Intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses from the ORA-IP project
Intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses from the ORA-IP project
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DOI：
10.1007/s00382-016-2985-y
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发表时间：
2017-08-01
期刊：
影响因子：
4.6
通讯作者：
Wang, Xiaochun
中科院分区：
文献类型：
--
作者：
Chevallier, Matthieu;Smith, Gregory C.;Wang, Xiaochun
海水冰的重新分析对于评估北极海冰覆盖的可变性和最新趋势至关重要。对于海冰量尤其如此，因为长期和大规模的海冰厚度观察结果不存在。介绍了海洋重新分析项目（ORA-IP）的结果，重点是由最先进的全球海洋重新分析重建的北极海冰场。根据数据同化，模型物理和大气强迫对海冰覆盖属性的影响，包括浓度，厚度，速度，速度和雪之间的差异。在这里研究的14个重新分析中，有9种吸收海冰浓度，没有吸收海冰厚度数据。该比较揭示了在重建浓度场中的总体一致性，这主要是因为直接同化海洋观测，规定或同化的大气强迫和同化海冰浓度所施加的表面温度的限制。但是，由于多种因素，在重新分析中仍然存在一些传播。特别是，在重新分析的合奏中发现了海冰厚度的大量扩散，部分原因是其海冰模型成分继承的偏见引起的。在数据同化过程中，海冰浓度的同化和海冰厚度的处理也受到偏见的影响。这项研究的一个重要结果是，冰容量的空间分布在产品之间差异很大，与高度计估计值相比，没有重新分析明显优越。没有海冰浓度同化的系统的冰厚度并不比海冰观测到的系统的冰厚度差。对海冰速度场的评估表明，在大多数系统中，冰的漂移太快了。作为一个合奏，Ora-IP Reanalyses捕获了北极海冰地区的趋势，并且程度相对较好。但是，该合奏不能用于对北极海冰量最新趋势进行强有力的估计。重新分析中的偏见无疑会影响极地地区的模拟空气通量，并质疑当前海冰重新分析的适合性，以初始化季节性预测。
Ocean-sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent relatively well. However, the ensemble can not be used to get a robust estimate of recent trends in the Arctic sea ice volume. Biases in the reanalyses certainly impact the simulated air-sea fluxes in the polar regions, and questions the suitability of current sea ice reanalyses to initialize seasonal forecasts.