Impact of the Monsoonal Surge on Extreme Rainfall of Landfalling Tropical Cyclones

A comparative analysis and quantitative diagnosis has been conducted of extreme rainfall associated with landfalling tropical cyclones (ERLTC) and non-extreme rainfall (NERLTC) using the dynamic composite analysis method. Reanalysis data and the tropical cyclone precipitation dataset derived from the objective synoptic analysis technique were used. Results show that the vertically integrated water vapor transport (Qvt) during the ERLTC is significantly higher than that during the NERLTC. The Qvt reaches a peak 1–2 days before the occurrence of the ERLTC and then decreases rapidly. There is a stronger convergence for both the Qvt and the horizontal wind field during the ERLTC. The Qvt convergence and the wind field convergence are mainly confined to the lower troposphere. The water vapor budget on the four boundaries of the tropical cyclone indicates that water vapor is input through all four boundaries before the occurrence of the ERLTC, whereas water vapor is output continuously from the northern boundary before the occurrence of the NERLTC. The water vapor inflow on both the western and southern boundaries of the ERLTC exceeds that during the NERLTC, mainly as a result of the different intensities of the southwest monsoonal surge in the surrounding environmental field. Within the background of the East Asian summer monsoon, the low-level jet accompanying the southwest monsoonal surge can increase the inflow of water vapor at both the western and southern boundaries during the ERLTC and therefore could enhance the convergence of the horizontal wind field and the water vapor flux, thereby resulting in the ERLTC. On the other hand, the southwest monsoonal surge decreases the zonal mean steering flow, which leads to a slower translation speed for the tropical cyclone associated with the ERLTC. Furthermore, a dynamic monsoon surge index (DMSI) defined here can be simply linked with the ERLTC and could be used as a new predictor for future operational forecasting of ERLTC.