnerabilities, and build resilience to weather and climate extremes.

Improving Public Engagement With Climate Change: Five "Best Practice" Insights From Psychological Science.

PubMed

van der Linden, Sander; Maibach, Edward; Leiserowitz, Anthony

2015-11-01

Despite being one of the most important societal challenges of the 21st century, public engagement with climate change currently remains low in the United States. Mounting evidence from across the behavioral sciences has found that most people regard climate change as a nonurgent and psychologically distant risk-spatially, temporally, and socially-which has led to deferred public decision making about mitigation and adaptation responses. In this article, we advance five simple but important "best practice" insights from psychological science that can help governments improve public policymaking about climate change. Particularly, instead of a future, distant, global, nonpersonal, and analytical risk that is often framed as an overt loss for society, we argue that policymakers should (a) emphasize climate change as a present, local, and personal risk; (b) facilitate more affective and experiential engagement; (c) leverage relevant social group norms; (d) frame policy solutions in terms of what can be gained from immediate action; and (e) appeal to intrinsically valued long-term environmental goals and outcomes. With practical examples we illustrate how these key psychological principles can be applied to support societal engagement and climate change policymaking. © The Author(s) 2015.

Fostering Engagement Activities To Advance Adaptation And Resiliency

NASA Astrophysics Data System (ADS)

Dissen, J.; Owen, T.; Brewer, M.; Hollingshead, A.; Mecray, E. L.; Werner, K.

2015-12-01

As the understanding of climate risks grows for public and private companies, the dissemination of meaningful climate and environmental information becomes important for improved risk management practices and innovation. In a broader effort to build capacity for adaptation and demonstrate the value of investment in resiliency, NCEI and its partners have made several shifts to showcase an improved understanding of uses and applications of climate and environmental data and information. The NOAA NCEI engagement initiative includes actively exploring ways to: 1) identify opportunities in data use and applications and 2) characterize needs and requirements from customers to help inform investment in the relevant science. This presentation will highlight: 1) NCEI's engagement initiative strategy, 2) our regional and national partnerships as agents of engagement in the region, 3) a few examples of uses of climate information with select stakeholders and 4) justification of customer engagement and requirements as a critical component in informing the science agenda.

Informing Decisions with a Climate Synthesis Product: Implications for Regional Climate Services

NASA Astrophysics Data System (ADS)

Guido, Z.; Hill, D.; Crimmins, M.; Ferguson, D. B.

2012-12-01

The demand for regional climate information is increasing and spurring efforts to provide a broad slate of climate services that inform policy and resource management and elevate general knowledge. Routine syntheses of existing climate-related information may be an effective strategy for connecting climate information to decision making, but few studies have formally assessed their contribution to informing decisions. During the 2010-2011 winter, drought conditions expanded and intensified in Arizona and New Mexico, creating an opportunity to develop and evaluate a pithy, monthly regional climate communication product—La Niña Drought Tracker—that synthesized and interpreted drought and climate information. Six issues were published and subsequently evaluated through an online survey. On average, 417 people consulted the publication each month. Many of the survey respondents indicated that they made at least one drought-related decision, and the product at least moderately influenced the majority of those decisions, some of which helped mitigate economic losses and reduce climate vulnerability. The product also improved understanding of climate and drought for more than 90 percent of the respondents and helped the majority of them better prepare for drought. These, and other results demonstrate that routine interpretation and synthesis of existing climate information can help enhance access to and understanding and use of climate information in decision-making. Moreover, developing regional, contextual knowledge within climate service programs can facilitate the implementation of activities like the Tracker that enhance the use of climate information without engaging in time-consuming collaborative processes that can prevent the timely production of the services. We present results from the case study of the Tracker and place it within the context of the challenges and opportunities associated with providing climate services, particularly those services that require several-to-many months of work but often do not generate substantial financial sponsorship. These medium-term climate services, like the Tracker, present formidable challenges. However, we argue, they are vital to satisfying stakeholder demand, creating new and strengthening existing partnerships, aiding decisions, advancing climate literacy, and fostering future projects—main goals of climate services.

A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

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

Kupriyanov, M. S., E-mail: mikhail.kupriyanov@gmail.com; Shukeilo, E. Y., E-mail: eyshukeylo@gmail.com; Shichkina, J. A., E-mail: strange.y@mail.ru

2015-11-17

Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient’s health condition using data from a wearable device considers in this article.

A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

NASA Astrophysics Data System (ADS)

Kupriyanov, M. S.; Shukeilo, E. Y.; Shichkina, J. A.

2015-11-01

Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient's health condition using data from a wearable device considers in this article.

An integrated strategy of knowledge application for optimal e-health implementation: A multi-method study protocol

PubMed Central

Gagnon, Marie-Pierre; Légaré, France; Fortin, Jean-Paul; Lamothe, Lise; Labrecque, Michel; Duplantie, Julie

2008-01-01

Background E-health is increasingly valued for supporting: 1) access to quality health care services for all citizens; 2) information flow and exchange; 3) integrated health care services and 4) interprofessional collaboration. Nevertheless, several questions remain on the factors allowing an optimal integration of e-health in health care policies, organisations and practices. An evidence-based integrated strategy would maximise the efficacy and efficiency of e-health implementation. However, decisions regarding e-health applications are usually not evidence-based, which can lead to a sub-optimal use of these technologies. This study aims at understanding factors influencing the application of scientific knowledge for an optimal implementation of e-health in the health care system. Methods A three-year multi-method study is being conducted in the Province of Quebec (Canada). Decision-making at each decisional level (political, organisational and clinical) are analysed based on specific approaches. At the political level, critical incidents analysis is being used. This method will identify how decisions regarding the implementation of e-health could be influenced or not by scientific knowledge. Then, interviews with key-decision-makers will look at how knowledge was actually used to support their decisions, and what factors influenced its use. At the organisational level, e-health projects are being analysed as case studies in order to explore the use of scientific knowledge to support decision-making during the implementation of the technology. Interviews with promoters, managers and clinicians will be carried out in order to identify factors influencing the production and application of scientific knowledge. At the clinical level, questionnaires are being distributed to clinicians involved in e-health projects in order to analyse factors influencing knowledge application in their decision-making. Finally, a triangulation of the results will be done using mixed methodologies to allow a transversal analysis of the results at each of the decisional levels. Results This study will identify factors influencing the use of scientific evidence and other types of knowledge by decision-makers involved in planning, financing, implementing and evaluating e-health projects. Conclusion These results will be highly relevant to inform decision-makers who wish to optimise the implementation of e-health in the Quebec health care system. This study is extremely relevant given the context of major transformations in the health care system where e-health becomes a must. PMID:18435853

A National Program for Analysis of the Climate System

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Arkin, Phil; Kalnay, Eugenia; Laver, James; Trenberth, Kevin

2002-01-01

Perhaps the single greatest roadblock to fundamental advances in our understanding of climate variability and climate change is the lack of robust and unbiased long-term global observations of the climate system. Such observations are critical for the identification and diagnosis of climate variations, and provide the constraints necessary for developing and validating climate models. The first generation of reanalysis efforts, by using fixed analysis systems, eliminated the artificial climate signals that occurred in analyses generated at the operational numerical weather prediction centers. These datasets are now widely used by the scientific community in a variety of applications including atmosphere-ocean interactions, seasonal prediction, climate monitoring, the hydrological cycle, and a host of regional and other diagnostic studies. These reanalyses, however, had problems that made them sub-optimal or even unusable for some applications. Perhaps the most serious problem for climate applications was that, while the assimilation system remained fixed, changes in the observing systems did produce spurious changes in the perceived climate. The first generation reanalysis products also exposed problems with physical consistency of the products and the accurate representation of physical processes in the climate system. Examples are bias in the estimates of ocean surface fluxes, and inadequate representation of polar hydrology. In this talk, I will describe some initial plans for a national program on reananlysis. The program is envisioned to be part of an on-going activity to maintain, improve, and reprocess our record of climate observations. I will discuss various issues affecting the quality of reanalyses, with a special focus on those relevant to the ocean.

Climate modeling with decision makers in mind

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

Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

Climate modeling with decision makers in mind

DOE PAGES

Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

2016-04-27

The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

Developing a Climate Change Boundary Organization: the Montana Adaptation Exchange

NASA Astrophysics Data System (ADS)

Whitlock, C. L.; Brooks, S.; Armstrong, T.; Bryan, B.

2016-12-01

Small-population large-area states like Montana are often challenged by a need to offer timely and relevant climate-change information that addresses diverse and widely dispersed stakeholder groups. In Montana, filling the gap between science and various types of decision-makers has motivated development of the first Montana Climate Assessment (MCA1), to be released in 2017 with a focus on climate-change impacts for agricultural, water and forestry sectors. To sustain and build on the MCA1 effort, we are also in the process of creating a Boundary Organization (defined by the National Academy of Sciences) called the Montana Adaptation Exchange (the Exchange); this entity will facilitate the flow of information across the boundaries between science, knowledge and implementation. In Montana, the Exchange brings scientists and practitioners together to seek solutions related to climate-change adaptation and other pressing environmental and social-economic challenges. The Montana Adaptation Exchange (1) is a collaborative partnership of members from the science and practitioner communities under a shared governance and participatory model; (2) presents research that has been vetted by the scientific community at large and represents the current state of knowledge; (3) allows for revision and expansion of assessments like the MCA; (4) communicates relevant, often technical, research and findings to a wide variety of resource managers and other stakeholders; (5) develops and maintains an extensive online database that organizes, regularly updates, and makes research data products readily available; and (6) offers an online portal and expert network of affiliated researchers and climate adaptation specialists to provide effective customer support. Boundary organizations, such as the Montana Adaptation Exchange, offer a scalable path to effectively move from "science to knowledge to action" while also allowing stakeholder needs to help inform research agendas.

Long Term Monitoring of Atmospheric Composition at NOAA - Driving Science with 60 Year-old Records

NASA Astrophysics Data System (ADS)

Butler, J. H.

2017-12-01

NOAA's Global Monitoring Division and its precursor organizations have provided some of the longest real-time records of the trends and distributions of climatically relevant substances in the atmosphere, some going back for 60 years (http://www.esrl.noaa.gov/gmd). The focus of these measurements has been on obtaining reliable records of global trends and distributions of these substances, but the experimental design and use of measurements have advanced over time with evolving scientific questions. Today, and into this century, scientific questions continue to progress and the observing systems that address them will need to progress accordingly. Long-term, ground based observing systems in NOAA's Global Monitoring Division focus largely on three sets of questions, two of which align with WCRP grand challenges. These are Carbon Cycle System Feedbacks, Trends in Surface Radiation and Cloud Distributions, and Recovery of Stratospheric Ozone. The data collected and analyzed help us understand radiative forcing, climate sensitivity, air quality, climate modification, renewable energy options, and arctic processes, and they are useful for verifying model output and satellite retrievals. Regional information will become increasingly important for mitigating and adapting to climate change, and this information must be accurate, precise, and without bias. NOAA, with its long-standing networks and its role in providing calibrations for partnering organizations, is well positioned to provide the linkages necessary to assure that regional measurements are comparable. This presentation will identify major, climate-relevant findings that have come from NOAA's networks in the past and will address the long-term monitoring needs to support decision-making over coming decades as society begins to seriously address climate change.

Arctic Council Nations Could Encourage Development of Climate Indicator: Flux to the Atmosphere from Arctic Permafrost Carbon

NASA Astrophysics Data System (ADS)

Ekwurzel, B.; Yona, L.; Natali, S.; Holmes, R. M.; Schuur, E.

2015-12-01

Permafrost regions store almost twice the carbon in the atmosphere (Tarnocai et al 2009). As climate warms a proportion of this carbon will be released as carbon dioxide and methane. The Arctic Council may be best suited to harness international scientific collaboration for policy relevant knowledge about the global impacts of permafrost thaw. Scientists in Arctic Council and observer states have historically collaborated on permafrost research (e.g. Permafrost Carbon Network, part of Study of Environmental Arctic Change (SEARCH) project). This work increased knowledge of permafrost carbon pool size and vulnerability. However, data gaps persist across the Arctic. Despite gaps, numerous studies directly inform international policy negotiations aiming to stay below 2° C. Some suggest "permafrost carbon feedback" may comprise 3 to 11% of total allowed emissions through 2100 under a RCP4.5 (Schaefer et al2014). Understanding and accounting for future permafrost atmospheric carbon release requires science and policy coordination that the Arctic Council could incentivize. For example, Council nations could convene scientists and stakeholders to develop a Permafrost-Climate Indicator providing more direct decision support than current permafrost indicators, and identify research needed for a periodic estimate of Arctic permafrost CO2 and CH4 emissions. This presentation covers current challenges scientists and policymakers may face to develop a practical and robust Permafrost Climate Indicator. For example, which timescales are most appropriate for international emissions commitments? Do policy-relevant timescales align with current scientific knowledge? What are the uncertainties and how can they be decreased? We present likely strengths and challenges of a Permafrost Climate Indicator co-developed by scientists and stakeholders. Potential greenhouse gas atmospheric flux from Arctic permafrost carbon may be greater than some nations' United Nations emissions reductions commitments. Investing in better understanding greenhouse gas emissions from thawing permafrost is relevant for all nations and essential to setting global emission targets.

Adaptation policies to increase terrestrial ecosystem resilience. Potential utility of a multicriteria approach

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

de Bremond, Ariane; Engle, Nathan L.

2014-01-30

Climate change is rapidly undermining terrestrial ecosystem resilience and capacity to continue providing their services to the benefit of humanity and nature. Because of the importance of terrestrial ecosystems to human well-being and supporting services, decision makers throughout the world are busy creating policy responses that secure multiple development and conservation objectives- including that of supporting terrestrial ecosystem resilience in the context of climate change. This article aims to advance analyses on climate policy evaluation and planning in the area of terrestrial ecosystem resilience by discussing adaptation policy options within the ecology-economy-social nexus. The paper evaluates these decisions in themore » realm of terrestrial ecosystem resilience and evaluates the utility of a set of criteria, indicators, and assessment methods, proposed by a new conceptual multi-criteria framework for pro-development climate policy and planning developed by the United Nations Environment Programme. Potential applications of a multicriteria approach to climate policy vis-A -vis terrestrial ecosystems are then explored through two hypothetical case study examples. The paper closes with a brief discussion of the utility of the multi-criteria approach in the context of other climate policy evaluation approaches, considers lessons learned as a result efforts to evaluate climate policy in the realm of terrestrial ecosystems, and reiterates the role of ecosystem resilience in creating sound policies and actions that support the integration of climate change and development goals.« less

Institutionalizing Telemedicine Applications: The Challenge of Legitimizing Decision-Making

PubMed Central

Lettieri, Emanuele

2011-01-01

During the last decades a variety of telemedicine applications have been trialed worldwide. However, telemedicine is still an example of major potential benefits that have not been fully attained. Health care regulators are still debating why institutionalizing telemedicine applications on a large scale has been so difficult and why health care professionals are often averse or indifferent to telemedicine applications, thus preventing them from becoming part of everyday clinical routines. We believe that the lack of consolidated procedures for supporting decision making by health care regulators is a major weakness. We aim to further the current debate on how to legitimize decision making about the institutionalization of telemedicine applications on a large scale. We discuss (1) three main requirements— rationality, fairness, and efficiency—that should underpin decision making so that the relevant stakeholders perceive them as being legitimate, and (2) the domains and criteria for comparing and assessing telemedicine applications—benefits and sustainability. According to these requirements and criteria, we illustrate a possible reference process for legitimate decision making about which telemedicine applications to implement on a large scale. This process adopts the health care regulators’ perspective and is made up of 2 subsequent stages, in which a preliminary proposal and then a full proposal are reviewed. PMID:21955510

Climate Change and Water Working Group - User Needs to Manage Hydrclimatic Risk from Days to Decades

NASA Astrophysics Data System (ADS)

Raff, D. A.; Brekke, L. D.; Werner, K.; Wood, A.; White, K. D.

