EAGER: Data-driven Physical Model for Hurricanes' Intensity-size Relation

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Hurricanes are among the most deadly and destructive storms impacting the United States, causing losses of life, devastating damages to buildings and infrastructures, and enormous financial losses. Both hurricanes’ intensity and size are the key factors determining their severity and destructive capability. Therefore, accurate prediction of hurricanes’ intensity and size is essential to general public and government officials. Observed hurricanes exhibit very rich and complex intensity-size relations. Even after taking the differences in the radius of the maximum wind into consideration, hurricanes with the same maximum wind can still have various sizes or hurricanes with the same size can have a large range of intensity. The existing empirical and theoretical models, however, tend to predict a nearly one-to-one relation between hurricanes’ intensity and size after taking the differences in the radius of the maximum wind into consideration. The goal of this project is to develop a data-driven physical model whose solutions can reproduce the rich and complex intensity-size relations of observed hurricanes. A successful project will lead to a better understanding of the physics governing hurricanes’ intensity-size relations. This project will provide a powerful tool to identify the major deficiencies in reproducing the rich and complex intensity-size relation by operational forecast models, leading to an improvement in forecasts and public safety and economic benefits. This project will train a postdoc in fields of atmospheric dynamics and data science and support STEM education by working with two undergraduate students on their honor theses research. The PIs will actively engage with North Florida Chapter of the American Meteorological Society and provide our experimental real time assessment of hurricanes’ intensity to the Florida State University/Tallahassee communities. This project will take a novel approach that combines theories and data-driven techniques to build a new model for the hurricanes’ intensity-size relation. Specifically, the PIs will utilize data analysis techniques to explore what are the factors controlling the variation of inward radial velocity among different hurricanes and then link these factors to the variation of hurricanes’ angular momentum loss. Another novelty of this project is that the developed model will be validated by examining its ability to predict the radial profile of azimuthal wind both inwardly from the boundary condition at outer radii and outwardly from the boundary condition at inner radii. Such exchangeability of the predictends and predictors allows ones to test whether the data-driven model possesses the quality of physical laws.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.