Comparison of ensemble-MOS methods in the Lorenz '96 setting
Article first published online: 25 JAN 2007
Copyright © 2006 John Wiley & Sons, Ltd.
Volume 13, Issue 3, pages 243–256, September 2006
How to Cite
Wilks, D. S. (2006), Comparison of ensemble-MOS methods in the Lorenz '96 setting. Met. Apps, 13: 243–256. doi: 10.1017/S1350482706002192
- Issue published online: 25 JAN 2007
- Article first published online: 25 JAN 2007
- Manuscript Revised: JAN 2006
- Manuscript Received: 24 AUG 2005
- ensemble forecasting;
- logistic regression;
- ensemble dressing
A suite of methods that have been proposed for statistical post-processing of ensemble forecasts based on historical verification data (i.e. ensemble-MOS methods) are compared with each other, and with direct probability estimates using ensemble relative frequencies, in the idealised Lorenz '96 setting. The three most promising methods are logistic regressions predicting probabilities associated with selected quantiles, ensemble dressing (a kernel density estimation approach), and linear regressions with non-constant prediction errors that depend on the ensemble variance. Copyright © 2006 John Wiley & Sons, Ltd.