Statistical post-processing of forecasts for extremes using bivariate brown-resnick processes with an application to wind gusts

Abstract

To improve the forecasts of weather extremes, we propose a joint spatial model for the observations and the forecasts, based on a bivariate Brown-Resnick process. As the class of stationary bivariate Brown-Resnick processes is fully characterized by the class of pseudo cross-variograms, we contribute to the theorical understanding of pseudo cross-variograms refining the knowledge of the asymptotic behaviour of all their components and introducing a parsimonious, but flexible parametric model. Both findings are of interest in classical geostatistics on their own. The proposed model is applied to real observation and forecast data for extreme wind gusts at 119 stations in Northern Germany.

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Correspondence to Marco Oesting.

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Oesting, M., Schlather, M. & Friederichs, P. Statistical post-processing of forecasts for extremes using bivariate brown-resnick processes with an application to wind gusts. Extremes 20, 309–332 (2017). https://doi.org/10.1007/s10687-016-0277-x

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Keywords

  • Bivariate random field
  • Matérn model
  • Max-stable process
  • Pseudo cross-variogram

AMS 2000 Subject Classifications

  • 60G70
  • 62M30
  • 60G60