3 June 2013 Improvements of satellite SST retrievals at full swath
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The ultimate goal of the prediction of Sea Surface Temperature (SST) from satellite data is to attain an accuracy of 0.3°K or better when compared to floating or drifting buoys located around the globe. Current daytime SST algorithms are able to routinely achieve an accuracy of 0.5°K for satellite zenith angles up to 53°. The full scan swath of VIIRS (Visible Infrared Imaging Radiometer Suite) results in satellite zenith angles up to 70°, so that successful retrieval of SST from VIIRS at these higher angles would greatly increase global coverage. However, the accuracy of present SST algorithms steadily degrades to nearly 0.7°K as the satellite zenith angle reaches 70°, due mostly to the effects of increased atmospheric path length. We investigated the use of Tfield, a gap-free first guess temperature field used in NLSST, as a separate predictor to the MCSST algorithm in order to clearly evaluate its effects. Results of this new algorithm, TfieldSST, showed how its rms error is heavily dependent on the aggressiveness of the pre-filtering of buoy matchup data with respect to Tfield. It also illustrated the importance of fully exploiting the a priori satellite-only information contained in Tfield, presently tamed in the NLSST algorithm due to the fact that it shows up as a multiplier to another predictor. Preliminary results show that SST retrievals using TfieldSST could be obtained using the full satellite swath with a 30% improvement in accuracy at large satellite zenith angles and that a fairly aggressive pre-filtering scheme could help attain the desired accuracy of 0.3°K or better using over 75% of the buoy matchup data.
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Walton McBride, Walton McBride, Robert Arnone, Robert Arnone, Jean-François Cayula, Jean-François Cayula, "Improvements of satellite SST retrievals at full swath", Proc. SPIE 8724, Ocean Sensing and Monitoring V, 87240R (3 June 2013); doi: 10.1117/12.2018399; https://doi.org/10.1117/12.2018399


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