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Hurricane Florence Makes Landfall in the Southeast USA: Sensitive Dependence on Initial Conditions, Parameterizations, and Integrated Enstrophy

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Atmospheric and Climate Sciences 2020年第2期10卷 101-124页

作者： Sarah S. Balkissoon Jonathan T. Bongard Thomas Cain Dominic M. Candela Corey Clay Bahtiyar Efe Qiuping Ji Emily M. Klaus Alex P. Korner Kenna Mitchell Jane M. Niemeyer Jordan L. Rabinowitz Samuel P. Ritter Katherine Rojas paula sumrall Patrick S. Market Anthony R. Lupo Atmospheric Science Program School of Natural Resources University of Missouri Columbia MO USA Department of Meteorological Engineering Samsun University Samsun Turkey

The overall purpose of this paper is to post-evaluate the predictability of Hurricane Florence using the Advanced Research Weather Research Forecast (WRF) (ARW) version of a mesoscale model. This was performed over the period from 0000 UTC 13 September 2018 through 0000 UTC 18 September 2018. The WRF ARW core resolution used here was the 27-km grid spacing chosen to in order to balance finer resolution against in house processing time and storage. The large-scale analysis showed that a change in the Northern Hemisphere flow regime, especially the flow in the western part of the Northern Hemisphere may have contributed partly to the reduced forward speed of the tropical cyclone. In order to measure the predictability of a system, we will use different convective and boundary layer schemes initialized from the same conditions. The results demonstrated that the sign of the local IRE tendency was similar to that of the Northern Hemisphere Integrated Enstrophy. The results also showed that when the boundary layer, convective, and cloud microphysical schemes of the model were varied, the areal coverage of heavy precipitation of Florence was under-forecast by approximately 10% or more, and the heaviest amounts were under-forecast by an average of about 20%.

关键词： Predictability Model Behavior Integrated Entrophy Precipitation Tropical Cyclone

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