Skip to main content

Open Access Enhancing COSMO-DE ensemble forecasts by inexpensive techniques

Download Article:
 Download
(PDF 827.8486328125 kb)
 
COSMO-DE-EPS, a convection-permitting ensemble prediction system based on the high-resolution numerical weather prediction model COSMO-DE, is pre-operational since December 2010, providing probabilistic forecasts which cover Germany. This ensemble system comprises 20 members based on variations of the lateral boundary conditions, the physics parameterizations and the initial conditions. In order to increase the sample size in a computationally inexpensive way, COSMO-DE-EPS is combined with alternative ensemble techniques: the neighborhood method and the time-lagged approach. Their impact on the quality of the resulting probabilistic forecasts is assessed. Objective verification is performed over a six months period, scores based on the Brier score and its decomposition are shown for June 2011. The combination of the ensemble system with the alternative approaches improves probabilistic forecasts of precipitation in particular for high precipitation thresholds. Moreover, combining COSMO-DE-EPS with only the time-lagged approach improves the skill of area probabilities for precipitation and does not deteriorate the skill of 2 m-temperature and wind gusts forecasts.
No References for this article.
No Supplementary Data.
No Data/Media
No Metrics

Keywords: ENSEMBLE FORECASTING; NEIGHBORHOOD; TIME-LAGGED

Document Type: Research Article

Publication date: 2013-02-01

More about this publication?
  • Meteorologische Zeitschrift (originally founded in 1866) is the joint periodical of the meteorological societies of Austria, Germany and Switzerland. It accepts high-quality peer-reviewed manuscripts on all aspects of observational, theoretical and computational research out of the entire field of meteorology, including climatology. Meteorologische Zeitschrift represents a natural forum for the meteorological community of Central Europe and worldwide.
  • Editorial Board
  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more