Log‐normal distribution based Ensemble Model Output Statistics models for probabilistic wind‐speed forecasting

@article{Baran2014LognormalDB,
  title={Log‐normal distribution based Ensemble Model Output Statistics models for probabilistic wind‐speed forecasting},
  author={S{\'a}ndor Baran and Sebastian Lerch},
  journal={Quarterly Journal of the Royal Meteorological Society},
  year={2014},
  volume={141}
}
  • S. Baran, S. Lerch
  • Published 11 July 2014
  • Environmental Science
  • Quarterly Journal of the Royal Meteorological Society
Ensembles of forecasts are obtained from multiple runs of numerical weather forecasting models with different initial conditions and typically employed to account for forecast uncertainties. However, biases and dispersion errors often occur in forecast ensembles: they are usually underdispersive and uncalibrated and require statistical post‐processing. We present an Ensemble Model Output Statistics (EMOS) method for calibration of wind‐speed forecasts based on the log‐normal (LN) distribution… 

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