Preliminary evaluation of the impact of the FORMOSAT 7R wind on tropical cyclone assimilation and prediction Shu Chih Yang 1,2, Cheng Chieh Kao 1,2, Wen Hao Yeh 3 and Stefani Huang 1 1 Dept. of Atmospheric sciences, National Central University, Taiwan 2 GPS Science and Application Research Center, National Central University, Taiwan 3 National Space Organization, National Applied Research Laboratory, Taiwan
FORMOSAT 7R Earth coverage 1 day Global coverage The satellite FORMOSAT 7 Reflectometry, as a part of 12 FORMOSAT 7/COSMIC 2 mission satellites, is built as GNSS Reflectometric mission (Formosat 7R, will launch in the end of 2010s). The altitude of the mission orbit is 600km and its inclination angle is 72deg. Measure the roughness and wind speed on ocean surface.
Data processing Data Processing Center (TROPS) Level 0 Products (on board, NSPO) 0a Raw I/Q samples 0b Fully resolved DDMs Telemetry downlink to NSPO Level 1 Products (NCKU) 1a Calibrated DDMs of received power 1b Calibrated DDMs of scattering cross section Level 2 Products (NCU/NSPO) 2a Mean square slope (surface roughness) in ungridded observatory coordinate system and serial time stamp without precision geolocation 2b Wind speed in ungridded observatory coordinate system and serial time stamp without precision geolocation Level 3 Products (TORI) 3a Gridded wind speed with precision geolocation 3b Gridded ocean surface roughness with precision geolocation Users/Science Team CWB,TTFRI,TORI,NCU,..
Mission requirement Goal Measurement requirements parameters Expected performance Measurement under precipitation condition < 120mm/hr Wind speed retrieval under TC range 20 70 m/s Wind speed error 10% Wind speed under regular conditions resolution range Wind speed error 25 km 3 20 m/s 1 m/s
Motivation Compared to the Atlantic ocean, TC targeted observations are limited over the Pacific ocean. Predicting TC intensity relies on the dropsondes or other vortex initialization schemes when TCs develop over ocean. The FORMOSAT 7R wind speed data has the advantage of observing high wind speed over TC inner core. Observation system simulation experiments are conducted to investigate the potential impact of the FORMOSAT 7R wind speed on TC assimilation and prediction. Understand the observation impact from different satellite wind products, including: Air motion vector (AMV), scatterometer wind and GNSS R windspeed
7 day Nature run based on 2015 Typhoon Dujuan 9 km simulation Max. Wind Speed WRFARW nested simulation (27 9km) Rapid intensification during 24 26 th SEP, 2015 Rapid intensification Heavy rainfall in TW 3 day accu. rain(obs) 3 day accu. rain (nature) 9 km simulation MSLP
Assimilation experiments Weather Research and Forecasting model (WRF V3.7.1) coupled with Local Ensemble Transform Kalman Filter (NCU WRF LETKF, Yang et al. 2013) Simulated RWS data are derived by directly interpolating the model 10 m wind speed to Robservation locations. DA Experiments: CNTL: GTS only RWS: GTS+GPS Reflectometry wind speed (RWS, 2.5 m/s) RWSLA: GTS+ RWS with low accuracy (5m/s) RWSAMV: GTS+RWS+AMV SCAT: GTS+SCAT wind (no data > 30m/s) 40 ensemble members Period: 06Z 23 00Z 25 SEP (6 h DA interval) 4 day forecast initialized at 00Z 25 SEP
Locations of FORMOSAT 7R wind speed 09/24 0000UTC 09/25 0000UTC Wide coverage Low coverage, Still has some data in innercore
Optimize the assimilation of surface data Surface wind speed increment Previous TC center Vertical cross section small vert. Loc OBS Current TC center With WRF LETKF, one windspeed data in inner core can improve TC position and intensity. Surface wind data can correct TC circulation at higher levels large vert. Loc
Analysis wind speed No R windspeed Small obs. error MSLP=973.8 Large obs. error MSLP=984.6 Assimilating wind speed with high accuracy can better capture the asymmetry of the TC (strong wind over south)
09/25 00Z N S vertical cross section Truth RWS RWS Lower Accuracy Strong wind TC position error 193km 24 00Z 25 00Z 22.2km 24 00Z 25 00Z
Satellite winds on 25 September AMV High level (<=400hPa) mid level (>400 <=700) low level (>700) Limited low level AMV data in the TC area. ASCAT
Symmetric wind speed TC structure Assimilating RWS can improve the TC development effectively. When assimilating AMV additionally, the TC structure is further improved. SCAT winds have limited impact on improving TC structure. CNTL RWS RWSAMV NATURE
5 day track prediction Assimilating AMV is able to improve the accuracy of the environmental condition.
3 day (48h 120h forecast) rainfall accumulation SCAT CNTL RWS RWSAMV Nature CNTL RWS nature RWSAMV SCAT Better track+ better intensity
Summary The FORMOSAT 7R wind speed data has the potential to improve TC assimilation and prediction. Positive impact can be obtained even with limited data in the inner core. The accuracy of the surface wind speed data is essential for depicting TC intensity, including the horizontal and vertical structure. When comparing with the satellite wind products, AMV and R wind data could be complementary. When both are assimilated, the TC structure and track can be better analyzed and predicted, leading to improvement on precipitation prediction. Further investigations based on realistic framework will be carried out by the wind speed data retrieved from DDMs.