Yoshiaki Miyamoto 1 and Ming Xue 2 1: DPRI, Kyoto University 2: CAPS, the university of Oklahoma

1. The impacts of bogus data assimilationon the forecast for tropical cyclones:a case study of Typhoon Nakri (2008).-Preliminary results and future plans- Yoshiaki Miyamoto1 and Ming Xue2 1: DPRI, Kyoto University 2: CAPS, the university of Oklahoma

2. Outline • Tropical cyclone Bogus • What is my interest? • The previous studies • Background and purpose of this study • Data (the obs. Project) • Numerical simulation for Typhoon Nakri (2008) • Concluding remarks and future works

3. What I’m interested in now… Dynamics of ToRnadoSin a bin!!!

4. Tropical cyclone Bogus • Tropical Cyclone (TC)-Bogus scheme In this two decades, forecast models for tropical cyclones (TCs) have adopted TC bogus schemes; an artificially-made vortex is embedded into the initial field, in order to compensate the lack of specific and correct structure as well as intensity. The scheme actually has improved the forecast skill not only for the intensity but the track. • Bogus Data Assimilation Zou and Xiao (2000) suggested the bogus data assimilation for TCs; data assimilation (3D or 4DVAR) using the bogus vortex as well as the observational data, to remove the artificiality of TC-bogus.

5. Bogus Data Assimilation (BDA) • Zou and Xiao (2000) proposed the “Bogus Data Assimilation (BDA)” which is the TC bogus scheme based on the data assimilation technique. They introduced the method to adjust to the pressure (and wind) field (they used Fujita’s formula) and showed the improvement of the forecast skill. It is also found that the satellite data is useful for BDA as indicated in the previous studies (Krishnamurti et al., 1989, 1991, 1995). Cost Function Fujita’s eq. and Gradient balance where : Error covariance matrix

6. Summary of the previous studies • All studies have examined the impact of various obs. Data as well as the bogus one and shown that BDA scheme has a positive impact compared to the control run. • =>How about radar data on the ocean??

7. Motivation • Tropical cyclones are generated and developed on the tropical ocean which contains a lot of energy and generally go to northward due to the gradient of Coriolis parameter or environmental wind. • People naturally think that if we have observation data by radar on the ocean where TCs experience their earlier stages, the skill of TC-forecast may be much better. • The purpose of this study: Examine impacts of the radar data and the bogus data assimilation (BDA) on the forecast of TC track as well as intensity.

8. Observation campaign • Japan Agency for Marine Science and TEChnology (JAMSTEC) is carrying out a series of observation trip using the research vessel, “Mirai”, once or twice a year. In some trips, the researchers focus on the atmospheric phenomena such as MJO or Tropical cyclones. The first author joined one of them from May 25th to July 2nd ’08.

9. time

10. numerical simulations • Purpose : to examine the impact of Bogus Data Assimilation and Radar data on TC intensity and track. • Data : • Radar refractivity • Satellite-derived wind • Bogus pressure (Fujita, 1952) • Model : Weather Research and Forecasting (WRF) and WRF-3DVAR • simulations:

11. Experimental settings

12. Domain and Observation 05311200UTC • The cyclone passed away 300 km from the vessel (the situation in the ship was horrible.)

13. Results: intensity and track • The track of BGS is close to the best track while that of BDA is far away. This may result from the assimilation of the satellite-derived wind. • Bogus data (BGS/BDA) has a positive impact on the forecast for TC-intensity. BDA

14. Results: spatial structure Ctl Rad Water mixing ratio at 850hPa (shaded) & sea level pressure (contour) at 053122UTC Both Ctl and Rad show too small amount of water content while all can simulate the tendency of asymmetric structure (wave number 1 structure). BDA observation But,,, in this case, Radar data has little impact not only on the track and intensity but the structure.

