In this study, the influence of assimilating the temperature and moisture soundings into the Weather Research and Forecasting (WRF) model using the Ensemble Kalman Filter (EnKF) is investigated for the cases of Typhoon Sinlaku (2008) and Hurricane Ike (2008) during their period of intensification. Three EnKF cycles, using 84 ensemble members with a horizontal resolution of 27 km on the analysis grid (and 9 km in the forward forecast model), are prepared. A Control' EnKF cycle is first produced with the assimilation of conventional observations (without radiances). In additional to the conventional observations, the second and third EnKF cycles, AIRS-STL2-TQ' and AIRS-CIMSS-TQ', assimilate temperature and moisture soundings from the AIRS Science Team Level 2 products and from those specially processed by CIMSS, respectively. The fourth (fifth) EnKF cycle in which moisture (temperature) from AIRS-STL2-TQ' is excluded is prepared, and named AIRS-STL2-T' (AIRS-STL2-Q). Similar to the fourth and fifth EnKF cycles, the sixth and seventh cycles exclude soundings from AIRS-CIMSS', and are named AIRS-CIMSS-T' and AIRS-CIMSS-Q'. Preliminary results suggest that the track and intensity of AIRS-CIMSS-TQ' analysis are closer to best track data if compared with AIRS-STL2-TQ'. While the track remains similar between data-denial cycles, the moisture soundings are important for maintaining intensity. Insights into the influence of the respective datasets on tropical cyclone structure will be provided.
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