Surface Wind Regionalization over Complex Terrain: Evaluation and Analysis of a High-Resolution WRF Simulation

This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model for the period 1992–2005. The evaluation focuses on the...

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Veröffentlicht in:Journal of applied meteorology and climatology 2010-02, Vol.49 (2), p.268-287
Hauptverfasser: Jiménez, Pedro A., González-Rouco, J. Fidel, García-Bustamante, Elena, Navarro, Jorge, Montávez, Juan P., De Arellano, Jordi Vilà-Guerau, Dudhia, Jimy, Muñoz-Roldan, Antonio
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Sprache:eng
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Zusammenfassung:This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model for the period 1992–2005. The evaluation focuses on the performance of the simulation to reproduce the wind variability within subregions identified from observations over the 1999–2002 period in a previous study. By comparing with wind observations, the model results show the ability of the WRF dynamical downscaling over a region of complex terrain. The higher spatiotemporal resolution of the WRF simulation is used to evaluate the extent to which the length of the observational period and the limited spatial coverage of observations condition one’s understanding of the wind variability over the area. The subregions identified with the simulation during the 1992–2005 period are similar to those identified with observations (1999–2002). In addition, the reduced number of stations reasonably represents the spatial wind variability over the area. However, the analysis of the full spatial dimension simulated by the model suggests that observational coverage could be improved in some subregions. The approach adopted here can have a direct application to the design of observational networks.
ISSN:1558-8424
1558-8432
DOI:10.1175/2009jamc2175.1