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


A validation of European Space Agency (ESA) remote sensing satellite (ERS) scatterometer ocean wind measurements is performed using a formalism recently proposed for and applied to NASA scatterometer (NSCAT) and Special Sensor Microwave Imager (SSM/I) measurements. This simple analytical model relates scatterometer measurements to true winds, taking into account errors in the satellite winds as well as errors in the data used for reference. In this study, National Data Buoy Center (NDBC) buoy winds are the chosen reference. In addition, ECMWF analysis winds are used as a third data source to completely determine the errors via a triple collocation analysis. According to this development, the resulting wind speed error analysis indicates that ERS scatterometer estimates are negatively biased at light winds. This result differs from recent results determined using standard regression analysis. It is also shown that ERS and NSCAT measurement accuracies are comparable in an overall sense.

This error model provides a more certain measure of both random and systematic terms and the authors use this tool to look at possible systematic scatterometer wind speed biases in two separate long-term (1992–98) ERS datasets. The chosen approach examines temporal and spatial variation between ocean buoy and ERS-derived winds to identify both seasonal and regional ERS wind error signatures. First, data indicate a time-dependent bias between NDBC and ERS winds that is strongly correlated with the seasonal cycle. Buoy-derived long-wave and atmospheric stability parameter averages exhibit similar cycles and are the likely geophysical links to this scatterometer error. An illustration of regional or spatially varying error sources is further provided using ERS data collocated with Tropical Atmosphere and Ocean (TAO) buoy array measurements. In this case the long-term average wind speed bias between TAO and ERS exhibits well-defined spatial structures within the equatorial belt (10°N, 10°S). Bias variations show qualitative agreement with a near-surface current climatology map for this Pacific region and also with the limited available buoy current measurements. Overall results indicate small but systematic nonwind sea surface effects on scatterometer products. It is concluded that there cannot be one set of values for ERS scatterometer wind validation parameters. Accounting for surface effects on scatterometer measurements may need consideration to ensure proper assimilation of scatterometer data into weather forecasting and climate prediction models.

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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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