Verification of gridded wind forecasts in complex Alpine terrain: A new wind verification methodology based on the neighborhood approach

Verification of gridded wind forecasts in complex Alpine terrain: A new wind verification... AbstractA novel wind verification methodology is presented and analyzed for six surface wind cases in the greater Alpine region as well as an idealized setup. The methodology is based on the idea of the Fractions Skill Score, a neighborhood-based spatial verification metric frequently used for verifying precipitation. The new score avoids the problems of traditional non-spatial verification metrics (the ‘double penalty’ problem and the failure to distinguish between a ‘near miss’ and much poorer forecasts) and can distinguish forecasts even when the spatial displacement of wind patterns is large. Moreover, the time-averaged score value in combination with a statistical significance test enables different wind forecasts to be ranked by their performance. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Monthly Weather Review American Meteorological Society

Verification of gridded wind forecasts in complex Alpine terrain: A new wind verification methodology based on the neighborhood approach

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0493
D.O.I.
10.1175/MWR-D-16-0471.1
Publisher site
See Article on Publisher Site

Abstract

AbstractA novel wind verification methodology is presented and analyzed for six surface wind cases in the greater Alpine region as well as an idealized setup. The methodology is based on the idea of the Fractions Skill Score, a neighborhood-based spatial verification metric frequently used for verifying precipitation. The new score avoids the problems of traditional non-spatial verification metrics (the ‘double penalty’ problem and the failure to distinguish between a ‘near miss’ and much poorer forecasts) and can distinguish forecasts even when the spatial displacement of wind patterns is large. Moreover, the time-averaged score value in combination with a statistical significance test enables different wind forecasts to be ranked by their performance.

Journal

Monthly Weather ReviewAmerican Meteorological Society

Published: Oct 25, 2017

References

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