Simultaneous ensemble postprocessing for multiple lead times with standardized anomalies

Markus Dabernig, Georg J. Mayr, Jakob Messner, Achim Zeileis

Research output: Contribution to journalJournal articleResearchpeer-review

214 Downloads (Pure)

Abstract

Separate statistical models are typically fit for each forecasting lead time to postprocess numerical weather prediction (NWP) ensemble forecasts. Using standardized anomalies of both NWP values and observations eliminates most of the lead-time-specific characteristics so that several lead times can be forecast simultaneously. Standardized anomalies are formed by subtracting a climatological mean and dividing by the climatological standard deviation. Simultaneously postprocessing forecasts between +12 and +120 h increases forecast coherence between lead times, yields a temporal resolution as high as the observation interval (e.g., up to 10 min), and speeds up computation times while achieving a forecast skill comparable to the conventional method.
Original languageEnglish
JournalMonthly Weather Review
Volume145
Issue number7
Pages (from-to)2523-2531
ISSN0027-0644
DOIs
Publication statusPublished - 2017
Externally publishedYes

Keywords

  • Meteorology
  • Atmospheric Properties
  • Atmosphere
  • Ensembles
  • Probability forecasts/models/distribution
  • Statistical forecasting
  • Statistical techniques
  • Earth atmosphere
  • Forecasting
  • Conventional methods
  • Ensemble post-processing
  • Numerical weather prediction
  • Observation interval
  • Weather forecasting

Fingerprint

Dive into the research topics of 'Simultaneous ensemble postprocessing for multiple lead times with standardized anomalies'. Together they form a unique fingerprint.

Cite this