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Journal Article

Citation

Mure-Ravaud M, Kavvas ML, Dib A. Sci. Total Environ. 2019; 672: 916-926.

Affiliation

University of California, Davis, 1 Shields Ave, Davis, CA 95616, United States of America.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.scitotenv.2019.03.471

PMID

30981167

Abstract

In this article, numerical experiments are performed to investigate the effects of increasing atmospheric moisture on the precipitation depth (PD) produced by Hurricane Ivan (2004) over a target area, chosen as the drainage basin of the city of Asheville, NC. Atmospheric moisture was increased indirectly by increasing the sea surface temperature (SST) in the simulation initial conditions, and by letting the regional atmospheric model adjust the atmospheric fields to the SST perturbation. The SST was increased in two ways: 1) using spatially constant increments and 2) using a climate change perturbation field obtained from a climate projection. For each SST scenario, the PD over the target area was maximized by using a physically based storm transposition method. Although the mean PD, that was obtained by averaging over all shifting increments, increased with SST, the maximum PD was obtained for the case of no SST increase. It was found that, in the case of no SST increase, the worst-case tropical cyclone track was significantly different than in the SST increase scenarios. In particular, in this case, the storm spent a longer time in the simulation inner domain, thus spawning a larger PD over the target area.

Copyright © 2019 Elsevier B.V. All rights reserved.


Language: en

Keywords

Dynamical downscaling; Hurricane Ivan; Intense precipitation; Moisture maximization; Storm transposition

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