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

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 fitti...

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Veröffentlicht in:Journal of atmospheric and oceanic technology 2019-10, Vol.36 (10), p.1957-1965
Hauptverfasser: Nie, Yafei, Wang, Yuzhe, Lv, Xianqing
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:0739-0572
1520-0426
DOI:10.1175/JTECH-D-18-0217.1