Two retrieval algorithms developed as a part of the European Space Agency Climate Change Initiative (ESA-CCI) project are used to assess the effects of withholding observations from selected frequency channels on the retrieved subskin Sea Surface Temperature (SST) from AQUA's Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) and to evaluate a Copernicus Imaging Microwave Radiometer (CIMR) like channel configuration. The first algorithm is a statistical regression-based retrieval algorithm, while the second is a physically based optimal estimation (OE) algorithm. A database with matching satellite and drifting buoy observations is used to test the performance of each channel configuration using both retrieval algorithms to identify the most optimal channel selection for accurate SST retrievals. The evaluation against in situ observations allows identification of the strengths and weaknesses of the two retrieval algorithms, and demonstrates the importance of using in situ observations to evaluate existing theoretical retrieval uncertainty studies. Overall, the performance increases as expected when more channels are included in the retrieval. In particular, more channels allow a better performance for the range of different observing conditions (e.g. cold waters). The two retrieval algorithms agree that for a three-channel configuration, the 6, 10, 18 GHz (V and H polarization) is better than the 6, 10, 23 GHz configuration (V and H polarization). This is demonstrated for different geographical regions and throughout all seasons. Of the different combinations tested here, it is evident that withholding observations from the 23 and 36 GHz channels from the retrieval has the least impact on the SST performance. Overall, this analysis shows that the CIMR like channel configuration performs very well when compared to an AMSR-E like constellation using both retrieval algorithms.
- Channel selection
- Copernicus imaging microwave radiometer (CIMR)
- Optimal estimation (OE)
- Passive microwaves
- Remote sensing
- Sea surface temperature (SST)