2012-12-01

The Federal Climate Change Water Working Group (CCAWWG) provides engineering and scientific collaborations in support of water management. CCAWWG objectives include building working relationships across federal science and water management agencies, provide a forum to share expertise and leverage resources, develop education and training forums, to work with water managers to understand scientific needs and to foster collaborative efforts across the Federal and non-Federal water management and science communities to address those needs. Identifying and addressing water management needs has been categorized across two major time scales: days to a decade and multi-decadal, respectively. These two time periods are termed "Short-Term" and "Long-Term" in terms of the types of water management decisions they support where Short-Term roughly correlates to water management operations and Long-Term roughly correlates to planning activities. This presentation will focus on portraying the identified water management user needs across these two time periods. User Needs for Long-Term planning were identified in the 2011 Reclamation and USACE "Addressing Climate Change in Long-Term Water Resources Planning and Management: User Needs for Improving Tools and Information." User needs for Long-Term planning are identified across eight major categories: Summarize Relevant Literature, Obtain Climate Change Information, Make Decisions About How to Use the Climate Change Information, Assess Natural Systems Response, Assess Socioeconomic and Institutional Response, Assess System Risks and Evaluate Alternatives, Assess and Characterize Uncertainties, and Communicating Results and Uncertainties to Decisionmakers. User Needs for Short-Term operations are focused on needs relative to available or desired monitoring and forecast products from the hydroclimatic community. These needs are presenting in the 2012 USACE, Reclamation, and NOAA - NWS "Short-Term Water Management Decisions: User Needs for Improved Climate, Weather, and Hydrologic Information." Identified needs are presented in four categories: Monitoring, Forecasting, Understanding on Product Relationships and Utilization in Water Management, and Information Services Enterprise. These needs represent everything from continuation and enhancement of in situ monitoring products such as USGS water gages and precipitation networks to supporting product maintenance and evolution to accommodate newly developed technologies.

Overview of Climate Confluence Security Issues

NASA Astrophysics Data System (ADS)

Reisman, J. P.

2011-12-01

Presentation will focus on an overview of the security perspectives based on the confluence considerations including energy, economics and climate change. This will include perspectives from reports generated by the Quadrennial Defense Review, Joint Forces Command, the Center for Strategic International Studies, MIT, the Inter-agency Climate Change Adaptation Task Force, the Central Intelligence Agency, the Center for Naval Analysis, and other relevant reports. The presentation will highlight the connections between resource issues and climate change which can be interpreted into security concerns. General discussion of global issues, contextual review of AR4 WGII may be included and any other report updates as applicable. The purpose of this presentation is to give a rounded view of the general qualitative and quantitative perspectives regarding climate related security considerations.

Relevance of methods and standards for the assessment of measurement system performance in a High-Value Manufacturing Industry

NASA Astrophysics Data System (ADS)

Loftus, Pete; Giudice, Seb

2014-08-01

Measurements underpin the engineering decisions that allow products to be designed, manufactured, operated, and maintained. Therefore, the quality of measured data needs to be systematically assured to allow decision makers to proceed with confidence. The use of standards is one way of achieving this. This paper explores the relevance of international documentary standards to the assessment of measurement system capability in High Value Manufacturing (HVM) Industry. An internal measurement standard is presented which supplements these standards and recommendations are made for a cohesive effort to develop the international standards to provide consistency in such industrial applications.

Communicating Uncertainty about Climate Change for Application to Security Risk Management

NASA Astrophysics Data System (ADS)

Gulledge, J. M.

2011-12-01

The science of climate change has convincingly demonstrated that human activities, including the release of greenhouse gases, land-surface changes, particle emissions, and redistribution of water, are changing global and regional climates. Consequently, key institutions are now concerned about the potential social impacts of climate change. For example, the 2010 Quadrennial Defense Review Report from the U.S. Department of Defense states that "climate change, energy security, and economic stability are inextricably linked." Meanwhile, insured losses from climate and weather-related natural disasters have risen dramatically over the past thirty years. Although these losses stem largely from socioeconomic trends, insurers are concerned that climate change could exacerbate this trend and render certain types of climate risk non-diversifiable. Meanwhile, the climate science community-broadly defined as physical, biological, and social scientists focused on some aspect of climate change-remains largely focused scholarly activities that are valued in the academy but not especially useful to decision makers. On the other hand, climate scientists who engage in policy discussions have generally permitted vested interests who support or oppose climate policies to frame the discussion of climate science within the policy arena. Such discussions focus on whether scientific uncertainties are sufficiently resolved to justify policy and the vested interests overstate or understate key uncertainties to support their own agendas. Consequently, the scientific community has become absorbed defending scientific findings to the near exclusion of developing novel tools to aid in risk-based decision-making. For example, the Intergovernmental Panel on Climate Change (IPCC), established expressly for the purpose of informing governments, has largely been engaged in attempts to reduce unavoidable uncertainties rather than helping the world's governments define a science-based risk-management framework for climate security. The IPCC's Fourth Assessment Report concluded that "Responding to climate change involves an iterative risk management process that includes both adaptation and mitigation and takes into account climate change damages, co-benefits, sustainability, equity and attitudes to risk." In risk management, key uncertainties guide action aimed at reducing risk and cannot be ignored or used to justify inaction. Security policies such as arms control and counter-terrorism demonstrate that high-impact outcomes matter to decision makers even if they are likely to be rare events. In spite of this fact, the long tail on the probability distribution of climate sensitivity was largely ignored by the climate science community until recently and its implications for decision making are still not receiving adequate attention. Informing risk management requires scientists to shift from a singular aversion to type I statistical error (i.e. false positive) to a balanced presentation of both type I error and type II error (i.e. false negative) when the latter may have serious consequences. Examples from national security, extreme weather, and economics illustrate these concepts.

Impacts of Landuse Management and Climate Change on Landslides Susceptibility over the Olympic Peninsula of Washington State

NASA Astrophysics Data System (ADS)

Barik, M. G.; Adam, J. C.

2009-12-01

The commercial forests on the western side of the Olympic Mountains in Washington State are a region of steep slopes and high annual rainfall (2500-6000 mm/year) and are therefore highly susceptible to landslides. Potential climatic change (more intense and frequent winter storms) may exacerbate landslide susceptibility unless forest management practices are changed. As this area is a critical habitat for numerous organisms, including salmon, this may result in potentially severe consequences to riparian habitat due to increased sediment loads. Therefore, there is a need to investigate potential forest management plans to promote the economic viability of timber extraction while protecting the natural habitat, particularly in riparian areas. The objective of this study is to predict the long term effects of forest management decisions under projected climate change on slope stability. We applied the physically-based Distributed Hydrology Soil Vegetation Model (DHSVM) with its sediment module to simulate mass wasting and sediment delivery under different vegetation and climate scenarios. Sub-basins were selected and classified according to elevation, slope, land cover and soil type. Various land management practices (such as clear-cutting in riparian areas, logging under short rotations, varying amount of timbers left intact in riparian areas) were applied to each of the selected sub-basins. DHSVM was used to simulate landslide volume, frequency, and sediment loads for each of the land cover applications under various future climate scenarios. We comment on the suitability of various harvesting techniques for different parts of the forest to minimize landslide-induced sediment loading to streams in an altered climate. This approach can be developed as a decision making tool that can be used by forest managers to make long-term planning decisions.

Uses and Applications of Climate Forecasts for Power Utilities.

NASA Astrophysics Data System (ADS)

Changnon, Stanley A.; Changnon, Joyce M.; Changnon, David

1995-05-01

The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-depth structured interviews were conducted with 56 decision makers in six utilities to assess existing and potential uses of climate forecasts. Only 3 of the 56 use forecasts. Eighty percent of those sampled envisioned applications of climate forecasts, given certain changes and additional information. Primary applications exist in power trading, load forecasting, fuel acquisition, and systems planning, with slight differences in interests between utilities. Utility staff understand probability-based forecasts but desire climatological information related to forecasted outcomes, including analogs similar to the forecasts, and explanations of the forecasts. Desired lead times vary from a week to three months, along with forecasts of up to four seasons ahead. The new NOAA forecasts initiated in 1995 provide the lead times and longer-term forecasts desired. Major hindrances to use of forecasts are hard-to-understand formats, lack of corporate acceptance, and lack of access to expertise. Recent changes in government regulations altered the utility industry, leading to a more competitive world wherein information about future weather conditions assumes much more value. Outreach efforts by government forecast agencies appear valuable to help achieve the appropriate and enhanced use of climate forecasts by the utility industry. An opportunity for service exists also for the private weather sector.

Addressing Climate Change in Long-Term Water Planning Using Robust Decisionmaking

NASA Astrophysics Data System (ADS)

Groves, D. G.; Lempert, R.

2008-12-01

Addressing climate change in long-term natural resource planning is difficult because future management conditions are deeply uncertain and the range of possible adaptation options are so extensive. These conditions pose challenges to standard optimization decision-support techniques. This talk will describe a methodology called Robust Decisionmaking (RDM) that can complement more traditional analytic approaches by utilizing screening-level water management models to evaluate large numbers of strategies against a wide range of plausible future scenarios. The presentation will describe a recent application of the methodology to evaluate climate adaptation strategies for the Inland Empire Utilities Agency in Southern California. This project found that RDM can provide a useful way for addressing climate change uncertainty and identify robust adaptation strategies.

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

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Solecki, William

1999-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2000-09-01

It has been estimated that severe El Niño-related flooding and droughts in Africa, Latin America, North America, and Southeast Asia resulted in more than 22 000 lives lost and in excess of $36 billion in damages during 1997-98. As one of the most severe events this century, the 1997-98 El Niño was unique not only in terms of physical magnitude, but also in terms of human response. This response was made possible by recent advances in climate-observing and forecasting systems, creation and dissemination of forecast information by institutions such as the International Research Institute for Climate Prediction and NOAA's Climate Prediction Center, and individuals in climate-sensitive sectors willing to act on forecast information by incorporating it into their decision-making. The supporting link between the forecasts and their practical application was a product of efforts by several national and international organizations, and a primary focus of the United States National Oceanic and Atmospheric Administration Office of Global Programs (NOAA/OGP).NOAA/OGP over the last decade has supported pilot projects in Latin America, the Caribbean, the South Pacific, Southeast Asia, and Africa to improve transfer of forecast information to climate sensitive sectors, study linkages between climate and human health, and distribute climate information products in certain areas. Working with domestic and international partners, NOAA/OGP helped organize a total of 11 Climate Outlook Fora around the world during the 1997-98 El Niño. At each Outlook Forum, climatologists and meteorologists created regional, consensus-based, seasonal precipitation forecasts and representatives from climate-sensitive sectors discussed options for applying forecast information. Additional ongoing activities during 1997-98 included research programs focused on the social and economic impacts of climate change and the regional manifestations of global-scale climate variations and their effect on decision-making in climate-sensitive sectors in the United States.The overall intent of NOAA/OGP's activities was to make experimental forecast information broadly available to potential users, and to foster a learning process on how seasonal-to-interannual forecasts could be applied in sectors susceptible to climate variability. This process allowed users to explore the capabilities and limitations of climate forecasts currently available, and forecast producers to receive feedback on the utility of their products. Through activities in which NOAA/OGP and its partners were involved, it became clear that further application of forecast information will be aided by improved forecast accuracy and detail, creation of common validation techniques, continued training in forecast generation and application, alternate methods for presenting forecast information, and a systematic strategy for creation and dissemination of forecast products.The overall intent of NOAA/OGP's activities was to make experimental forecast information broadly available to potential users, and to foster a learning process on how seasonal-to-interannual forecasts could be applied in sectors susceptible to climate variability. This process allowed users to explore the capabilities and limitations of climate forecasts currently available, and forecast producers to receive feedback on the utility of their products. Through activities in which NOAA/OGP and its partners were involved, it became clear that further application of forecast information will be aided by improved forecast accuracy and detail, creation of common validation techniques, continued training in forecast generation and application, alternate methods for presenting forecast information, and a systematic strategy for creation and dissemination of forecast products.

Water Resource Planning Under Future Climate and Socioeconomic Uncertainty in the Cauvery River Basin in Karnataka, India.

PubMed

Bhave, Ajay Gajanan; Conway, Declan; Dessai, Suraje; Stainforth, David A

2018-02-01

Decision-Making Under Uncertainty (DMUU) approaches have been less utilized in developing countries than developed countries for water resources contexts. High climate vulnerability and rapid socioeconomic change often characterize developing country contexts, making DMUU approaches relevant. We develop an iterative multi-method DMUU approach, including scenario generation, coproduction with stakeholders and water resources modeling. We apply this approach to explore the robustness of adaptation options and pathways against future climate and socioeconomic uncertainties in the Cauvery River Basin in Karnataka, India. A water resources model is calibrated and validated satisfactorily using observed streamflow. Plausible future changes in Indian Summer Monsoon (ISM) precipitation and water demand are used to drive simulations of water resources from 2021 to 2055. Two stakeholder-identified decision-critical metrics are examined: a basin-wide metric comprising legal instream flow requirements for the downstream state of Tamil Nadu, and a local metric comprising water supply reliability to Bangalore city. In model simulations, the ability to satisfy these performance metrics without adaptation is reduced under almost all scenarios. Implementing adaptation options can partially offset the negative impacts of change. Sequencing of options according to stakeholder priorities into Adaptation Pathways affects metric satisfaction. Early focus on agricultural demand management improves the robustness of pathways but trade-offs emerge between intrabasin and basin-wide water availability. We demonstrate that the fine balance between water availability and demand is vulnerable to future changes and uncertainty. Despite current and long-term planning challenges, stakeholders in developing countries may engage meaningfully in coproduction approaches for adaptation decision-making under deep uncertainty.

Water Resource Planning Under Future Climate and Socioeconomic Uncertainty in the Cauvery River Basin in Karnataka, India

NASA Astrophysics Data System (ADS)

Bhave, Ajay Gajanan; Conway, Declan; Dessai, Suraje; Stainforth, David A.

2018-02-01

Decision-Making Under Uncertainty (DMUU) approaches have been less utilized in developing countries than developed countries for water resources contexts. High climate vulnerability and rapid socioeconomic change often characterize developing country contexts, making DMUU approaches relevant. We develop an iterative multi-method DMUU approach, including scenario generation, coproduction with stakeholders and water resources modeling. We apply this approach to explore the robustness of adaptation options and pathways against future climate and socioeconomic uncertainties in the Cauvery River Basin in Karnataka, India. A water resources model is calibrated and validated satisfactorily using observed streamflow. Plausible future changes in Indian Summer Monsoon (ISM) precipitation and water demand are used to drive simulations of water resources from 2021 to 2055. Two stakeholder-identified decision-critical metrics are examined: a basin-wide metric comprising legal instream flow requirements for the downstream state of Tamil Nadu, and a local metric comprising water supply reliability to Bangalore city. In model simulations, the ability to satisfy these performance metrics without adaptation is reduced under almost all scenarios. Implementing adaptation options can partially offset the negative impacts of change. Sequencing of options according to stakeholder priorities into Adaptation Pathways affects metric satisfaction. Early focus on agricultural demand management improves the robustness of pathways but trade-offs emerge between intrabasin and basin-wide water availability. We demonstrate that the fine balance between water availability and demand is vulnerable to future changes and uncertainty. Despite current and long-term planning challenges, stakeholders in developing countries may engage meaningfully in coproduction approaches for adaptation decision-making under deep uncertainty.

Data mining to predict climate hotspots: an experiment in aligning federal climate enterprises in the Northwest

NASA Astrophysics Data System (ADS)

Mote, P.; Foster, J. G.; Daley-Laursen, S. B.

2014-12-01

The Northwest has the nation's strongest geographic, institutional, and scientific alignment between NOAA RISA, DOI Climate Science Center, USDA Climate Hub, and participating universities. Considering each of those institutions' distinct mission, funding structures, governance, stakeholder engagement, methods of priority-setting, and deliverables, it is a challenge to find areas of common interest and ways for these institutions to work together. In view of the rich history of stakeholder engagement and the deep base of previous research on climate change in the region, these institutions are cooperating in developing a regional capacity to mine the vast available data in ways that are mutually beneficial, synergistic, and regionally relevant. Fundamentally, data mining means exploring connections across and within multiple datasets using advanced statistical techniques, development of multidimensional indices, machine learning, and more. The challenge is not just what we do with big datasets, but how we integrate the wide variety and types of data coming out of scenario analyses to create knowledge and inform decision-making. Federal agencies and their partners need to learn integrate big data on climate change and develop useful tools for important stake-holders to assist them in anticipating the main stresses of climate change to their own resources and preparing to abate those stresses.

Identifying and assessing the application of ecosystem services approaches in environmental policies and decision making.

PubMed

Van Wensem, Joke; Calow, Peter; Dollacker, Annik; Maltby, Lorraine; Olander, Lydia; Tuvendal, Magnus; Van Houtven, George

2017-01-01

The presumption is that ecosystem services (ES) approaches provide a better basis for environmental decision making than do other approaches because they make explicit the connection between human well-being and ecosystem structures and processes. However, the existing literature does not provide a precise description of ES approaches for environmental policy and decision making, nor does it assess whether these applications will make a difference in terms of changing decisions and improving outcomes. We describe 3 criteria that can be used to identify whether and to what extent ES approaches are being applied: 1) connect impacts all the way from ecosystem changes to human well-being, 2) consider all relevant ES affected by the decision, and 3) consider and compare the changes in well-being of different stakeholders. As a demonstration, we then analyze retrospectively whether and how the criteria were met in different decision-making contexts. For this assessment, we have developed an analysis format that describes the type of policy, the relevant scales, the decisions or questions, the decision maker, and the underlying documents. This format includes a general judgment of how far the 3 ES criteria have been applied. It shows that the criteria can be applied to many different decision-making processes, ranging from the supranational to the local scale and to different parts of decision-making processes. In conclusion we suggest these criteria could be used for assessments of the extent to which ES approaches have been and should be applied, what benefits and challenges arise, and whether using ES approaches made a difference in the decision-making process, decisions made, or outcomes of those decisions. Results from such studies could inform future use and development of ES approaches, draw attention to where the greatest benefits and challenges are, and help to target integration of ES approaches into policies, where they can be most effective. Integr Environ Assess Manag 2017;13:41-51. © 2016 SETAC. © 2016 SETAC.

