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The tropical cyclone response to changing wind shear using the method of time-varying point-downscaling

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Previous studies using idealized numerical simulations to understand the tropical cyclone (TC) response to time-varying wind shear have applied instantaneous changes in the TC environment. This was typically accomplished by… Click to show full abstract

Previous studies using idealized numerical simulations to understand the tropical cyclone (TC) response to time-varying wind shear have applied instantaneous changes in the TC environment. This was typically accomplished by pausing the simulation, constructing a new environmental vertical wind profile, rebalancing the mass field, and then restarting the simulation. A new modeling framework allows for smoothly transitioning environmental wind states: time-varying point-downscaling (TVPDS). TVPDS uses large-scale relaxation to smoothly transition between different vertical profiles of environmental wind (and/or temperature and moisture) while coordinating the point-downscaling method such that the environment remains in balance. TVPDS simulations of quasi-steady state, moderately intense (∼50 m s−1) TCs show that the response to increasing wind shear is a steady reduction in intensity without recovery to the pre-shear intensity. These results, which are consistent with the typical evolution of real TCs, stand in contrast to some previous studies that found a recovery to pre-storm intensity after an initial weakening due to increased shear. TVPDS simulations also show that the rate at which the TC weakens depends on how rapidly the environment transitions to greater shear. Analyses of surface fluxes, regions of convection, and other variables are presented to determine how time-varying shear affects TCs. Finally, TVPDS simulations of TCs transitioning from environments characterized by high-shear into low-shear environments show that a similar but opposite response occurs.

Keywords: wind; wind shear; response; time varying; point downscaling

Journal Title: Journal of Advances in Modeling Earth Systems
Year Published: 2017

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