Evaluation of HY-2B SMR Sea Surface Temperature Products from 2019 to 2024

Haiyang 2B (HY-2B), the second Chinese ocean dynamic environment monitoring satellite, has been operational for nearly six years. The scanning microwave radiometer (SMR) onboard HY-2B provides global sea surface temperature (SST) observations. Comprehensive validation of these data is essential before they can be effectively applied. This study evaluates the operational SST product from the SMR, covering the period from 1 January 2019 to 31 August 2024, using direct comparison and extended triple collocation (ETC) methods. The direct comparison assesses bias and root mean square error (RMSE), while ETC analysis estimates the random error of the SST measurement systems and evaluates their ability to detect SST variations. Additionally, the spatial and temporal variations in error characteristics, as well as the crosstalk effects of sea surface wind speed, columnar water vapor, and columnar cloud liquid water, are analyzed. Compared with iQuam SST, the total RMSE of SMR SST for ascending and descending passes are 0.88 °C and 0.85 °C, with total biases of 0.1 °C and −0.08 °C, respectively. ETC analysis indicates that the random errors for ascending and descending passes are 0.87 °C and 0.80 °C, respectively. The SMR’s ability to detect SST variations decreases significantly at high latitudes and near 10°N latitude. Error analysis reveals that the uncertainty in SMR SSTs has increased over time, and the presence of crosstalk effects in SMR SST retrieval has been confirmed.

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Publication Details

Journal
Remote Sensing
Published
2025-01-16
DOI
https://doi.org/10.3390/rs17020300
Citations
3
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
Field-Weighted Citation Impact
3.90

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article

Evaluation of HY-2B SMR Sea Surface Temperature Products from 2019 to 2024

Shishuai Wang, Yili Zhao, Wu Zhou, Ping Liu
3 citations
Remote Sensing
Arctic and Antarctic ice dynamics
3.90
article

Evaluation of HY-2B SMR Sea Surface Temperature Products from 2019 to 2024

Shishuai Wang, Yili Zhao, Wu Zhou, Ping Liu
article en
3 citations

Abstract

Haiyang 2B (HY-2B), the second Chinese ocean dynamic environment monitoring satellite, has been operational for nearly six years. The scanning microwave radiometer (SMR) onboard HY-2B provides global sea surface temperature (SST) observations. Comprehensive validation of these data is essential before they can be effectively applied. This study evaluates the operational SST product from the SMR, covering the period from 1 January 2019 to 31 August 2024, using direct comparison and extended triple collocation (ETC) methods. The direct comparison assesses bias and root mean square error (RMSE), while ETC analysis estimates the random error of the SST measurement systems and evaluates their ability to detect SST variations. Additionally, the spatial and temporal variations in error characteristics, as well as the crosstalk effects of sea surface wind speed, columnar water vapor, and columnar cloud liquid water, are analyzed. Compared with iQuam SST, the total RMSE of SMR SST for ascending and descending passes are 0.88 °C and 0.85 °C, with total biases of 0.1 °C and −0.08 °C, respectively. ETC analysis indicates that the random errors for ascending and descending passes are 0.87 °C and 0.80 °C, respectively. The SMR’s ability to detect SST variations decreases significantly at high latitudes and near 10°N latitude. Error analysis reveals that the uncertainty in SMR SSTs has increased over time, and the presence of crosstalk effects in SMR SST retrieval has been confirmed.

Remote SensingVol. 17(2)
National Satellite Ocean Application Service (CN), Ocean University of China (CN)
National Natural Science Foundation of China, European Centre for Medium-Range Weather Forecasts, National Oceanic and Atmospheric Administration
Openalex Percentile: Top 9%
Arctic and Antarctic ice dynamics
3.90
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Evaluation of HY-2B SMR Sea Surface Temperature Products from 2019 to 2024 — Shishuai Wang, Yili Zhao, et al. · Remote Sensing (2025) | TGRS Research Map | TGRS