Impact of channel selection on sea surface temperature retrievals from passive microwave observations

Pia Englyst1,2, Jacob Hoyer3, Emy Alerskans4 and Leif Toudal Pedersen2, (1)Danish Meteorological Institute, København Ø, Denmark, (2)DTU Space, Lyngby, Denmark, (3)Danish Meteorological Institute, National Centre for Climate Research, København Ø, Denmark, (4)University of Copenhagen, NBI, København Ø, Denmark
Global accurate all-weather sea surface temperature (SST) observations are crucial for monitoring, understanding and predicting the state of the ocean, atmosphere and sea ice. Passive microwave observations are important as these are not prevented by non-precipitating clouds and the impact of aerosols is small. The Copernicus Imaging Microwave Radiometer (CIMR) being investigated by the European Space Agency (ESA) for the Copernicus Expansion program of the European Union is a polar mission, designed to observe all-weather, high-resolution, high-accuracy, sub-daily observations of SST and sea ice. It is the intention to include several of the radiometer channels, which are also on the Japanese Advanced Microwave Scanning Radiometer (AMSR2) and it is therefore important to assess the impact on SST of using different channel selections. This will be done using two different retrieval algorithms developed within ESA Climate Change Initiative (ESA-CCI) for SST. The first is an Optimal Estimation (OE) algorithm and the second retrieval algorithm is made up of a two-stage regression model, which retrieves wind speed and SST. The SSTs retrieved by the two different algorithms using different channel combinations will be compared to independent in situ SSTs from drifting buoys to assess the most optimal channel selection for each of the two algorithms. The results from two algorithms will be compared and discussed to provide recommendations for the most optimal set of channels for CIMR regarding accurate SST estimation. The evaluation against in situ observations and the use of two different retrieval algorithms further allow for an identification of the strengths and weaknesses of each of the two retrieval algorithms and these will be discussed as well.