Abstract's details
SWIM: a new potential for sea-ice remote sensing
Event: 2022 Ocean Surface Topography Science Team Meeting
Session: Science IV: Altimetry for Cryosphere and Hydrology
Presentation type: Poster
CFOSAT is a new mission concept carrying SWIM, a scatterometer in Ku-band, aimed at measuring ocean waves spectra worldwide. It carries 6 low incidence rotating beams: one at nadir, and the 5 others at 2, 4, 6, 8 and 10 degrees incidence. These characteristics make CFOSAT a good intermediate between altimeters and classical scatterometers operating at higher incidence angles.
At nadir, sea-ice reflects more energy than over open water, implying peaky waveforms, that are not well processed using classical retraking algorithms. An adaptative retracking algorithm is applied to CFOSAT nadir data, which provides a so-called pseudo mss parameter over sea-ice, that directly relatesto its surface roughness.
Off nadir, sea-ice reflects less energy than open water and exhibits a convex response with incidence. To our knowledge, apart from very specific studies, these characteristics had never been performed in the past to discriminate sea-ice from open water. A bayesian sea-ice flagging algorithm is developped, that is based on the prior knowledge of the average behavior of NRCS over sea-ice and open water, the so-called Geophysical Model Functions. Comparison with SSMI sea-ice concentration data shows better performances than the existing flag based on forecasts, and shows promising potential for more specific sea-ice characterization.
At nadir, sea-ice reflects more energy than over open water, implying peaky waveforms, that are not well processed using classical retraking algorithms. An adaptative retracking algorithm is applied to CFOSAT nadir data, which provides a so-called pseudo mss parameter over sea-ice, that directly relatesto its surface roughness.
Off nadir, sea-ice reflects less energy than open water and exhibits a convex response with incidence. To our knowledge, apart from very specific studies, these characteristics had never been performed in the past to discriminate sea-ice from open water. A bayesian sea-ice flagging algorithm is developped, that is based on the prior knowledge of the average behavior of NRCS over sea-ice and open water, the so-called Geophysical Model Functions. Comparison with SSMI sea-ice concentration data shows better performances than the existing flag based on forecasts, and shows promising potential for more specific sea-ice characterization.
Contribution: SC42022-SWIM__a_new_potential_for_sea-ice_remote_sensing.pdf (pdf, 2165 ko)
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