Economic Value of an Advanced Climate Observing System

NASA Astrophysics Data System (ADS)

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

2013-12-01

Scientific missions increasingly need to show the monetary value of knowledge advances in budget-constrained environments. For example, suppose a climate science mission promises to yield decisive information on the rate of human caused global warming within a shortened time frame. How much should society be willing to pay for this knowledge today? The US interagency memo on the social cost of carbon (SCC) creates a standard yardstick for valuing damages from carbon emissions. We illustrate how value of information (VOI) calculations can be used to monetize the relative value of different climate observations. We follow the SCC, setting uncertainty in climate sensitivity to a truncated Roe and Baker (2007) distribution, setting discount rates of 2.5%, 3% and 5%, and using one of the Integrated Assessment Models sanctioned in SCC (DICE, Nordhaus 2008). We consider three mitigation scenarios: Business as Usual (BAU), a moderate mitigation response DICE Optimal, and a strong response scenario (Stern). To illustrate results, suppose that we are on the BAU emissions scenario, and that we would switch to the Stern emissions path if we learn with 90% confidence that the decadal rate of temperature change reaches or exceeds 0.2 C/decade. Under the SCC assumptions, the year in which this happens, if it happens, depends on the uncertain climate sensitivity and on the emissions path. The year in which we become 90% certain that it happens depends, in addition, on our Earth observations, their accuracy, and their completeness. The basic concept is that more accurate observations can shorten the time for societal decisions. The economic value of the resulting averted damages depends on the discount rate, and the years in which the damages occur. A new climate observation would be economically justified if the net present value (NPV) of the difference in averted damages, relative to the existing systems, exceeds the NPV of the system costs. Our results (Cooke et al. 2013) compared the proposed CLARREO advance in satellite absolute calibration for climate change records to an existing system for detecting decadal temperature change using infrared spectra from weather satellites. New results extend this to observational detection of cloud feedback which is the largest uncertainty in determining climate sensitivity and therefore the uncertainty in economic impacts. New results also include the use of multiple societal decision triggers. While CLARREO is used as an example, the value should be considered as relevant to a complete high accuracy climate observing system, as societal decisions are unlikely to be based on one or a few observations. The VOI is found to depend on the required confidence level, the trigger value at which we would abandon the BAU emissions path, the path to which we switch, and the date at which the new system is launched. The VOI of advanced climate observations in this decision context is the surfeit of NPV of averted damages, relative to the existing system. Over all it is in the order of tens of trillions of US dollars in Net Present Value. The results conclude that the economic value of advanced climate observing systems is dramatically larger than their cost, and argues for the continual enhancement of the SCC assessment process.

SDSM-DC: A smarter approach to downscaling for decision-making? (Invited)

NASA Astrophysics Data System (ADS)

Wilby, R. L.; Dawson, C. W.

2011-12-01

General Circulation Model (GCM) output has been used for downscaling and impact assessments for at least 25 years. Downscaling methods raise awareness about risks posed by climate variability and change to human and natural systems. However, there are relatively few instances where these analyses have translated into actionable information for adaptation. One reason is that conventional ';top down' downscaling typically yields very large uncertainty bounds in projected impacts at regional and local scales. Consequently, there are growing calls to use downscaling tools in smarter ways that refocus attention on the decision problem rather than on the climate modelling per se. The talk begins with an overview of various application of the Statistical DownScaling Model (SDSM) over the last decade. This sample offers insights to downscaling practice in terms of regions and sectors of interest, modes of application and adaptation outcomes. The decision-centred rationale and functionality of the latest version of SDSM is then explained. This new downscaling tool does not require GCM input but enables the user to generate plausible daily weather scenarios that may be informed by climate model and/or palaeoenvironmental information. Importantly, the tool is intended for stress-testing adaptation options rather than for exhaustive analysis of uncertainty components. The approach is demonstrated by downscaling multi-basin, multi-elevation temperature and precipitation scenarios for the Upper Colorado River Basin. These scenarios are used alongside other narratives of future conditions that might potential affect the security of water supplies, and for evaluating steps that can be taken to manage these risks.

SDSM-DC: A smarter approach to downscaling for decision-making? (Invited)

NASA Astrophysics Data System (ADS)

Wilby, R. L.; Dawson, C. W.

2013-12-01

General Circulation Model (GCM) output has been used for downscaling and impact assessments for at least 25 years. Downscaling methods raise awareness about risks posed by climate variability and change to human and natural systems. However, there are relatively few instances where these analyses have translated into actionable information for adaptation. One reason is that conventional ';top down' downscaling typically yields very large uncertainty bounds in projected impacts at regional and local scales. Consequently, there are growing calls to use downscaling tools in smarter ways that refocus attention on the decision problem rather than on the climate modelling per se. The talk begins with an overview of various application of the Statistical DownScaling Model (SDSM) over the last decade. This sample offers insights to downscaling practice in terms of regions and sectors of interest, modes of application and adaptation outcomes. The decision-centred rationale and functionality of the latest version of SDSM is then explained. This new downscaling tool does not require GCM input but enables the user to generate plausible daily weather scenarios that may be informed by climate model and/or palaeoenvironmental information. Importantly, the tool is intended for stress-testing adaptation options rather than for exhaustive analysis of uncertainty components. The approach is demonstrated by downscaling multi-basin, multi-elevation temperature and precipitation scenarios for the Upper Colorado River Basin. These scenarios are used alongside other narratives of future conditions that might potential affect the security of water supplies, and for evaluating steps that can be taken to manage these risks.

Managing United States public lands in response to climate change: a view from the ground up.

PubMed

Ellenwood, Mikaela S; Dilling, Lisa; Milford, Jana B

2012-05-01

Federal land managers are faced with the task of balancing multiple uses and goals when making decisions about land use and the activities that occur on public lands. Though climate change is now well recognized by federal agencies and their local land and resource managers, it is not yet clear how issues related to climate change will be incorporated into on-the-ground decision making within the framework of multiple use objectives. We conducted a case study of a federal land management agency field office, the San Juan Public Lands Center in Durango, CO, U.S.A., to understand from their perspective how decisions are currently made, and how climate change and carbon management are being factored into decision making. We evaluated three major management sectors in which climate change or carbon management may intersect other use goals: forests, biofuels, and grazing. While land managers are aware of climate change and eager to understand more about how it might affect land resources, the incorporation of climate change considerations into everyday decision making is currently quite limited. Climate change is therefore on the radar screen, but remains a lower priority than other issues. To assist the office in making decisions that are based on sound scientific information, further research is needed into how management activities influence carbon storage and resilience of the landscape under climate change.

Collaborative Workshops for Assessment and Creation of Multi-Objective Decision Support for Multiple Sectors

NASA Astrophysics Data System (ADS)

Kasprzyk, J. R.; Smith, R.; Raseman, W. J.; DeRousseau, M. A.; Dilling, L.; Ozekin, K.; Summers, R. S.; Balaji, R.; Livneh, B.; Rosario-Ortiz, F.; Sprain, L.; Srubar, W. V., III

2017-12-01

This presentation will report on three projects that used interactive workshops with stakeholders to develop problem formulations for Multi-Objective Evolutionary Algorithm (MOEA)-based decision support in diverse fields - water resources planning, water quality engineering under climate extremes, and sustainable materials design. When combined with a simulation model of a system, MOEAs use intelligent search techniques to provide new plans or designs. This approach is gaining increasing prominence in design and planning for environmental sustainability. To use this technique, a problem formulation - objectives and constraints (quantitative measures of performance) and decision variables (actions that can be modified to improve the system) - must be identified. Although critically important for MOEA effectiveness, the problem formulations are not always developed with stakeholders' interests in mind. To ameliorate this issue, project workshops were organized to improve the tool's relevance as well as collaboratively build problem formulations that can be used in applications. There were interesting differences among the projects, which altered the findings of each workshop. Attendees ranged from a group of water managers on the Front Range of Colorado, to water utility representatives from across the country, to a set of designers, academics, and trade groups. The extent to which the workshop participants were already familiar with simulation tools contributed to their willingness to accept the solutions that were generated using the tool. Moreover, in some instances, brainstorming new objectives to include within the MOEA expanded the scope of the problem formulation, relative to the initial conception of the researchers. Through describing results across a diversity of projects, the goal of this presentation is to report on how our approach may inform future decision support collaboration with a variety of stakeholders and sectors.

Farmer Decision-Making for Climate Adaptation

NASA Astrophysics Data System (ADS)

Lubell, M.; Niles, M.; Salerno, J.

2015-12-01

This talk will provide an overview of several studies of how farmers make decisions about climate change adaptation and mitigation. A particular focus will be the "limiting factors hypothesis", which argues that farmers will respond to the climate variables that usually have the largest impact on their crop productivity. For example, the most limiting factor in California is usually water so how climate change affects water will be the largest drive of climate adaptation decisions. This basic idea is drawn from the broader theory of "psychological distance", which argue that human decisions are more attuned to ideas that are psychologically closer in space, time, or other factors. Empirical examples come from California, New Zealand, and Africa.

Vista goes online: Decision-analytic systems for real-time decision-making in mission control

NASA Technical Reports Server (NTRS)

Barry, Matthew; Horvitz, Eric; Ruokangas, Corinne; Srinivas, Sampath

1994-01-01

The Vista project has centered on the use of decision-theoretic approaches for managing the display of critical information relevant to real-time operations decisions. The Vista-I project originally developed a prototype of these approaches for managing flight control displays in the Space Shuttle Mission Control Center (MCC). The follow-on Vista-II project integrated these approaches in a workstation program which currently is being certified for use in the MCC. To our knowledge, this will be the first application of automated decision-theoretic reasoning techniques for real-time spacecraft operations. We shall describe the development and capabilities of the Vista-II system, and provide an overview of the use of decision-theoretic reasoning techniques to the problems of managing the complexity of flight controller displays. We discuss the relevance of the Vista techniques within the MCC decision-making environment, focusing on the problems of detecting and diagnosing spacecraft electromechanical subsystems component failures with limited information, and the problem of determining what control actions should be taken in high-stakes, time-critical situations in response to a diagnosis performed under uncertainty. Finally, we shall outline our current research directions for follow-on projects.

The Economic Value of Climate Science

NASA Astrophysics Data System (ADS)

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

2012-12-01

While demonstrating the economic value of science is challenging, it can be more direct for some Earth observations. For example, suppose a climate science mission can yield decisive information on climate change within a shortened time frame. How much should society be willing to pay for this knowledge today? The US interagency memo on the social cost of carbon (SCC) provides a standard for valuing damages from carbon emissions. We illustrate how value of information (VOI) calculations can be used to monetize the relative value of different climate observations. We follow the SCC, stipulating uncertainty in climate sensitivity, using discount rates of 2.5%, 3% and 5%, and using one of the Integrated Assessment Models sanctioned in SCC (DICE, Nordhaus 2008). We consider three mitigation scenarios: Business as Usual (BAU), a moderate response (DICE Optimal), and a strong response (Stern). To illustrate results, suppose that we would switch from BAU to the Stern emissions path if we learn with 90% confidence that the decadal rate of temperature change reaches or exceeds 0.2 C/decade. Under the SCC assumptions, the year in which this happens, if it happens, depends on uncertain climate sensitivity and on the emissions path. The year in which we become 90% certain also depends on our Earth observations, their accuracy, and their completeness. The resolving power of a climate observing system cannot exceed climate system natural variability. All climate observations add noise to natural variability caused by observing limitations, including calibration errors and space/time sampling uncertainty. The basic concept is that more accurate observations can advance the time for societal decisions. The economic value of the resulting averted damages depends on the discount rate, and the years in which the damages occur. A new climate observation would be economically justified if the net present value (NPV) of the difference in averted damages, relative to the existing systems, exceeds the NPV of the system costs. We present illustrative results comparing the proposed CLARREO advance in satellite absolute calibration for climate change records to an existing system for detecting decadal temperature change and cloud feedback (i.e. climate sensitivity uncertainty). While CLARREO is used as an example, the value should be considered as relevant to an improved climate observing system, since societal decisions are unlikely to be based on one or a few observations. The VOI is found to depend on the required confidence level, the trigger value at which we would abandon the BAU emissions path, the path to which we switch, and the date at which the new system is launched. The VOI of CLARREO in this decision context is the surfeit of NPV of averted damages, relative to the existing system. Over all it is in the order of tens of trillions of US dollars. Among the noteworthy conclusions are (1) switching to either the DICE optimal or Stern emissions paths makes only a modest difference in the VOI of CLARREO, (2) raising the trigger value from 0.2C to 0.3C/decade, increases the VOI of CLARREO, while increasing the total NPV of climate damages, and (3) the choice of discount rate affects the VOI by a factor ~ 5. The results conclude that the economic value of advanced climate observing systems is dramatically larger than their cost, and argues for the continual enhancement of the SCC assessment process.

On the use and potential use of seasonal to decadal climate predictions for decision-making in Europe

NASA Astrophysics Data System (ADS)

Soares, Marta Bruno; Dessai, Suraje

2014-05-01

The need for climate information to help inform decision-making in sectors susceptible to climate events and impacts is widely recognised. In Europe, developments in the science and models underpinning the study of climate variability and change have led to an increased interest in seasonal to decadal climate predictions (S2DCP). While seasonal climate forecasts are now routinely produced operationally by a number of centres around the world, decadal climate predictions are still in its infancy restricted to the realm of research. Contrary to other regions of the world, where the use of these types of forecasts, particularly at seasonal timescales, has been pursued in recent years due to higher levels of predictability, little is known about the uptake and climate information needs of end-users regarding S2DCP in Europe. To fill this gap we conducted in-depth interviews with experts and decision-makers across a range of European sectors, a workshop with European climate services providers, and a systematic literature review on the use of S2DCP in Europe. This study is part of the EUropean Provision Of Regional Impact Assessment on a Seasonal-to-decadal timescale (EUPORIAS) project which aims to develop semi-operational prototypes of impact prediction systems in Europe on seasonal to decadal timescales. We found that the emerging landscape of users and potential users of S2DCP in Europe is complex and heterogeneous. Differences in S2DCP information needs across and within organisations and sectors are largely underpinned by factors such as the institutional and regulatory context of the organisations, the plethora of activities and decision-making processes involved, the level of expertise and capacity of the users, and the availability of resources within the organisations. In addition, although the use of S2DCP across Europe is still fairly limited, particular sectors such as agriculture, health, energy, water, (re)insurance, and transport are taking the lead on the use of seasonal forecasts. The potential to use decadal predictions across European sectors was also noted although these are currently not used due to the limitations of the science and the experimental nature of existing predictions. Despite the limited use of these types of climate predictions there is a general understanding that information on the uncertainty of such predictions is a fundamental component of S2DCP although approaches for dealing with such uncertainty also tend to differ across organisations. Perceived barriers to the uptake of these types of climate predictions are mainly associated with low skill and reliability of the models but also with other factors such as relevance, usability, and accessibility of S2DCP by end-users. Potential solutions to overcome such barriers include the potential to explore existing 'windows of opportunity' in Europe, improve current understanding of users' needs, and increase accessibility and awareness of users to available S2DCP in Europe. This paper will present findings from our analysis and consider some of the broader issues raised by the emergence of S2DCP for climate services in Europe.

Mommy, Where Do Climate Service Products Come From?

NASA Astrophysics Data System (ADS)

Redmond, K. T.

2015-12-01

Since the middle 20th Century -- and earlier-- a large variety of climate services have become available to existing and potential users needing climate information to inform a decision of interest to them. Climate may play a minor to major role in such decisions. Originally, most such information was delivered in the form of products, which could range in complexity from the simplest possible form, the original or edited data themselves, to more highly developed and manipulated information in the form of summaries, typically in fixed forms. These were intended to serve a need for widely, routinely, and frequently requested basic statistical information about climate, in the form of tables, graphics and sometimes narratives. With the rise of the internet this approach has given way to applications that can generate tailored summaries on demand, with the user able to control date intervals, statistical thresholds, formats, and a variety of other issues of both substance and style. A much richer environment for the creation of such information now exists. This tradition arose largely through the combined efforts of NOAA and predecessor agencies via the National Weather Records Center, renamed the National Climate Center, renamed the National Climatic Data Center, now combined with geophysical and oceanographic counterparts into the National Centers for Environmental Information, in analogy with the National Centers for Environmental Prediction. A steady partner during this history has been the membership of the American Association of State Climatologists. The first efforts were intended to address to most common questions and to assist with reduction in workload in answering multiple repeated requests for the same information. Over time users and uses have become increasingly sophisticated, specialized, and diverse. Increasing efforts are directed to a more systematic approach, involving explicit engagement of stakeholders, to learn which applications to develop or improve. The recent merger of three centers into NCEI presents opportunities in this realm.

