MODIS sea surface temperature retrievals using different channel combinations and hybrid cloud detection

Abstract

NASA has been providing global sea-surface temperatures (SST) from MODIS on daily to decadal periods, and these are extensively used for a wide range of atmospheric and oceanic studies. However, the retrieval quality and cloud detection are somewhat problematic. We will present a new physical deterministic algorithm based on truncated total least squares (TTLS) using multiple channels for SST retrieval from MODIS measurements in conjunction with a new cloud detection scheme using a radiative transfer model atop a functional spectral difference method. The TTLS method is a new addition to improve the information content of the retrieval compared to our earlier work using modified total least squares (MTLS). A systematic study is conducted to ascertain the optimal channel selection from the 16 channels in the thermal IR of MODIS. Our new algorithm can reduce average RMSE of ~50% while increasing the average data coverage by ~50% compared to the operationally available MODIS SST.