The Evolution and Distribution of Precipitation during Tropical Cyclone Landfalls using the GPM IMERG Product

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Virginia Tech


Landfalling tropical cyclone (TC) induced precipitation poses a great risk to the rising coastal population globally. However, the impacts of tropical cyclone precipitation (TCP) are still difficult to predict due to rapid structural changes during landfall. This study applies a shape metric methodology to quantify the spatiotemporal evolution of TCP in the North Indian (NI), Western Pacific (WP), and North Atlantic (NA) basins. The International Best Track Archive for Climate Stewardship (IBTrACS) data and the Global Precipitation Mission (GPM)'s advanced Integrated Multisatellite Retrievals for GPM (IMERG) dataset is employed to study the 2014-2020 landfalling TCP at three analysis times: pre-landfall, landfall, and post-landfall. We examine three thresholds (2, 5, and 10 mm hr-1) and use six spatial metrics (area, closure, solidity, fragmentation, dispersion, and elongation) to quantify the shape of the precipitation pattern. To identify precipitation changes among the three analysis times and three basins, the Kruskal-Wallis test is applied. The three basins show important differences in size evolution. The greatest structural changes occur during post-landfall when the rainfall extent shrinks. The WP has the largest area of TCP and generates the highest maximum TCP of all basins. NA is the only basin where the precipitation area expands after landfall. NA also has the lowest closure for the three precipitation thresholds. NI precipitation has the lowest dispersion and maximum closure. Shape metrics such as closure and dispersion show a consistent inverse correlation. The maximum precipitation direction within the TCs is also examined in each basin. These results can inform guidelines that contribute to improved TCP forecasting and disaster mitigation strategies for vulnerable coastal populations globally. Future studies can apply shape metrics to the sub-basins in NI and WP to examine regional variability as there has been no such study in these basins. Future work can also investigate if the location of heavy rainfall within the TC structure affects flooding or other water hazards.



tropical cyclone, landfall, precipitation, satellite data, IMERG