Decadal Evaluation of Sea Surface Temperature Products from MWRI Onboard FY-3B/C/D Satellites
Microwave Radiation Imagers (MWRIs) onboard the FY-3B, FY-3C, and FY-3D satellites are the primary sensors for sea surface temperature (SST) observation. Benefiting from the resolution of several key calibration issues in brightness temperature products, MWRI SST records spanning more than a decade have been reprocessed. In this study, these reprocessed SST products are evaluated using direct comparison and the extended triple collocation (ETC) method, along with additional error analyses. Compared with iQuam SST, the reprocessed MWRI SST products from the three satellites show total root mean square errors (RMSEs) of 0.80–0.82 °C and total biases of −0.12 °C to 0.00 °C. ETC analyses based on MWRI, ERA5, and Argo SSTs indicate random errors of 0.76–0.78 °C. Furthermore, the reprocessed MWRI SST products demonstrate temporal stability and exhibit minimal crosstalk effects from sea surface wind speed, columnar water vapor, and columnar cloud liquid water in SST retrievals. Compared with previous versions, the reprocessed products show significant improvements, with consistent performance across FY-3B, FY-3C, and FY-3D. However, differences in SST observations due to the varying local times of the ascending nodes among the three satellites should be corrected in practical applications.
Authors
- Na Xu (ORCID: https://orcid.org/0000-0002-2547-0223)
- Shuai Zha (ORCID: https://orcid.org/0000-0001-6773-7830)
- Yili Zhao (ORCID: https://orcid.org/0000-0001-9820-9221)
- Miao Zhang (ORCID: https://orcid.org/0000-0002-1497-4151)
- Song Song (ORCID: https://orcid.org/0000-0002-7618-5692)
- Lin Chen (ORCID: https://orcid.org/0000-0002-2390-899X)
- Ping Liu (ORCID: https://orcid.org/0009-0000-2496-7329)
Institutions
- China Meteorological Administration (CN)
Publication Details
- Journal
- Journal of Marine Science and Engineering
- Published
- 2025-11-12
- DOI
- https://doi.org/10.3390/jmse13112136
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- European Centre for Medium-Range Weather Forecasts
- National Oceanic and Atmospheric Administration