Validation of Sentinel-3 SLSTR Land Surface Temperature Retrieved by the Operational Product and Comparison with Explicitly Emissivity-Dependent Algorithms

Land surface temperature (LST) is an essential climate variable (ECV) for monitoring the Earth system. To ensure accurate retrieval from satellite data, it important to validate derived LSTs and that they are within required accuracy precision thresholds. An emissivity-dependent split-window algorithm with viewing angle dependence two dual-angle algorithms proposed Sentinel-3 SLSTR sensor. Furthermore, these validated together operational LST product as well several in-situ data a rice paddy site. The were over three different land covers: flooded soil, bare full vegetation cover. Ground measurements performed wide band thermal infrared radiometer at permanent station. coefficients of estimated using Cloudless Atmosphere Radiosounding (CLAR) database: types overall systematic uncertainty (median) −0.4 K (robust standard deviation) 1.1 obtained. For Sentinel-3A product, 1.3 A first evaluation Sentinel-3B was also performed: 1.5 1.2 K. results obtained covers found site show algorithms, i.e., ones here previously without angular dependence, provide more precise than current version product.