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Retrieval of snow depth on the Antarctic Sea Ice from the FY-3B MWRI satellite data

  • role： First author第一作者
  • Affiliation：

    Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China

  • Email：yanzhongnan@whu.edu.cn
  • Introduction：闫忠男，研究方向为南极海冰表面积雪遥感反演。E-mail：yanzhongnan@whu.edu.cn
YAN Zhongnan1,  
  • Affiliation：

    Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China

    Key Laboratory of Polar Surveying and Mapping Science, Ministry of Natural Resources, Wuhan 430079, China

PANG Xiaoping12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China

    Key Laboratory of Polar Surveying and Mapping Science, Ministry of Natural Resources, Wuhan 430079, China

  • Email：jiqing@whu.edu.cn
  • Introduction：季青，研究方向为极地海冰遥感。E-mail：jiqing@whu.edu.cn
JI Qing12*,  
  • Affiliation：

    Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China

XIAO Zehui1

Resümee

Snow depth on sea ice is an important part of the cryosphere and global climate system because it is essential in the energy transfer of the ocean, sea ice, and atmosphere. Monitoring and understanding the change of snow depth on the Antarctic sea ice is beneficial to sea ice research and global climate change. Given the lack of Chinese satellite data products for snow depth on the Antarctic sea ice, we explored the application of FY-3B MWRI passive microwave brightness temperature data to retrieve the snow depth on the Antarctic sea ice.We used FY-3B MWRI 18.7 GHz, 36.5 GHz vertical polarization brightness temperature, and sea ice concentration data to retrieve the snow depth on the Antarctic sea ice by using Comiso03 model. The accuracy of snow depth on the Antarctic sea ice based on Markus98 and Comiso03 models was evaluated and compared with GCOM-W1 AMSR-2 snow depth product. The influence of brightness temperature on the retrieval of snow depth on Antarctic sea ice from FY-3B MWRI was discussed.Snow depth on the Antarctic sea ice retrieved by using Comiso03 model than Markus98 model is better based on FY-3B MWRI 18.7 GHz, 36.5 GHz vertical polarization brightness temperature, and sea ice concentration data in 2016, and the average deviation against with ice mass balance buoy measurements (2016S31, 2016S37, and 2016S40) in the Weddell Sea in 2016 is -1.72 cm. The snow depth retrieved on the Antarctic sea ice in 2016 form FY-3B MWRI, which is consistent with that of GCOM-W1 AMSR-2 released data product by NSIDC (the average deviation is -0.11 cm, and the correlation coefficient is 0.90). The difference between the FY-3B-derived and the NSIDC-released AMSR-2 snow depths is small (the spatial-temporal average deviation is -0.80 cm, and the correlation coefficient is 0.93) in the snow accumulation and stable period (from April to October), and relative large (the spatial–temporal average deviation is 2.76 cm, and the correlation coefficient is 0.85) in the snow melting period (from November to March). These differences mainly distributed in the northern Weddell Sea and margin ice zones.Snow depth on the Antarctic sea ice retrieved by Comiso03 model based on FY-3B MWRI satellite data is in good agreement with the GCOM-W1 AMSR-2 snow depth product released by NSIDC. The study on the retrieval of snow depth on the Antarctic sea ice using FY-3B MWRI satellite data can provide scientific data and technical support for monitoring polar ice and snow environment and evaluation of Antarctic sea ice change with its global effects.

Schlüsselwort

snow depth;Antarctic sea ice;passive microwave remote sensing;satellite remote sensing

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