Estimation of the value of weather forecasts is a special case of the problem of valuing information. Decision theory provides an elegant method for making estimates of the value of information, but the validity of the resulting estimates has been shown to rest on some shaky assumptions. The shakiest of these is that users of the information are rational and act optimally on the information they are given. Descriptive methods are needed to incorporate realistic assumptions about decision making behavior into models for estimating forecast value.
We report a detailed case study of the impact of improved precipitation forecasts on ground transportation. Specifically, we examined the impact of improved precipitation forecasts on the snowfighting operations of the New York State Thruway. Currently available data and literature on forecast process, communication, and use were used in conjunction with observations and interviews with key decision makers to derive a model that yields estimates of value under various assumptions about forecast quality. It was found that the primary benefit of improved forecasts would be in the reduced application of salt to the roadway. It was also found that the full benefit of improved forecasts would require some adjustments in the way information is used by decision makers. A major lesson learned from this research is the importance of forecast verification data for supporting studies of the value of weather information.
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