15. Concluding remarks • Numerical simulations for Typhoon Nakri (2008) are carried out by using Bogus Data Assimilation (BDA) with the observation data of radar on the ocean. • Impact of BDA • => positive on the intensity / negative on the track • Impact of Radar data => Very small… Of course, the more careful examinations are needed. But, on the other hand, this result suggests that one radar which locates at 300 km away from the center of TC is not enough to affect on the results. • Future plans • Simulations for other cases are needed to investigate the impacts of BDA. • the ensemble experiments are just being carried out for down-scaling experiments under the global warming condition.

16. Acknowledgement • This study is partly supported by the research grant of Japan Society for the Promotion of Science (JSPS) : DC20776. All simulations and analysis are carried out using CAPS computer and OU supercomputer. • The first author appreciates kindness of his supervisor, Dr. Takemi, and Drs. Yoshi Sasaki, Bob Palmer, Tian Yu and Yasuko Umemoto. He is also grateful for Mr. Kefeng, Ms. Ningzhu and other CAPS members, in addition to Drs. Michihiro Teshiba and Ken-ichi Shimose. Without their help, I couldn’t go to and live in Oklahoma. Thanks for coming and your attention!

17. WRF-Var (Skamarock et al., 2005; Barker et al., 2003) Goal: minimize the cost function Initial guess (WPS,real) Observation (obsproc) Background error (gen_be) xb yo B WRF-Var xa NWC method (Parrish and Derber, 1992) Boundary condition (WRF_BC) WRF

18. Recent studies 1/5 (Zou and Xiao, 2000) • Zou and Xiao (2000) proposed the “Bogus Data Assimilation (BDA)” which is the TC bogus scheme based on the data assimilation technique. They introduced the method using the satellite data to adjust to the Fujita’s surface pressure distribution (Fujita, 1952) and showed the improvement of the forecast skill and the satellite data is also useful for BDA as shown in the previous study (Krishnamurti et al., 1989, 1991, 1995). Cost Function Fujita’s eq. and Gradient balance where : Error covariance matrix

19. Recent studies 2/5 (Xiao et al., 2000) • Xiao et al. (2000) confirmed the performance of BDA scheme and showed that the intensity forecast is sensitive to the initial RMW. • Zhang et al. (2003) also confirmed that in Typhoon case study. CTL After BDA procedure

20. Recent studies 3/5 (Pu and Braun, 2001) • Based on 4DVAR, Pu and Braun (2001) modified the method of Zou and Xiao (2000) because they pointed out their BDA scheme uses only the pressure field. The information of pressure is not generally provided while there are several routine works which observe the wind field (e.g., satellite). CTL assimilation of SLP only They confirmed the progress of forecast skill by BDA and showed the importance of assimilation of winds. In addition, the initial RMW should be “reasonable” (not so small and not so large as to be unrealistic). assimilation of wind only assimilation of SLP and wind

21. Recent studies 4/5 (Wu et al., 2006) • Wu et al. (2006) carried out a series of OSSEs to assess the potential impact of different variables on BDA. Their results indicated that the assimilation of wind fields produced better initial structure and predicted intensity than that of pressure fields. Moreover, they pointed out that interestingly, to include the initial movement of TC in the assimilation window improve the track forecast.

22. Recent studies 5/5 (Chow and Wu, 2008) • Chow and Wu (2008) also attacked the TC initialization problem using the dropwindsonde data obtained from DOTSTAR which is an obs. campaign for Typhoon movement and its detail is described in Wu et al., (2005, 2007a,b). This is a “data impact study”. They showed the combination of TC bogus and dropwindsonde data based on 3DVAR improves the track and intensity forecast skill. In the one case, the run with no/weak bogus vortex and without the dropwindsonde data could not capture the recurvature.

23. Increments of Figs. a, b and c: Ctl - Rad Figs. d, e and f: Ctl - RadBDA

24. Results: track and intensity Almost no impact on the track, maximum wind speed and central pressure.

25. Results of simulations (vertical cross section at the initial time) • Pressure deviation (shaded) and tangential velocity (contour)

26. Results and Concluding remarks Grid point (dx=12km) No perturbation (CTL) Perturbed *8 • In this case, BGS performs better than BDA. • The initial peturbation of position does not have large impacts on forecasts. • The exact position of CTL (no perturbation) seems to be the key factor especially for the track.