An Impact Study of GPS RO Data on the Typhoon Track Forecast using the CWB Global Forecast System

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1 An Impact Study of GPS RO Data on the Typhoon Track Forecast using the CWB Global Forecast System Ming-Jen Yang 1, Yu-Chun Chen 2,1, Yen-Chih Shen 2, Chin-Tzu Fong 2, and Wen-Mei Chen 2 1 National Central University, Chung-Li, Taiwan 2 Central Weather Bureau, Taipei, Taiwan 2011/04/13 COSMIC workshop

2 Dynamics CWB-GFS Resolution: T239L30 Semi-implicit time integration Physics surface layer: similarity theory Gravity wave drag: similar to Palmer et al. (1986) Shallow convection scheme (Li and Young 1993) Land process: two-layer soil model Boundary layer: a first-order nonlocal scheme Cumulus parameterization: Simple Arakawa- Schubert Radiation scheme: Fu and Liou (1996)

3 Assimilation of GPSRO Grid-point Statistical Interpolation (GSI) Local refractivity 3-terms forward operator N P T + k P T + k P T d w w = k QC and observation error characterization are the same as for NCEP-GFS Cucurull, 2010

4 ALL TCs during 2008 to 2010 Typhoon Period Category Type Impact of RO Kalmaegi Northward Fung-Won Recurved Nuri Westward Sinlaku Recurved Hagupit Westward Jangmi Recurved Morakot Recurved Parma Westward Melor Recurved Fanapi Recurved Megi Recurved Negative Positive Neutral

5 Track Error (ALL) CNTL: without RO GPS: with RO total along cross

6 Track Error (only TCPE Recurved) CNTL: without RO GPS: with RO total along cross

7 Track Error (only TCPE Westward) CNTL: without RO GPS: with RO total along cross

8 RMSE of wind in West Pacific Compare track error and RMSE of wind in west pacific domain. West Pacific

9 Track Error Time series along: along track error cross: cross track error Purple: RMSE of wind Track Error and 500 mb RMSE of wind MEGI Positive Impactin average Recurving period NEGATIVE POSITIVE

10 Red: CNTL, without RO Blue: GPS, with RO Black: NCEP analysis Orange dots: GPSRO sounding Typhoon MEGI 5880 of Sub-tropical high shows the eastward extension with GPSRO assimilation, and the forecast track is more correct

11 For typhoon Megi, the assimilation of GPSRO will change the forecast steering flow significantly.

12 CNTL GPS

13 Track Error Time series along: along track error cross: cross track error Purple: RMSE of wind Track Error and 500 mb RMSE of wind SINLAKU Negative Impactin average Recurving period NEGATIVE POSITIVE

14 The horizontal drift and the radio ray directions of GPSRO cross the TC inner areas

$Spherical Symmetry Assumption When assimilating local refractivity, we should remove the$

15 Spherical Symmetry Assumption When assimilating local refractivity, we should remove the observation violated SSA. If the observation is close to TC inner area, how about the impact when removing it?

16 Ini. Time: Remove this GPSRO will decrease forecast error EXP: Remove the RO GPS: with RO

17 For typhoon Melor, removing this GPSRO doesn t change the forecast steering flow significantly, except at the initial time.

18 Summary Most positive impacts occur at the time of typhoons having curved tracks. GPSRO observations can usually improve the RMS error of wind in synoptic scale. Most negative impacts are found when the GPS limb soundings penetrate through the typhoon inner cores with large horizontal temperature and moisture gradients.

19 The End

20 Track Error Time series along: along track error cross: cross track error Purple: RMSE of wind Track Error and 500 mb RMSE of U MEGI Positive case in average Recurving period

21 Track Error Time series along: along track error cross: cross track error Purple: RMSE of wind Track Error and 500 mb RMSE of V MEGI Positive case in average Recurving period

22 Track Error Time series along: along track error cross: cross track error Purple: RMSE of wind Track Error and 700 mb RMSE of wind SINLAKU Negative case in average Recurving period

23 Track Error Time series along: along track error cross: cross track error Purple: RMSE of wind Track Error and 500 mb RMSE of U SINLAKU Negative case in average Recurving period

24 Track Error Time series along: along track error cross: cross track error Purple: RMSE of wind Track Error and 500 mb RMSE of V SINLAKU Negative case in average Recurving period

Impact of GPS RO Data on the Prediction of Tropical Cyclones

Impact of GPS RO Data on the Prediction of Tropical Cyclones Ying-Hwa Kuo, Hui Liu, UCAR Ching-Yuang Huang, Shu-Ya Chen, NCU Ling-Feng Hsiao, Ming-En Shieh, Yu-Chun Chen, TTFRI Outline Tropical cyclone