Cloud Computing-based Platform for Drought Decision-Making using Remote Sensing and Modeling Products: Preliminary Results for Brazil

NASA Astrophysics Data System (ADS)

Vivoni, E.; Mascaro, G.; Shupe, J. W.; Hiatt, C.; Potter, C. S.; Miller, R. L.; Stanley, J.; Abraham, T.; Castilla-Rubio, J.

2012-12-01

Droughts and their hydrological consequences are a major threat to food security throughout the world. In arid and semiarid regions dependent on irrigated agriculture, prolonged droughts lead to significant and recurring economic and social losses. In this contribution, we present preliminary results on integrating a set of multi-resolution drought indices into a cloud computing-based visualization platform. We focused our initial efforts on Brazil due to a severe, on-going drought in a large agricultural area in the northeastern part of the country. The online platform includes drought products developed from: (1) a MODIS-based water stress index (WSI) based on inferences from normalized difference vegetation index and land surface temperature fields, (2) a volumetric water content (VWC) index obtained from application of the NASA CASA model, and (3) a set of AVHRR-based vegetation health indices obtained from NOAA/NESDIS. The drought indices are also presented in terms of anomalies with respect to a baseline period. Since our main objective is to engage stakeholders and decision-makers in Brazil, we incorporated other relevant geospatial data into the platform, including irrigation areas, dams and reservoirs, administrative units and annual climate information. We will also present a set of use cases developed to help stakeholders explore, query and provide feedback that allowed fine-tuning of the drought product delivery, presentation and analysis tools. Finally, we discuss potential next steps in development of the online platform, including applications at finer resolutions in specific basins and at a coarser global scale.

Applications of subseasonal-to-seasonal (S2S) predictions

NASA Astrophysics Data System (ADS)

White, Christopher; Lamb, Rob; Carlsen, Henrik; Robertson, Andrew; Klein, Richard; Lazo, Jeffrey; Kumar, Arun; Vitart, Frederic; Coughlan de Perez, Erin; Ray, Andrea; Murray, Virginia; Graham, Richard; Buontempo, Carlo

2017-04-01

While long-range seasonal outlooks have been operational for many years, until recently the extended-range timescale - referred to as 'subseasonal-to-seasonal' (S2S) and which sits between the medium- to long-range forecasting timescales - has received relatively little attention. The S2S timescale has long been seen as a 'predictability desert', yet a new generation of S2S predictions are starting to bridge the gap between weather forecasts and longer-range prediction. Decisions in a range of sectors are made in this extended-range lead time, therefore there is a strong demand for this new generation of predictions. At least ten international weather centres now have some capability for issuing experimental or operational S2S predictions, including the European Centre for Medium-Range Weather Forecasting (ECMWF) and the National Oceanic and Atmospheric Administration (NOAA) that now have operational S2S outputs. International efforts are now underway to identify key sources of predictability, improve forecast skill and operationalise aspects of S2S forecasts, however challenges remain in advancing this new frontier. If S2S predictions are to be utilised effectively, it is important that along with science advances, we learn how to develop, communicate and apply these forecasts appropriately. In this study, we present the potential of the emerging operational S2S forecasts to the wider weather and climate applications community by undertaking the first comprehensive review of sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. We explore the value of applications-relevant S2S predictions, and highlight the opportunities and challenges facing their uptake. We show how social sciences can be integrated with S2S development - from communication to decision-making and valuation of forecasts - to enhance the benefits of 'climate services' approaches for extended-range forecasting. We highlight the availability of data repositories of near real-time S2S forecasts and hindcasts, including the WWRP-WCRP (http://apps.ecmwf.int/datasets/data/s2s) and North American Multimodel Ensemble (NMME; http://www.cpc.ncep.noaa.gov/products/NMME/data.html) repositories, and discuss how they are promoting the use (and aiding the development) of S2S predictions. While S2S forecasting is at a relatively early stage of development, we conclude that it presents a significant new window of opportunity that can be explored for application-ready capabilities that could allow many sectors the opportunity to systematically plan on a new time horizon.

Opportunistic management of estuaries under climate change: A new adaptive decision-making framework and its practical application.

PubMed

Peirson, William; Davey, Erica; Jones, Alan; Hadwen, Wade; Bishop, Keith; Beger, Maria; Capon, Samantha; Fairweather, Peter; Creese, Bob; Smith, Timothy F; Gray, Leigh; Tomlinson, Rodger

2015-11-01

Ongoing coastal development and the prospect of severe climate change impacts present pressing estuary management and governance challenges. Robust approaches must recognise the intertwined social and ecological vulnerabilities of estuaries. Here, a new governance and management framework is proposed that recognises the integrated social-ecological systems of estuaries so as to permit transformative adaptation to climate change within these systems. The framework lists stakeholders and identifies estuarine uses and values. Goals are categorised that are specific to ecosystems, private property, public infrastructure, and human communities. Systematic adaptation management strategies are proposed with conceptual examples and associated governance approaches. Contrasting case studies are used to illustrate the practical application of these ideas. The framework will assist estuary managers worldwide to achieve their goals, minimise maladaptative responses, better identify competing interests, reduce stakeholder conflict and exploit opportunities for appropriate ecosystem restoration and sustainable development. Copyright © 2015 Elsevier Ltd. All rights reserved.

Climate Change Education on Public Health Consequences and Impacts to the Human System - An Interdisciplinary Approach to Promoting Climate Literacy

NASA Astrophysics Data System (ADS)

Matiella Novak, M.; Paxton, L. J.

2012-12-01

In this talk we will discuss our approach to translating an abstract, difficult to internalize idea ("climate change") into knowledge that speaks to people directly in terms of their own lives. Recent research suggests that communicating climate change in the context of public health impacts, and even national security risks, is a more effective method of reaching communities that are currently disengaged or nonresponsive to climate change science than the approaches currently being used. Understanding that these new perspectives might reach a broader audience, the Global Assimilation of Information for Action (GAIA) project has proposed implementing a suite of education activities that focus on the public health consequences that will arise and/or becoming exacerbated by climate change. Reaching the disparate communities that must be brought together to create a workable approach is challenging. GAIA has developed a novel framework for sharing information and developing communities of interest that cross boundaries in what is otherwise a highly disciplinary approach to climate change studies. Members of the GAIA community include climate change, environmental and public health experts, as well as relevant stakeholders, policy makers and decision makers. By leveraging the existing expertise within the GAIA community, an opportunity exists to present climate change education (CCE) in a way that emphasizes how climate change will affect public health, and utilizes an approach that has been shown to engage a broader and more diverse audience. Focusing CCE on public health effects is a new and potentially transformative method since it makes the results more tangible and less "random". When CCE is focused on what will happen to the Earth's climate and associated meteorological hazards one might be tempted to view this as something that can be coped with thus enabling the individualist entrepreneur point of view. Weather disasters always seem to happen to someone else - someone not like you. On the other hand, public health impacts are felt by millions and lead to very high costs and those impacts are something with which most people have direct experiences. We will discuss, for example, how climate change can be framed as a cost/benefit problem by looking at the long term costs of increase in disease and illness such as the startling trends in childhood asthma. Changes in water availability, and water and air quality, will result from a warming climate, with measureable consequences for public health: disease spread, food and water security, respiratory health, etc. By integrating this information with education efforts, society, educators and decision makers will have a better understanding of how climate change affects the human system, and what decisions can be made at the individual and community levels to mitigate and adapt to climate change. We will show how this can be achieved.

Developing Climate Resilience Toolkit Decision Support Training Sectio

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Highway deicing salt dynamic runoff to surface water and subsequent infiltration to groundwater during severe UK winters.

PubMed

Rivett, Michael O; Cuthbert, Mark O; Gamble, Richard; Connon, Lucy E; Pearson, Andrew; Shepley, Martin G; Davis, John

2016-09-15

Dynamic impact to the water environment of deicing salt application at a major highway (motorway) interchange in the UK is quantitatively evaluated for two recent severe UK winters. The contaminant transport pathway studied allowed controls on dynamic highway runoff and storm-sewer discharge to a receiving stream and its subsequent leakage to an underlying sandstone aquifer, including possible contribution to long-term chloride increases in supply wells, to be evaluated. Logged stream electrical-conductivity (EC) to estimate chloride concentrations, stream flow, climate and motorway salt application data were used to assess salt fate. Stream loading was responsive to salt applications and climate variability influencing salt release. Chloride (via EC) was predicted to exceed the stream Environmental Quality Standard (250mg/l) for 33% and 18% of the two winters. Maximum stream concentrations (3500mg/l, 15% sea water salinity) were ascribed to salt-induced melting and drainage of highway snowfall without dilution from, still frozen, catchment water. Salt persistance on the highway under dry-cold conditions was inferred from stream observations of delayed salt removal. Streambed and stream-loss data demonstrated chloride infiltration could occur to the underlying aquifer with mild and severe winter stream leakage estimated to account for 21 to 54% respectively of the 70t of increased chloride (over baseline) annually abstracted by supply wells. Deicing salt infiltration lateral to the highway alongside other urban/natural sources were inferred to contribute the shortfall. Challenges in quantifying chloride mass/fluxes (flow gauge accuracy at high flows, salt loading from other roads, weaker chloride-EC correlation at low concentrations), may be largely overcome by modest investment in enhanced data acquisition or minor approach modification. The increased understanding of deicing salt dynamic loading to the water environment obtained is relevant to improved groundwater resource management, highway salt application practice, surface-water - ecosystem management, and decision making on highway drainage to ground. Copyright © 2016 Elsevier B.V. All rights reserved.

Physico-chemical properties of manufactured nanomaterials - Characterisation and relevant methods. An outlook based on the OECD Testing Programme.

PubMed

Rasmussen, Kirsten; Rauscher, Hubert; Mech, Agnieszka; Riego Sintes, Juan; Gilliland, Douglas; González, Mar; Kearns, Peter; Moss, Kenneth; Visser, Maaike; Groenewold, Monique; Bleeker, Eric A J

2018-02-01

Identifying and characterising nanomaterials require additional information on physico-chemical properties and test methods, compared to chemicals in general. Furthermore, regulatory decisions for chemicals are usually based upon certain toxicological properties, and these effects may not be equivalent to those for nanomaterials. However, regulatory agencies lack an authoritative decision framework for nanomaterials that links the relevance of certain physico-chemical endpoints to toxicological effects. This paper investigates various physico-chemical endpoints and available test methods that could be used to produce such a decision framework for nanomaterials. It presents an overview of regulatory relevance and methods used for testing fifteen proposed physico-chemical properties of eleven nanomaterials in the OECD Working Party on Manufactured Nanomaterials' Testing Programme, complemented with methods from literature, and assesses the methods' adequacy and applications limits. Most endpoints are of regulatory relevance, though the specific parameters depend on the nanomaterial and type of assessment. Size (distribution) is the common characteristic of all nanomaterials and is decisive information for classifying a material as a nanomaterial. Shape is an important particle descriptor. The octanol-water partitioning coefficient is undefined for particulate nanomaterials. Methods, including sample preparation, need to be further standardised, and some new methods are needed. The current work of OECD's Test Guidelines Programme regarding physico-chemical properties is highlighted. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A decision science approach for integrating social science in climate and energy solutions

NASA Astrophysics Data System (ADS)

Wong-Parodi, Gabrielle; Krishnamurti, Tamar; Davis, Alex; Schwartz, Daniel; Fischhoff, Baruch

2016-06-01

The social and behavioural sciences are critical for informing climate- and energy-related policies. We describe a decision science approach to applying those sciences. It has three stages: formal analysis of decisions, characterizing how well-informed actors should view them; descriptive research, examining how people actually behave in such circumstances; and interventions, informed by formal analysis and descriptive research, designed to create attractive options and help decision-makers choose among them. Each stage requires collaboration with technical experts (for example, climate scientists, geologists, power systems engineers and regulatory analysts), as well as continuing engagement with decision-makers. We illustrate the approach with examples from our own research in three domains related to mitigating climate change or adapting to its effects: preparing for sea-level rise, adopting smart grid technologies in homes, and investing in energy efficiency for office buildings. The decision science approach can facilitate creating climate- and energy-related policies that are behaviourally informed, realistic and respectful of the people whom they seek to aid.

Research Priorities for NCD Prevention and Climate Change: An International Delphi Survey.

PubMed

Colagiuri, Ruth; Boylan, Sinead; Morrice, Emily

2015-10-16

Climate change and non-communicable diseases (NCDs) are arguably the greatest global challenges of the 21st Century. However, the confluence between them remains under-examined and there is little evidence of a comprehensive, systematic approach to identifying research priorities to mitigate their joint impact. Consequently, we: (i) convened a workshop of academics (n = 25) from the Worldwide Universities Network to identify priority areas at the interface between NCDs and climate change; (ii) conducted a Delphi survey of international opinion leaders in public health and relevant other disciplines; and (iii) convened an expert panel to review and advise on final priorities. Three research areas (water security; transport; conceptualising NCD harms to support policy formation) were listed among the top 10 priorities by >90% of Delphi respondents, and ranked among the top 12 priorities by >60% of respondents who ranked the order of priority. A fourth area (reducing the carbon footprint of cities) was ranked highest by the same >60% of respondents. Our results are consistent with existing frameworks on health and climate change, and extends them by focusing specifically on NCDs. Researching these priorities could progress understanding of climate change and NCDs, and inform global and national policy decisions for mitigating associated harms.

Meeting the challenge of policy-relevant science: lessons from a water resource project

USGS Publications Warehouse

Lamb, Berton L.

1986-01-01

Water resource scientists face complex tasks in evaluating aspects of water projects, but relatively few assessment procedures have been applied and accepted as standard applications. Decision-makers often rely on environmental assessments to evaluate the value and operation of projects. There is often confusion about scientists' role in policy decisions. The scientist can affect policy-making as an expert withess, an advocate or a surrogate. By understanding the policy process, scientists can make their work more “policy relevant.” Using the Terror Lake hydro project in Alaska as a guide, three lessons are discussed: (1) not all problems are able to be solved with technology; (2) policy-relevant technology is rarely imposed on a problem; and (3) the scientist need not just react to the policy process, but can have an impact on how that process unfolds.

Difficult decisions: Migration from Small Island Developing States under climate change

NASA Astrophysics Data System (ADS)

Kelman, Ilan

2015-04-01

The impacts of climate change on Small Island Developing States (SIDS) are leading to discussions regarding decision-making about the potential need to migrate. Despite the situation being well-documented, with many SIDS aiming to raise the topic to prominence and to take action for themselves, limited support and interest has been forthcoming from external sources. This paper presents, analyzes, and critiques a decision-making flowchart to support actions for SIDS dealing with climate change-linked migration. The flowchart contributes to identifying the pertinent topics to consider and the potential support needed to implement decision-making. The flowchart has significant limitations and there are topics which it cannot resolve. On-the-ground considerations include who decides, finances, implements, monitors, and enforces each decision. Additionally, views within communities differ, hence mechanisms are needed for dealing with differences, while issues to address include moral and legal blame for any climate change-linked migration, the ultimate goal of the decision-making process, the wider role of migration in SIDS communities and the right to judge decision-making and decisions. The conclusions summarize the paper, emphasizing the importance of considering contexts beyond climate change and multiple SIDS voices.

Advantages and applicability of commonly used homogenisation methods for climate data

NASA Astrophysics Data System (ADS)

Ribeiro, Sara; Caineta, Júlio; Henriques, Roberto; Soares, Amílcar; Costa, Ana Cristina

2014-05-01

Homogenisation of climate data is a very relevant subject since these data are required as an input in a wide range of studies, such as atmospheric modelling, weather forecasting, climate change monitoring, or hydrological and environmental projects. Often, climate data series include non-natural irregularities which have to be detected and removed prior to their use, otherwise it would generate biased and erroneous results. Relocation of weather stations or changes in the measuring instruments are amongst the most relevant causes for these inhomogeneities. Depending on the climate variable, its temporal resolution and spatial continuity, homogenisation methods can be more or less effective. For example, due to its natural variability, precipitation is identified as a very challenging variable to be homogenised. During the last two decades, numerous methods have been proposed to homogenise climate data. In order to compare, evaluate and develop those methods, the European project COST Action ES0601, Advances in homogenisation methods of climate series: an integrated approach (HOME), was released in 2008. Existing homogenisation methods were improved based on the benchmark exercise issued by this project. A recent approach based on Direct Sequential Simulation (DSS), not yet evaluated by the benchmark exercise, is also presented as an innovative methodology for homogenising climate data series. DSS already proved to be a successful geostatistical method in environmental and hydrological studies, and it provides promising results for the homogenisation of climate data. Since DSS is a geostatistical stochastic approach, it accounts for the joint spatial and temporal dependence between observations, as well as the relative importance of stations both in terms of distance and correlation. This work presents a chronological review of the most commonly used homogenisation methods for climate data and available software packages. A short description and classification is provided for each method. Their advantages and applicability are discussed based on literature review and on the results of the HOME project. Acknowledgements: The authors gratefully acknowledge the financial support of "Fundação para a Ciência e Tecnologia" (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 ("GSIMCLI - Geostatistical simulation with local distributions for the homogenization and interpolation of climate data").

