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Improvement of Ocean State Estimation by Assimilating Mapped Argo Drift Data

机译:通过吸收映射的Argo漂移数据改进海洋状态估计

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摘要

We investigated the impact of assimilating a mapped dataset of subsurface ocean currents into an ocean state estimation. We carried out two global ocean state estimations from 2000 to 2007 using the K7 four-dimensional variational data synthesis system, one of which included an additional map of climatological geostrophic currents estimated from the global set of Argo floats. We assessed the representativeness of the volume transport in the two exercises. The assimilation of Argo ocean current data at only one level, 1000 dbar depth, had subtle impacts on the estimated volume transports, which were strongest in the subtropical North Pacific. The corrections at 10°N, where the impact was most notable, arose through the nearly complete offset of wind stress curl by the data synthesis system in conjunction with the first mode baroclinic Rossby wave adjustment. Our results imply that subsurface current data can be effective for improving the estimation of global oceanic circulation by a data synthesis.
机译:我们调查了将地下海流的映射数据集同化为海洋状态估计的影响。我们使用K7三维变分数据综合系统从2000年到2007年进行了两次全球海洋状态估算,其中之一包括从全球Argo浮标集中估算出的另一幅气候地转流图。我们在两个练习中评估了体积运输的代表性。 Argo海流数据仅在一个深度1000 dbar的水平上被同化,对估计的体积输运量产生了细微的影响,在亚热带北太平洋,该体积输运量最大。数据综合系统结合第一模式斜压Rossby波调整,几乎完全抵消了风应力卷曲,在10°sN处进行了校正,这是影响最明显的地方。我们的结果表明,通过数据综合,地下洋流数据可以有效地改善全球海洋环流的估计。

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