WRF Hub-Height Wind Forecast Sensitivity to PBL Scheme, Grid Length, and Initial Condition Choice in Complex Terrain

David Siuta University of British Columbia, Vancouver, British Columbia, Canada

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Gregory West University of British Columbia, Vancouver, British Columbia, Canada

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Roland Stull University of British Columbia, Vancouver, British Columbia, Canada

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Abstract

This study evaluates the sensitivity of wind turbine hub-height wind speed forecasts to the planetary boundary layer (PBL) scheme, grid length, and initial condition selection in the Weather Research and Forecasting (WRF) Model over complex terrain. Eight PBL schemes available for the WRF-ARW dynamical core were tested with initial conditions sources from the North American Mesoscale (NAM) model and Global Forecast System (GFS) to produce short-term wind speed forecasts. The largest improvements in forecast accuracy primarily depended on the grid length or PBL scheme choice, although the most important factor varied by location, season, time of day, and bias-correction application. Aggregated over all locations, the Asymmetric Convective Model, version 2 (ACM2) PBL scheme provided the best forecast accuracy, particularly for the 12-km grid length. Other PBL schemes and grid lengths, however, did perform better than the ACM2 scheme for individual seasons or locations.

Denotes content that is immediately available upon publication as open access.

© 2017 American Meteorological Society.

This article is licensed under a Creative Commons Attribution 4.0 license. (http://creativecommons.org/licenses/by/4.0/).

Corresponding author e-mail: David Siuta, dsiuta@eos.ubc.ca

Abstract

This study evaluates the sensitivity of wind turbine hub-height wind speed forecasts to the planetary boundary layer (PBL) scheme, grid length, and initial condition selection in the Weather Research and Forecasting (WRF) Model over complex terrain. Eight PBL schemes available for the WRF-ARW dynamical core were tested with initial conditions sources from the North American Mesoscale (NAM) model and Global Forecast System (GFS) to produce short-term wind speed forecasts. The largest improvements in forecast accuracy primarily depended on the grid length or PBL scheme choice, although the most important factor varied by location, season, time of day, and bias-correction application. Aggregated over all locations, the Asymmetric Convective Model, version 2 (ACM2) PBL scheme provided the best forecast accuracy, particularly for the 12-km grid length. Other PBL schemes and grid lengths, however, did perform better than the ACM2 scheme for individual seasons or locations.

Denotes content that is immediately available upon publication as open access.

© 2017 American Meteorological Society.

This article is licensed under a Creative Commons Attribution 4.0 license. (http://creativecommons.org/licenses/by/4.0/).

Corresponding author e-mail: David Siuta, dsiuta@eos.ubc.ca
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