Arctic Snow Depth and Sea Ice Thickness From ICESat-2 and CryoSat-2 Freeboards: A First Examination

被引:85
|
作者
Kwok, R. [1 ]
Kacimi, S. [1 ]
Webster, M. A. [2 ]
Kurtz, N. T. [3 ]
Petty, A. A. [3 ,4 ]
机构
[1] CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA
[2] Univ Alaska Fairbanks, Inst Geophys, Fairbanks, AK 99775 USA
[3] Goddard Space Flight Ctr, Greenbelt, MD USA
[4] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20742 USA
基金
美国国家航空航天局;
关键词
Arctic Ocean; CryoSat-2; ICESat-2; sea ice; snow depth; thickness; AIRBORNE LASER; GPS DATA; RADAR; RETRIEVAL; MODEL; OCEAN; BAND;
D O I
10.1029/2019JC016008
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
We present a first examination of Arctic sea ice snow depth estimates from differencing satellite lidar (ICESat-2) and radar (CryoSat-2) freeboards. These estimates cover the period between 14 October 2018 and the end of April 2019. Snow depth is related to freeboard differences by the refractive index/bulk density of the snow layer-the only free parameter in the approach. Area-averaged snow depth ranges from 9 cm (on first-year ice: 5 cm, multiyear ice: 14 cm) in late October to 19 cm (first-year ice: 17 cm, multiyear ice: 27 cm) in April; on average, this snow is thinner over FYI. Spatial patterns and gradients of snow depth estimates compare well with reconstructions using snowfall from ERA-Interim and ERA5, although snowfall from ERA5 is systematically higher. For all months, the results suggest that similar to 50% of the total freeboard is comprised of snow. Retrievals are within a few centimeters of snow depth data acquired by Operation IceBridge in April 2019. Sources of uncertainties associated with this freeboard-differencing approach are discussed. Further, sea ice thicknesses calculated using the retrieved snow depth and a modified climatology are contrasted. Comparatively, the snow depth and calculated ice thickness using a modified climatology are higher by similar to 5 cm and 0.33 m, although these differences are not uniform throughout the season. Snow accumulation was slower between October and December but increased between December and January, unlike the modified climatology, which exhibited a monotonic accumulation for all months. Future opportunities for assessment and improvement of these estimates are discussed. Plain Language Summary The snow layer atop Arctic sea ice is an important component of the climate system. In winter, the insulating effects of snow slow the rate of ice growth. In spring, the onset of ice surface melt is delayed until the highly reflective snow layer disappears. During summer, meltwater from snow collects in depressions to form melt ponds, which enhances the absorption of solar radiation leading to more rapid surface warming. Presently, there are no routine measurements of snow depth suitable for assessing the impact of climate changes on the precipitation and accumulation of snow on sea ice. Our current understanding of snow depth is limited and has been based on field measurements conducted in the middle of last century and from airborne surveys conducted over the last decade. In this paper, we combine the measurements from two altimetry missions (ICESat-2 and CryoSat-2) to calculate snow depth over the entire Arctic Ocean. ICESat-2 (a lidar) and CryoSat-2 (a radar) measure the heights to the top and bottom of the snow layer, respectively. Differencing the two heights provides an estimate of the thickness of the snow layer. This paper describes this novel approach and an assessment of the snow depth estimates.
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页数:19
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