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Now available in PDF format: Abstract Book [7.4 Mb] (posted 10 November 2005)

Abstracts for Posters

Decision Support: Processes & Products (P-DS)

Sub-Theme 4: International

P-DS4.1

Robust Adaptation Decisions amid Climate Change Uncertainties

Suraje Dessai, Tyndall Centre for Climate Change Research and University of East

Anglia, UK, s.dessai@uea.ac.uk

Mike Hulme, Tyndall Centre for Climate Change Research and University of East Anglia, UK

This presentation deals with the sensitivity of water supply decisions to various uncertainties associated with climate change (e.g., emissions of greenhouse gases, climate sensitivity, global climate models, and regional climate models). The setting is in the East of England, in the UK, the driest region in the country where climate change could exacerbate drought-like conditions.

UK water companies have to plan for the next 25 years and decide what actions they will take in order to maintain security of supply. They currently take into account climate change by using climate change scenarios produced by the UK Climate Impacts Programme (UKCIP02). Our approach tries to quantify a much larger set of uncertainties than those included in UKCIP02 in the assessment of future climate. We are then able to determine the sensitivity of water adaptation decisions to these uncertainties.

Our role in the decision-support process has not been as purely a "user" or a "producer" of climate information. Our role could be better described as an observer or facilitator in the interface between "user" and "producer." We have been "producers" of climate information because we have used publicly available climate data to quantify uncertainties in climate change scenarios. This has been done using a combination of a simple climate model and various global and regional climate models. We also interacted with numerous "users" to elicit what adaptation options they were considering.

The presentation will introduce a number of topics such as the type of information decision makers want; use of scientific information (in particular models and their results) to support decision-making; participatory approaches; communicating uncertainty; and methods and metrics to evaluate outcomes. In order to support their decision-making, water companies in the UK would prefer to use probabilistic climate projections rather than scenarios. We have noted that models are important for incorporating climate change into water resources planning. The industry has attempted to follow a simple approach, but because of the complexity introduced by climate change it is particularly important to manage and communicate uncertainties associated with climate change. We have also found that participatory approaches are crucial for the users to trust the information from the producers and for the researchers to elicit adaptation strategies from the users. We evaluated adaptation strategies using criteria based on robustness, i.e., decisions that are insensitive to uncertainties.

P-DS4.2

Decision Systems Research and Tool Development at the IRI

Neil Ward, International Research Institute for Climate Prediction (IRI), The Earth Institute at Columbia University, nward@iri.columbia.edu

James Hansen, International Research Institute for Climate Prediction (IRI), The Earth Institute at Columbia University

Sankar Arumugam, International Research Institute for Climate Prediction (IRI), The Earth Institute at Columbia University

Daniel Osgood, International Research Institute for Climate Prediction (IRI), The Earth Institute at Columbia University

Lareef Zubair, International Research Institute for Climate Prediction (IRI), The Earth Institute at Columbia University

Casey Brown, International Research Institute for Climate Prediction (IRI), The Earth Institute at Columbia University

Ashok Mishra, International Research Institute for Climate Prediction (IRI), The Earth Institute at Columbia University

We report progress in the development or enhancement of decision tools and decision strategies that account for climate risk. Our experiences to date have been focused on tools for climate risk management at seasonal timescales, that is, incorporating climate forecasts for the upcoming several months, and subsequent monitoring of the evolution of the climate over those months. The experiences are gained through collaboration with partners and stakeholders in many places.

Applications of quantitative decision tools that incorporate seasonal climate information typically focus on either (a) translation into impacts and information that is directly relevant to management, (b) understanding and modeling decision responses and assessing the resulting benefits of alternate decision-making strategies, and (c) fostering and guiding decision responses.

Tailoring climate information ((a) above) can involve linking climate information at a high spatial and temporal resolution into dynamic, process-oriented models of the impacts of interest. We provide such examples in monitoring and predicting crop production, and spatially distributed
hydrological variables. For such examples, downscaled daily weather series are often needed, and examples of approaches are given. More direct statistical approaches are also possible for prediction of impact variables. Examples include methods for predicting malaria risk, patterns of remotely sensed vegetation indices, and stream-flow.