Adapting agriculture to climate change.

PubMed

Howden, S Mark; Soussana, Jean-François; Tubiello, Francesco N; Chhetri, Netra; Dunlop, Michael; Meinke, Holger

2007-12-11

The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists.

Useful to Usable (U2U): Transforming climate information into usable tools to support Midwestern agricultural production

NASA Astrophysics Data System (ADS)

Prokopy, L. S.; Widhalm, M.

2014-12-01

There is a close connection between weather and climate patterns and successful agricultural production. Therefore, incorporating climate information into farm management is likely to reduce the risk of economic losses and increase profitability. While weather and climate information is becoming ever more abundant and accessible, the use of such information in the agricultural community remains limited. Useful to Usable (U2U): Transforming Climate Variability and Change Information for Cereal Crop Producers is a USDA-NIFA funded research and extension project focused on improving the use of climate information for agricultural production in the Midwestern United States by developing user-driven decision tools and training resources. The U2U team is a diverse and uniquely qualified group of climatologists, crop modelers, agronomists, and social scientists from 9 Midwestern universities and two NOAA Regional Climate Centers. Together, we strive to help producers make better long-term plans on what, when and where to plant and also how to manage crops for maximum yields and minimum environmental damage. To ensure relevance and usability of U2U products, our social science team is using a number of techniques including surveys and focus groups to integrate stakeholder interests, needs, and concerns into all aspects of U2U research. It is through this coupling of physical and social science disciplines that we strive to transform existing climate information into actionable knowledge.

Improving Predictions and Management of Hydrological Extremes

NASA Astrophysics Data System (ADS)

Wijngaard, Janet; Liggins, Felicity; Hurk, Bart vd; Lavers, David; Magnusson, Linus; Bouwer, Laurens; Weerts, Albrecht; Kjellström, Erik; Mañez, Maria; Ramos, Maria-Helena; Hananel, Cedric; Ercin, Ertug; Hunink, Johannes; Klein, Bastian; Pouget, Laurent; de Moel, Hans

2017-04-01

The EU Roadmap on Climate Services can be seen as a result of convergence between society's call for "actionable research" and the climate research community's provision of tailored data, information and knowledge. Although weather and climate have distinct definitions, a strong link between weather and climate services does exist but, to date, this link has not been explored extensively. Stakeholders being interviewed in the context of the Roadmap consider changes in our climate as distant, long-term impacts that are difficult to consider in present-day decision making, a process usually dominated by their daily experience with handling adverse weather and extreme events. However, it could be argued that this experience is a rich source of inspiration to increase society's resilience to an unknown future. The European research project, IMPREX, is built on the notion that "experience in managing present day weather extremes can help us anticipate the consequences of future climate variability and change". This presentation illustrates how IMPREX is building the link between the providers and users of information and services addressing both the weather and climate timescales. For different stakeholders in key economic sectors the needs and vulnerabilities in their daily practice are discussed, followed by an analysis of how weather and climate (W&C) services could contribute to the demands that arise from this. Examples of case studies showing the relevance of the tailored W&C information in users' operations will be included.

The science of decisionmaking: applications for sustainable forest and grassland management in the National Forest System

Treesearch

Matthew P. Thompson; Bruce G. Marcot; Frank R. Thompson; Steven McNulty; Larry A. Fisher; Michael C. Runge; David Cleaves; Monica Tomosy

2013-01-01

Sustainable management of national forests and grasslands within the National Forest System (NFS) often requires managers to make tough decisions under considerable uncertainty, complexity, and potential conflict. Resource decisionmakers must weigh a variety of risks, stressors, and challenges to sustainable management, including climate change, wildland fire, invasive...

Haunted by a doppelgänger: irrelevant facial similarity affects rule-based judgments.

PubMed

von Helversen, Bettina; Herzog, Stefan M; Rieskamp, Jörg

2014-01-01

Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.

Designing ecological climate change impact assessments to reflect key climatic drivers

USGS Publications Warehouse

Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.

2017-01-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Designing ecological climate change impact assessments to reflect key climatic drivers.

PubMed

Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T

2017-07-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.

Integrating Communication Best Practices in the Third National Climate Assessment

NASA Astrophysics Data System (ADS)

Hassol, S. J.

2014-12-01

Modern climate science assessments now have a history of nearly a quarter-century. This experience, together with important advances in relevant social sciences, has greatly improved our ability to communicate climate science effectively. As a result, the Third National Climate Assessment (NCA) was designed to be truly accessible and useful to all its intended audiences, while still being comprehensive and scientifically accurate. At a time when meeting the challenge of climate change is increasingly recognized as an urgent national and global priority, the NCA is proving to be valuable to decision-makers, the media, and the public. In producing this latest NCA, a communication perspective was an important part of the process from the beginning, rather than an afterthought as has often been the case with scientific reports. Lessons learned from past projects and science communications research fed into developing the communication strategy for the Third NCA. A team of editors and graphic designers worked closely with the authors on language, graphics, and photographs throughout the development of the report, Highlights document, and other products. A web design team helped bring the report to life online. There were also innovations in outreach, including a network of organizations intended to extend the reach of the assessment by engaging stakeholders throughout the process. Professional slide set development and media training were part of the preparation for the report's release. The launch of the NCA in May 2014 saw widespread and ongoing media coverage, continued references to the NCA by decision-makers, and praise from many quarters for its excellence in making complex science clear and accessible. This NCA is a professionally crafted report that exemplifies best practices in 21st century communications.

Adverse outcome pathway (AOP) development: Guiding principles and best practices

EPA Science Inventory

Adverse outcome pathways (AOPs) represent a conceptual framework that can support greater application of mechanistic data in regulatory decision-making. However, in order for the scientific community to collectively address the daunting challenge of describing relevant toxicologi...

Statistical downscaling of regional climate scenarios for the French Alps : Impacts on snow cover

NASA Astrophysics Data System (ADS)

Rousselot, M.; Durand, Y.; Giraud, G.; Mérindol, L.; Déqué, M.; Sanchez, E.; Pagé, C.; Hasan, A.

2010-12-01

Mountain areas are particularly vulnerable to climate change. Owing to the complexity of mountain terrain, climate research at scales relevant for impacts studies and decisive for stakeholders is challenging. A possible way to bridge the gap between these fine scales and those of the general circulation models (GCMs) consists of combining high-resolution simulations of Regional Climate Models (RCMs) to statistical downscaling methods. The present work is based on such an approach. It aims at investigating the impacts of climate change on snow cover in the French Alps for the periods 2021-2050 and 2071-2100 under several IPCC hypotheses. An analogue method based on high resolution atmospheric fields from various RCMs and climate reanalyses is used to simulate local climate scenarios. These scenarios, which provide meteorological parameters relevant for snowpack evolution, subsequently feed the CROCUS snow model. In these simulations, various sources of uncertainties are thus considered (several greenhouse gases emission scenarios and RCMs). Results are obtained for different regions of the French Alps at various altitudes. For all scenarios, temperature increase is relatively uniform over the Alps. This regional warming is larger than that generally modeled at the global scale (IPCC, 2007), and particularly strong in summer. Annual precipitation amounts seem to decrease, mainly as a result of decreasing precipitation trends in summer and fall. As a result of these climatic evolutions, there is a general decrease of the mean winter snow depth and seasonal snow duration for all massifs. Winter snow depths are particularly reduced in the Northern Alps. However, the impact on seasonal snow duration is more significant in the Southern and Extreme Southern Alps, since these regions are already characterized by small winter snow depths at low elevations. Reference : IPCC (2007a). Climate change 2007 : The physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. In : Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, and H.L. Miller (eds.). Cambridge University Press, Cambridge, UK and New York, NY, USA. This work is performed in the framework of the SCAMPEI ANR (French research project).

Vulnerability of eco-environmental health to climate change: the views of government stakeholders and other specialists in Queensland, Australia.

PubMed

Strand, Linn B; Tong, Shilu; Aird, Rosemary; McRae, David

2010-07-28

There is overwhelming scientific evidence that human activities have changed and will continue to change the climate of the Earth. Eco-environmental health, which refers to the interdependencies between ecological systems and population health and well-being, is likely to be significantly influenced by climate change. The aim of this study was to examine perceptions from government stakeholders and other relevant specialists about the threat of climate change, their capacity to deal with it, and how to develop and implement a framework for assessing vulnerability of eco-environmental health to climate change. Two focus groups were conducted in Brisbane, Australia with representatives from relevant government agencies, non-governmental organisations, and the industry sector (n = 15) involved in the discussions. The participants were specialists on climate change and public health from governmental agencies, industry, and non-governmental organisations in South-East Queensland. The specialists perceived climate change to be a threat to eco-environmental health and had substantial knowledge about possible implications and impacts. A range of different methods for assessing vulnerability were suggested by the participants and the complexity of assessment when dealing with multiple hazards was acknowledged. Identified factors influencing vulnerability were perceived to be of a social, physical and/or economic nature. They included population growth, the ageing population with associated declines in general health and changes in the vulnerability of particular geographical areas due to for example, increased coastal development, and financial stress. Education, inter-sectoral collaboration, emergency management (e.g. development of early warning systems), and social networks were all emphasised as a basis for adapting to climate change. To develop a framework, different approaches were discussed for assessing eco-environmental health vulnerability, including literature reviews to examine the components of vulnerability such as natural hazard risk and exposure and to investigate already existing frameworks for assessing vulnerability. The study has addressed some important questions in regard to government stakeholders and other specialists' views on the threat of climate change and its potential impacts on eco-environmental health. These findings may have implications in climate change and public health decision-making.

Vulnerability of eco-environmental health to climate change: the views of government stakeholders and other specialists in Queensland, Australia

PubMed Central

2010-01-01

Background There is overwhelming scientific evidence that human activities have changed and will continue to change the climate of the Earth. Eco-environmental health, which refers to the interdependencies between ecological systems and population health and well-being, is likely to be significantly influenced by climate change. The aim of this study was to examine perceptions from government stakeholders and other relevant specialists about the threat of climate change, their capacity to deal with it, and how to develop and implement a framework for assessing vulnerability of eco-environmental health to climate change. Methods Two focus groups were conducted in Brisbane, Australia with representatives from relevant government agencies, non-governmental organisations, and the industry sector (n = 15) involved in the discussions. The participants were specialists on climate change and public health from governmental agencies, industry, and non-governmental organisations in South-East Queensland. Results The specialists perceived climate change to be a threat to eco-environmental health and had substantial knowledge about possible implications and impacts. A range of different methods for assessing vulnerability were suggested by the participants and the complexity of assessment when dealing with multiple hazards was acknowledged. Identified factors influencing vulnerability were perceived to be of a social, physical and/or economic nature. They included population growth, the ageing population with associated declines in general health and changes in the vulnerability of particular geographical areas due to for example, increased coastal development, and financial stress. Education, inter-sectoral collaboration, emergency management (e.g. development of early warning systems), and social networks were all emphasised as a basis for adapting to climate change. To develop a framework, different approaches were discussed for assessing eco-environmental health vulnerability, including literature reviews to examine the components of vulnerability such as natural hazard risk and exposure and to investigate already existing frameworks for assessing vulnerability. Conclusion The study has addressed some important questions in regard to government stakeholders and other specialists' views on the threat of climate change and its potential impacts on eco-environmental health. These findings may have implications in climate change and public health decision-making. PMID:20663227

Using climate information for fuels management

USGS Publications Warehouse

Kolden, Crystal A.; Brown, Timothy J.

2008-01-01

Climate has come to the forefront of wildfire discussions in recent years as research contributes to the general understanding of how climate influences fuels availability to burn, the occurrence of severe fire weather conditions and other wildfire parameters. This understanding has crossed over into wildfire management applications through the creation of tools like climate forecasts for wildfire and drought indices, which are now widely used in wildfire suppression and mitigation planning. The overall question is how can climate information help fire managers meet management objectives? Climate underlies weather. For example, a number of days could be generally wet, but that may occur in the context of a two-year overall drought. Knowing the baseline climate is not only critical to preventing escaped prescribed fires, but also how it may affect fire behavior, fire effects and whether or not fire managers will meet their fuels management objectives. Thus, for fire managers to use prescribed and WFU fire safely and effectively, and to minimize the number of escaped fires and conversions to suppression, they need to understand how current climate conditions will impact the use of fire. One example is the need to use prescribed fire under set “burn windows”. Since meteorological conditions vary considerably from year to year for a given day, fire managers will be more successful in utilizing burn windows effectively if they understand those climate thresholds conducive to an increased number of safe burn windows, and are able to predict and take advantage of those burn windows. While climate and wildfire has been studied extensively, climate and fire use has not. The initial goal of this project was to assess how climate impacts prescribed fire use in a more general sense. After a preliminary informal survey in the spring of 2003, we determined that 1) there is insufficient data (less than 10 years) to conduct empirical correlative studies similar to those of the relationships between climate and wildfire (e.g., Swetnam and Betancourt 1990), and 2) prescribed fire policy has many regulations that potentially inhibited the use of climate information for decision-making. It was also determined that because fire use is a human decision, it would be more informative to ask fire managers themselves how climate impacts fire use through their decision-making processes, and whether or not they use climate information for prescribed fire. The first task for this project was to complete a regional survey of prescribed fire managers in California and Nevada. During the second phase of the project, additional prescribed fire managers were surveyed across the country. During the third year a second survey of WFU managers was completed. The goals of these inquiries were to determine: 1) If fire managers use climate information for fuels management; 2) The perspective fire managers have towards climate affecting fuels management; 3) Determine any obstacles that make it difficult to use climate information for fuels management; and 4) Determine climate information managers need to help them make better decisions for fire use.

An Object-Based Approach to Evaluation of Climate Variability Projections and Predictions

NASA Astrophysics Data System (ADS)

Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.

2017-12-01

Evaluations of the performance of earth system model predictions and projections are of critical importance to enhance usefulness of these products. Such evaluations need to address specific concerns depending on the system and decisions of interest; hence, evaluation tools must be tailored to inform about specific issues. Traditional approaches that summarize grid-based comparisons of analyses and models, or between current and future climate, often do not reveal important information about the models' performance (e.g., spatial or temporal displacements; the reason behind a poor score) and are unable to accommodate these specific information needs. For example, summary statistics such as the correlation coefficient or the mean-squared error provide minimal information to developers, users, and decision makers regarding what is "right" and "wrong" with a model. New spatial and temporal-spatial object-based tools from the field of weather forecast verification (where comparisons typically focus on much finer temporal and spatial scales) have been adapted to more completely answer some of the important earth system model evaluation questions. In particular, the Method for Object-based Diagnostic Evaluation (MODE) tool and its temporal (three-dimensional) extension (MODE-TD) have been adapted for these evaluations. More specifically, these tools can be used to address spatial and temporal displacements in projections of El Nino-related precipitation and/or temperature anomalies, ITCZ-associated precipitation areas, atmospheric rivers, seasonal sea-ice extent, and other features of interest. Examples of several applications of these tools in a climate context will be presented, using output of the CESM large ensemble. In general, these tools provide diagnostic information about model performance - accounting for spatial, temporal, and intensity differences - that cannot be achieved using traditional (scalar) model comparison approaches. Thus, they can provide more meaningful information that can be used in decision-making and planning. Future extensions and applications of these tools in a climate context will be considered.

The Use of Economic Evidence to Inform Drug Pricing Decisions in Jordan.

PubMed

Hammad, Eman A

2016-01-01

Drug pricing is an example of a priority setting in a developing country with official requirements for the use of cost-effectiveness (CE) evidence. To describe the role of economic evidence in drug pricing decisions in Jordan. A prospective review of all applications submitted between November 2013 and May 2015 to the Jordan Food and Drug Association's drug pricing committee was carried out. All applications that involved requests for CE evidence were reviewed. Details on the type of study, the extent, and whether the evidence submitted was part of the formal deliberations were extracted and summarized. The committee reviewed a total of 1608 drug pricing applications over the period of the study. CE evidence was requested in only 11 applications. The submitted evidence was of limited use to the committee due to concerns about quality, relevance of studies, and lack of pharmacoeconomic expertise. There were also no clear rules describing how CE would inform pricing decisions. Limited local data and health economic experience were the main barriers to the use of economic evidence in drug pricing decisions in Jordan. In addition, there are no official rules describing the elements and process by which the CE evidence would inform drug pricing decisions. This study summarized accumulated observations for the current use of economic evaluations and evidence-based decision making in Jordan. Recommendations have been proposed to applicants and key decision makers to enhance the role of economic evidence in influencing health policies and evidence-based decision making across priority settings. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

How are genetic test results being used by Australian life insurers?

