Event Title

Operation Wind Gust Forecasting

Mentor 1

Dr. Paul Roebber

Location

Union Wisconsin Room

Start Date

29-4-2016 1:30 PM

End Date

29-4-2016 3:30 PM

Description

Current methods for operational forecasting of wind gusts rely on a “Gust Factor” which is a multiplier applied to the steady wind. Knowledge about these peak winds or gusts is important for many operations (for example, energy companies concerned with power outages). Scientifically, gusts are produced by the mixing of higher winds from above the earth’s surface to the surface, and this mixing is promoted by certain environmental factors, including time of day, the strength of the prevailing winds, and land use characteristics. Because wind gusts are confined to very short time and spatial scales, they are best considered from a probabilistic standpoint: what is the probability of winds exceeding a given threshold at a certain location within a certain time period. Using modern data analytics techniques, it should be possible to relate larger-scale atmospheric factors to wind gust probabilities. We will do this work by making use of long-period archives of meteorological conditions in the Milwaukee area. The outcome of this research will be a forecast tool that can be used in the operations of Innovative Weather as a weather decision support aid to energy and cable clients.

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Apr 29th, 1:30 PM Apr 29th, 3:30 PM

Operation Wind Gust Forecasting

Union Wisconsin Room

Current methods for operational forecasting of wind gusts rely on a “Gust Factor” which is a multiplier applied to the steady wind. Knowledge about these peak winds or gusts is important for many operations (for example, energy companies concerned with power outages). Scientifically, gusts are produced by the mixing of higher winds from above the earth’s surface to the surface, and this mixing is promoted by certain environmental factors, including time of day, the strength of the prevailing winds, and land use characteristics. Because wind gusts are confined to very short time and spatial scales, they are best considered from a probabilistic standpoint: what is the probability of winds exceeding a given threshold at a certain location within a certain time period. Using modern data analytics techniques, it should be possible to relate larger-scale atmospheric factors to wind gust probabilities. We will do this work by making use of long-period archives of meteorological conditions in the Milwaukee area. The outcome of this research will be a forecast tool that can be used in the operations of Innovative Weather as a weather decision support aid to energy and cable clients.