Mechanisms for Rapid Intensity Changes in Hurricanes

University Of New Mexico, Albuquerque NM

Investigators

Abstract

The problem of better forecasting of the intensity of hurricanes has been identified by the U.S. Weather Research Program as a high priority research area. As hurricanes approach landfall, the horizontal distribution of intense winds in hurricanes often becomes highly asymmetrical, as does the intense convection in the eyewall and rainbands. Intense mesoscale vortices, as small as a few kilometers in scale, are believed to produce major damage in intense landfalling hurricanes. This project aims to analyze the physical mechanisms associated with interaction of a tropical cyclone with environmental vertical wind shear using a full-physics, high resolution advanced numerical modeling system. Previous studies have shown that persistent and predictable convective asymmetries develop in response to imposed environmental vertical wind shear. By better understanding the processes that produce asymmetries in tropical cyclone convection, and by understanding how those asymmetries feed back on the tropical cyclone intensity and structure, improved prediction of these events should be possible. Of particular interest is the development of asymmetries in the hurricane core convection during interaction with vertical wind shear caused by transient circulations. As the vertical wind shear is imposed on the hurricane core, asymmetries should develop that are well predicted by the constant-shear studies. However, as the wind shear recedes, the time-evolution of the core structural changes in the hurricane will be studied, particularly as they feed back on changes in the storm intensity. This study seeks to achieve knowledge of these processes through examination of a series of initial-value and time varying, full-physics simulations utilizing a very fine mesh and explicit moist physics. The results will be synthesized to establish a series of cause and effect relationships governing core intensity changes, and these relationships will be tested by examining real-data cases. Successful completion of this research potentially will lead to improvements in the forecasting of landfalling hurricanes.