C-Band SAR Winds for Tropical Cyclone Monitoring and Forecast in the South-West Indian Ocean

Type Article
Date 2021-05
Language English
Author(s) Duong Quoc-PhiORCID1, Langlade Sébastien2, Payan ChristopheORCID3, Husson Romain4, Mouche AlexisORCID5, Malardel Sylvie1
Affiliation(s) 1 : Laboratoire de l’Atmosphère et des Cyclones (UMR8105 LACy), Université de La Réunion, CNRS, Météo-France, 97400 Saint-Denis, France
2 : Regional Specialized Meteorological Center for Tropical Cyclones La Réunion, Météo-France, 97400 Saint-Denis, France
3 : Centre National de Recherche Météorologique (UMR3589 CNRM), Université de Toulouse, CNRS, Météo-France, 31057 Toulouse, France
4 : Collecte Localisation Satellites (CLS), 29280 Brest, France
5 : Laboratoire d’Océanographie Physique et Spatiale, Ifremer, Université de Brest, CNRS, IRD, IUEM, 29280 Brest, France
Source Atmosphere (2073-4433) (MDPI AG), 2021-05 , Vol. 12 , N. 5 , P. 576 (27p.)
DOI 10.3390/atmos12050576
WOS© Times Cited 2
Note This article belongs to the Special Issue Tropical Cyclones in the Indian Ocean
Keyword(s) SAR, 3D-Var, data assimilation, tropical cyclone, sentinel, IDAI, GELENA

Tropical cyclone (TC) monitoring and forecast in the South West Indian Ocean (SWIO) basin remain challenging, notably because of the lack of direct observations. During the 2018–2019 cyclone season, S-1 Sentinel SAR images were acquired, as part of the ReNovRisk-Cyclone research program, giving access to unprecedented detailed TC wind structure description without wind speed limitation. This paper assesses the quality of these data and the impact of their assimilation for TC forecasts. SAR observations are compared with analyses from a convection-permitting, limited area model AROME OI 3D-Var and with wind products used for operational TC monitoring. Their bias depends on the angle of incidence of the radar and the observation error is larger for extreme wind speed. The impact of SAR assimilation in AROME OI 3D-Var is assessed through two case studies. In the TC GELENA case, it leads to a better TC positioning and an improved representation of inner and outer vortex structures. The TC intensity reduction in the analysis propagates through subsequent analyses and it has an impact on forecasts for around 12 h. In the TC IDAI case, the 3D-Var does not manage to reproduce TC intensity captured by SAR. In both cases, the modification of the initial conditions has little influence on the intensification rate of the model forecasts. Sensitivity tests show that these results are robust to different observation errors and thinning.

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