Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/116668
Title: Combining statistical and ensemble methods for probabilistic wind field prediction
Authors: Oliver Serra, Albert 
Mazorra-Aguiar, Luis 
Rodríguez, Eduardo 
Montero, Gustavo 
UNESCO Clasification: 1206 Análisis numérico
Keywords: Ensemble methods
Wind modeling
Issue Date: 2019
Conference: 9th International Congress on Industrial and Applied Mathematics (ICIAM 2019) 
Abstract: Probabilistic wind forecasting is a methodology to deal with uncertainties in numerical weather prediction models (NWP). In this work, we present a combination of statistical and ensemble methods designed for the downscaling wind model Wind3D coupled with the HARMONIE-AROME mesoscale model. The ensemble method is based on a Monte Carlo approach, and the statistical method is the linear model in quantile regression (LMQR). The combination of both results give a probabilistic forecasting.
URI: http://hdl.handle.net/10553/116668
Source: 9th International Congress on Industrial and Applied Mathematics (ICIAM 2019), p. 130
Appears in Collections:Actas de congresos
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