Wind gust forecasting in complex terrain

In fire-prone areas such as southern California, wind gusts are potentially hazardous to lives, properties, and public transportation since strong gusty winds can knock down trees and power lines, and spark and spread fires. Due to its chaotic nature and lack of adequate knowledge of its formation and behavior, it remains a day-to-day challenge to accurately predict wind gust speed, especially in the mountainous regions. Since mesoscale models are incapable of directly simulating gusts, empirical and heuristic attempts have been made to estimate wind gusts by multiplying the solved-scale sustained wind speed by a gust factor (a gust-to-wind ratio) empirically determined from available observations (e.g. Mitsuta and Tsukamoto 1989), or adding a scalar value to the sustained wind, assuming a normal distribution of wind fluctuations (e.g., Wieringa 1973).

Our study employs large physics ensembles composed of high-resolution simulations of severe downslope windstorms that involve an exhaustive examination of available model physical parameterizations. Model results are calibrated and validated against the San Diego Gas and Electric (SDGE) mesonet observations, a homogenous, well-positioned, and high-resolution network with uniform high quality. We have devised a new gust parameterization that can skillfully anticipate extreme wind events in the complex topography such as San Diego county. The improved gust forecast technique is of special interest in the context of routine weather combined with atmospheric humidity and fuel moisture information.