西南大西洋大陆架次年海平面异常及其与风力变化的关系评估

IF 2.2 3区 地球科学 Q2 OCEANOGRAPHY Ocean Dynamics Pub Date : 2024-07-01 DOI:10.1007/s10236-024-01621-y
Marie-Christin Juhl, Marcello Passaro, Denise Dettmering, Martin Saraceno
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引用次数: 0

摘要

我们分析了西南大西洋大陆架风力变化与海平面异常(SLA)之间的关系,重点是次年度时间尺度。为此,我们测试了网格测高法表示风驱动海平面异常的能力,并利用海洋学模型和验潮数据对结果进行了比较。本研究利用相干性分析来分析 SLA 与风压相干的频率。与模式 SLA 相比,测高 SLA 在三个月周期以下的能量较小。沿岸风应力与测高 SLA 的一致性仅在 50 天(d)内显著,而模式 SLA 在 20 天至全年的所有时段均显示出显著的一致性。通过经验正交函数(EOF)分析,我们发现第二模式与沿岸风压高度一致,分别占模式和测高海平面异常变化的 18.1%和 10.7%。
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Evaluation of the sub-annual sea level anomalies in the continental shelf of the Southwestern Atlantic and their relation to wind variability

We have analyzed the relationship between wind variability and sea level anomalies (SLA) on the Southwestern Atlantic Continental Shelf, focusing on sub-annual temporal scales. For this, we tested the capability of gridded altimetry to represent wind-driven SLA and compared results using an oceanographic model and tide gauge data. The present study used coherence analysis to analyze frequencies for which SLA and wind stress are coherent. The altimetry-SLA were found to have less energy below the three-month period compared to the model SLA. The coherence of along-shore wind stress and altimetry SLA was only significant for > 50 days (d), while the model SLA showed significant agreement in all periods considered, 20 d to annual. We further showed that geostrophic velocities on the continental shelf agreed significantly with SLA for > 50 d. As a result of an Empirical Orthogonal Function (EOF) analysis, we found that the second mode is highly coherent with the along-shore wind stress and accounts for 18.1% and 10.7% of variability in the model and altimetry sea level anomalies, respectively.

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来源期刊
Ocean Dynamics
Ocean Dynamics 地学-海洋学
CiteScore
5.40
自引率
0.00%
发文量
37
审稿时长
6-12 weeks
期刊介绍: Ocean Dynamics is an international journal that aims to publish high-quality peer-reviewed articles in the following areas of research: Theoretical oceanography (new theoretical concepts that further system understanding with a strong view to applicability for operational or monitoring purposes); Computational oceanography (all aspects of ocean modeling and data analysis); Observational oceanography (new techniques or systematic approaches in measuring oceanic variables, including all aspects of monitoring the state of the ocean); Articles with an interdisciplinary character that encompass research in the fields of biological, chemical and physical oceanography are especially encouraged.
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