Abstract

Radiometers aboard satellites provide an essential Sea Surface Temperature (SST) data archive, which is one of the key indicators of climate change. Since new radiometers are planned to fill the gap in the temporal data coverage, it is important to quantify the retrieval accuracy to utilize the data and seamlessly merge it into an existing SST data-archive. In this regard, we validate SST product from SLSTR/Sentinel-3A with in-situ measurements to create a reference frame for evaluating the new sensors products. We used NOAA <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> Quam SST dataset for validating satellite-retrievals, since it’s easily obtainable unlike skin-SST measurements. Several criteria have yielded a total of 30,353 high-quality cloud-free collocated data points between SLSTR and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> Quam SST datasets for 2017. Detailed evaluation of biases globally under different wind speeds and precipitable water vapor conditions indicates the fundamental difference between the satellite and in-situ SST, and recommendations are made for how datasets should be handled. SLSTR-retrieved skin-SST agrees with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> Quam subsurface-SST, irrespective of region and time of measurement, within -0.17±0.04K for all-day, -0.11±0.06K for daytime and -0.21±0.05K for nighttime datasets, with respective RMSE values of 0.62±0.10K, 0.58±0.09K and 0.65±0.13K. These small differences are partly due to the difference between ocean skin-temperature and subsurface-temperature, measurement uncertainties and sampling mismatch. Comprehensive validation carried out for SLSTR-retrieved SST has direct implications for future validation studies and future blended infrared, microwave and in-situ SST products.

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