To study the precipitation characteristics in tropical cyclones (TCs), this research employs the Global Satellite Mapping of Precipitation (GSMaP) dataset developed by the Japan Aerospace Exploration Agency (JAXA), with a spatial resolution of 0.5° × 0.5° and hourly temporal resolution (Kubota et al. 2009, 2020). In terms of Global Climate Models (GCMs), the Dynamics of the Atmospheric General Circulation Modeled On Nonhydrostatic Domains (DYAMOND) dataset contains nine global models initialized on 1 August 2016 with ECMWF analysis and integrated for 40 days at convection-permitting resolution (Stevens et al. 2019). We choose the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) for further TC analysis together with GSMaP.

Based on DYAMOND-NICAM and GSMaP observations, the relationship between TC wind structure and internal convective precipitation is investigated. Precipitation profiles are sensitive to intensity changes, particularly for Category 3 and above. In observations, as TC intensity increases, both wind and precipitation centers contract inward, while NICAM shows varying amplitude of precipitation profile changes across ocean basins. The C15 surface wind model (Chavas et al. 2015) is applied to correct NICAM wind fields. A Category 4 typhoon is selected to analyze precipitation, surface wind, boundary-layer inflow, and three-dimensional wind structure at different stages. Results indicate that during development, the C15-based wind profile effectively predicts the inflow center. During decay, using corrected wind data to estimate radial inflow reduces errors from outer-core wind oscillations. By calculating vertical water vapor flux at the boundary-layer top, the horizontal profile of precipitation conversion efficiency is characterized, revealing that stronger TC intensity corresponds to larger maximum conversion efficiency.

Finally, combining boundary-layer inflow and surface wind information, we attempt to predict TC accumulated precipitation. For strong typhoons, precipitation predicted using surface wind information shows higher correlation with model-output precipitation. Further analysis reveals that for TCs with greater intensity and larger size, using C15-corrected wind fields significantly improves prediction accuracy. These findings provide new insights for studying and forecasting TC precipitation, and suggest that boundary-layer wind structure critically modulates TC rainfall distribution and intensity. Future work will extend this analysis to additional DYAMOND models and explore operational applicability.
 

Tropical cyclone,TC wind,TC precipitation