Perbandingan Prediksi Asimilasi data Radiasi Satelit Pada Kejadian Siklon Tropis Seroja Menggunakan WRFDA CRTM dan RTTOV - Kurniati, Ranti; Sagita, Novvria; Hanggoro, Wido (Pusat Penelitian dan Pengembangan BMKG, 2024)
Tropical cyclone prediction is essential for the process of mitigating the resulting disasters. Several numerical weather models have been developed but still produce errors in tropical cyclone predictions. Data assimilation is one method that can improve the initial condition values of numerical weather prediction models so that they can approach actual atmospheric conditions to reduce tropical cyclone prediction errors. Due to the limited meteorological parameter data used for data assimilation at the location of tropical cyclone events, most of which occur in ocean areas, satellite data is needed. Radiation data is initial data from satellite data, which is then transformed into meteorological parameter data using the radiative transfer model (RTM). The Weather Research and Forecasting (WRF) model data assimilation system (WRFDA) is an open-based numerical weather and data assimilation model that has 2 RTM options, namely the Radiative Transfer Model for TIROS Operational Vertical Sounder (RTTOV) and the Community Radiative Transfer Model (CRTM). This research uses two different RTMs to compare the prediction results of Tropical Cyclone Seroja, including minimum pressure, maximum wind speed, and trajectory. The research results show that predictions of minimum pressure, maximum wind speed, and trajectory of tropical cyclone Seroja by a numerical weather model assimilated with satellite radiation data are better than without assimilation. Furthermore, the assimilation of radiation data with RTTOV has the best accuracy in predicting the maximum wind speed and minimum pressure of tropical cyclone Seroja. Meanwhile, the assimilation of radiation data with CRTM can produce a minimum error in the trajectory of tropical cyclone Seroja. Future research requires adding satellite radiation data from various sensors and satellites.