Quality assessment of satellite remote sensing of sea-surface temperature

Bin Xu; Zhihong Liao; Chunxiang Shi

doi:10.1117/12.2626864

2 March 2022 Quality assessment of satellite remote sensing of sea-surface temperature

Bin Xu, Zhihong Liao, Chunxiang Shi

Proceedings Volume 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021); 121580C (2022) https://doi.org/10.1117/12.2626864
Event: 2021 International Conference on Computer Vision and Pattern Analysis, 2021, Guangzhou, China

Abstract

Sea surface temperature, as one of the most important variables, is widely used in the research of climate change, sea-air heat exchange, ocean-atmosphere numerical simulation and prediction. So the construction of real-time global coverage high resolution sea surface temperature dataset is very important for weather forecasting and climate prediction. But due to the spatial limitation of in suit sea surface temperature observation, more and more satellite remote sensing of seasurface temperature data were widely used as the main input data of global sea surface temperature dataset. As the first part, quality assessment of satellite remote sensing of sea-surface temperature is very necessary to understand the performance and quantify the error.f In this paper, FY-3C/VIRR SST, Metop-B/AVHRR SST, and GCOM-W1/AMSR2 SST were collected as the main input data and evaluated using buoy observed SST from iQuam. The result shows that the RMSE of Metop-B/AVHRR SST data is 0.4059°C in day time and 0.4329°C in night time. The RMSE of AMSR2 SST data is a little larger than AVHRR, is 0.5823°C in day time and 0.5224 °C in night time. Although, the RMSE of VIRR SST data is a litter large, from the time series and spatial distribution, the VIRR SST can provide more useful information over the global region. And with the new instrument development, Fengyun satellite retrieval SST will be improved and play more and more important in ocean science.

Citation Download Citation

Bin Xu, Zhihong Liao, and Chunxiang Shi "Quality assessment of satellite remote sensing of sea-surface temperature", Proc. SPIE 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021), 121580C (2 March 2022); https://doi.org/10.1117/12.2626864

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