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      Stochastic simulation of predictive space-time scenarios of wind speed using observations and physical models

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          Abstract

          We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines multiple sources of past physical model outputs and measurements along with model predictions in order to produce a probabilistic wind speed forecast within the prediction window. We illustrate this strategy on a ground wind speed forecast for several months in 2012 for a region near the Great Lakes in the United States. The results show that the prediction is improved in the mean-squared sense relative to the numerical forecasts as well as in probabilistic scores. Moreover, the samples are shown to produce realistic wind scenarios based on the sample spectrum.

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          Journal
          2015-11-30
          2016-02-03
          1511.09416

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          ANL/MCS-P5432-1015
          stat.AP

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