The climate of 1997-1998 attracted the attention of people and governments worldwide not only because of a large number of extreme weather events, but also because the climate anomalies that caused many of them were accurately predicted months in advance. In early 1997, ocean monitors detected that sea surface temperatures in the equatorial Pacific Ocean were rising sharply over an expanding area. Coupled models of ocean-atmosphere interactions transformed the data, which indicated a severe El Niño-Southern Oscillation (ENSO) episode, into predictions of anomalous weather extremes in several parts of the globe, many of which were confirmed by subsequent events. Many catastrophic events were linked to the ENSO episode, including water shortages, fires, and crop failure in Central and South America; fires in Southeast Asia; major storms in South America and California; tornadoes that killed more than 120 in the United States; and increased rainfall in the U.S. Southwest that fostered vegetation growth and increased the potential for serious wildfires and the threat of a hantavirus outbreak.
The improved ability to model ocean-atmosphere interactions and thereby to predict seasonal-to-interannual climatic variations across broad reaches of the planet has been a hallmark achievement of the first 10 years of the U.S. Global Change Research Program. Predictive skill has now increased to the point that the U.S. National Oceanic and Atmospheric Administration (NOAA) and weather services in other countries release forecasts of ENSO-related weather phenomena to the public in the expectation that these forecasts will allow individuals and organizations to
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Page 1 Summary The climate of 1997-1998 attracted the attention of people and governments worldwide not only because of a large number of extreme weather events, but also because the climate anomalies that caused many of them were accurately predicted months in advance. In early 1997, ocean monitors detected that sea surface temperatures in the equatorial Pacific Ocean were rising sharply over an expanding area. Coupled models of ocean-atmosphere interactions transformed the data, which indicated a severe El Niño-Southern Oscillation (ENSO) episode, into predictions of anomalous weather extremes in several parts of the globe, many of which were confirmed by subsequent events. Many catastrophic events were linked to the ENSO episode, including water shortages, fires, and crop failure in Central and South America; fires in Southeast Asia; major storms in South America and California; tornadoes that killed more than 120 in the United States; and increased rainfall in the U.S. Southwest that fostered vegetation growth and increased the potential for serious wildfires and the threat of a hantavirus outbreak. The improved ability to model ocean-atmosphere interactions and thereby to predict seasonal-to-interannual climatic variations across broad reaches of the planet has been a hallmark achievement of the first 10 years of the U.S. Global Change Research Program. Predictive skill has now increased to the point that the U.S. National Oceanic and Atmospheric Administration (NOAA) and weather services in other countries release forecasts of ENSO-related weather phenomena to the public in the expectation that these forecasts will allow individuals and organizations to
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Page 2 prepare for climatic events and be better off as a result. It is clear that public awareness of El Eiño has increased dramatically since early 1997. However, there is as yet no full accounting of how beneficial forecasts have been in reducing climate-related damage or in allowing people to benefit from climate-related opportunities. Even though the scientific capability to forecast seasonal-to-interannual climate variability remains imperfect, there is good reason to believe that much benefit can be gained by appropriately linking this capability to the practical needs of society. To do this requires scientific understanding of social processes as well as climatic ones. How does society cope with seasonal-to-interannual climatic variations? How is the vulnerability to such variations distributed within and among societies? How have individuals and organizations used climate forecasts in the recent past? What kinds of forecast information are most useful to people whose well-being is sensitive to climatic variations? Who is likely to benefit from the newly acquired forecast skill? How do the benefits depend on characteristics of the users, the information in the forecast, and the ways in which it is delivered? What is the nature of the potential benefits, and how can they be measured? This volume responds to a request from NOAA to review the state of knowledge and to identify needed research on such questions. It identifies a set of scientific questions the pursuit of which is likely to yield knowledge that can make seasonal-to-interannual climate forecasts more useful. The scientific questions flow from our findings. Here, we summarize the major findings and the scientific questions under three thematic categories: (1) the potential benefits of climate forecast information; (2) improved dissemination of forecast information; and (3) the consequences of climatic variations and climate forecasts. Potential Benefits of Climate Forecast Information Climate forecasts are inherently uncertain due to chaos in the atmospheric system; moreover, forecasting skill varies geographically, temporally, and by climate parameter. We expect forecasting skill to improve in regions and for climatic parameters for which limited skill now exists, thus increasing the potential usefulness of forecasts over time. However, research addressed to questions framed by climate science is not necessarily useful to those whom climate affects. A climate forecast is useful to a recipient only if the outcome variables it skillfully predicts are relevant and the forecast is timely in relation to actions the recipient can take to improve outcomes. Useful forecasts are those that meet recipients' needs in terms of such attributes as timing, lead time, and currency; climate
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Page 3 parameters; spatial and temporal resolution; and accuracy. The usefulness of climate forecast information also depends on the strategies recipients use for coping with climatic variability, which are often culturally, regionally, and sectorally specific. Although many coping strategies are widely available in principle, the ones available to any particular set of actors, and the relative costs of using them, can be known only by observation. Because the usefulness of forecasts is dependent on both their accuracy and their relationship to recipients' informational needs and coping strategies, we find that the utility of forecasts can be increased by systematic efforts to bring scientific outputs and users' needs together. These systematic efforts should focus on two scientific questions: 1. Which regions, sectors, and actors would benefit from improved forecast information, and which forecast information would potentially be of the greatest benefit? 2. Which regions, sectors, and actors can benefit most from current forecast skill? Research on the first question would aim to set an agenda for climate science to make its outputs more useful to recipients: it would provide a voice of consumer demand to the climate science community. Research on the second would proceed from the viewpoint of climate science and would explore ways to get the most social benefit from currently available forecast information. For both kinds of research, two scientific strategies are appropriate and should be conducted in parallel. One uses models and other analytic techniques to identify and estimate the benefits that particular recipients could gain from optimal use of particular kinds of forecast information. The other relies on querying potential users of climate forecast information about their informational needs, either by using survey methodologies or via structured discussions involving the producers and consumers of forecasts. Some of the research on these questions should be directed at improving the effectiveness of participatory, structured discussion methods. Dissemination of Climate Forecast Information The limited evidence from past climate forecasts and a much larger body of evidence on the use of analogous kinds of information show that the effectiveness of forecast information depends strongly on the systems that distribute the information, the channels of distribution, recipients' modes of understanding and judgment about the information sources, and the ways in which the information is presented. This evidence suggests that information deliv-