PubMed

Barlow-Stewart, K; Liepins, M; Doble, A; Otlowski, M

2018-06-11

In Australia, the USA and many Asian countries the life insurance industry is self-regulated. Individuals must disclose genetic test results known to them in applications for new or updated policies including cover for critical care, income protection and death. There is limited information regarding how underwriting decisions are made for policies with such disclosures. The Australian Financial Services Council (FSC) provided de-identified data collected on applications with genetic test result disclosure from its life insurance member companies 2010-2013 to enable repetition of an independent examination undertaken of applications 1999-2003: age; gender; genetic condition; testing result; decision-maker; and insurance cover. Data was classified as to test result alone or additional other factors relevant to risk and decision. Where necessary, the FSC facilitated clarification by insurers. 345/548 applications related to adult-onset conditions. The genetic test result solely influenced the decision in 165/345 applications: positive (n = 23), negative (n = 139) and pending (n = 3). Detailed analyses of the decisions in each of these result categories are presented with specific details of 11 test cases. Policies with standard decisions were provided for all negative test results with evidence of reassessment of previous non-standard decisions and 20/23 positive results with recognition of risk reduction strategies. Disclosure of positive results for breast/ovarian cancer, Lynch syndrome and hereditary spastic paraplegia, and three pending results, generated non-standard decisions. The examination demonstrates some progress in addressing concerns in regard to utilisation of genetic test information but the self-regulatory system in Australia only goes some way in meeting internationally recommended best practice.

Assessing the near-term risk of climate uncertainty : interdependencies among the U.S. states.

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

Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.

2010-04-01

Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-modelmore » ensemble from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.« less

Providing rapid climate risk assessments to support cities (Invited)

NASA Astrophysics Data System (ADS)

Rosenzweig, C.; Solecki, W.; Horton, R. M.; Bader, D.; Ali, S.

2013-12-01

Hurricane Sandy struck the East Coast of the United States on October 29, 2012 and brought the issue of urban resilience to the forefront of public discussion not only in New York City, but in cities around the world. While Hurricane Sandy as an individual extreme climate event cannot be attributed to climate change, it can serve as a warning for cities regarding disaster risks, focus attention on the importance of reducing climate vulnerability, and the need to include increasing climate risks and resilience into rebuilding programs. As severe as Sandy was, the the storm could have been much worse. The science behind potential impacts was ';in place' and ';in time,' i.e., climate risks were well understood before the storm, due to work by scientists in the region starting in the late 1990s. In the wake of this transformative storm, the rebuilding process in New York is being informed by the potential for a changing climate. The $20 billion Special Initiative for Rebuilding and Resiliency (SIRR) Plan for New York is grounded upon climate risk information provided by the New York City Panel on Climate Change (NPCC). This expert panel, tasked with advising on the City on climate-related issues, completed a 'rapid response' climate assessment with updated climate projections and coastal flood maps. Cities are emerging as the ';first responders' to climate change in both adaptation and mitigation. Their efforts are playing a role in catalyzing national and international responses as well. New York City's actions in the wake of Hurricane Sandy are an example of a positive tipping-point response. The Urban Climate Change Research Network, a consortium of over 450 scholars and practitioners in developing and developed country cities around the world, was established in 2007 to enhance science-based decision-making on climate and other sustainability related issues in urban areas around the world. The UCCRN's first major publication is the First UCCRN Assessment Report on Climate Change and Cities (ARC3), which represents a four-year effort by 110 authors from 50+ cities around the world, and is the first ever global, interdisciplinary, science-based assessment to address climate risks, adaptation, mitigation, and policy mechanisms relevant to cities. The UCCRN has initiated the process of developing the Second UCCRN Report on Climate Change and Cities (ARC3-2), to facilitate ongoing and active learning and to continue providing practical, evidence-based guidance for city decision-makers.

[Development of APSIM (agricultural production systems simulator) and its application].

PubMed

Shen, Yuying; Nan, Zhibiao; Bellotti, Bill; Robertson, Michael; Chen, Wen; Shao, Xinqing

2002-08-01

Soil-crop simulator model is an effective tool for providing decision on agricultural management. APSIM (Agricultural Production Systems Simulator) was developed to simulate the biophysical process in farming system, and particularly in the economic and ecological features of the systems under climatic risk. The current literatures revealed that APSIM could be applied in wide zone, including temperate continental, temperate maritime, sub-tropic and arid climate, and Mediterranean climates, with the soil type of clay, duplex soil, vertisol, silt sandy, silt loam and silt clay loam. More than 20 crops have been simulated well. APSIM is powerful on describing crop structure, crop sequence, yield prediction, and quality control as well as erosion estimation under different planting pattern.

WWOSC 2014: Research Needs for Better Health Resilience to Weather Hazards

PubMed Central

Jancloes, Michel; Anderson, Vidya; Gosselin, Pierre; Mee, Carol; Chong, Nicholas J.

2015-01-01

The first World Weather Open Science Conference (WWOSC, held from 17–21 August 2014 in Montreal, Québec), provided an open forum where the experience and perspective of a variety of weather information providers and users was combined with the latest application advances in social sciences. A special session devoted to health focused on how best the most recent weather information and communication technologies (ICT) could improve the health emergency responses to disasters resulting from natural hazards. Speakers from a plenary presentation and its corresponding panel shared lessons learnt from different international multidisciplinary initiatives against weather-related epidemics, such as malaria, leptospirosis and meningitis and from public health responses to floods and heat waves such as in Ontario and Quebec, Canada. Participants could bear witness to recent progress made in the use of forecasting tools and in the application of increased spatiotemporal resolutions in the management of weather related health risks through anticipative interventions, early alert and warning and early responses especially by vulnerable groups. There was an agreement that resilience to weather hazards is best developed based on evidence of their health impact and when, at local level, there is a close interaction between health care providers, epidemiologists, climate services, public health authorities and communities. Using near real time health data (such as hospital admission, disease incidence monitoring…) combined with weather information has been recommended to appraise the relevance of decisions and the effectiveness of interventions and to make adjustments when needed. It also helps appraising how people may be more or less vulnerable to a particular hazard depending on the resilience infrastructures and services. This session was mainly attended by climate, environment and social scientists from North American and European countries. Producing a commentary appears to be an effective way to share this session’s conclusions to research institutions and public health experts worldwide. It also advocates for better linking operational research and decision making and for appraising the impact of ICT and public health interventions on health. PMID:25809508

Assessments of regional climate change and its impacts in Northern Europe

NASA Astrophysics Data System (ADS)

Omstedt, Anders; von Storch, Hans; Reckermann, Marcus; Quante, Markus

2015-04-01

Regional climate change assessments are urgently needed to complement the big picture with regional results and scenarios of higher resolution and with relevance for local decision makers and stakeholders. A new type of assessment report originated in the original BACC report of 2008 (BALTEX Assessment of Climate Change for the Baltic Sea region) which has served as role model for other assessments published or in preparation. It represents an approach to assessing and making available current knowledge on regional climate change and its regional impacts on the physical, biogeochemical and biological environment (ecosystems, socio-economic sphere). Reports of this type which are available or underway are the original BACC book (2008), the second BACC book (2015), the climate report for the greater Hamburg area (2011), and the NOSCCA report (North Sea Climate Change Assessment) which is expected to be published in 2016. The assessments are produced by teams of scientists from the region, led by lead authors who recruit experts from relevant topics to contribute. The process is not externally funded and completely based on published scientific evidence, and not biased by political or economic interest groups. The BACC-type reports aim to bring together consolidated knowledge that has broad consensus in the scientific community, but also acknowledging issues for which contradicting opinions are found in the literature, so that no consensus can be reached ("consensus on dissensus"). An international steering committee is responsible for overlooking the process, and all manuscripts are anonymously peer-reviewed by independent international experts. An outstanding outreach aspect of these reports is the close collaboration with regional stakeholders (for the BACC reports: HELCOM, the intergovernmental Baltic Marine Environment Protection Commission and the major regional science-policy interface in the Baltic Sea region; for the Hamburg climate report: the Hamburg city government; for NOSCCA: OSPAR, the intergovernmental commission for protecting and conserving the North-East Atlantic and its resources).

Serving California's Science and Governance Needs through Crisis-driven Collaborations

NASA Astrophysics Data System (ADS)

Bernacchi, L.

2015-12-01

Due to its magnitude, the ongoing drought in California (USA) serves as an experimental space for innovative resource management and will define responses to predicted widespread drought. Due to the magnitude of its effect on humans and natural ecosystems and the water resources on which they depend, governmental programs are granting support to scientifically-valid, locally-produced solutions to water scarcity. Concurrently, University of California Water (UC Water) Security and Sustainability Research Initiative is focused on strategic research to build the knowledge base for better water resources management. This paper examines how a team of transdisciplinary scientists are engaged in water governance and information, providing examples of actionable research successfully implemented by decision makers. From a sociology of science perspective, UC Water scientists were interviewed about their engagement practices with California water decision makers. Their "co-production of knowledge" relationships produce effective responses to climatic, landcover and population changes by expanding from singularly information-based, unidirectional communication to governance-relevant, co-constructed knowledge and wisdom. This is accomplished by serving on decision making organizational boards and developing information in a productive format. The perceived crisis of California's drought is an important impetus in cross-sector collaborations, and in combination with governance and institution parameters, defines the inquiry and decision space. We conclude by describing a process of clear problem-solution definition made possible through transparent communication, salient and credible information, and relevant tools and techniques for interpreting scientific findings.

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

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.

2017-12-01

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

Why should health be a central argument in climate negotiations? Can a MOOC help to bring the message across?

PubMed

Sauerborn, Rainer

There are four key messages from health for climate negotiations. Two positive ones include (i) health as a motivator for action and policy and (ii) huge health co-benefits to be included in the cost-benefit trade-offs of climate negotiations. Two warning messages: (iii) there are health-based absolute limits of adaptations and (iv) hotter average temperatures will cut work productivity of farmers and other outdoor workers as well as workers in non-air conditioned factories in poor countries. This paper will examine how massive open online courses (MOOCs) have been used in the run-up to this COP to disseminate these four messages to the audience of high-level policy-makers. This required a departure from the classic MOOC format in several ways: duration, focus on decision-making rationale, policy-relevant messages presented in big brush, leaving "traceable accounts" to evidence in two layers of resources provided: essential and "deep dive".

Reading the water table: The interaction between literacy practices and groundwater management training in preparing farmers for climate change in South India

NASA Astrophysics Data System (ADS)

Chavva, Konda Reddy; Smith, Cristine A.

2012-06-01

This article focuses on farmers' use of literacy for individual decision-making on crop-water management and crop choices and investigates how farmer participants perceive the usefulness of Farmer Water School (FWS) training. It draws upon a study conducted with farmers of Kurnool district of Andhra Pradesh, India. This study has demonstrated that literacy skills, while valued, are not a prerequisite for all farmers to improve their groundwater and crop management, as long as training includes (1) the presence of at least some literate farmers, (2) activities that involve learning by doing, and (3) learning in small mixed groups of literate and non-literate participants. The study outcomes are of increasing relevance in the context of climate change and variability, as small and marginal farmers constitute over 87 per cent of Indian farmers. Their inability to cope with consequences of climate change could adversely affect the food security in the country.

Integrated Management of Residential Indoor Air Quality: A Call for Stakeholders in a Changing Climate.

PubMed

Levasseur, Marie-Eve; Poulin, Patrick; Campagna, Céline; Leclerc, Jean-Marc

2017-11-25

A paradigm change in the management of environmental health issues has been observed in recent years: instead of managing specific risks individually, a holistic vision of environmental problems would assure sustainable solutions. However, concrete actions that could help translate these recommendations into interventions are lacking. This review presents the relevance of using an integrated indoor air quality management approach to ensure occupant health and comfort. At the nexus of three basic concepts (reducing contaminants at the source, improving ventilation, and, when relevant, purifying the indoor air), this approach can help maintain and improve indoor air quality and limit exposure to several contaminants. Its application is particularly relevant in a climate change context since the evolving outdoor conditions have to be taken into account during building construction and renovation. The measures presented through this approach target public health players, building managers, owners, occupants, and professionals involved in building design, construction, renovation, and maintenance. The findings of this review will help the various stakeholders initiate a strategic reflection on the importance of indoor air quality and climate change issues for existing and future buildings. Several new avenues and recommendations are presented to set the path for future research activities.

Integrated Management of Residential Indoor Air Quality: A Call for Stakeholders in a Changing Climate

PubMed Central

Levasseur, Marie-Eve; Poulin, Patrick; Campagna, Céline; Leclerc, Jean-Marc

2017-01-01

A paradigm change in the management of environmental health issues has been observed in recent years: instead of managing specific risks individually, a holistic vision of environmental problems would assure sustainable solutions. However, concrete actions that could help translate these recommendations into interventions are lacking. This review presents the relevance of using an integrated indoor air quality management approach to ensure occupant health and comfort. At the nexus of three basic concepts (reducing contaminants at the source, improving ventilation, and, when relevant, purifying the indoor air), this approach can help maintain and improve indoor air quality and limit exposure to several contaminants. Its application is particularly relevant in a climate change context since the evolving outdoor conditions have to be taken into account during building construction and renovation. The measures presented through this approach target public health players, building managers, owners, occupants, and professionals involved in building design, construction, renovation, and maintenance. The findings of this review will help the various stakeholders initiate a strategic reflection on the importance of indoor air quality and climate change issues for existing and future buildings. Several new avenues and recommendations are presented to set the path for future research activities. PMID:29186831

Evaluating the Performance of a Climate-Driven Mortality Model during Heat Waves and Cold Spells in Europe

PubMed Central

Lowe, Rachel; Ballester, Joan; Creswick, James; Robine, Jean-Marie; Herrmann, François R.; Rodó, Xavier

2015-01-01

The impact of climate change on human health is a serious concern. In particular, changes in the frequency and intensity of heat waves and cold spells are of high relevance in terms of mortality and morbidity. This demonstrates the urgent need for reliable early-warning systems to help authorities prepare and respond to emergency situations. In this study, we evaluate the performance of a climate-driven mortality model to provide probabilistic predictions of exceeding emergency mortality thresholds for heat wave and cold spell scenarios. Daily mortality data corresponding to 187 NUTS2 regions across 16 countries in Europe were obtained from 1998–2003. Data were aggregated to 54 larger regions in Europe, defined according to similarities in population structure and climate. Location-specific average mortality rates, at given temperature intervals over the time period, were modelled to account for the increased mortality observed during both high and low temperature extremes and differing comfort temperatures between regions. Model parameters were estimated in a Bayesian framework, in order to generate probabilistic simulations of mortality across Europe for time periods of interest. For the heat wave scenario (1–15 August 2003), the model was successfully able to anticipate the occurrence or non-occurrence of mortality rates exceeding the emergency threshold (75th percentile of the mortality distribution) for 89% of the 54 regions, given a probability decision threshold of 70%. For the cold spell scenario (1–15 January 2003), mortality events in 69% of the regions were correctly anticipated with a probability decision threshold of 70%. By using a more conservative decision threshold of 30%, this proportion increased to 87%. Overall, the model performed better for the heat wave scenario. By replacing observed temperature data in the model with forecast temperature, from state-of-the-art European forecasting systems, probabilistic mortality predictions could potentially be made several months ahead of imminent heat waves and cold spells. PMID:25625407

Quantifying the Sources and Sinks of Greenhouse Gases: What Does It Take to Satisfy Scientific and Decision-Making Needs?

NASA Astrophysics Data System (ADS)

Davis, K. J.; Keller, K.; Ogle, S. M.; Smith, S.

2014-12-01

Changes in the sources and sinks of greenhouse gases (GHGs) are key drivers of anthropogenic climate change. It is hence not surprising that current and emerging U.S. governmental science priorities and programs focused on climate change (e.g. a U.S. Carbon Cycle Science Plan; the U.S. Carbon Cycle Science Program, the U.S. Global Change Research Program, Executive Order 13653 'Preparing the U.S. for the Impacts of Climate Change') all call for an improved understanding of these sources and sinks.. Measurements of the total atmospheric burden of these gases are well established, but measurements of their sources and sinks are difficult to make over spatial and temporal scales that are relevant for scientific and decisionmaking needs. Quantifying the uncertainty in these measurements is particularly challenging. This talk reviews the intersection of the state of knowledge of GHG sources and sinks, focusing in particular on CO2 and CH4, and science and decision-making needs for this information. Different science and decision-making needs require differing levels of uncertainty. A number of high-priority needs (early detection of changes in the Earth system, projections of future climate, support of markets or regulations) often require a high degree of accuracy and/or precision. We will critically evaluate current U.S. planning to documents to infer current perceived needs for GHG source/sink quantification, attempting to translate these needs into quantitative uncertainty metrics. We will compare these perceived needs with the current state of the art of GHG source/sink quantification, including the apparent pattern of systematic differences between so-called "top down" and "bottom-up" flux estimates. This comparison will enable us to identify where needs can be readily satisfied, and where gaps in technology exist. Finally, we will examine what steps could be taken to close existing gaps.

