| Abstract Submission No. | ABS-3.1-0113 |
| Title of Abstract | Improving Cyclone Forecast over the NIO through All-Sky SAPHIR Data Assimilation in WRF model |
| Authors | Dr. Vivek Singh*, Dr. Gaurav Tiwari |
| Organisation | Indian Institute of Tropical Meteorology, New Delhi Branch |
| Address | Indian Institute of Tropical Meteorology (New Delhi Branch) Rajendra Place, Delhi, India Pincode: 110060 E-mail: vivek.singh@tropmet.res.in |
| Country | India |
| Presentation | Oral |
| Abstract | In this study, all-sky Microwave (MW) brightness temperature (TB) measured from the Sondeur Atmosphérique du Profil d¿Humidité Intertropicale par Radiométrie (SAPHIR) onboard Megha-Tropiques (MT) satellite has been assimilated in the Weather Research and Forecasting (WRF) model to understand the importance and challenges in all-sky data assimilation. Simultaneous assimilation experiments have been performed using three-dimensional variational (3D-Var) data assimilation technique to assess the impact of all-sky TB against clear-sky TB assimilation for the prediction of very severe cyclonic storm Ockhi. Approximately 10-25 % more TB observations are added for different SAPHIR channels in all-sky data assimilation as compared to clear-sky assimilation. Results suggest that the assimilation of all-sky TB data with Gaussian transformation, Digital Filter Initialization (DFI) technique and covariance inflation method provides better prediction skill. The assimilation of all-sky TB improved the track prediction (~10%) compared to clear-sky data assimilation, and demonstrated applications of additional MW observations mainly over ice and rain conditions. Moreover, marginal positive impact (~2%) is noted in intensity prediction with all-sky data assimilation. |
| Keywords | All-sky, SAPHIR, 3D-Var, Track error. |