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Page 4 ery systems will be most effective when organized to meet recipients' needs in terms of their coping strategies, cultural traits, and specific situations; that participatory strategies are likely to be most useful in designing effective climate forecast information systems; that new organizations delivering climate forecast information will require a period of social learning to become fully effective; and that useful information is likely to flow first to the wealthiest and most educated in any target group. Individual and organizational responses to climate forecasts are likely to conform to known generalities about responses to similar kinds of new information. For example, interpretations of forecast information are likely to be strongly affected by individuals' preexisting mental models and organizations' preexisting routines and role responsibilities. Knowledge about information processing suggests several specific hypotheses about the use of forecast information, such as that forecasts that turn out to be wrong have a strong negative influence on the future use of forecast information. Research on five scientific questions can advance knowledge about how to improve the dissemination of climate forecast information: 3. How do individuals conceptualize climate variability and react to climate forecasts? What roles do their expectations of climate variability play in their acceptance and use of forecasts? 4. How do organizations interpret climatic information and react to climate forecasts? What are the roles of organizational routines, cultures, structures, and responsibilities in the use and acceptance of forecasts? 5. How do recipients of forecasts deal with forecast uncertainty, the risk of forecast failure, and actual forecast failure? What are the implications of these reactions for the design of forecast information? 6. How are the effects of forecasts shaped by aspects of the systems that disseminate information (e.g., weather forecasting agencies, mass media) and of the forecast messages? How do these effects interact with attributes of the forecast users? 7. What are the ethical and legal issues created by the dissemination of skillful, but uncertain, climate forecasts? Research on these scientific questions can usefully begin with generalizations and hypotheses derived from existing knowledge, based largely on analogous situations of information dissemination. It should expand and refine this knowledge by studying responses to climate forecast information. Responses to past climate forecasts, including those for the 1997-1998 El Niño, are an essential source of information for addressing these scientific questions.
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Page 5 Consequences of Climatic Variations and of Climate Forecasts Climatic events and forecasts have differing effects across regions, sectors, and actors (e.g., farmers, firms). Moreover, these effects are shaped by a complex mosaic of anticipatory (ex ante) strategies that individuals, organizations, and societies have developed for coping with climate variability, including risk sharing (e.g., insurance), technological innovations (e.g., irrigation), and information delivery systems. Some coping strategies interact synergistically, some compete and offset one another, and some substitute for others. These coping strategies are neither universally available to nor used consistently by all actors at all times. To understand and estimate the consequences of climatic events and of skillful forecasts, it is necessary to take these coping strategies and differences in their use into account. It is also necessary to consider that social, environmental, and economic forces having little or nothing to do with climate variability will partly govern the sensitivity or vulnerability to climatic events and determine the types of information needed to respond. Building an improved capability to estimate the human consequences of climatic variation requires improved basic understanding of these nonclimatic phenomena and of how they interact with climatic ones. Various quantitative and qualitative methods exist for estimating the consequences of climate variability and the value of forecasts. However, the methods now in use have important methodological and conceptual limitations, such as overreliance on simplifying assumptions; oversimplification of the dynamic relationships between climate and human consequences; imprecise definitions of key concepts such as adaptation, sensitivity, and vulnerability; lack of distinction between potential and actual value of climate forecasts; lack of attention to outcomes that are not easily measured; lack of explicit attention to the distribution of damages and benefits, especially the impacts of catastrophically large negative events on highly vulnerable activities or groups; and lack of reliable strategies for defining baseline conditions of actors, regions, sectors, and populations. Estimating consequences is also complicated by the fact that the resolution of data in space and time determines the ability to model and detect certain types of consequences. Many governments and other organizations collect potentially relevant data, but little or no meta-data exist describing the availability, quality, resolution, and other essential traits of these data. Research on five scientific questions can improve the ability to estimate the consequences of climatic variations and the value of climate forecasts:
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Page 6 8. How are the human consequences of climate variability shaped by the conjunctions and dynamics of climatic events and social and other nonclimatic factors (e.g., technological and economic change, the availability of insurance, the adequacy of emergency warning and response systems)? How do seasonal forecasts interact with other factors and types of information in ways that affect the value of forecasts? 9. How are the effects of forecasts shaped by the coping systems available to affected groups and sectors? How might improved forecasts change coping mechanisms and how might changes in coping systems make climate forecasts more valuable? 10. Which methods should be used to estimate the effects of climate variation and climate forecasts? 11. How will the gains and losses from improved forecasts be distributed among those affected? To what extent might improved forecasting skill exacerbate socioeconomic inequalities among individuals, sectors, and countries? How might the distribution of gains and losses be affected by policies specially aimed at bringing the benefits of forecasts to marginalized and vulnerable groups? 12. How adequate are existing data for addressing questions about the consequences of climate variability and the value and consequences of climate forecasts? To what extent are existing data sources under-exploited?