Evaluating the performance of a climate-driven mortality model during heat waves and cold spells in Europe.

PubMed

Lowe, Rachel; Ballester, Joan; Creswick, James; Robine, Jean-Marie; Herrmann, François R; Rodó, Xavier

2015-01-23

The impact of climate change on human health is a serious concern. In particular, changes in the frequency and intensity of heat waves and cold spells are of high relevance in terms of mortality and morbidity. This demonstrates the urgent need for reliable early-warning systems to help authorities prepare and respond to emergency situations. In this study, we evaluate the performance of a climate-driven mortality model to provide probabilistic predictions of exceeding emergency mortality thresholds for heat wave and cold spell scenarios. Daily mortality data corresponding to 187 NUTS2 regions across 16 countries in Europe were obtained from 1998-2003. Data were aggregated to 54 larger regions in Europe, defined according to similarities in population structure and climate. Location-specific average mortality rates, at given temperature intervals over the time period, were modelled to account for the increased mortality observed during both high and low temperature extremes and differing comfort temperatures between regions. Model parameters were estimated in a Bayesian framework, in order to generate probabilistic simulations of mortality across Europe for time periods of interest. For the heat wave scenario (1-15 August 2003), the model was successfully able to anticipate the occurrence or non-occurrence of mortality rates exceeding the emergency threshold (75th percentile of the mortality distribution) for 89% of the 54 regions, given a probability decision threshold of 70%. For the cold spell scenario (1-15 January 2003), mortality events in 69% of the regions were correctly anticipated with a probability decision threshold of 70%. By using a more conservative decision threshold of 30%, this proportion increased to 87%. Overall, the model performed better for the heat wave scenario. By replacing observed temperature data in the model with forecast temperature, from state-of-the-art European forecasting systems, probabilistic mortality predictions could potentially be made several months ahead of imminent heat waves and cold spells.

A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.

PubMed

Leibfried, Felix; Braun, Daniel A

2015-08-01

Rate distortion theory describes how to communicate relevant information most efficiently over a channel with limited capacity. One of the many applications of rate distortion theory is bounded rational decision making, where decision makers are modeled as information channels that transform sensory input into motor output under the constraint that their channel capacity is limited. Such a bounded rational decision maker can be thought to optimize an objective function that trades off the decision maker's utility or cumulative reward against the information processing cost measured by the mutual information between sensory input and motor output. In this study, we interpret a spiking neuron as a bounded rational decision maker that aims to maximize its expected reward under the computational constraint that the mutual information between the neuron's input and output is upper bounded. This abstract computational constraint translates into a penalization of the deviation between the neuron's instantaneous and average firing behavior. We derive a synaptic weight update rule for such a rate distortion optimizing neuron and show in simulations that the neuron efficiently extracts reward-relevant information from the input by trading off its synaptic strengths against the collected reward.

Variability of basin scale water resources indicators derived from global hydrological and land surface models

NASA Astrophysics Data System (ADS)

Werner, Micha; Blyth, Eleanor; Schellekens, Jaap

2016-04-01

Global hydrological and land-surface models are becoming increasingly available, and as the resolution of these improves, as well how hydrological processes are represented, so does their potential. These offer consistent datasets at the global scale, which can be used to establish water balances and derive policy relevant indicators in medium to large basins, including those that are poorly gauged. However, differences in model structure, model parameterisation, and model forcing may result in quite different indicator values being derived, depending on the model used. In this paper we explore indicators developed using four land surface models (LSM) and five global hydrological models (GHM). Results from these models have been made available through the Earth2Observe project, a recent research initiative funded by the European Union 7th Research Framework. All models have a resolution of 0.5 arc degrees, and are forced using the same WATCH-ERA-Interim (WFDEI) meteorological re-analysis data at a daily time step for the 32 year period from 1979 to 2012. We explore three water resources indicators; an aridity index, a simplified water exploitation index; and an indicator that calculates the frequency of occurrence of root zone stress. We compare indicators derived over selected areas/basins in Europe, Colombia, Southern Africa, the Indian Subcontinent and Australia/New Zealand. The hydrological fluxes calculated show quite significant differences between the nine models, despite the common forcing dataset, with these differences reflected in the indicators subsequently derived. The results show that the variability between models is related to the different climates types, with that variability quite logically depending largely on the availability of water. Patterns are also found in the type of models that dominate different parts of the distribution of the indicator values, with LSM models providing lower values, and GHM models providing higher values in some climates, and vice versa in others. How important this variability is in supporting a policy decision, depends largely on how a decision thresholds are set. For example in the case of the aridity index, with areas being denoted as arid with an index of 0.6 or above, we show that the variability is primarily of interest in transitional climates, such as the Mediterranean The analysis shows that while both LSM's and GHM's provide useful data, indices derived to support water resources management planning may differ substantially, depending on the model used. The analysis also identifies in which climates improvements to the models are particularly relevant to support the confidence with which decisions can be taken based on derived indicators.

Development of Joint Climate and Discharge Projections for the International Rhine River Basin - the CHR RheinBlick2050 Project

NASA Astrophysics Data System (ADS)

Görgen, K.; Pfister, L.

2008-12-01

The anticipated climate change will lead to modified hydro-meteorological regimes that influence discharge behaviour and hydraulics of rivers. This has variable impacts on managed (anthropogenic) and unmanaged (natural) systems, depending on their sensitivity and vulnerability (ecology, economy, infrastructure, transport, energy production, water management, etc.). Decision makers in these contexts need adequate adaptation strategies to minimize adverse effects of climate change, i.e. an improved knowledge on the potential impacts including uncertainties means an extension of the informed options open to users. The goal of the highly applied study presented here is the development of joint, consistent climate and discharge projections for the international Rhine River catchments (Switzerland, France, Germany, Netherlands) in order to assess future changes of hydro-meteorological regimes in the meso- and macroscale Rhine River catchments and to derive and improve the understanding of such impacts on hydrologic and hydraulic processes. The RheinBlick2050 project is an international effort initiated by the International Commission for the Hydrology of the Rhine Basin (CHR) in close cooperation with the International Commission for the Protection of the Rhine. The core experiment design foresees a data-synthesis, multi-model approach where (transient) (bias- corrected) regional climate change projections are used as forcing data for existing calibrated hydrological (and hydraulic) models at a daily temporal resolution over mesoscale catchments of the Rhine River. Mainly for validation purposes, hydro-meteorological observations from national weather services are compiled into a new consistent 5 km x 5 km reference dataset from 1961 to 2005. RCM data are mainly used from the ENSEMBLES project and other existing dynamical downscaling model runs to derive probabilistic ensembles and thereby also access uncertainties on a regional scale. A benchmarking is helping to identify those atmospheric forcing data that ideally suit the needs for the subsequent hydrological model runs with the LARSIM and HBV models and evaluate those simulations too. As a result, usable information and quantifiable statements (e.g. extreme value statistics, uncertainty assessment, validation), that might form the basis for further planning or policy relevant decisions, are to be derived. Our analyses are highly influenced by the requirements of the potential users and stakeholders from government agencies who shall make use of the data and results. Here we present first results of the application of the complete data processing and modelling chain towards discharge projections on a subset of input data, albeit still without any bias correction applied to the meteorological forcing data.

The Irrelevance of the Risk-Uncertainty Distinction.

PubMed

Roser, Dominic

2017-10-01

Precautionary Principles are often said to be appropriate for decision-making in contexts of uncertainty such as climate policy. Contexts of uncertainty are contrasted to contexts of risk depending on whether we have probabilities or not. Against this view, I argue that the risk-uncertainty distinction is practically irrelevant. I start by noting that the history of the distinction between risk and uncertainty is more varied than is sometimes assumed. In order to examine the distinction, I unpack the idea of having probabilities, in particular by distinguishing three interpretations of probability: objective, epistemic, and subjective probability. I then claim that if we are concerned with whether we have probabilities at all-regardless of how low their epistemic credentials are-then we almost always have probabilities for policy-making. The reason is that subjective and epistemic probability are the relevant interpretations of probability and we almost always have subjective and epistemic probabilities. In contrast, if we are only concerned with probabilities that have sufficiently high epistemic credentials, then we obviously do not always have probabilities. Climate policy, for example, would then be a case of decision-making under uncertainty. But, so I argue, we should not dismiss probabilities with low epistemic credentials. Rather, when they are the best available probabilities our decision principles should make use of them. And, since they are almost always available, the risk-uncertainty distinction remains irrelevant.

7 CFR 3550.5 - Environmental requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Policy. RHS will consider environmental quality as equal with economic, social, and other relevant factors in program development and decision-making processes. RHS will take into account potential environmental impacts of proposed projects by working with RHS applicants, other federal agencies, Indian tribes...

Constructing Perceptions of Climate Change: a case study of regional political decision makers

NASA Astrophysics Data System (ADS)

Bray, D.

2012-12-01

This case study of climate change communications assesses the salient means of communication and the message adopted by regional political decision makers on the German Baltic coast. Realizing that cultural factors and local values (and not simply knowledge) are significant influences in explaining attitudes towards climate change, this analysis draws from the records of regional weather, from scientists with a specific focus on the region, from the political decision makers for that region, and the media message reaching the decision makers, ensuring all elements of the analysis are drawn from the same socioeconomic, geophysical, political and cultural context. This is important as the social dynamics surrounding the trust in science is of critical importance and, as such, all elements of the case study are specifically contained within a common context. If the utility of climate change knowledge is to prompt well conceived adaptation/mitigation strategies then the political decision process, or at least the perceptions shaping it, can best be understood by locating it within the world view of the decision makers involved in the production process. Using the results of two survey questionnaires, one of regional climate scientists and one of regional political decision makers, ten years of local weather records, and a summary of the message from mass media circulation, the discord in perceptions of regional climate change are quantitatively explored. The conclusions drawn from the analysis include, compared to the scientific assessment: The decision makers' perceptions of recent past differ from actual observations. The decision makers' perceptions of the future differ from scientific assessments. The decision makers tend to over estimate the magnitude of regional climate change and its impacts. The decision makers tend to over estimate the sense of immediacy for adaptation measures. The conclusions drawn suggest that in the regional political realm, it is often a social construction of climate change, not scientific claims, that are shaping decisions. While certainty is the common demand of those charged with making decisions concerning climate change, certainty is the quality that seems to be given least value in taking action. Weather records are all but ignored. The direct voice of scientists was heeded but not fully accepted. In the transition, the truth-to-power model appears to be somewhat modified, whereby power states that the future will be different, but the difference is determined by other sources; shaping images of risk and danger. One could not deny that climate and sea level have always been forces shaping patterns of human settlement. And one could not deny that perhaps the time is nigh to reassess the human relationship with nature. However, any measure considered should be done so with a rational sense of objectivity. To do otherwise, there is the risk of misallocating scare resources.

Utility of biological sensor tags in animal conservation.

PubMed

Wilson, A D M; Wikelski, M; Wilson, R P; Cooke, S J

2015-08-01

Electronic tags (both biotelemetry and biologging platforms) have informed conservation and resource management policy and practice by providing vital information on the spatial ecology of animals and their environments. However, the extent of the contribution of biological sensors (within electronic tags) that measure an animal's state (e.g., heart rate, body temperature, and details of locomotion and energetics) is less clear. A literature review revealed that, despite a growing number of commercially available state sensor tags and enormous application potential for such devices in animal biology, there are relatively few examples of their application to conservation. Existing applications fell under 4 main themes: quantifying disturbance (e.g., ecotourism, vehicular and aircraft traffic), examining the effects of environmental change (e.g., climate change), understanding the consequences of habitat use and selection, and estimating energy expenditure. We also identified several other ways in which sensor tags could benefit conservation, such as determining the potential efficacy of management interventions. With increasing sensor diversity of commercially available platforms, less invasive attachment techniques, smaller device sizes, and more researchers embracing such technology, we suggest that biological sensor tags be considered a part of the necessary toolbox for conservation. This approach can measure (in real time) the state of free-ranging animals and thus provide managers with objective, timely, relevant, and accurate data to inform policy and decision making. © 2015 Society for Conservation Biology.

Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

NASA Astrophysics Data System (ADS)

White, C. J.; Franks, S. W.; McEvoy, D.

2015-06-01

Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

Assessing Interventions to Manage West Nile Virus Using Multi-Criteria Decision Analysis with Risk Scenarios

PubMed Central

Hongoh, Valerie; Campagna, Céline; Panic, Mirna; Samuel, Onil; Gosselin, Pierre; Waaub, Jean-Philippe; Ravel, André; Samoura, Karim; Michel, Pascal

2016-01-01

The recent emergence of West Nile virus (WNV) in North America highlights vulnerability to climate sensitive diseases and stresses the importance of preventive efforts to reduce their public health impact. Effective prevention involves reducing environmental risk of exposure and increasing adoption of preventive behaviours, both of which depend on knowledge and acceptance of such measures. When making operational decisions about disease prevention and control, public health must take into account a wide range of operational, environmental, social and economic considerations in addition to intervention effectiveness. The current study aimed to identify, assess and rank possible risk reduction measures taking into account a broad set of criteria and perspectives applicable to the management of WNV in Quebec under increasing transmission risk scenarios, some of which may be related to ongoing warming in higher-latitude regions. A participatory approach was used to collect information on categories of concern to relevant stakeholders with respect to WNV prevention and control. Multi-criteria decision analysis was applied to examine stakeholder perspectives and their effect on strategy rankings under increasing transmission risk scenarios. Twenty-three preventive interventions were retained for evaluation using eighteen criteria identified by stakeholders. Combined evaluations revealed that, at an individual-level, inspecting window screen integrity, wearing light colored, long clothing, eliminating peridomestic larval sites and reducing outdoor activities at peak times were top interventions under six WNV transmission scenarios. At a regional-level, the use of larvicides was a preferred strategy in five out of six scenarios, while use of adulticides and dissemination of sterile male mosquitoes were found to be among the least favoured interventions in almost all scenarios. Our findings suggest that continued public health efforts aimed at reinforcing individual-level preventive behaviours combined with the application of larvicides to manage the risk of WNV infection are the interventions most acceptable and effective at reaching current management objectives now and under future theoretical transmission risk. PMID:27494136

Climate Change Impacts at Department of Defense

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

Kotamarthi, Rao; Wang, Jiali; Zoebel, Zach

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

ClimateWizard: A Framework and Easy-to-Use Web-Mapping Tool for Global, Regional, and Local Climate-Change Analysis

NASA Astrophysics Data System (ADS)

Girvetz, E. H.; Zganjar, C.; Raber, G. T.; Hoekstra, J.; Lawler, J. J.; Kareiva, P.

2008-12-01

Now that there is overwhelming evidence of global climate change, scientists, managers and planners (i.e. practitioners) need to assess the potential impacts of climate change on particular ecological systems, within specific geographic areas, and at spatial scales they care about, in order to make better land management, planning, and policy decisions. Unfortunately, this application of climate science to real world decisions and planning has proceeded too slowly because we lack tools for translating cutting-edge climate science and climate-model outputs into something managers and planners can work with at local or regional scales (CCSP 2008). To help increase the accessibility of climate information, we have developed a freely-available, easy-to-use, web-based climate-change analysis toolbox, called ClimateWizard, for assessing how climate has and is projected to change at specific geographic locations throughout the world. The ClimateWizard uses geographic information systems (GIS), web-services (SOAP/XML), statistical analysis platforms (e.g. R- project), and web-based mapping services (e.g. Google Earth/Maps, KML/GML) to provide a variety of different analyses (e.g. trends and departures) and outputs (e.g. maps, graphs, tables, GIS layers). Because ClimateWizard analyzes large climate datasets stored remotely on powerful computers, users of the tool do not need to have fast computers or expensive software, but simply need access to the internet. The analysis results are then provided to users in a Google Maps webpage tailored to the specific climate-change question being asked. The ClimateWizard is not a static product, but rather a framework to be built upon and modified to suit the purposes of specific scientific, management, and policy questions. For example, it can be expanded to include bioclimatic variables (e.g. evapotranspiration) and marine data (e.g. sea surface temperature), as well as improved future climate projections, and climate-change impact analyses involving hydrology, vegetation, wildfire, disease, and food security. By harnessing the power of computer and web- based technologies, the ClimateWizard puts local, regional, and global climate-change analyses in the hands of a wider array of managers, planners, and scientists.

