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The Influence of Rainfall on Scatterometer Backscatter Within Tropical Cyclone Environments—Implications on Parameterization of Sea-Surface Stress

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2 Author(s)
David E. Weissman ; Department of Engineering, Hofstra University, Hempstead, NY, USA ; Mark A. Bourassa

The use of satellite scatterometers to probe the winds in and near strong tropical cyclones (TCs) is a valuable tool for both numerical weather prediction and weather forecasters. The presence of widespread rain in these storms impedes the estimation of surface winds from the radar cross section measurements, when using a Ku-band radar. This paper seeks improvements in the methodology to infer surface winds and stresses from the satellite radar cross section data, by removing the effects of rain contamination at the ocean surface. The findings provide insights into improvements in the modeling efforts of TC intensity. This study demonstrates the use of high-resolution rain measurements obtained from a Next-Generation Radar collocated and simultaneous with the National Aeronautics and Space Ad ministration Quick Scatterometer. Through the application of the National Oceanic and Atmospheric Administration/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Re search Division TC wind analysis (H* WIND), we are studying the dependence of a surface normalized radar cross section (NRCS), which is related to surface stress, on the TC wind speed and rain rate. One of our findings is that, in the three TCs we have studied, the highest winds are accompanied by significant rain. Another is that the wind-driven rain can act as a roughening effect as measured by the H-pol NRCS. We also offer reasons why this can be interpreted as an additional stress on the surface. This roughening affects both the estimation of surface winds by scatterometers and the air-sea energy exchanges. This information could lead to an improved understanding of the dependence of the drag coefficient on both wind and rain.

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:49 ,  Issue: 12 )