A 10-year record of Arctic summer sea ice freeboard from CryoSat-2
A 10-year record of Arctic summer sea ice freeboard from CryoSat-2
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DOI：
10.1016/j.rse.2021.112744
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发表时间：
2022-01
影响因子：
13.5
通讯作者：
G. Dawson;J. Landy;M. Tsamados;A. Komarov;S. Howell;H. Heorton;T. Krumpen
中科院分区：
文献类型：
--
作者：
G. Dawson;J. Landy;M. Tsamados;A. Komarov;S. Howell;H. Heorton;T. Krumpen
迄今为止，对泛北极海冰厚度的卫星观测仅限于冬季。对于雷达高度计，常规方法无法区分夏季月份积累在冰面上的融水池的铅，这是冰厚计算中的关键步骤。在这里，我们使用来自夏季的350多幅光学和合成孔径雷达（SAR）图像来训练一个一维卷积神经网络，用于将CryoSat-2雷达高度计从海冰中分离出来，并以> 80%的精度领先。这使我们能够生成2011年至2020年5月至9月期间海冰雷达干舷的第一个泛北极测量值。结果表明，在五月和九月的干舷分布比较密切，从传统的“冬季”处理器在四月和十月，分别。干舷捕捉到了北极夏季海冰融化的预期模式，与博福特环流探测计划（BGEP）系泊处的冰吃水观测结果吻合良好。然而，与冰桥行动的机载激光扫描仪干舷和阿尔弗雷德·韦格纳研究所（AWI）冰鸟计划的机载EM冰厚度调查相比，CryoSat-2干舷被低估了0.02-0.2米，冰厚度被低估了0.28-1.0米，最大的差异是在较厚的多年海冰上。为了创建第一个泛北极夏季海冰厚度数据集，我们必须解决从雷达干舷到冰厚转换的不确定性的主要来源。
Satellite observations of pan-Arctic sea ice thickness have so far been constrained to winter months. For radar altimeters, conventional methods cannot differentiate leads from meltwater ponds that accumulate at the ice surface in summer months, which is a critical step in the ice thickness calculation. Here, we use over 350 optical and synthetic aperture radar (SAR) images from the summer months to train a 1D convolution neural network for separating CryoSat-2 radar altimeter returns from sea ice floes and leads with an accuracy >80%. This enables us to generate the first pan-Arctic measurements of sea ice radar freeboard for May–September between 2011 and 2020. Results indicate that the freeboard distributions in May and September compare closely to those from a conventional ‘winter’ processor in April and October, respectively. The freeboards capture expected patterns of sea ice melt over the Arctic summer, matching well to ice draft observations from the Beaufort Gyre Exploration Program (BGEP) moorings. However, compared to airborne laser scanner freeboards from Operation IceBridge and airborne EM ice thickness surveys from the Alfred Wegener Institute (AWI) IceBird program, CryoSat-2 freeboards are underestimated by 0.02–0.2 m, and ice thickness is underestimated by 0.28–1.0 m, with the largest differences being over thicker multi-year sea ice. To create the first pan-Arctic summer sea ice thickness dataset we must address primary sources of uncertainty in the conversion from radar freeboard to ice thickness.