Acquiring the Arctic-Scale Spatial Distribution of Snow Depth Based on AMSR-E Snow Depth Product

Yafei Nie Physical Oceanography Laboratory, Qingdao Collaborative Innovation Center of Marine Science and Technology, Ocean University of China, and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Yuzhe Wang Physical Oceanography Laboratory, Qingdao Collaborative Innovation Center of Marine Science and Technology, Ocean University of China, and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Xianqing Lv Physical Oceanography Laboratory, Qingdao Collaborative Innovation Center of Marine Science and Technology, Ocean University of China, and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Abstract

Snow on sea ice is a key variable in Arctic climate studies and thus plays an important role in geophysics. However, snow depths (SDs) derived from passive satellite remote sensing data are missing on multiyear ice due to the limitation of algorithm. We interpolate the SDs using the polynomial fitting (PF) method, trigonometric polynomial fitting (TPF) method, and multiquadric function interpolation method, and NASA’s Operation IceBridge (OIB) SD product is used to assess errors. Results show that TPF with the highest degree in x direction equaling 2 and the highest degree in y direction equaling 4 (TPF24) is the most satisfactory method, which has a deviation of 7.19 cm from OIB SD. Although PF with the highest degree in x and y directions being 7 and 8, respectively (PF78), also performs well in terms of error (7.22 cm), unreasonable value will be obtained at the edge due to its high degree. Results of TPF24 show a thicker SD area located in the north of Greenland, which is in good agreement with the actual situation.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Xianqing Lv, xqinglv@ouc.edu.cn

Abstract

Snow on sea ice is a key variable in Arctic climate studies and thus plays an important role in geophysics. However, snow depths (SDs) derived from passive satellite remote sensing data are missing on multiyear ice due to the limitation of algorithm. We interpolate the SDs using the polynomial fitting (PF) method, trigonometric polynomial fitting (TPF) method, and multiquadric function interpolation method, and NASA’s Operation IceBridge (OIB) SD product is used to assess errors. Results show that TPF with the highest degree in x direction equaling 2 and the highest degree in y direction equaling 4 (TPF24) is the most satisfactory method, which has a deviation of 7.19 cm from OIB SD. Although PF with the highest degree in x and y directions being 7 and 8, respectively (PF78), also performs well in terms of error (7.22 cm), unreasonable value will be obtained at the edge due to its high degree. Results of TPF24 show a thicker SD area located in the north of Greenland, which is in good agreement with the actual situation.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Xianqing Lv, xqinglv@ouc.edu.cn
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