Despite the revolutionary development of numerical weather and climate prediction (NWCP) in the second half of the last century, quantitative interaction between model developers and forecast customers has been rather limited. This is apparent in the diverse ways in which weather forecasts are assessed by these two groups: root-mean-square error of 500 hPa height on the one hand; pounds, euros or dollars saved on the other.
These differences of approach are changing with the development of ensemble forecasting. Ensemble forecasts provide a qualitative tool for the assessment of weather and climate risk for a range of user applications, and on a range of time-scales, from days to decades. Examples of the commercial application of ensemble forecasting, from electricity generation, ship routeing, pollution modelling, weather-risk finance, disease prediction and crop yield modelling, are shown from all these time-scales.
A generic user decision model is described that allows one to assess the potential economic value of numerical weather and climate forecasts for a range of customers. Using this, it is possible to relate analytically, potential economic value to conventional meteorological skill scores. A generalized meteorological measure of forecast skill is proposed which takes the distribution of customers into account. It is suggested that when customers' exposure to weather or climate risk can be quantified, such more generalized measures of skill should be used in assessing the performance of an operational NWCP system. Copyright © 2002 Royal Meteorological Society.