Impact of GPS Radio Occultation Data on Tropical Cyclone Prediction

1. Impact of GPS Radio Occultation Data on Tropical Cyclone Prediction Y.-H. Kuo, X. Fang, Y.-R. Guo, H. Liu, and Z. Ma UCAR and NCAR

2. Impact of COSMIC on HurricaneErnesto (2006) Forecast With COSMIC Without COSMIC Results from Hui Liu, NCAR

3. Impact of COSMIC on HurricaneErnesto (2006) Forecast With COSMIC GOES Image GOES Image from Tim Schmitt, SSEC

4. Verification of WRF/DART analysis by about 100 dropsondes during the Ernesto genesis stage. See Hui Liu’s presentation later this morning, at 11:40 a.m.

5. Super Typhoon Jangmi (2008)

6. 4-km WRF forecast experiments for the genesis of Typhoon Jangmi • Start model at T = 3, 2.5, 2, and 1.5 days before the genesis • Use NCEP FNL as well as ECMWF I.C. • Mix FNL and ECMWF initial conditions by swapping moisture fields • FNL u.v. T + ECMWF q • FNL q + ECMWF u, v, T

7. FNL initial conditions T = -3 d T = -2.5 d T = -2 d T = -1.5 d

8. ECMWF initial conditions T = -3 d T = -2.5 d T = -2 d T = -1.5 d

9. 2-day forecast FNL u, v, T, q ECMWF u, v, T, q FNL – u, v, T EC -- q FNL - q EC – u, v, T

10. Comparison of WRF 3DVAR and WRF/DART forecast of Shanshan (2006) • Assimilation for 24 hours starting 00Z 13 September 2006 using both 3DVAR and WRF/DART ensemble system • Assimilation of CWB conventional data with/without RO data DARTNBNG: NO GPS run using WRF DART DARTNB: With GPS run suing WRF DART CYCLNBNG: NO GPS run using WRF 3dvar CYCLNB: With GPS run using WRF 3dvar • Followed by a 3-day forecast on 14 September 00Z.

11. Vorticity Analysis along typhoon centers (125.8E) on 00Z 14 September WRF/DART 3DVAR Vortex is stronger in WRF/DART analysis

12. Analysis at 00Z 14 Sept 2006 DART 3D-Var GPS - NO GPS EnKF - 3D-Var With GPS Without GPS

13. Typhoon intensity (central pressure) 3DVAR WRF/DART OBS

14. Typhoon track error 3DVAR WRF/DART

15. 24h forecast of 24-h accumulated rainfall (Aug 7-8) Ensemble mean Observed GPS NOGPS

16. Rain Probability Forecast (August 7-8 00Z) Ensemble mean Observed

17. Data Density for COSMIC and COSMIC-II Options: A, B, C, and D COSMIC - 6 x 72o COSMIC-IIA - 8 x 72o + 4 x 24o COSMIC-IIB - 12 x 72o COSMIC-IIC - 6 x 72o + 6 x 24o COSMIC-IIB - 4 x 72o + 8 x 24o

18. 3 hour 1 hour COSMIC-II SoundingsGeographic Coverage(6@72°, 6@24°) 24 hour 6 hour

19. Summary • Analysis and prediction of tropical cyclogenesis is highly sensitive to moisture distributions over the tropics. • GPS RO data provide valuable information on moisture that are important to tropical cyclone prediction. • The assimilation methods and strategies have significant influence on the impacts of GPS RO data on tropical cyclogenesis. Ensemble based data assimilation system performs better than 3D-Var. True for both global and regional weather prediction systems (e.g., WRF and NCEP GFS). • Use of cloud-scale ensemble system, coupled with advanced data assimilation system can be very valuable for the prediction of disastrous event such as Morakot. GPS RO data help improve the precipitation forecast for this case.

20. Outlook • Current COSMIC sounding distribution is NOT optimal for tropical prediction. We have the lowest data density over the tropics. • Future mission (e.g., COSMIC-II) should seek to substantially increase the data density over the tropics.