Analyzing the complexity of tropical cyclone landfall dynamics through the integration of radar data

Tropical cyclones (TCs) over the Indian subcontinent often led to devastating impacts, especially during landfall. This study exclusively investigates the dynamical changes of the TCs during their landfall phases, covering pre-landfall (PrL), during-landfall (DL), and post-landfall (PoL) periods. Three landfalling TCs—Hudhud (2014), Titli (2018), and Fani (2019)—are simulated using the Weather Research and Forecasting model, incorporating Doppler Weather Radar reflectivity (Rf) data through two sets of experiments: CNTL (without Rf assimilation) and Rf_DA (with Rf assimilation). Rf_DA has minimal impact on the TC track; however, it significantly improves the intensity in terms of minimum central pressure (MCP, 43 % & 8 % reduced error) and maximum sustained surface wind (MSSW, 53 % & 15 % reduced error) for Hudhud and Fani, respectively, during the landfall process. The weakening phase is accurately captured, and structural changes in the DL phase are closely aligned with observations for Rf_DA. Realistic rainfall distribution and associated thermodynamic processes during DL and PoL are better replicated in Rf_DA compared to CNTL. The water budget analysis shows that lower-level moisture convergence (1000–700hPa) and upper-level (400–100hPa) advection are the dominant factors regulating DL and PoL rainfall characteristics of TCs. Furthermore, TC-associated rainfall is strongly influenced by frozen hydrometeors at the mid to upper-level (600–200hPa) and liquid hydrometeors at the lower-level (1000–700hPa) in the DL and PoL phases. In summary, incorporating Rf data considerably improved the key features of TCs—the structure, intensity, and rainfall patterns during the landfall phase. These findings have significant implications for improving early warning systems for TC landfall, especially in coastal areas with high population densities.