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Studying Brown Ocean Re‐Intensification of Hurricane Florence Using CYGNSS and SMAP Soil Moisture Data and a Numerical Weather Model

Studying Brown Ocean Re‐Intensification of Hurricane Florence Using CYGNSS and SMAP Soil Moisture Data and a Numerical Weather Model

Authors :
Zhi Li
Alka Tiwari
Xinxin Sui
James Garrison
Frank Marks
Dev Niyogi
Source :
Geophysical Research Letters, Vol 50, Iss 19, Pp n/a-n/a (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract Hurricane Florence made landfall over the Carolinas 14 September 2018, bringing over 30 inches of rainfall. What remains understudied is the possible storm re‐intensification by wet and warm antecedent soil moisture (ASM), known as the Brown Ocean Effect (BOE). This study investigates this effect with two approaches: (a) two satellite‐based soil moisture (SM) data and (b) model simulation. The averaged Cyclone Global Navigation System and Soil Moisture Active Passive SM enables examination of land‐atmosphere interaction at a sub‐daily scale. Both observations and simulation results manifest positive feedback between ASM and rainfall intensity, with 3 days prior to landfall being the typical antecedent time scale. Wet (dry) ASM lead to intense (light) and concentrated (widespread) rains. We also found that soil temperature can modulate the BOE. This study aims to advance our understanding of land‐atmosphere feedback and calls to acquire accurate antecedent land states to enhance forecast skills.

Details

Language :
English
ISSN :
19448007 and 00948276
Volume :
50
Issue :
19
Database :
Directory of Open Access Journals
Journal :
Geophysical Research Letters
Publication Type :
Academic Journal
Accession number :
edsdoj.2bdce31c2dd49559596a2500ec77e35
Document Type :
article
Full Text :
https://doi.org/10.1029/2023GL105102