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to find when the outcomes result from nonextreme climatic events and when the outcome variables are difficult to quantify.

Social and economic data are widely collected, however, on outcomes that are affected by seasonal-to-interannual climate variation and that might therefore be improved by skillful forecasts. For example, most countries collect data on agricultural production, human morbidity and mortality from various causes, streamflows in important rivers, yields from fishing and lumbering, and various other phenomena that are sensitive to weather and climate. Such data can be used to model the effects of climate variability and the value of forecasts. However, their usefulness for this purpose depends on the extent to which sufficiently long time series are available, data are comparable across time and geographical regions, measurement procedures are constant, and other such factors. There is reason to believe that the data available in many countries on many of these variables fall short of the necessary quality and comparability. However, the extent of this shortfall is not well understood.

Research Based on the Use of Actual Climate Forecasts

Empirical decision studies attempt to shed light on how decision makers actually use (or fail to use) and value forecasts. These studies examine the ways actual forecasts are received, interpreted, and applied, drawing lessons about forecast value from actual experiences. The ledger on such studies is thin, but there are a few deserving of mention here. Stewart (1997) divides empirical studies of forecast use and valuation into the categories of: (1) anecdotal reports and case studies; (2) user surveys; (3) interviews and protocol analysis; and (4) decision experiments. We add a fifth category of empirical modeling studies.

Case studies on the value of climate forecasts are common in government publications (e.g., Aber, 1990) and agricultural cooperative extension circulars. A typical case may recount how farmers used forecasts to improve the efficiency of operations. A grain grower might be interviewed and asked how valuable the forecasts are in managing the crop and may provide a dollar estimate of how much was saved by using the forecast. The problem with such reporting is that the information given is subjective and apt to be unreliable.

Ex post case studies of actual forecasts provide important insights into how decision makers actually apply climate forecasts. Stewart cites a case study by Glantz (1982) of the ramifications of using a faulty streamflow forecast in the Yakima valley in the state of Washington as an example. As previously noted, Glantz detailed the costs in terms of the value of legal claims brought by farmers who, at great cost, had undertaken preemptive actions to avoid loss due to the erroneously forecast

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