Probabilistic forecasts using analogs in the idealized Lorenz96 setting

Jakob W. Messner*, Georg J. Mayr

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Three methods to make probabilistic weather forecasts by using analogs are presented and tested. The basic idea of these methods is that finding similar NWP model forecasts to the current one in an archive of past forecasts and taking the corresponding analyses as prediction should remove all systematic errors of the model. Furthermore, this statistical postprocessing can convert NWP forecasts to forecasts for point locations and easily turn deterministic forecasts into probabilistic ones. These methods are tested in the idealized Lorenz96 system and compared to a benchmark bracket formed by ensemble relative frequencies from direct model output and logistic regression. The analog methods excel at longer lead times.

Original languageEnglish
JournalMonthly Weather Review
Volume139
Issue number6
Pages (from-to)1960-1971
Number of pages12
ISSN0027-0644
DOIs
Publication statusPublished - Jun 2011
Externally publishedYes

Keywords

  • Ensembles
  • Model comparison
  • Numerical weather prediction/forecasting
  • Probability forecasts/models/distribution
  • Ranking methods

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