Satellite Sea Surface Temperature Product Comparison for the Southern African Marine Region

Several satellite-derived Sea Surface Temperature (SST) products were compared to determine their potential for research and monitoring applications around the southern African marine region. This study provides the first detailed comparison for the region, demonstrating good overall agreement (variance < 0.4 degrees C-2) between merged SST products for most of the South African marine region. However, strong disagreement in absolute SST values (variance of 0.4-1.2 degrees C-2 and differences of up to 6 degrees C) was observed at well-known oceanographic features characterized by complex temperature structures and strong SST gradients. Strong seasonal bias in the discrepancy between SST was observed and shown to follow seasonal increases in cloud cover or local oceanographic dynamics. Disagreement across the L4 products showed little dependence on their spatial resolutions. The periods of disagreement were characterized by large deviations among all products, which resulted mainly from the lack of input observations and reliance on interpolation schemes. This study demonstrates that additional methods such as the ingestion of additional in situ observations or daytime satellite acquisitions, especially along the west coast of southern Africa, might be required in regions of strong SST gradient, to improve their representations in merged SST products. The use of ensemble means may be more appropriate when conducting research and monitoring in these regions of high SST variance.

Automated summary

This study compared several satellite-derived sea surface temperature products for research and monitoring applications in the southern African marine region. Overall, there was good agreement between merged sea surface temperature products for most of the region, but strong disagreement was observed at areas with complex temperature structures and strong sea surface temperature gradients. Seasonal bias in temperature discrepancy was found to be influenced by cloud cover and local oceanographic dynamics. Additional methods such as ingesting more in situ observations or daytime satellite acquisitions may be required to improve the representations in merged sea surface temperature products, especially in regions of high temperature variance.