Estimating the Health Effects of Greenhouse Gas Mitigation Strategies: Addressing Parametric, Model, and Valuation Challenges

PubMed Central

Hess, Jeremy J.; Ebi, Kristie L.; Markandya, Anil; Balbus, John M.; Wilkinson, Paul; Haines, Andy; Chalabi, Zaid

2014-01-01

Background: Policy decisions regarding climate change mitigation are increasingly incorporating the beneficial and adverse health impacts of greenhouse gas emission reduction strategies. Studies of such co-benefits and co-harms involve modeling approaches requiring a range of analytic decisions that affect the model output. Objective: Our objective was to assess analytic decisions regarding model framework, structure, choice of parameters, and handling of uncertainty when modeling health co-benefits, and to make recommendations for improvements that could increase policy uptake. Methods: We describe the assumptions and analytic decisions underlying models of mitigation co-benefits, examining their effects on modeling outputs, and consider tools for quantifying uncertainty. Discussion: There is considerable variation in approaches to valuation metrics, discounting methods, uncertainty characterization and propagation, and assessment of low-probability/high-impact events. There is also variable inclusion of adverse impacts of mitigation policies, and limited extension of modeling domains to include implementation considerations. Going forward, co-benefits modeling efforts should be carried out in collaboration with policy makers; these efforts should include the full range of positive and negative impacts and critical uncertainties, as well as a range of discount rates, and should explicitly characterize uncertainty. We make recommendations to improve the rigor and consistency of modeling of health co-benefits. Conclusion: Modeling health co-benefits requires systematic consideration of the suitability of model assumptions, of what should be included and excluded from the model framework, and how uncertainty should be treated. Increased attention to these and other analytic decisions has the potential to increase the policy relevance and application of co-benefits modeling studies, potentially helping policy makers to maximize mitigation potential while simultaneously improving health. Citation: Remais JV, Hess JJ, Ebi KL, Markandya A, Balbus JM, Wilkinson P, Haines A, Chalabi Z. 2014. Estimating the health effects of greenhouse gas mitigation strategies: addressing parametric, model, and valuation challenges. Environ Health Perspect 122:447–455; http://dx.doi.org/10.1289/ehp.1306744 PMID:24583270

Application of data on climate extremes for the southwestern United States

NASA Astrophysics Data System (ADS)

Redmond, K. T.; Fleishman, E.; Cayan, D. R.; Daudert, B.; Gershunov, A.

2015-12-01

We are improving the scientific capacity to evaluate responses of natural resources to climate extremes. We also are enhancing a platform for derivation of and access to customized climate information for the full extent or any subset of the southwestern United States. Extreme climate can have substantial effects on species, ecological and evolutionary processes, and the health of visitors to public lands. We are working with federal and state managers and with researchers who collaborate with decision-makers to use data on climate extremes to inform resource management. Current applications include sudden oak death, estuarine management, and fine-resolution manipulation of montane vegetation. To facilitate practical use of data on climate extremes, we are screening global climate models on the basis of their realism in representing natural regional patterns and extremes of temperature and precipitation, including those driven by El Niño and La Niña. We are assessing how well each model represents different climate elements. We also are delivering point and gridded observations and downscaled model projections, all at daily and 6 km resolution, on past and future climate extremes. Additionally, we are using the downscaled outputs to drive a hydrologic model and derive multiple probabilistic measures of water availability, flood, and drought. Moreover, we are extending the capacity of the Southwest Climate and Environmental Information Collaborative (SCENIC; wrcc.dri.edu/csc/scenic), a product developed by the Western Regional Climate Center, to provide access to diverse observed and simulated data on regional weather and climate, particularly on extremes.

The Template for Assessing Climate Change Impacts and Management Options (TACCIMO): Science at Your Fingertips

NASA Astrophysics Data System (ADS)

Jennings, L. N.; Treasure, E.; Moore Myers, J.; McNulty, S.

2012-12-01

There is an ever-increasing volume of useful scientific knowledge about climate change effects and management options for natural ecosystems. Agencies such as the USDA Forest Service have been charged with the need to evaluate this body of knowledge and if necessary adapt to the impacts of climate change in their forest planning and management. However, the combined volume of existing information and rate of development of new information, lack of climate change specialists, and limited technology transfer mechanisms make efficient access and use difficult. The Template for Assessing Climate Change Impacts and Management Options (TACCIMO) addresses this difficulty through its publically accessible web-based tool that puts current and concise climate change science at the fingertips of forest planners and managers. A collaborative product of the USDA Forest Service Research Stations and the National Forest System, TACCIMO integrates peer-reviewed research with management and planning options through search and reporting tools that connect land managers with information they can trust. TACCIMO highlights elements from the wealth of climate change science with attention to what natural resource planners and managers need through a searchable repository of over 4,000 effects of climate change and close to 1,000 adaptive management options, all excerpted from a growing body of peer-reviewed scientific literature. A geospatial mapping application provides downscaled climate data for the nation and other spatially explicit models relevant to evaluating climate change impacts on forests. Report generators assist users in capturing outputs specific to a given location and resource area in a consistent and organized manner. For USDA Forest Service users, science findings can be readily linked with management conditions and capabilities from national forest management plans. The development of TACCIMO was guided by interactions with natural resource professionals, resulting in a flexible framework that allows new information to be added routinely and existing information to be reorganized as new science emerges and management needs change. TACCIMO is currently being used to support climate change science assessments for national forest land and management plan revisions in El Yunque National Forest in Puerto Rico, the Southern Sierra national forests in California, and Francis Marion National Forest in South Carolina. The tool is also being actively used by state, extension, and private natural resource professionals for climate change education and outreach. For all users, TACCIMO provides a fast, concise, and creditable starting point to guide critical thinking, additional analysis, and expert consultation to support all aspects of natural resource management decision making.

Integrating climate forecasts and natural gas supply information into a natural gas purchasing decision

NASA Astrophysics Data System (ADS)

Changnon, David; Ritsche, Michael; Elyea, Karen; Shelton, Steve; Schramm, Kevin

2000-09-01

This paper illustrates a key lesson related to most uses of long-range climate forecast information, namely that effective weather-related decision-making requires understanding and integration of weather information with other, often complex factors. Northern Illinois University's heating plant manager and staff meteorologist, along with a group of meteorology students, worked together to assess different types of available information that could be used in an autumn natural gas purchasing decision. Weather information assessed included the impact of ENSO events on winters in northern Illinois and the Climate Prediction Center's (CPC) long-range climate outlooks. Non-weather factors, such as the cost and available supplies of natural gas prior to the heating season, contribute to the complexity of the natural gas purchase decision. A decision tree was developed and it incorporated three parts: (a) natural gas supply levels, (b) the CPC long-lead climate outlooks for the region, and (c) an ENSO model developed for DeKalb. The results were used to decide in autumn whether to lock in a price or ride the market each winter. The decision tree was tested for the period 1995-99, and returned a cost-effective decision in three of the four winters.

Multi-criteria decision analysis using hydrological indicators for decision support - a conceptual framework.

NASA Astrophysics Data System (ADS)

Butchart-Kuhlmann, Daniel; Kralisch, Sven; Meinhardt, Markus; Fleischer, Melanie

2017-04-01

Assessing the quantity and quality of water available in water stressed environments under various potential climate and land-use changes is necessary for good water and environmental resources management and governance. Within the region covered by the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) project, such areas are common. One goal of the SASSCAL project is to develop and provide an integrated decision support system (DSS) with which decision makers (DMs) within a given catchment can obtain objective information regarding potential changes in water flow quantity and timing. The SASSCAL DSS builds upon existing data storage and distribution capability, through the SASSCAL Information System (IS), as well as the J2000 hydrological model. Using output from validated J2000 models, the SASSCAL DSS incorporates the calculation of a range of hydrological indicators based upon Indicators of Hydrological Alteration/Environmental Flow Components (IHA/EFC) calculated for a historic time series (pre-impact) and a set of model simulations based upon a selection of possible climate and land-use change scenarios (post-impact). These indicators, obtained using the IHA software package, are then used as input for a multi-criteria decision analysis (MCDA) undertaken using the open source diviz software package. The results of these analyses will provide DMs with an indication as to how various hydrological indicators within a catchment may be altered under different future scenarios, as well providing a ranking of how each scenario is preferred according to different DM preferences. Scenarios are represented through a combination of model input data and parameter settings in J2000, and preferences are represented through criteria weighting in the MCDA. Here, the methodology is presented and applied to the J2000 Luanginga model results using a set of hypothetical decision maker preference values as input for an MCDA based on the PROMETHEE II outranking method. Future work on the SASSCAL DSS will entail automation of this process, as well as its application to other hydrological models and land-use and/or climate change scenarios.

Vulnerability-based evaluation of water supply design under climate change

NASA Astrophysics Data System (ADS)

Umit Taner, Mehmet; Ray, Patrick; Brown, Casey

2015-04-01

Long-lived water supply infrastructures are strategic investments in the developing world, serving the purpose of balancing water deficits compounded by both population growth and socio-economic development. Robust infrastructure design under climate change is compelling, and often addressed by focusing on the outcomes of climate model projections ('scenario-led' planning), or by identifying design options that are less vulnerable to a wide range of plausible futures ('vulnerability-based' planning). Decision-Scaling framework combines these two approaches by first applying a climate stress test on the system to explore vulnerabilities across many traces of the future, and then employing climate projections to inform the decision-making process. In this work, we develop decision scaling's nascent risk management concepts further, directing actions on vulnerabilities identified during the climate stress test. In the process, we present a new way to inform climate vulnerability space using climate projections, and demonstrate the use of multiple decision criteria to guide to a final design recommendation. The concepts are demonstrated for a water supply project in the Mombasa Province of Kenya, planned to provide domestic and irrigation supply. Six storage design capacities (from 40 to 140 million cubic meters) are explored through a stress test, under a large number climate traces representing both natural climate variability and plausible climate changes. Design outcomes are simulated over a 40-year planning period with a coupled hydrologic-water resources systems model and using standard reservoir operation rules. Resulting performance is expressed in terms of water supply reliability and economic efficiency. Ensemble climate projections are used for assigning conditional likelihoods to the climate traces using a statistical distance measure. The final design recommendations are presented and discussed for the decision criteria of expected regret, satisficing, and conditional value-at-risk (CVaR).

Accounting for false-positive acoustic detections of bats using occupancy models

USGS Publications Warehouse

Clement, Matthew J.; Rodhouse, Thomas J.; Ormsbee, Patricia C.; Szewczak, Joseph M.; Nichols, James D.

2014-01-01

4. Synthesis and applications. Our results suggest that false positives sufficient to affect inferences may be common in acoustic surveys for bats. We demonstrate an approach that can estimate occupancy, regardless of the false-positive rate, when acoustic surveys are paired with capture surveys. Applications of this approach include monitoring the spread of White-Nose Syndrome, estimating the impact of climate change and informing conservation listing decisions. We calculate a site-specific probability of occupancy, conditional on survey results, which could inform local permitting decisions, such as for wind energy projects. More generally, the magnitude of false positives suggests that false-positive occupancy models can improve accuracy in research and monitoring of bats and provide wildlife managers with more reliable information.

40 CFR 86.1721-99 - Application for certification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... which the vehicle is certifying: LDV, LDT 0-3750 lbs LVW, LDT 3751-5750 lbs LVW (state test weight range... of the propulsion system for the vehicle. (4) Identification and description of the climate control... state-of-charge, battery charging capacity and recharging procedures, and any other relevant information...

40 CFR 86.1721-99 - Application for certification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... which the vehicle is certifying: LDV, LDT 0-3750 lbs LVW, LDT 3751-5750 lbs LVW (state test weight range... of the propulsion system for the vehicle. (4) Identification and description of the climate control... state-of-charge, battery charging capacity and recharging procedures, and any other relevant information...

40 CFR 86.1721-99 - Application for certification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... which the vehicle is certifying: LDV, LDT 0-3750 lbs LVW, LDT 3751-5750 lbs LVW (state test weight range... of the propulsion system for the vehicle. (4) Identification and description of the climate control... state-of-charge, battery charging capacity and recharging procedures, and any other relevant information...

Chances of short-term cooling trends over Canada for the next decades

NASA Astrophysics Data System (ADS)

Grenier, Patrick; de Elia, Ramon; Chaumont, Diane

2014-05-01

As climate services continue to develop in Quebec, Canada, an increasing number of requests are made for providing information relevant for the near term. As a response, one approach has been to consider short-term cooling trends as a basis for climate products. This project comprises different aspects: technical steps, knowledge transfer, and societal use. Each step does represent a different challenge. The technical part, i.e. producing probabilistic distributions of short-term temperature trends, involves relatively complex scenario construction methods including bias-related post-processing, and access to wide simulation and observation databases. Calculations are performed on 60 CMIP5-based scenarios on a grid covering Canada during the period 2006-2035, and for 5, 10, 15, 20 and 25-year trend durations. Knowledge transfer implies overcoming misinterpretation, given that probabilistic projections based on simulation ensembles are not perfectly related to real-Earth possible outcomes. Finally, societal use of this information remains the biggest challenge. On the one hand, users clearly state their interest in near-term relevant information, and intuitively it seems clear that short-term cooling trends embedded within the long-term warming path should be considered in adaptation plans, for avoiding over-adaptation. On the other hand, the exact way of incorporating such information within a decision-making process has proven not to be obvious. Irrespective of that, the study and communication of short-term cooling chances is necessary for preventing decision-makers to infer from the eventual occurrence of such a trend that global warming isn't happening. The presentation will discuss the three aspects aforementioned.

Household perceptions of coastal hazards and climate change in the Central Philippines.

PubMed

Combest-Friedman, Chelsea; Christie, Patrick; Miles, Edward

2012-12-15

As a tropical archipelagic nation, the Philippines is particularly susceptible to coastal hazards, which are likely to be exacerbated by climate change. To improve coastal hazard management and adaptation planning, it is imperative that climate information be provided at relevant scales and that decision-makers understand the causes and nature of risk in their constituencies. Focusing on a municipality in the Central Philippines, this study examines local meteorological information and explores household perceptions of climate change and coastal hazard risk. First, meteorological data and local perceptions of changing climate conditions are assessed. Perceived changes in climate include an increase in rainfall and rainfall variability, an increase in intensity and frequency of storm events and sea level rise. Second, factors affecting climate change perceptions and perceived risk from coastal hazards are determined through statistical analysis. Factors tested include social status, economic standing, resource dependency and spatial location. Results indicate that perceived risk to coastal hazards is most affected by households' spatial location and resource dependency, rather than socio-economic conditions. However, important differences exist based on the type of hazard and nature of risk being measured. Resource dependency variables are more significant in determining perceived risk from coastal erosion and sea level rise than flood events. Spatial location is most significant in determining households' perceived risk to their household assets, but not perceived risk to their livelihood. Copyright © 2012 Elsevier Ltd. All rights reserved.

Building the Capacity for Climate Services: Thoughts on Training Next Generation Climate Science Integrators

NASA Astrophysics Data System (ADS)

Garfin, G. M.; Brugger, J.; Gordon, E. S.; Barsugli, J. J.; Rangwala, I.; Travis, W.

2015-12-01

For more than a decade, stakeholder needs assessments and reports, including the recent National Climate Assessment, have pointed out the need for climate "science translators" or "science integrators" who can help bridge the gap between the cultures and contexts of researchers and decision-makers. Integration is important for exchanging and enhancing knowledge, building capacity to use climate information in decision making, and fostering more robust planning for decision-making in the context of climate change. This talk will report on the characteristics of successful climate science integrators, and a variety of models for training the upcoming generation of climate science integrators. Science integration characteristics identified by an experienced vanguard in the U.S. include maintaining credibility in both the scientific and stakeholder communities, a basic respect for stakeholders demonstrated through active listening, and a deep understanding of the decision-making context. Drawing upon the lessons of training programs for Cooperative Extension, public health professionals, and natural resource managers, we offer ideas about training next generation climate science integrators. Our model combines training and development of skills in interpersonal relations, communication of science, project implementation, education techniques and practices - integrated with a strong foundation in disciplinary knowledge.

Meeting the challenge of policy-relevant science: lessons from a water resource project

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

Lamb, B.L.

Water resources scientists face complex tasks in evaluating aspects of water projects, but relatively few assessment procedures have been applied and accepted as standards applications. Decision-makers often rely on environmental assessments to evaluate the value and operation of projects. There is often confusion about scientists' role in policy decisions. The scientist can affect policy-making as an expert witness, an advocate or a surrogate. By understanding the policy process, scientists can make their work more policy relevant. Using the Terror Lake hydro project in Alaska as a guide, three lessons are discussed: (1) not all problems are able to be solvedmore » with technology; (2) policy-relevant technology is rarely imposed on a problem; and (3) the scientist need not just to react to the policy process, but can have an impact on how that process unfolds.« less