By: Thomas M. Smith, Andrew Harris, Seonju Lee
Sea surface temperature (SST) is a fundamental oceanic parameter for understanding climate trends and variability. Since the early 1980s, SSTs have been retrieved globally using inverse methods from measured radiation through several satellites. One essential goal is the generation of accurate long-term satellite SST datasets for near-real-time anomaly and trend detection. However, even after reprocessing, satellite SST requires correction for residual biases in the data, which is a challenging task due to limited in situ data and potential nonlinear bias characteristics.




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