Abstract Intra and inter-annual variations in the sea ice thickness are highly sensitive indicators of climatic variations undergoing in the earth’s atmosphere and oceans. This paper describes the method of estimating sea ice thickness using radar waveforms data acquired by SARAL/Altika mission during its drifting orbit phase from July 2016 onwards yielding spatially dense data coverage. Based on statistical analysis of return echoes, classification of the surface has been carried out in three different types, viz. floe, lead and mixed. Time delay correction methods were suitably selected and implemented to make corrections in altimetric range measurements and thereby freeboard. By assuming hydrostatic equilibrium, freeboard data were converted into sea ice thickness. Results show that sea ice thickness varies from 4 to 5 m near ice shelves and 1 to 2.5 m in the marginal sea ice regions. Freeboard and sea ice thickness estimates were also validated using NASA’s Operation Ice Bridge (OIB) datasets. Freeboard measurements show very high correlation (0.97) having RMSE of 0.13. Overestimation of approximately 1–2 m observed in the sea ice thickness, which could be attributed to distance between AltiKa footprint and OIB locations. Moreover, sensitivity analysis shows that snow depth and snow density over sea ice play crucial role in the estimation of sea ice thickness.

中文翻译：

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SARAL/AltiKa在漂移轨道阶段的海冰厚度估计

摘要 海冰厚度的年内和年际变化是地球大气和海洋气候变化的高度敏感指标。本文描述了使用 SARAL/Altika 任务从 2016 年 7 月起在其漂移轨道阶段获取的雷达波形数据估算海冰厚度的方法，产生了空间密集的数据覆盖。基于回波的统计分析，对地表进行了三种不同类型的分类，即。浮冰、铅和混合。适当地选择并实施了时间延迟校正方法，以在高度范围测量中进行校正，从而进行干舷校正。通过假设静水平衡，干舷数据被转换成海冰厚度。结果表明，海冰厚度在冰架附近从 4 到 5 m 不等，在边缘海冰区从 1 到 2.5 m 不等。干舷和海冰厚度估计也使用 NASA 的冰桥行动 (OIB) 数据集进行了验证。干舷测量显示非常高的相关性 (0.97)，RMSE 为 0.13。在海冰厚度中观察到的大约 1-2 m 的高估，这可能归因于 AltiKa 足迹和 OIB 位置之间的距离。此外，敏感性分析表明，海冰上的积雪深度和积雪密度在估计海冰厚度方面起着至关重要的作用。在海冰厚度中观察到的大约 1-2 m 的高估，这可能归因于 AltiKa 足迹和 OIB 位置之间的距离。此外，敏感性分析表明，海冰上的积雪深度和积雪密度在估计海冰厚度方面起着至关重要的作用。在海冰厚度中观察到的大约 1-2 m 的高估，这可能归因于 AltiKa 足迹和 OIB 位置之间的距离。此外，敏感性分析表明，海冰上的积雪深度和积雪密度在估计海冰厚度方面起着至关重要的作用。