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Highlight of the CWB WRF development

Highlight of the CWB WRF development . OUTLINE. Re-center the EAKF using the blending scheme Hybrid variational /ensemble data assimilation . Blending Scheme. Guess Blending. Analysis Blending. Fields to be Blended ( 13) - U, V, T, QVAPOR, PH, P, MU, - U10, V10, T2, Q2, PSFC, TH2.

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Highlight of the CWB WRF development

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  1. Highlight of the CWB WRF development

  2. OUTLINE • Re-center the EAKF using the blending scheme • Hybrid variational/ensemble data assimilation

  3. Blending Scheme Guess Blending Analysis Blending Fields to be Blended (13) - U, V, T, QVAPOR, PH, P, MU, - U10, V10, T2, Q2, PSFC, TH2 CLS=1200 km

  4. Ensemble Forecast 6hr analysis analysis guess EA K F Xb1 Xb1 EA K F RECENTER Xa1 Xb2 Xb2 Xa2 Xb32 Xb32 Xa32 guess_mean Blend guess_mean Blend analy_mean Guess Blending WRF 72hr

  5. Ensemble Forecast 6hr guess analysis EA K F Xb1 Xa1 Xa1 RECENTER Xb2 Xa2 Xa2 Xb32 Xa32 Xa32 Blend Blend analy_mean analy_mean Blend Analysis Blending WRF 72hr

  6. Experimental Design • Model Version：CWB OP24 • Run：Full Cycling • Domain：CWB WRF Domain 1 (45KM) • Period： 2008/09/04 00UTC ~ 2008/09/23 00 UTC T-PARC • Experiments： • Without Blending (woBL, CTL) • Guess Blending (guessBL) • Analysis Blending (analyBL) • analyBL + Ensemble Mean Analysis with Bleinding (analyBL_mBL)

  7. Ensemble Performance T U V woBL small guessBL over analyBL

  8. SCORE of Ensemble Mean Analysis Forecast 72hr (against NCEP) woBL：代表無Blending guessBL：Guess Blneding analyBL：Analysis Blending analyBL_m：blending again on analyBL ensemble mean 24hr T H U V

  9. SCORE of Ensemble Mean Analysis Forecast 72hr (against NCEP) woBL：代表無Blending guessBL：Guess Blneding analyBL：Analysis Blending analyBL_m：blending again on analyBL ensemble mean T H U V 48hr

  10. SCORE of Ensemble Mean Analysis Forecast 72hr (against NCEP) woBL：代表無Blending guessBL：Guess Blneding analyBL：Analysis Blending analyBL_m：blending again on analyBL ensemble mean T H U V 72hr

  11. TC Track Forecasts - SINLAKU (1) woBL：代表無Blending guessBL：Guess Blneding analyBL：Analysis Blending analyBL_m：blending again on analyBL ensemble mean woBL guessBL analyBL analyBL_m from 2008/09/09 00UTC to 2008/09/13 00UTC

  12. TC Track Forecasts - SINLAKU (2) woBL：代表無Blending guessBL：Guess Blneding analyBL：Analysis Blending analyBL_m：blending again on analyBL ensemble mean from 2008/09/09 00UTC to 2008/09/13 00UTC

  13. TC Track Forecasts - HAGUPIT (1) woBL：代表無Blending guessBL：Guess Blneding analyBL：Analysis Blending analyBL_m：blending again on analyBL ensemble mean woBL guessBL analyBL analyBL_m from 2008/09/20 00UTC to 2008/09/23 00UTC

  14. TC Track Forecasts - HAGUPIT (2) woBL：代表無Blending guessBL：Guess Blneding analyBL：Analysis Blending analyBL_m：blending again on analyBL ensemble mean from 2008/09/20 00UTC to 2008/09/23 00UTC

  15. Summary • Guess-blending outperforms the other experiments, especially for the typhoon track • More detail analysis is undergoing to answer why guess blending is the best • The effect of the blending scheme is bounded by the GFS performance, the blending strategy should be re-evaluated as the GFS was improved, e.g. 2012 NCEP GFS

  16. Performance of the hybrid system • Single Observation Tests in 3DVAR-Hybrid - Tests of Tuning Factors in Hybrid • Localization Scale • Ensemble Covariance Weighting • Vertical localization • The use of the ensemble perturbation

  17. Single Observation Tests in 3DVAR-Hybrid • Observation Setting • Tuning Factors in Hybrid • Localization Scale • Ensemble Covariance Weighting • Temperature • innov = 1 K，obs_err = 1 K • Lon ~ 137.143 ( x = 150 ) • Lat ~ 28.2 ( y = 69 ) • Lev ~ 860 mb ( z = 11 )

  18. Localization Scale 200 km 375 km 750 km Ensemble System：EAKF Shade：Increment Green Line：Geopotential Height of Ensemble Forecast 6hr Mean.

