Abstract

SST is an essential climate variable [Bojinski et al., 2014] that is crucial for a wide range of applications, such as e.g. input to NWP models [Brasnett and Colan, 2016, Chelton and Wentz, 2005] and ocean models [Le Traon et al., 2015, Liang et al., 2017], for understanding air-sea interactions [Monzikova et al., 2017, Ning et al., 2018] and monitoring the climate [Merchant et al., 2019]. Observations of SST from IR satellites have been available since the early 1980’s, however these observations are affected by atmospheric aerosols and limited to clear-sky conditions [Merchant et al., 2019, Reynolds et al., 2002, Vázquez-Cuervo et al., 2004]. PMW observations of SST are an important and complementary alternative as they are not affected by non-precipitating clouds and the effect from aerosols is negligible [Donlon et al., 2007, Ulaby et al., 1981, Wentz et al., 2000].

This ATBD describes the algorithm for the retrieval of SST from CIMR. The algorithm presented here is based on the work by Alerskans et al. [2020] and consists of a statistically-based regression retrieval for SST and an optional regression-based retrieval for WS. Initial evaluation of the retrieval algorithm is performed using the ESA CCI MMD, described in Nielsen-Englyst et al. [2018] and Alerskans et al. [2020].