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Physically based storm transposition of four Atlantic tropical cyclones
Mathieu Mure-Ravaud1, Alain Dib1, M Levent Kavvas1
1University of California, Davis, 1 Shields Ave, Davis, CA 95616, United States of America.
The Science of the Total Environment
|February 25, 2019
Summary
This study introduces a physically based storm transposition method for tropical cyclones, using regional atmospheric models to conserve system mass, momentum, and energy. The method demonstrated that shifting a hurricane
Area of Science:
- Atmospheric Science
- Meteorology
- Climate Modeling
Background:
- Tropical cyclones pose significant risks due to extreme precipitation events.
- Accurate simulation of tropical cyclone impacts, particularly precipitation, is crucial for disaster preparedness.
- Existing storm transposition methods may lack physical basis, affecting simulation accuracy.
Purpose of the Study:
- To present a novel, physically based storm transposition method for tropical cyclones.
- To conserve fundamental physical properties (mass, momentum, energy) during storm transposition.
- To assess the impact of spatial shifting of tropical cyclone initial conditions on precipitation fields and tracks.
Main Methods:
- Utilized a regional atmospheric model for reconstructing precipitation depth fields.
- Implemented a physically based storm transposition by spatially shifting the tropical cyclone vortex in initial conditions.
- Applied the method to four historical hurricanes (Floyd, Frances, Ivan, Isaac) impacting the United States.
Main Results:
- Physically based storm transposition significantly altered precipitation depth fields in structure and intensity.
- Tropical cyclone tracks exhibited high sensitivity to initial condition changes, a characteristic of nonlinear dynamics.
- Small shifts in the initial vortex location led to substantially different tracks and precipitation distribution.
Conclusions:
- The developed physically based storm transposition method provides a more accurate simulation of tropical cyclone precipitation.
- This method allows for repositioning precipitation fields over target areas by adjusting initial conditions.
- Findings highlight the importance of precise initial conditions for predicting tropical cyclone impacts.
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