A convective‐scale 1,000‐member ensemble simulation and potential applications

Tobias Necker, Stefan Geiss, Martin Weissmann, Juan Ruiz , Takemasa Miyoshi, Guo‐Yuan Lien

Publications: Contribution to journalArticlePeer Reviewed

Abstract

This study presents the first convective‐scale 1,000‐member ensemble simulation over central Europe, which provides a unique data set for various applications. A comparison with the operational regional 40‐member ensemble of Deutscher Wetterdienst shows that the 1,000‐member simulation exhibits realistic spread properties overall. Based on this, we discuss two potential applications. First, we quantify the sampling error of spatial covariances of smaller subsets compared with the 1,000‐member simulation. Knowledge about sampling errors and their dependence on ensemble size is crucial for ensemble and hybrid data assimilation and for developing better approaches for localization in this context. Secondly, we present an approach for estimating the relative potential impact of different observable quantities using ensemble sensitivity analysis. This will provide the basis for consecutive studies developing future observation and data assimilation strategies. Sensitivity studies on the ensemble size indicate that about 200 ensemble members are required to estimate the potential impact of observable quantities with respect to precipitation forecasts.
Original languageEnglish
Pages (from-to)1423-1442
Number of pages20
JournalQuarterly Journal of the Royal Meteorological Society
Volume146
Issue number728
DOIs
Publication statusPublished - Apr 2020

Austrian Fields of Science 2012

  • 105206 Meteorology

Keywords

  • BIG DATA ASSIMILATION
  • COVARIANCE LOCALIZATION
  • IMPACT
  • INFRARED RADIANCES
  • KALMAN FILTER
  • MODEL
  • SAMPLING ERROR
  • SENSITIVITY-ANALYSIS
  • TRANSFORM
  • WEATHER PREDICTION
  • convective-scale
  • covariance
  • data assimilation
  • ensemble sensitivity analysis
  • localization
  • observing system
  • sampling error

Cite this