Impact of the 4D-Var Assimilation of Airborne Doppler Radar Data on Numerical Simulations of the Genesis of Typhoon Nuri (2008) Zhan Li and Zhaoxia Pu Department of Atmospheric Sciences University of Utah WRF Users' Workshop 2013

Introduction The forecast of tropical cyclone (TC) genesis (predicting developing and non-developing systems) is still challenging. Many previous studies indicate large impact of initial conditions on numerical simulations of TC genesis (Davis and Bosart 2002; Kieu and Zhang 2010). Previous studies demonstrate that assimilation of radar observations improves the initial conditions and numerical prediction of mature TCs (Pu et al. 2009; Zhang et al. 2012). The Office of Naval Research sponsored Tropical Cyclone Structure 2008 (TCS-08) field experiment collects airborne radar observations during the TC genesis stage. It offers a good opportunity to examine the impact of radar data on predicting TC genesis.

Objectives To examine the capability of the radar data assimilation to improve the numerical prediction of TC genesis. To investigate the sensitivity of TC genesis forecasts to different DA methods: assimilating the retrieved radar wind analysis (u, v) and directly assimilating the radar radial velocity. To understand how initial conditions are changed via the radar data assimilation and why these changes in the initial conditions lead to the improvement of TC genesis forecasts.

NCAR/EOL ELDORA: an airborne, dual beam, X-band Doppler radar. TCS-08/TPARC field experiment: Radar reflectivity and radial velocity are obtained from 2300 UTC Aug 15 to 0415 UTC Aug 16 for Typhoon Nuri. After processing data quality control, the 3-dimensional wind analysis is produced using a 3-dimensional variational method. ELDORA and the radar wind analysis ELDORA on NRL P3 aircraft UV at 1.5 km RV at 1.5 km Radar observations in early phase of Typhoon Nuri (2008)

Model and 4D-Var system WRF-ARW, Version 3.2.1; Cumulus: Kain-Fritsch; Planetary boundary layer: YSU; Microphysics: WRF Single- Moment 6-class scheme; Long Wave: Rapid Radiative Transfer Model; Short Wave: Dudhia scheme. D01 36 km D02 12 km Typhoon Nuri’s genesis occurred at 18 UTC 16 Aug Numerical simulation is conducted between 00 UTC 16 to 00 UTC 18 Aug WRF 4D-Var data assimilation system (Huang et al. 2009) is used from 00 UTC to 05 UTC 16 Aug 2008 for radar data assimilation.

Numerical experiments ExperimentDescription CtrlInitial conditions from GFS FNL UV Assimilation of the u v wind components from the retrieved radar wind analysis RVDirect assimilation of radar radial velocity

Intensity and track forecasts Both UV and RV predict Nuri’s genesis with enhanced storm intensity, while the control run fails to predict Nuri’s genesis. RV predicts the intensity forecasts closer to the best-track data. UV produces more accurate track forecasts by largely reducing track error.

Precipitation verification Ctrl Satellite measurement UVRV Rain rate is much weaker in the control run than the observed rain rate. UV and RV both produce larger rain rate in the inner core of storm. The rainfall intensity and structure are similar to the observed precipitation. The radar data assimilation significantly improves the convection and precipitation forecasts.

Impact on the initial conditions: Relative vorticity Compared with the control run, UV and RV both produce stronger relative vorticity at middle levels in the initial conditions. The stronger middle-level vortex maintains the moist environment, which is favorable for the persistent development of deep convection and Nuri’s genesis. Ctrl UV RV

Impact on the initial conditions: Temperature increments With the radar data assimilation, UV and RV both show temperature increment with the upper- level warming and the low- level cooling. The structure of the temperature increment is consistent with the enhancement of the middle- level vortex. UV RV

Impact on the initial conditions: Relative Humidity Compared with the control run, UV and RV both produce the increase in the initial moisture from 900 to 500 hPa around the storm center. The enhancement in the initial moisture benefits the moist convection and contributes to the successful simulation of Nuri’s genesis. CtrlUV RV

Concluding Remarks Experiments with radar data assimilation (both assimilating the retrieved u v wind analysis and the radial velocity) predict Nuri’s genesis with enhanced storm intensity, while the control experiment fails to predict Nuri’s genesis. The assimilation of radar radial velocity leads to more improvement in the intensity forecasts. The track forecasts are better improved with the assimilation of the retrieved wind analysis. Radar data assimilation produces the enhanced middle-level vortex and moist conditions, which are favorable for the development of deep convection and eventually contribute to the successful simulations of Nuri’s genesis.

Thank you!