To improve Antarctic sea-ice simulations and estimations, an ensemble-based Data Assimilation System for the Southern Ocean (DASSO) was developed based on a regional sea ice–ocean coupled model, which assimilates sea-ice thickness (SIT) together with sea-ice concentration (SIC) derived from satellites. To validate the performance of DASSO, experiments were conducted from 15 April to 14 October 2016. Generally, assimilating SIC and SIT can suppress the overestimation of sea ice in the model-free run. Besides considering uncertainties in the operational atmospheric forcing data, a covariance inflation procedure in data assimilation further improves the simulation of Antarctic sea ice, especially SIT. The results demonstrate the effectiveness of assimilating sea-ice observations in reconstructing the state of Antarctic sea ice, but also highlight the necessity of more reasonable error estimation for the background as well as the observation.

中文翻译：

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DASSO：利用海冰浓度和厚度观测的南大洋数据同化系统

为了改进南极海冰的模拟和估计，基于区域海冰-海洋耦合模型开发了基于集合的南大洋数据同化系统（DASSO），该模型将海冰厚度（SIT）与海-来自卫星的冰浓度（SIC）。为了验证 DASSO 的性能，实验于 2016 年 4 月 15 日至 10 月 14 日进行。通常，同化 SIC 和 SIT 可以抑制无模型运行中海冰的高估。除了考虑业务大气强迫数据的不确定性外，数据同化中的协方差膨胀程序进一步改进了南极海冰的模拟，特别是 SIT。结果证明了同化海冰观测在重建南极海冰状态方面的有效性，