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. / Master of Science / Landfalling tropical cyclones (TC) pose a significant threat to coastal populations worldwide, primarily due to the heavy rainfall. Predicting the rainfall during landfall is challenging as they undergo rapid changes. This study uses shape metrics to measure how this rainfall changes over time and space in three ocean basins: North Indian (NI), Western Pacific (WP), and North Atlantic (NA). The study uses a comprehensive collection of global TC best-track data i.e., International Best Track Archive for Climate Stewardship (IBTrACS). The rainfall measurement is derived from the satellite data i.e., the Global Precipitation Mission (GPM)'s advanced Integrated Multisatellite Retrievals for GPM (IMERG) to study landfalling rainfall between 2014 to 2020. Six spatial metrics (area, closure, solidity, fragmentation, dispersion, and elongation) were applied to quantify the shape and size of the precipitation pattern at three landfall times: pre-landfall, landfall, and post-landfall. The values of the shape metrics are compared between the ocean basins and landfall times using a statistical test. The results show that the most significant changes occur after landfall when the rainfall area decreases. WP has the largest area of rainfall and generates the highest maximum rainfall of all basins. NA is the only basin where the rainfall area expands after landfall. Shape metrics such as closure and dispersion share a consistent negative relationship. The maximum precipitation direction within the TCs is also examined in each basin. These results can contribute to improved tropical cyclone rainfall 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.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115373 |
| Date | 07 June 2023 |
| Creators | Sauda, Samrin Sumaiya |
| Contributors | Geography, Zick, Stephanie E., Shao, Yang, Ramseyer, Craig A. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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