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Statistical adaptation of COSMO predictions with the Kalman Filter

Statistical adaptation of COSMO predictions with the Kalman Filter. COSMO-GM at Krakau September 2008. Vanessa Stauch. Outline. Local forecast corrections with the Kalman Filter 2m temperature of COSMO-LEPS “10m windspeed” of COSMO-7 & COSMO-2. Statistical adaptation. (Forster 2007).

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Statistical adaptation of COSMO predictions with the Kalman Filter

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  1. Statistical adaptation of COSMO predictions with the Kalman Filter COSMO-GM at Krakau September 2008 Vanessa Stauch

  2. Outline • Local forecast corrections with the Kalman Filter • 2m temperature of COSMO-LEPS • “10m windspeed” of COSMO-7 & COSMO-2

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

  4. fcst corrected fcst first guess obs Statistical adaptation with KF err t=2- t=1 TDMO

  5. fcst corrected fcst first guess obs Statistical adaptation with KF err t=2- t=2 t=1 TDMO

  6. fcst corrected fcst first guess obs Statistical adaptation with KF err t=2 t=1 TDMO

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

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

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

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

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

  12. First results

  13. Verification

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

  15. COSMO-7 vs COSMO-2 at Guetsch

  16. COSMO-7 vs COSMO-2

  17. Kalman Filter corrections winter 07/08

  18. Kalman Filter corrections spring 08

  19. COSMO-7 vs COSMO-2

  20. 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. COSMO-7 vs COSMO-2

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