To evaluate the abilities of satellite retrievals in reflecting precipitation features related to tropical cyclones (TCs) affecting mainland China, four years of 6-and 24-h precipitation retrievals from three datasets, namely the Tropical Rainfall Measuring Mission satellite algorithm 3B42, version 6 (3B42), Climate Prediction Center morphed (CMORPH) product, and one based on the Geostationary Meteorological Satellite-5 infrared brightness temperature (GMS5-TBB), are compared statistically with direct measurements from surface gauge rainfall data during the periods affected by TCs. The GMS5-TBB dataset was set up by a method of considering the GMS5-TBB characteristics, hourly precipitation intensity, and horizontal distribution for landfalling TCs. The results show that in a general sense, all three satellite-retrieved rainfall datasets give quite reasonable 6-and 24-h rainfall distributions, with skill decreasing with the increase in both latitude and rainfall amount. The 3B42 has a little bit better skill than CMORPH, which is likely related to the fact that the 3B42 product has a rain gauge adjustment and CMORPH does not. Further analyses show that both 3B42 and CMORPH considerably underestimate the moderate and heavy rainfall and overestimate the very light precipitation. The overestimation of the GMS5-TBB data for the light rain is larger than that for 3B42 and CMORPH, probably due to the fact that the GMS5-TBB method considers stratiform and convective rainfall separately with a fixed stratiform rain rate of 2 mm h 21 . For the heavy rainfall events, the GMS5-TBB data perform much better than the 3B42 and CMORPH data with an almost halved bias, owing to the fact that the GMS5-TBB method adopted the adjustment of the convective rain rate by considering TBB characteristics of landfalling TCs and using hourly gauge rainfall in the setup process. Since the heavy rainfall events associated with landfalling TCs are of the most concern, the compared GMS5-TBB data could be useful as an operational/research reference.

Urbanization effects on rainfall induced by landfalling tropical cyclones have rarely been studied. Here high-resolution numerical simulations with the Weather Research and Forecasting/Noah/Single-layer urban canopy model system (WRF/SLUCM) are conducted to investigate impacts of urban land cover and building heights on heavy rainfall induced by landfalling Typhoon Lekima (2019) over the Megacity Shanghai. The default single urban category in WRF was updated to a new land cover data with three urban categories. Results indicate that WRF/SLUCM captures the typhoon intensity, track and total rainfall amount quite well. Urbanization has a small positive effect on rainfall amount for this event. However, urbanization has a significant impact on the spatial distribution of the accumulated rainfall with enhancement not confined over the urban area but mainly to the southwest of Shanghai possibly due to the changes of the typhoon tracks. With the impact of typhoon Lekima, the urban heat island disappears, indicating that the thermal effect of urbanization has limited influence on the rainfall processes. The model performance is very sensitive to the building height. More realistic building height values can noticeably improve simulations of the diurnal patterns of rainfall, urban heat island and the urban wind speed stilling effect. With the rising of building heights, the surface frictional dynamic effect and vertical uplift is enhanced, but seems not enough to evidently intensify the rainfall. The simulated lower level large moisture flux convergence corresponds well to rainfall peaks. This study has important scientific significance for the accuracy of rainfall forecast of landfalling typhoons and disaster mitigation in cities.

The precipitation during landfall of typhoon Haitang (2005) showed asymmetric structures (left side/right side of the track). Analysis of Weather Research and Forecasting model simulation data showed that rainfall on the right side was more than 15 times stronger than on the left side. The causes were analyzed by focusing on comparing the water vapor flux, stability and upward motion between the two sides. The major results were as follows: (1) Relative humidity on both sides was over 80%, whereas the convergence of water vapor flux in the lower troposphere was about 10 times larger on the right side than on the left side.(2) Both sides featured conditional symmetric instability [MPV (moist potential vorticity) <0], but the right side was more unstable than the left side. (3) Strong (weak) upward motion occurred throughout the troposphere on the right (left) side. The Q Q Q vector diagnosis suggested that large-scale and mesoscale forcing accounted for the difference in vertical velocity. Orographic lift and surface friction forced the development of the asymmetric precipitation pattern. On the right side, strong upward motion from the forcing of different scale weather systems and topography caused a substantial release of unstable energy and the transportation of water vapor from the lower to the upper troposphere, which produced torrential rainfall. However, the above conditions on the left side were all much weaker, which led to weaker rainfall. This may have been the cause of the asymmetric distribution of rainfall during the landfall of typhoon Haitang.Citation: Yue, C. J., S. T. Gao, L. Liu, and X. F. Li, 2015: A diagnostic study of the asymmetric distribution of rainfall during the landfall of typhoon Haitang (2005).

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