Decision models with flexible user interfaces that facilitate "what-if" analysis of outcomes of decision alternatives can be used both to explore potential benefits, and also as decision support tools that communicate opportunities to stakeholders. We present a modeling analysis of the use of forecasts for rainfed crop management in Kenya. Another example that has been explored is a model-based analysis of management of a multiple use reservoir system in the Philippines, which in particular illustrates expected increases in hydroelectric power generation. A windows-based software tool has been developed for exploration of reservoir management with and without seasonal forecasts of expected inflow distributions. Such tools are one piece in a suite of approaches to fostering and guiding response strategies. Other pieces are being explored to contribute to knowledge on how to achieve the most effective uptake of new climate-related information in decision-making, including approaches to ensuring tools best meet the needs of targeted users, and alternative ways to communicate opportunities for improvements in decision-making practice (for example, insurance schemes, games for learning).

[Poster PDF]

P-DS4.3

Applying Climate Variability/Change Information for Early Warning and Response Decision-Making: Lessons Learned from the Conflict Early Warning and Response Mechanism (CEWARN)

Patrick Meier, Center for Int'l Environment & Resource Policy, The Fletcher School
Water: Systems, Science & Society, Tufts University, ppm2005@columbia.edu

The vulnerability of coupled human-environment systems is one of the central elements of sustainability research whose object requires improved dialogue between sciences and decision-making (Turner et. al, 2003b). African systems are particularly vulnerable to climate variability and related
environmental processes. Overall rises in temperature are expected to reach double the global rise in central Africa, with increased risk of extreme droughts, floods and outbreaks of disease in the rest of Africa. However, just as technological progress and human activity have contributed to this problem, it is also within our means to develop, improve, and disseminate structured information for use in decision-making and policy formulation.

It is evident that earth science-based information is needed by local and national resource managers to make environmentally and economically sound decisions. However, human-environment systems are "predicated on synergy between the human and bio physical processes operating at different
spatiotemporal (as well as functional) scales" (Turner et. al. 2003b). One basic challenge in providing decision-makers and stakeholders with relevant information is therefore geo­statistical: how to correlate structural data (e.g., rural sub-national development indicators in the Horn of Africa for a specific polygon), with behavioral boundary data (e.g., violent behavior such as pastoral conflict), with raster data of various resolutions (e.g., local climatic/rainfall/ temperature/vegetation variations) in an integrated—yet necessarily asynchronous—decision-oriented framework.

The purpose of this presentation is to explain how the Conflict Early Warning and Response Mechanism (CEWARN) integrates climate information to address societal and scientific challenges within a client-based, decision-oriented framework. The Intergovernmental Authority on Development (IGAD) in East Africa directs the CEWARN project and as a (non-scientific) senior consultant and developer of CEWARN, I seek to integrate information on environmental/climate variability/change and related processes with behavioral/social variability/change to inform early response decision-making by Member States. For example, the project draws on observations and seasonal-to-inter annual precipitation forecasts to enhance environment-conflict analysis for early warning. The framework thus combines geophysical time series data with geospatial social/behavioral time series data using geographic information systems and baseline analyses. This presentation explores CEWARN's application of information developed through science and technology research to support decision making in the areas of water and conflict prevention. The presentation will suggest priorities for future research in view of information science potential and CEWARN's information needs for decision-making.

[Poster PDF]

P-DS4.4

Climate Change Science for Development

Keya Chatterjee, USAID

Jon Padgham, USAID, jpadgham@usaid.gov

The USAID Global Climate Change Program funds environmental programs that reduce growth in greenhouse gas emissions while promoting sustainable agriculture, forest conservation, biodiversity, and other development goals. These projects rely on up-to-date scientific information and
specific scientific deliverables that address both the potential for developing countries to mitigate climate change and the effects of climate change on developing countries.

USAID has adopted a "multiple benefits" approach to addressing climate change, in which projects are designed to help mitigate or adapt to climate change, while advancing development goals such as improved natural resource management, biodiversity conservation, food security, and improved health and nutrition. These same projects can also help reduce the vulnerability of ecosystems to climate change. For instance, reduced tillage and contour planting by farmers increases soil organic carbon sequestration and therefore enhances soil fertility, which helps increase food security in developing countries.

In order to identify the best opportunities for concurrently addressing climate change and sustainable development through the multiple benefits approach, USAID requires science evaluating the effects of various mitigation strategies and information on sectors and regions most vulnerable to
climate change. Informed decisions are essential to climate change mitigation and adaptation as well as sustainable natural resource management and economic development, all of which are key priorities for USAID.

[Poster PDF]