Exploiting the Smooth Atmosphere to Improve Surface Temperature Retrieval from Space
Merchant, Christopher1; Le Borgne, Pierre2; Roquet, Herve2
1University of Edinburgh/Reading, UNITED KINGDOM; 2Meteo-France, FRANCE
Sea surface temperature (SST) can be estimated by optimal estimation (OE). However, coefficient-based techniques additionally have included an additional step of ''atmospheric correction smoothing''. This step improves the noise performance, and hitherto had no analogue within the OE framework. We show how to include atmospheric correction smoothing in OE, based on the expectation that atmospheric total column water vapour has a longer spatial correlation length scale than SST features. The retrieved quantities are the single-pixel SST and the clear-sky total column water vapour averaged over the vicinity of the pixel.
The new OE has been tested on day and night observations of the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI). The SST noise at single-pixel level is very low, with a robust standard deviation compared to matched drifting buoys of 0.39 K. The smoothed OE simultaneously improves SST sensitivity to 98% on average. This means that diurnal temperature variability and ocean frontal gradients are more faithfully estimated. This benefit is not available using traditional atmospheric correction smoothing.
The applicability of this new technique for the future Sea and Land Surface Temperature Radiometer (SLSTR) ocean mission will be discussed. Some adaptation of the technique will be required for best use of the dual-view part of the SLSTR swath. Results of trials using Advanced Along Track Scanning Radiometer data will be presented.