  19. Ensemble Covariance Weighting Factor VAR 50% 75% Full Ensemble System：EAKF Shade：Increment Green Line：Geopotential Height of Ensemble Forecast 6hr Mean.

  20. Lev=11 (~860mb) Y-Z Plane EnSRF HGSI EAKF HVAR

  21. Lev=21 (~520mb) Y-Z Plane EnSRF HGSI EAKF HVAR

  22. Lev=30 (~250mb) Y-Z Plane EnSRF HGSI EAKF HVAR

  23. Summary • Localization scale of 200 km and 75% ensemble BE are used in the hybrid analysis. • Vertical localization in WRF VAR-Hybrid should be tuned. • The moisture field has the most dramatic change as including the ensemble BE.

  24. Evaluation of the 3DVAR-Hybrid • PART-1：Ensemble Members of EAKF without/with Blending • PART-2：3DVAR vs. Hybrid-EAKF • PART-3：Hybrid-WEPS vs. Hybrid-EAKF • PART-4：WEPS + EAKF

  25. Evaluation of the 3DVAR-Hybrid3DVAR vs. Hybrid-EAKF Experimental Design： • Model Version：CWB OP25 • Run：Partial Cycling • Domain：CWB WRF Domain 1 (45KM) • Period： 2008/09/09 00UTC ~ 2008/09/30 12 UTC T-PARC • Ensemble members of Hybrid-EAKF from “analyBL” case. • Verified against the NCEP GFS analysis and RAOB/dropsound

  26. 3DVARHEAKF ana H T U V

  27. 3DVARHEAKF H T U V 12hr

  28. 3DVARHEAKF H T U V 24hr

  29. 3DVARHEAKF H T U V 72hr

  30. One Month Mean 100 mb V U ana 12hr Shade： Difference ( 3DVAR - HEAKF ) Green Line：Geopotential Height of HEAKF 72hr

  31. One Month Mean 300 mb V U ana 12hr Shade： Difference ( 3DVAR - HEAKF ) Green Line：Geopotential Height of HEAKF 72hr

  32. One Month Mean 850 mb Q T ana 12hr Shade： Difference ( 3DVAR - HEAKF ) Green Line：Geopotential Height of HEAKF 72hr

  33. OBS Location

  34. 12hr 3DVARHEAKF T WIND Qs

  35. 24hr 3DVARHEAKF T WIND Qs

  36. 72hr 3DVARHEAKF T WIND Qs

  37. Summary • Compare to the 3DVAR, the forecast performance is slightly better in the hybrid system. • The major differences are high level wind, low level temperature and moisture. • The reason to cause the difference is not clear yet.

  38. Evaluation of the 3DVAR-HybridHybrid-WEPS vs. Hybrid-EAKF Spin-up Hybrid-EAKF Hybrid-WEPS ϐe : ϐb = 0.75 : 0.25

  39. SCORE of Ensemble Mean Analysis Forecast 72hr (against NCEP) HWPESHEAKF T 24hr ANA. 48hr 72hr

  40. Analysis Difference in SINLAKU Period T 850 mb 3DVAR HEAKF HWEPS HEAKF Qv

  41. SINLAKU Typhoon Track 3DVAR HEAKF HWEPS from 2008/08/09 12UTC to 2008/08/13 00UTC

  42. HAGUPIT Typhoon Track 3DVAR HEAKF HWEPS from 2008/08/20 00UTC to 2008/08/23 00UTC

  43. JANGMI Typhoon Track 3DVAR HEAKF HWEPS from 2008/08/24 12UTC to 2008/08/28 00UTC

  44. Evaluation of the 3DVAR-HybridHybrid-EAKF+WEPS vs. Hybrid-EAKF 32 members EAKF 52 members EAKF+WEPS 3DVAR-Hybrid 20 members WEPS

  45. Analysis Difference in SINLAKU Period 850 mb T, Qv HEKWP - HEAKF HEKWP T Qv HWEPS - HEAKF

  46. SCORE of Ensemble Mean Analysis Forecast 72hr (against DROPSONDES_SPECIFIC_HUMIDITY) HEKWP 12hr 24hr HEAKF 48hr 72hr

  47. 𝛽e 1.0 Lev=11 (~860mb) Full ensemble mode T Q V U HEKWP HEAKF HWEPS

  48. 𝛽e Lev=30 (~250mb) 1.0 Full ensemble mode T Q V U HEKWP HEAKF HWEPS

  49. Summary The difference between HEAKF, HWEPS, and HEKW is limited. HWEPS has the moisture spin-up issue.

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