Gust Speed Forecasting Using Weather Model Outputs and Meteorological Observations

Strong wind gust can cause severe damages, such as power outages, which are major concerns for emergency management of utility companies. Yet, gust speed is not a standard output from weather forecasting models. In this paper, we proposed a Bayesian hierarchical model which combines historical meteorological observations and weather model outputs to forecast hourly gust speed. The exploratory analysis suggested a two-step sequential spatio-temporal model as follows. In the first step, we calibrated sustained wind speed forecast and in the second step, we forecasted gust speed based on calibrated wind forecast. We demonstrated the use of our model by a real application concerning gust-caused damages for a local power utility company from New York area.

By: Hongfei Li; Fei Liu; Jonathan R. M. Hosking; Yasuo Amemiya

Published in: RC25087 in 2010


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