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.

<p>Landfalling tropical cyclones bring tremendous coastal and inland hazard, which depends strongly on the evolution of the wind field after the landfall. This work investigates the inland evolution of the tropical cyclone wind field via idealized numerical simulation experiments and existing theories explaining the physics of storms over the ocean. The complicated landfall process is idealized as a transient response of a mature axisymmetric tropical cyclone to instantaneous surface forcings associated with landfall.</p><p><br></p><p>First, idealized landfall experiments are performed in the f-plane Bryan Cloud Model (CM1), where surface drag coefficient and evaporative fraction are individually or simultaneously modified systematically beneath an axisymmetric mature storm. Surface drying stabilizes the eyewall and consequently weakens the overturning circulation, thereby reducing inward angular momentum transport that slowly decays the low-level wind field only within the inner-core. In contrast, surface roughening first weakens the entire low-level wind field rapidly and enhances the overturning circulation dynamically despite the concurrent thermodynamic stabilization of the eyewall; thereafter, the storm gradually decays in a manner similar to drying. As a result, total precipitation temporarily increases with roughening but uniformly decreases with drying. Storm inner size and outer size decrease monotonically and rapidly with surface roughening, while the radius of maximum wind can increase with moderate surface drying.</p><p><br></p><p>Second, the extent to which existing intensity theory formed for tropical cyclones over the ocean can explain the intensity response to idealized landfall is explored in this work. Existing theoretical predictions for the equilibrium response and transient response of storm intensity are compared against the simulated response found in previous idealized simulations. The equilibrium and transient response of storm intensity to combined surface forcings can be reproduced by the product of their individual responses, in line with traditional potential intensity theory. The intensification theory of Emanuel (2012) is generalized for predicting the weakening process and found capable of reproducing the transient intensity decay. Specifically, the rapid initial decay of near-surface wind can be captured by how kinetic energy is instantaneously reduced by surface friction, where the decay is a function of surface roughness.</p><p><br></p><p>Third, existing structural theory and TC radial length scale formed or identified for storms over the ocean are tested against the idealized landfall experiment where surface is individually dried or roughened. The equilibrium storm radial length scale can predict the transient response of storm size to surface roughening throughout the decay evolution. For surface drying experiments, TC size scales with the intensity after around 12h. The E04 wind field model can generally capture the transient response of TC low-level wind field to individual surface drying and roughening, from radius of maximum wind speed to the outer region. The E04 prediction for these two types of experiments exhibits limited dependence on the subsidence cooling rate applied in the model.</p><p><br></p><p>Overall, though results are insufficient to explain the complicated wind field evolution of every real-world landfalling storm, it provides a fundamental understanding of how storm low-level wind fields respond to inland surface properties. This work also indicates the potential for existing theory to predict how tropical cyclone intensity evolves after landfall in the real world, which is essential for improving the forecasts on any timescale and the risk assessments.</p>

Tropical Rainfall Measuring Mission (TRMM) rainfall retrieval algorithms are evaluated in tropical cyclones (TCs). Differences between the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) retrievals are found to be related to the storm region (inner core vs. rainbands) and the convective nature of the precipitation as measured by radar reflectivity and ice scattering signature. In landfalling TCs, the algorithms perform differently depending on whether the rainfall is located over ocean, land, or coastal surfaces. Various statistical techniques are applied to quantify these differences and identify the discrepancies in rainfall detection and intensity. Ground validation is accomplished by comparing the landfalling storms over the Southeast US to the NEXRAD Multisensor Precipitation Estimates (MPE) Stage-IV product. Numerous recommendations are given to algorithm users and developers for applying and interpreting these algorithms in areas of heavy and widespread tropical rainfall such as tropical cyclones.

Many Climate Scientists believe that global warming will produce more extreme weather events such as tropical storms, hurricanes, intense rainfall, and flooding. These events are considered to be the most catastrophic natural events for transportation systems especially in coastal areas. Due to the severe damage from storm surge and flooding. Evaluating the magnitude of possible storm surges and their impacts on transportation systems in coastal areas is fundamental to developing adaptation plans and impact assessments to mitigate the damage. This thesis focuses on existing transportation systems in the Georgia coastal area that could be affected by several storm surges. An existing storm surge model is used to estimate the storm surges and the surge heights based on the category, direction, and forward speed of a storm. The ground elevation of the ports, interstates, state roads, railroads, and the principal airports on the Georgia coast are identified through a GIS analysis using the national elevation data set. Having the storm surge elevation and the elevation of the existing infrastructure, a GIS study is performed to identify those parts of the transportation system that will be affected by each type of storm giving results such as the length or sections of transportation assets under or above the surge elevation. A literature review of storm surge, rising sea levels, and their impacts on coastal bridges, roads, airports, ports, and railroads is presented in the thesis. Also, a description of the software used to analyze and estimate the impacts of climate change on transportation systems is described.

<p dir="ltr">Tropical Cyclones (TCs) are intense low-pressure weather systems that acts as a meteorological monster causing severe rainfall and widespread freshwater flooding, leading to extensive damage and disruption. Quantitative precipitation estimates (QPEs) are crucial for accurately understanding and evaluating the impacts of TCs. However, QPEs derived from various modalities, such as rain gauges, ground-based merged radars, and satellites, can differ significantly and require thorough comparison. Understanding the limitations/advantages of using each QPE is essential to simulate a hydrological model especially to estimate extreme events like TCs. The objective of the dissertation is to 1) characterize the tropical cyclone precipitation (TCP) using three gridded products, 2) characterize the impact of using different QPEs in estimation of hydrological variables using a hydrology model, and 3) understand the usability of satellite-derived QPEs for eight cases of TC and its impact on the estimate of hydrological variables. The QPEs include near real-time and post-processed satellite data from NASA’s Global Precipitation Mission-Integrated Multi-sensor Retrievals for GPM Rainfall Product (IMERG), merged ground radar observations (Stage IV) from the National Centers for Environmental Prediction (NCEP), and interpolated gauge observations from the National Weather Service Cooperative Observer Program (GCOOP). The study quantifies how differences in rainfall intensity and location, as derived from these gridded precipitation datasets, impact surface hydrology. The Variable Infiltration Capacity (VIC) model and the geographic information system (GIS) routing assess the propagation of bias in the daily rainfall rate to total runoff, evapotranspiration, and flooding. The analysis covers eight tropical cyclones, including Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Jeanne (2004), Tropical Storm Fay (2008), Tropical Storm Beryl (2012), Tropical Storm Debby (2012), Hurricane Irma (2017) and Hurricane Michael (2018) focusing on different regions in South-Atlantic Gulf region and land uses. The findings indicate that IMERG underpredicts precipitation at higher quantiles but aligns closely with ground-based and radar-based products at lower quantiles. IMERG reliably estimates total runoff and evapotranspiration in 90% of TC scenarios along the track and in agricultural and forested regions. There is substantial overlap ~ 70% between IMERG and GCOOP/Stage IV for the 90th percentile rainfall spatially for the case of TC Beryl 2012. Despite previous perceptions of underestimation, the study suggests that satellite-derived rainfall products can be valuable in simulating streamflow, particularly in data-scarce regions where ground estimates are lacking. The relative error in estimation is 12% and 22% when using IMERG instead of Stage IV and GCOOP rainfall data. The findings contribute to a broader perspective on usability of IMERG in estimating near real-time hydrological characteristics, paving the way for further research in this area. This analysis demonstrates that IMERG can be a reliable data product for hydrological studies even in the extreme events like landfalling TCs. This will be helpful in improving the preparedness of vulnerable communities and infrastructure against TC-induced flooding in data scare regions.</p>