Volume 42 Issue 12
Dec.  2023
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Zhongnan Yan, Xiaoping Pang, Qing Ji, Yizhuo Chen, Chongxin Luo, Pei Fan, Zeyu Liang. Retrieval of snow depth on Antarctic sea ice from the FY-3D MWRI data[J]. Acta Oceanologica Sinica, 2023, 42(12): 105-117. doi: 10.1007/s13131-023-2179-5
Citation: Zhongnan Yan, Xiaoping Pang, Qing Ji, Yizhuo Chen, Chongxin Luo, Pei Fan, Zeyu Liang. Retrieval of snow depth on Antarctic sea ice from the FY-3D MWRI data[J]. Acta Oceanologica Sinica, 2023, 42(12): 105-117. doi: 10.1007/s13131-023-2179-5

Retrieval of snow depth on Antarctic sea ice from the FY-3D MWRI data

doi: 10.1007/s13131-023-2179-5
Funds:  The National Natural Science Foundation of China under contract No. 42076235; the Fundamental Research Funds for the Central Universities under contract No. 2042022kf0018.
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  • Corresponding author: E-mail: pxp@whu.edu.cn; jiqing@whu.edu.cn; jiqing@whu.edu.cn
  • Received Date: 2022-10-17
  • Accepted Date: 2023-02-28
  • Available Online: 2023-06-06
  • Publish Date: 2023-12-01
  • The snow depth on sea ice is an extremely critical part of the cryosphere. Monitoring and understanding changes of snow depth on Antarctic sea ice is beneficial for research on sea ice and global climate change. The Microwave Radiation Imager (MWRI) sensor aboard the Chinese FengYun-3D (FY-3D) satellite has great potential for obtaining information of the spatial and temporal distribution of snow depth on the sea ice. By comparing in-situ snow depth measurements during the 35th Chinese Antarctic Research Expedition (CHINARE-35), we took advantage of the combination of multiple gradient ratio (GR (36V, 10V) and GR (36V, 18V)) derived from the measured brightness temperature of FY-3D MWRI to estimate the snow depth. This method could simultaneously introduce the advantages of high and low GR in the snow depth retrieval model and perform well in both deep and shallow snow layers. Based on this, we constructed a novel model to retrieve the FY-3D MWRI snow depth on Antarctic sea ice. The new model validated by the ship-based observational snow depth data from CHINARE-35 and the snow depth measured by snow buoys from the Alfred Wegener Institute (AWI) suggest that the model proposed in this study performs better than traditional models, with root mean square deviations (RMSDs) of 8.59 cm and 7.71 cm, respectively. A comparison with the snow depth measured from Operation IceBridge (OIB) project indicates that FY-3D MWRI snow depth was more accurate than the released snow depth product from the U.S. National Snow and Ice Data Center (NSIDC) and the National Tibetan Plateau Data Center (NTPDC). The spatial distribution of the snow depth from FY-3D MWRI agrees basically with that from ICESat-2; this demonstrates its reliability for estimating Antarctic snow depth, and thus has great potential for understanding snow depth variations on Antarctic sea ice in the context of global climate change.
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