Both the atmosphere and the earth's surface act to change the structure of a tropical cyclone during landfall. These structural changes affect the overall spatial patterns of rainfall produced by the storm, which then control the magnitude and timing of flooding that may occur. Although models of tropical cyclones have incorporated geophysical variables such as wind shear and terrain to improve the prediction of rainfall totals, they are still lacking in their ability to accurately depict the geographical distribution of the rainfall. This project addresses the critical need to improve the spatial modeling of tropical cyclone rain fields. Shape analysis techniques employed within a Geographic Information System (GIS) will quantify the extent and locations of rain-producing regions of tropical cyclones, including heavy rainfall regions as defined by radar reflectivity returns. These regions will then be linked to key geophysical variables that influence the storm's structure through comparisons of observed patterns against data from model-generated storms. The research supported through this CAREER award will develop a set of metrics to describe shapes that tropical cyclone rain fields frequently resemble to determine the processes responsible for creating those shapes, and it will derive statistical models to predict those shapes. By modeling rain field shapes within a GIS, these shapes can potentially be incorporated into pre-existing GIS-based hydrological models to improve the rainfall inputs into these models. Multivariate logistic regression analysis will also be employed to predict which areas will receive no rain versus some rain, and low rainfall rates versus high rainfall rates. This research will contribute to improving rainfall forecasting, both through the quantification of tropical cyclone rain fields and the improved ability to identify the location of flood-producing rainfall.
An integral component of this project is an effort to educate a new generation of researchers in advanced spatial analysis techniques. These efforts will contribute to cultivating innovative perspectives and fostering further improvement of rain forecasts for tropical cyclones that reach land. These outcomes will be achieved through an educational program that emphasizes GIS-based analysis of meteorological and climatological data. Both graduate and undergraduate students will receive enhanced training in GIS-based atmospheric data analysis and two newly designed courses will allow an undergraduate minor in meteorology to be developed. Students, both funded and non-funded, will undertake individual research projects related to the spatial analysis of weather events, interact with a series of topically relevant special guest lecturers from outside the university, and travel to professional meetings and workshops featuring GIS or weather-related research. Mentoring activities are expected to increase the number of minority students selecting science-based careers.
