1. Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Statistical adaptation of COSMO predictions with the Kalman Filter Vanessa Stauch COSMO-GM at Krakau September 2008

2. 2 MeteoSwiss Statistical Postprocessing Vanessa Stauch Outline Local forecast corrections with the Kalman Filter 2m temperature of COSMO-LEPS “10m windspeed” of COSMO-7 & COSMO-2

3. 3 MeteoSwiss Statistical Postprocessing Vanessa Stauch Statistical adaptation (Forster 2007) Correct for systematic deviations between NWP model output and local observations » identification of an error model

4. 4 MeteoSwiss Statistical Postprocessing Vanessa Stauch Statistical adaptation with KF err T DMO t=1 t=2 - obs fcst corrected fcst first guess

5. 5 MeteoSwiss Statistical Postprocessing Vanessa Stauch Statistical adaptation with KF err T DMO t=2 - t=1 t=2 obs fcst corrected fcst first guess

6. 6 MeteoSwiss Statistical Postprocessing Vanessa Stauch Statistical adaptation with KF err T DMO obs fcst corrected fcst first guess t=1 t=2

7. 7 MeteoSwiss Statistical Postprocessing Vanessa Stauch Statistical adaptation with KF err T DMO » minimising the prediction error variance for noise variances » assumptions on error propagation obs fcst corrected fcst first guess t=2 t=1

8. 8 MeteoSwiss Statistical Postprocessing Vanessa Stauch 2m temperature of COSMO-7 Annual mean error along with its standard deviation and compared to persistence (Lugano 2006) Kalman filter successful for COSMO-7 (implemented by D. Cattani)

9. 9 MeteoSwiss Statistical Postprocessing Vanessa Stauch 2m temperature of COSMO-LEPS Annual mean error along with its standard deviation and compared to persistence (Lugano 2006) What about COSMO- LEPS? Verification on ensemble mean still to do! Kalman filter successful for COSMO-7 (implemented by D. Cattani)

10. 10 MeteoSwiss Statistical Postprocessing Vanessa Stauch KF experiments with COSMO-LEPS » „deterministic“ KF with mean, median, random member » identify best method but also confirm assumptions about „common error structure“ of all members Geneva, 01.02.2008

11. 11 MeteoSwiss Statistical Postprocessing Vanessa Stauch KF experiments with COSMO-LEPS obs at t - 1 forecast at t forecast at t - 1 forecast at t - 2 forecast at t - 3 forecast at t - 4 forecast at t - 5 12 UTC » account for lead time dependent error if systematic changes observable » optimise one-step ahead prediction error variance » start with latest 00UTC observations

12. 12 MeteoSwiss Statistical Postprocessing Vanessa Stauch First results

13. 13 MeteoSwiss Statistical Postprocessing Vanessa Stauch Verification

14. 14 MeteoSwiss Statistical Postprocessing Vanessa Stauch Wind speed of COSMO-7 & COSMO-2 Wiforch (Meteotest, MeteoSwiss) Fore- and Nowcasting of wind power production in complex terrain. Windturbine at Gütsch » 24-48 hour power forecasts for energy market (COSMO-7) » 1-6 hour power forcast for intradaily trading (COSMO-2) » Comparison with WindSim (CFD)

15. 15 MeteoSwiss Statistical Postprocessing Vanessa Stauch COSMO-7 vs COSMO-2 at Guetsch

16. 16 MeteoSwiss Statistical Postprocessing Vanessa Stauch COSMO-7 vs COSMO-2

17. 17 MeteoSwiss Statistical Postprocessing Vanessa Stauch Kalman Filter corrections winter 07/08

18. 18 MeteoSwiss Statistical Postprocessing Vanessa Stauch Kalman Filter corrections spring 08

19. 19 MeteoSwiss Statistical Postprocessing Vanessa Stauch COSMO-7 vs COSMO-2

20. 20 MeteoSwiss Statistical Postprocessing Vanessa Stauch Conclusions » Local corrections for T2m of COSMO-LEPS = work in progress! » Verification of different error models and assumptions on the error prediction should identify a „best“ set-up » KF for wind speed results in better predictions for the sites investigated. » 3months testphase from October will evaluate performance in more detail and compare to a linear MOS and the DMOs

21. 21 MeteoSwiss Statistical Postprocessing Vanessa Stauch

22. 22 MeteoSwiss Statistical Postprocessing Vanessa Stauch COSMO-7 vs COSMO-2