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Predicting the Loop Current dynamics combining altimetry and deep flow measurements through the Yucatan Channel
Frontiers in Marine Science ( IF 2.8 ) Pub Date : 2023-05-25 , DOI: 10.3389/fmars.2023.1156159
Gaston Manta , Giovanni Durante , Julio Candela , Uwe Send , Julio Sheinbaum , Matthias Lankhorst , Rémi Laxenaire

The Loop Current is the main mesoscale feature of the Gulf of Mexico oceanic circulation. With peak velocities above 1.5 m s–1, the Loop Current and its mesoscale eddies are of interest to fisheries, hurricane prediction and of special concern for the security of oil rig operations in the Gulf of Mexico, and therefore understanding their predictability is not only of scientific interest but also a major environmental security issue. Combining altimetric data and an eddy detection algorithm with 8 years of deep flow measurements through the Yucatan Channel, we developed a predictive model for the Loop Current extension in the following month that explains 74% of its variability. We also show that 4 clusters of velocity anomalies in the Yucatan Channel represent the Loop Current dynamics. A dipole with positive and negative anomalies towards the western side of the Channel represents the growing and retracted phases respectively, and two tripole shape clusters represent the transition phases, the one with negative anomalies in the center associated with 50% of the eddy separation events. The transition between these clusters is not equally probable, therefore adding predictability. Finally, we show that eddy separation probability begins when the Loop Current extends over 1800 km (~27.2°N), and over 2200 km of extension, eddy detachment and reattachment is more frequent than separation. These results represent a step forward towards having the best possible operational Loop Current forecast in the near future, incorporating near real-time data transmission of deep flow measurements and high resolution altimetric data.

中文翻译:

通过尤卡坦海峡结合测高和深流测量预测环路电流动态

环流是墨西哥湾海洋环流的主要中尺度特征。峰值速度超过 1.5 毫秒–1, Loop Current 及其中尺度涡流对渔业、飓风预测以及墨西哥湾石油钻井平台作业安全的特别关注,因此了解它们的可预测性不仅具有科学意义,而且是一个重要的环境安全问题。将测高数据和涡流检测算法与 8 年通过尤卡坦海峡的深层流量测量相结合,我们开发了下个月环路电流扩展的预测模型,解释了其 74% 的可变性。我们还表明,尤卡坦海峡中的 4 个速度异常簇代表环路电流动力学。向海峡西侧具有正异常和负异常的偶极子分别代表生长阶段和收缩阶段,两个三极形状的星团代表过渡阶段,中间负异常的星团与 50% 的涡流分离事件相关。这些集群之间的转换不是等概率的,因此增加了可预测性。最后,我们表明,当环路电流延伸超过 1800 公里(~27.2°N)时,涡流分离概率开始,并且延伸超过 2200 公里时,涡流分离和重新附着比分离更频繁。这些结果代表了在不久的将来朝着尽可能最佳的运行环路电流预测迈出的一步,结合了深度流量测量和高分辨率高度测量数据的近实时数据传输。这些集群之间的转换不是等概率的,因此增加了可预测性。最后,我们表明,当环路电流延伸超过 1800 公里(~27.2°N)时,涡流分离概率开始,并且延伸超过 2200 公里时,涡流分离和重新附着比分离更频繁。这些结果代表了在不久的将来朝着尽可能最佳的运行环路电流预测迈出的一步,结合了深度流量测量和高分辨率高度测量数据的近实时数据传输。这些集群之间的转换不是等概率的,因此增加了可预测性。最后,我们表明,当环路电流延伸超过 1800 公里(~27.2°N)时,涡流分离概率开始,并且延伸超过 2200 公里时,涡流分离和重新附着比分离更频繁。这些结果代表了在不久的将来朝着尽可能最佳的运行环路电流预测迈出的一步,结合了深度流量测量和高分辨率高度测量数据的近实时数据传输。
更新日期:2023-05-25
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