Abstract
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 °C2) 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 °C2 and differences of up to 6 °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.
Highlights
This study aims to identify how both oceanographic dynamics and techniques used to produce Level 4 (L4) Sea surface temperature (SST) products may be responsible for the observed discrepancy between L4 products in southern Africa
Low variance indicates a small spread between observed SST values and better agreement between SST products
While there was good agreement between SST products for most of the southern African marine region, there was substantial disagreement in regions characterized by a strong SST gradient, in highly dynamic regions and within coastal upwelling systems
Summary
Sea surface temperature (SST) data are essential to environmental research, monitoring, and forecasting. SST fields are extensively used in oceanographic and atmospheric research to identify and investigate oceanographic processes, air-sea interactions, and long-term climate variability [1,2,3,4,5]. SST fields are vital inputs for the numerical ocean models used by weather and operational oceanography forecasting systems, which in turn inform industry, government agencies and the general public [6]. Ocean temperature strongly influences the distribution and diversity of biota as well as the functioning of ecosystems, rendering SST an essential variable when monitoring the impacts of climate change in environmentally sensitive systems [7,8]
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