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The ReNovRisk-Cyclone program aimed at developing an observation network in the south-west Indian ocean (SWIO) in close synergy with the implementation of numerical tools to model and analyze the impacts of tropical cyclones (TC) in the present and in a context of climate change. This paper addresses the modeling part of the program. First, a unique coupled system to simulate TCs in the SWIO is developed. The ocean–wave–atmosphere coupling is considered along with a coherent coupling between sea surface state, wind field, aerosol, microphysics, and radiation. This coupled system is illustrated through several simulations of TCs: the impact of air–sea flux parameterizations on the evolution of TC Fantala is examined, the full coupling developed during the program is illustrated on TC Idai, and the potential of novel observations like space-borne synthetic aperture radar and sea turtles to validate the atmosphere and ocean models is presented with TC Herold. Secondly, the evolution of cyclonic activity in the SWIO during the second half of the 21st century is assessed. It was addressed both using climate simulation and through the implementation of a pseudo global warming method in the high-resolution coupled modeling platform. Our results suggest that the Mascarene Archipelago should experience an increase of TC related hazards in the medium term.

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.