| Zhang Xuefeng,Yang Lu,Fu Hongli,Li Dong,Shen Zheqi,Zhang Lianxin,Hu Xuhui. 2020. A variational successive corrections approach for the sea ice concentration analysis. Acta Oceanologica Sinica, 39(9):140－154 |
| A variational successive corrections approach for the sea ice concentration analysis |
| 一种基于变分优化的逐步订正法在海冰密集度分析中的应用 |
| Received:June 03, 2019 |
| DOI：10.1007/s13131-020-1654-5 |
| Key words:variational successive corrections spatial multi-scale recursive filter sea ice concentration |
| 中文关键词: 逐步订正法 空间多尺度递归滤波 海冰密集度 |
| 基金项目:The National Key Research and Development Program of China under contract Nos 2017YFC1404103 and 2016YFC1401701; the National Programme on Global Change and Air-Sea Interaction of China under contract GASI-IPOVAI-04; the National Natural Science Foundation of China under contract Nos 41876014 and 41606039. |
| Author Name | Affiliation | E-mail | | Zhang Xuefeng | School of Marine Science and Technology, Tianjin University, Tianjin 300110, China | | | Yang Lu | School of Marine Science and Technology, Tianjin University, Tianjin 300110, China | | | Fu Hongli | Key Laboratory of Marine Environmental Information Technology, National Marine Data and Information Service, Ministry of Natural Resources, Tianjin 300171, China | fhlkjj@163.com | | Li Dong | Key Laboratory of Marine Environmental Information Technology, National Marine Data and Information Service, Ministry of Natural Resources, Tianjin 300171, China | | | Shen Zheqi | Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China | | | Zhang Lianxin | Key Laboratory of Marine Environmental Information Technology, National Marine Data and Information Service, Ministry of Natural Resources, Tianjin 300171, China | | | Hu Xuhui | School of Marine Science and Technology, Tianjin University, Tianjin 300110, China | |
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| Abstract: |
| The sea ice concentration observation from satellite remote sensing includes the spatial multi-scale information. However, traditional data assimilation methods cannot better extract the valuable information due to the complicated variability of the sea ice concentration in the marginal ice zone. A successive corrections analysis using variational optimization method, called spatial multi-scale recursive filter (SMRF), has been designed in this paper to extract multi-scale information resolved by sea ice observations. It is a combination of successive correction methods (SCM) and minimization algorithms, in which various observational scales, from longer to shorter wavelengths, can be extracted successively. As a variational objective analysis scheme, it gains the advantage over the conventional approaches that analyze all scales resolved by observations at one time, and also, the specification of parameters is more convenient. Results of single-observation experiment demonstrate that the SMRF scheme possesses a good ability in propagating observational signals. Further, it shows a superior performance in extracting multi-scale information in a two-dimensional sea ice concentration (SIC) experiment with the real observations from Special Sensor Microwave/Imager SIC (SSMI). |
| 中文摘要: |
| 卫星遥感获取的海冰密集度观测资料中包含着空间多尺度信息。然而，多数传统的数据同化方法难以在海冰密集度变化较为复杂的海冰边缘区有效提取这些多尺度信息。为解决上述问题，本文设计了一种基于变分优化的逐步订正分析方法—空间多尺度递归滤波，该方法是逐步订正分析与最小化算法的结合，它能够从长波到短波依次提取观测中的各种空间尺度信息。与传统的客观分析相比，这种基于变分的多尺度分析方法不仅能够在最小化过程中一次性的提取出观测中的多尺度信息，而且能够方便合理的进行参数配置。单观测点同化试验的分析结果表明，空间多尺度递归滤波方法具有良好的观测信息空间传播能力。随后在二维海冰密集度的分析试验中，该方法能够较好的提取SSMI海冰密集度观测资料中的空间多尺度信息，进而获得高精度的海冰密集度分析结果。 |
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