Post-processing methods for calibrating the wind speed forecasts in central regions of Chile

Mailiu Díaz, Orietta Nicolis, Julio César Marín, Sándor Baran

Research output: Contribution to journalArticlepeer-review


In this paper we propose some parametric and non-parametric post-processing methods for calibrating wind speed forecasts of nine Weather Research and Forecasting (WRF) models for locations around the cities of Valparaíso and Santiago de Chile (Chile). The WRF outputs are generated with different planetary boundary layers and land-surface model parametrizations and they are calibrated using observations from 37 monitoring stations. Statistical calibration is performed with the help of ensemble model output statistics and quantile regression forest (QRF) methods both with regional and semi-local approaches. The best performance is obtained by the QRF using a semi-local approach and considering some specific weather variables from WRF simulations.

Original languageEnglish
Pages (from-to)93-108
Number of pages16
JournalAnnales Mathematicae et Informaticae
Publication statusPublished - 2021


  • Ensemble calibration
  • Ensemble model output statistics
  • Quantile regression forest
  • Statistical post-processing
  • Wind speed

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


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