A shift in the ocean circulation has warmed the subpolar North Atlantic Ocean since 2016
A shift in the ocean circulation has warmed the subpolar North Atlantic Ocean since 2016
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DOI：
10.1038/s43247-021-00120-y
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发表时间：
2021-02-26
影响因子：
7.9
通讯作者：
Maze, Guillaume
中科院分区：
文献类型：
--
作者：
Desbruyeres, Damien;Chafik, Leon;Maze, Guillaume
副极地北大西洋以年代际温度趋势的快速逆转而闻名，其后果包括大规模的纬向翻转和环流，北极热量和质量平衡或极端大陆天气。在这里，我们结合联合收割机数据集来自持续的海洋观测系统（卫星和原位），理想化的基于观测的建模（对流扩散的被动示踪剂），和机器学习技术（海洋剖面聚类），以记录和解释最近和正在进行的冷却到变暖的过渡的副极地北大西洋。自2006年以来，该地区逐渐变冷，2016年，随着海洋环流的转变，加强了西部亚热带温暖和盐水沃茨向东北方向的渗透，出现了表面强化和大规模变暖。副极地北大西洋的长期海洋记忆意味着，这种平流驱动的变暖可能会持续在不久的将来与大西洋的几十年变化及其全球影响的可能影响。根据通过理想化建模和机器学习技术对观测结果的分析，2016年后，随着来自西亚热带的温暖盐水沃茨的输送增强，副极地北大西洋急剧变暖-在2006年至2016年期间的冷却期之后。
The Subpolar North Atlantic is known for rapid reversals of decadal temperature trends, with ramifications encompassing the large-scale meridional overturning and gyre circulations, Arctic heat and mass balances, or extreme continental weather. Here, we combine datasets derived from sustained ocean observing systems (satellite and in situ), idealized observation-based modelling (advection-diffusion of a passive tracer), and a machine learning technique (ocean profile clustering) to document and explain the most-recent and ongoing cooling-to-warming transition of the Subpolar North Atlantic. Following a gradual cooling of the region that was persisting since 2006, a surface-intensified and large-scale warming sharply emerged in 2016 following an ocean circulation shift that enhanced the northeastward penetration of warm and saline waters from the western subtropics. The long ocean memory of the Subpolar North Atlantic implies that this advection-driven warming is likely to persist in the near-future with possible implications for the Atlantic multidecadal variability and its global impacts. The subpolar North Atlantic Ocean warmed sharply after 2016 as the transport of warm saline waters from the western subtropics was enhanced - following a period of cooling between 2006 and 2016 - according to analyses of observations via idealized modelling and machine-learning techniques.