Quantification of Uncertainity in Fire-Weather Forecasts: Some Results of Operational and Experimental Forecasting Programs

Abstract

Fire-weather forecasts (FWFs) prepared by National Weather Service (NWS) forecasters on an operational basis are traditionally expressed in categorical terms. However, to make rational and optimal use of such forecasts, fire managers need quantitative information concerning the uncertainty inherent in the forecasts. This paper reports the results of two studies related to the quantification of uncertainty in operational and experimental FWFs. Evaluation of samples of operational categorical FWFs reveals that these forecasts contain considerable uncertainty. The forecasts also exhibit modest but consistent biases which suggest that the forecasters are influenced by the impacts of the relevant events on fire behavior. These results underscore the need for probabilistic FWFs. The results of a probabilistic fire-weather forecasting experiment indicate that NWS forecasters are able to make quite reliable and reasonably precise credible interval temperature forecasts. However, the experimental relative humidity and wind speed forecasts exhibit considerable overforecasting and minimal skill. Although somewhat disappointing, these results are not too surprising in view of the fact that (a) the forecasters had little, if any, experience in probability forecasting; (b) no feedback was provided to the forecasters during the experimental period; and (c) the experiment was of quite limited duration. More extensive experimental and operational probability forecasting trials as well as user-oriented studies are required to enhance the quality of FWFs and to ensure that the forecasts are used in an optimal manner.