10C.8 Use of MADRAS on Megha-Tropiques to study Hurricane Sandy and Typhoon Bophat Evolution

Wednesday, 2 April 2014: 3:15 PM
Pacific Ballroom (Town and Country Resort )
Nicolas Viltard, LATMOS-CNRS, Guyancourt, France; and A. Martini

Megha-Tropiques is a French-Indian satellite dedicated to tropical convection. The low-inclination of (20°) its orbit and the large swath of its main instrument MADRAS allows us to sample the rain systems in series of overpasses separated by 1h30 time lags. Coupled with other similar sensors like TMI on TRMM, AMSR2 on GCOM-W or SSMI and SSMIS on NOAA satellites, we are able to get a good sampling of the temporal evolution of those systems in terms of rain structures and intensities. Hurricanes are particularly interesting because their characteristic life time is a few days and their general motion is relatively slow. Furthermore, the characteristic scale and structure of their precipitation field gives a lot of information about their evolution and those fields are compatible with the spatial resolution of the spaceborne instruments even if the smallest details cannot be captured.

MADRAS produced only 15 month of data from October 2011 to January 2013; During its life time it captured a number of hurricanes and typhoons in the various basins. We will focus here on the evolution of two storms that were nicely sampled by MADRAS. First, Hurricane Sandy in October 2011 was observed in its first few days about 16 times from its the tropical storm stage in the Gulf of Mexico and until it moved out of the Caribbean regions as a mature hurricane after crossing through the Island of Cuba. Similarly, typhoon Bophat was sampled while it formed and intensified in the Warm Pool and until it made its landfall in the Philippines.

We will show in the presentation how, through examination of the brightness temperatures at 89 and 157 GHz and the rain retrieval algorithm known as BRAIN, we can understand the evolution of each of the storms and how critical satellite with low-inclinations orbits are critical for hurricane forecasts and studies.

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