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Y. Quilfen, B. Chapron, F. Collard, and D. Vandemark


Potential effects of environmental parameters such as sea state or atmospheric boundary layer stability on the normalized radar cross section (NRCS) measured by spaceborne sensors have been investigated for a long time. Using neural networks and large high quality collocated datasets, the relation between the European Remote Sensing Satellite (ERS) C-band scatterometer NRCS measurement and integrated sea state parameters (i.e., the mean wave period and significant wave height) measured by buoys is studied. As anticipated, NRCS measurements correlate well with an empirically derived parameter H α/T β, revealing the mean bulk relationship between a mean 10-m wind speed and the corresponding sea state development. The correlation and exponents exhibit dependency on the scatterometer incidence angles. A neural model that relates the scatterometer NRCS measurements to these wave spectral integrated parameters and wind speed is also developed. As obtained, the retrieval skill is significantly improved, by comparison with operational empirical models such as CMOD-IFR2 or CMOD4, when including wave effects. As illustrated, systematic biases occur under particular environmental conditions when using the operational scatterometer backscatter model functions.

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N. Reul, B. Chapron, E. Zabolotskikh, C. Donlon, A. Mouche, J. Tenerelli, F. Collard, J. F. Piolle, A. Fore, S. Yueh, J. Cotton, P. Francis, Y. Quilfen, and V. Kudryavtsev


Wind radii estimates in tropical cyclones (TCs) are crucial to helping determine the TC wind structure for the production of effective warnings and to constrain initial conditions for a number of applications. In that context, we report on the capabilities of a new generation of satellite microwave radiometers operating at L-band frequency (∼1.4 GHz) and dual C band (∼6.9 and 7.3 GHz). These radiometers provide wide-swath (>1,000 km) coverage at a spatial resolution of ∼40 km and revisit of ∼3 days. The L-band measurements are almost unaffected by rain and atmospheric effects, while dual C-band data offer an efficient way to significantly minimize these impacts. During storm conditions, increasing foam coverage and thickness at the ocean surface sufficiently modify the surface emissivity at these frequencies and, in turn, the brightness temperature (Tb) measurements. Based on aircraft measurements, new geophysical model functions have been derived to infer reliable ocean surface wind speeds from measured Tb variations. Data from these sensors collected over 2010–15 are shown to provide reliable estimates of the gale-force (34 kt), damaging (50 kt), and destructive winds (64 kt) within the best track wind radii uncertainty. Combined, and further associated with other available observations, these measurements can now provide regular quantitative and complementary surface wind information of interest for operational TC forecasting operations.

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