On 12 August 2004, Typhoon Rananim (0414) moved inland over China and stagnated over the Poyang Lake area, resulting in torrential rainfall and severe geologic hazards. The Advanced Weather Research and Forecasting (ARW-WRF) model and its different land surface models (LSMs) were employed to study the impacts of land surface process on the inland behavior of Typhoon Rananim. Results show that simulations, coupled with LSMs or not, have no significant differences in predicting typhoon track, intensity, and largescale circulation. However, the simulations of mesoscale structure, rainfall rate, and rainfall distribution of typhoon are more reasonable with LSMs than without LSMs. Although differences are slight among LSMs, NOAH is better than the others. Based on outputs using the NOAH scheme, the interaction between land surtace and typhoon was explored in this study. Notably, typhoon rainfall and cloud cover can cool land surface, but rainfall expands the underlying saturated wetland area, which exacerbates the asymmetric distribution of surface heat fluxes. Accordingly, an energy frontal zone may form in the lower troposphere that enhances ascending motion and local convection, resulting in heavier rainfall. Moreover, the expanded underlying saturated wetlands provide plentiful moisture and unstable energy for the maintenance of Typhoon Rananim and increased rainfall in return.
The ability to forecast heavy rainfall associated with landfalling tropical cyclones (LTCs) can be improved with a better understanding of the mechanism of rainfall rates and distributions of LTCs. Research in the area of LTCs has shown that associated heavy rainfall is related closely to mechanisms such as moisture transport, extratropical transition (ET), interaction with monsoon surge, land surface processes or topographic effects, mesoscale convective system activities within the LTC, and boundary layer energy transfer etc.. LTCs interacting with environmental weather systems, especially the westerly trough and mei-yu front, could change the rainfall rate and distribution associated with these mid-latitude weather systems. Recently improved technologies have contributed to advancements within the areas of quantitative precipitation estimation (QPE) and quantitative precipitation forecasting (QPF). More specifically, progress has been due primarily to remote sensing observations and mesoscale numerical models which incorporate advanced assimilation techniques. Such progress may provide the tools necessary to improve rainfall forecasting techniques associated with LTCs in the future.