Abstract's details

The cross-analysis of dual-instrument CFOSAT measurements: Towards multiparameter all-angle Ku-band Geophysical Modulation Function

Alexey Mironov (eOdyn, France)


Yves Quilfen (LOPS, IFREMER, France); Jean-Francois Piole (LOPS, IFREMER, France); Bertrand Chapron (LOPS, IFREMER, France)

Event: 2022 Ocean Surface Topography Science Team Meeting

Session: CFOSAT

Presentation type: Type Oral

Alexey Mironov, , Jean-Francois Piolle, Bertrand Chapron

The CFOSAT satellite operates two Ku-band rotating radars: the nadir/near-nadir Ku-band wave scatterometer (SWIM) and the dual-polarization, moderate incidence angle, Ku-band wind scatterometer (SCAT). This unique instrumental configuration provides regular global collocated measurements of radar backscatter to retrieve sea surface state parameters, including significant wave height, directional wave spectrum, and wind vector. Two sensors also give the opportunity to improve the quality of the retrieved parameters by combining both data sources. This approach can be applied for the improvement of SCAT wind retrievals using SWIM observations, and vice-versa, SWIM wave spectrum measurements could be interpreted better with the use of additional SCAT information. Observations for different incidence angles have a different sensibility to sea surface parameters: short and long waves, surface currents, surface temperature, etc. Thus, the joint use of CFOSAT instruments requires a common unified description of multi-angle radar backscatter properties (σ0) as a function of a wide set of environmental parameters.
The IFREMER Wave and Wind Operational Center (IWWOC) provides CFOSAT nadir/near-nadir and moderate angle measurements together with model data with SWISCA S Level 2 product. In the present work, an alternative multi-parameter Ku-band Geophysical Model Function (GMF) was derived from this extensive dataset of radar and collocated model output in the common 25 km reference grid. The traditional set of GMF variables (wind vector, incidence angle, polarization, ….) was extended with various additional geophysical parameters: significant wave height, sea surface current vector, sea surface temperature, ice concentration, precipitation rate. The obtained GMF reproduces the main features of NSCAT-4 GMF for moderate incidence angles and TRMM/GPM GMF for near-nadir observations. However, the real backscattering properties of SWIM and SCAT are quite different from commonly used Ku-band GMFs due to various reasons like radar antenna design, swath patterns and noise signal distortions. These instrument-specific features are clearly distinguished as well.
The high volume of available data enables precise studies on the particular impact of different isolated geophysical variables on the backscattering coefficient value. As well, the total observational dataset could be regressed with the use of the neural network (NN) approach. In this case, the machine learning strategy should be adapted specifically to reduce possible biasing due to unequally distributed geophysical input variables. The resulting NN GMF could be considered as the approximation of the Ku-band radar cross-section as a function of a multi-parameter environment. In addition to wind/wave inversion tasks, it can serve as a robust platform for rapid signal calibration and re-adjustment during mission exploitation.
We anticipate the implementation of the demonstrated results and resulting model to extend the existing SCAT data processing with collocated SWIM nadir/near-nadir observations and additional NWP variables. As well, to improve existing SWIM nadir/near-nadir measurement interpretation.

Oral presentation show times:

Room Start Date End Date
Sala Pasinetti Thu, Nov 03 2022,10:00 Thu, Nov 03 2022,10:15
Alexey Mironov