Offshore wind field: Application of statistical models as a spatial validation technique
Generally, atmospheric mesoscale models are used as tools to perform wind atlases. In recent decades, significant efforts have been applied to the development and improvement of this kind of models to reduce their systematic errors. These ones are assessed when model results are compared with observ...
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| Outros Autores: | , , |
| Formato: | conferenceObject |
| Idioma: | eng |
| Publicado em: |
2012
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.9/1501 |
| País: | Portugal |
| Oai: | oai:repositorio.lneg.pt:10400.9/1501 |
| Resumo: | Generally, atmospheric mesoscale models are used as tools to perform wind atlases. In recent decades, significant efforts have been applied to the development and improvement of this kind of models to reduce their systematic errors. These ones are assessed when model results are compared with observations. In practice, such errors could be statistically corrected if observational data was available for the same area. A deviation matrix of the wind field between WRF (Weather Research and Forecasting) mesoscale model and wind data retrieved from the QuiKSCAT satellite was obtained by the application of two statistical techniques – kriging interpolation and composite method. The spatial validation performance was evaluated with observational wind data from an anemometric mast installed on Berlengas islet since November 2006 to the present. The following are a preliminary assessment of the statistical methods as spatial validation techniques. These are a part of the spatial validation methodology to be used within the EU FP7 NORSEWInD project. |
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