Impact of rain-affected SSM/I data assimilation on the analyses and forecasts of tropical cyclones, and study of flow-dependent ensemble background errors, over the Southwest Indian ocean

Abstract

Tropical cyclones are tremendous natural hazards that threaten coastal populations worldwide, including in the Indian Ocean, the third most active basin. The purpose of this study is to perform data impact studies with the ALADIN Réunion Limited Area Model, which is the largest and the only tropical implementation of all of the versions of the ALADIN consortium. It allows special focus on the Indian Ocean area and a tropicalized 3D-Var data assimilation. Studies are performed for several storms of the 2006/2007 cyclonic season of the Southwest Indian Ocean (SWIO) basin. That season proved to be very active with ten named storms, four of which attained the major hurricane wind threshold of 50 m/s. Satellite data have proven most invaluable when trying to initialize NWP models, since the oceanic zones over which the cyclones develop are, by nature, data-sparse. Yet, the occurrence of clouds or rain proves to be a challenge when trying to assimilate satellite data: nonlinear processes predominate and the use of refined, costly numerical methods might be required. These computational costs are usually found to be prohibitive and cloudy/rainy data assimilation usually is a missing component in most operational centers. This proves to be of critical importance when dealing with tropical cyclones the data-sparse core, where observations are systematically rejected. © 2010 Springer Science+Business Media B.V.