PANG Xiaoping, LIU Qingquan, JI Qing. Retrieval and Analysis of Snow Depth on Arctic First-Year Sea Ice[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 971-977. DOI: 10.13203/j.whugis20160259
Citation: PANG Xiaoping, LIU Qingquan, JI Qing. Retrieval and Analysis of Snow Depth on Arctic First-Year Sea Ice[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 971-977. DOI: 10.13203/j.whugis20160259

Retrieval and Analysis of Snow Depth on Arctic First-Year Sea Ice

  • The snow depth on the Arctic sea ice is not only a significant geophysical variable, but also an important parameter for the study of mass and energy balance, calculating sea ice thickness.To reduce the systematic error from different passive microwave sensor, we calibrated brightness temperature data obtained from the DMSP F17-SSMIS and F13-SSM/I during the overlap period.Forty-eight calibration models at the monthly scale were built up and compared with traditional calibration model at the yearly scale, which formed the basis for the snow depth retrieval and analysis on the Arctic first-year sea ice from 2003 to 2014.The results show that the correlation coefficients of the monthly fitting models of 19H, 19V, 22V, 37V channels are higher than the traditional model from January to May.Based on the calibrated satellite observation data, there is a general decline trend of snow depth on the Arctic first-year sea ice from 2003 to 2014, with the East Siberia Sea, the Laptev Sea and the Barents Sea decreasing obviously during the study period.
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