Stochastic simulation of predictive space-time scenarios of wind speed using observations and physical model outputs. (English) Zbl 1393.62121

Summary: 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 in order to produce a probabilistic wind speed forecast within the prediction window. We illustrate this strategy on wind speed forecasts during 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 sample spectra and space-time correlation structure.


62P12 Applications of statistics to environmental and related topics
62M30 Inference from spatial processes
Full Text: DOI arXiv Euclid


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