Tracking Subtropical Water Mass Anomalies to the Tropics and Their Potential for Re-emergence

追踪热带副热带水团异常及其重新出现的潜力

• 批准号: 1830007
• 负责人: Susan Wijffels
• 金额: $ 76.06万
• 依托单位: Woods Hole Oceanographic Institution
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830007&HistoricalAwards=false
• 关键词: Tracking; Subtropical; Water; Mass; Anomalies

How tropical oceans, which are strong drivers of global climate variability, are influenced by subtropical processes remains unresolved. Tropical-subtropical teleconnections occur either via the atmosphere, which can set up within a season, or through subsurface ocean pathways operating over years to decades. The formation in the subtropics and subsequent advection of anomalous heat due to water mass anomalies is a potentially important ocean pathway. Some theoretical studies suggest this process controls multiyear to decadal climate variability. Anomalies are created in two ways: at the surface by wind, heat and freshwater flux changes or in the subsurface by anomalous advection. Using the recent record from the Argo array of profiling floats, many regional studies have identified the formation and propagation of water mass anomalies in most ocean basins. Modern ocean general circulation model studies with realistic surface forcing can form and advect anomalies similar to the observed ones. However, the two descriptions do not agree on whether these anomalies can survive to reach the equator, and then re-emerge to the surface. This project will take a globally consistent observational and modelling approach to quantitatively understand the source, fate and potential re-emergence of subtropical water mass anomalies, and thus their potential to influence the climate. As part of this project, an improved gridded global Argo analysis will be made freely available with particular focus on water mass variability and realistic estimates of resolved scales and errors. A production system will be put in place to ensure ongoing updates and distribution of the analysis. A graduate student in the MIT-WHOI Joint Program will learn both numerical modelling (including the analysis of ensembles) and observational analysis techniques. Since the targeted processes are a prime candidate for enabling longer term climate forecasting, results will discussed directly with climate forecasting teams in the US and Australia via collaborator Peter Oke.This project will combine a novel analysis of Argo data with a set of tailored ensembles of OGCM runs to identify source regions of observed water mass variability. A model-based ensemble optimal interpolation (OI) will be used for the first time to map Argo data, both on depth and density surfaces. Global observed surface conditions will be used to force a numerical model specifically configured and tuned to simulate the water mass variability in the Argo period. This all-forcing ensemble will then be compared to parallel ensembles with restricted tropical and subtropical/hemispheric forcing where the temperature, salinity and wind components will be varied to examine the generation and fate of anomalies generated in different regions. The goal is to attribute observed equatorial variability in each ocean basin to local and/or remote drivers and assess if there is any evidence for re-emergence. Examining all basins, which vary in source strength, advective pathways, mixing rates and throughflows, will result in a more unified view of where and when subtropical variability impacts the far field. The observational approach will involve carefully checking and removing sensor errors and using a dynamically-intelligent model-based ensemble OI framework. Rather than diagnosing formation mechanisms through incomplete observations or from a single all-forcing model run, the study will use dedicated ensembles of simulations with controlled regional surface forcing. An ensemble approach will clearly quantify the role that intrinsic variability (due to instabilities) plays in the model system and in turn, will help better understand the observed record. By focusing on the feeder flows to the equatorial upwelling systems, the team will then assess the importance of the proposed ocean tunnel to climate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

热带海洋是全球气候变异性的强大驱动力，它如何受到副热带过程的影响仍未得到解决。热带-亚热带遥相关要么通过大气发生，后者可以在一个季节内建立，要么通过运行数年至数十年的次表层海洋路径发生。水团异常在亚热带的形成和随后的异常热平流是一条潜在的重要海洋路径。一些理论研究表明，这一过程控制着多年到十年的气候变化。异常以两种方式产生：在地表由风、热量和淡水通量变化造成，或在次表层由异常平流造成。利用Argo剖面浮标阵列的最新记录，许多区域研究已经确定了大多数海洋盆地中水团异常的形成和传播。现代海洋环流模式的研究具有现实的表面强迫作用，可以形成和平流类似于观测到的异常。然而，对于这些异常是否能够存活到赤道，然后重新出现在地表上，这两种描述并不一致。该项目将采用全球一致的观测和建模方法，以定量了解副热带水团异常的来源、命运和可能重新出现的可能性，从而了解它们影响气候的潜力。作为该项目的一部分，将免费提供改进的格网全球ARGO分析，特别侧重于水质量的可变性和对已解决的尺度和误差的现实估计。将建立一个生产系统，以确保不断更新和分发分析。麻省理工学院-世界卫生组织联合项目的研究生将学习数值建模(包括集合分析)和观测分析技术。由于目标过程是实现长期气候预测的最佳候选者，结果将通过合作者Peter Oke直接与美国和澳大利亚的气候预测团队讨论。该项目将结合对ARGO数据的新颖分析和一套量身定制的OGCM运行集合，以确定观测到的水团可变性的来源区域。基于模型的集合最优内插(OI)将首次用于绘制深度和密度表面上的ARGO数据。全球观测到的地表条件将被用来强制建立一个专门配置和调整的数值模型，以模拟阿尔戈时期的水团变化。然后将这种全强迫集合与具有受限热带和副热带/半球强迫的平行集合进行比较，其中温度、盐度和风分量将发生变化，以检查在不同区域产生的异常的产生和命运。其目标是将在每个大洋盆地观测到的赤道变化归因于当地和/或远程驱动因素，并评估是否有任何证据表明重新出现。检查所有盆地，这些盆地在源强度、平流路径、混合率和贯穿流方面存在差异，将导致对副热带变化影响远场的地点和时间的更统一的看法。观察性方法将涉及仔细检查和消除传感器错误，并使用基于动态智能模型的集成OI框架。这项研究不是通过不完整的观测或从单一的强迫模式运行来诊断形成机制，而是使用专门的模拟集合，并控制区域表面强迫。集合方法将清楚地量化内在可变性(由于不稳定)在模型系统中所起的作用，反过来，将有助于更好地理解观察到的记录。通过将重点放在流向赤道上升流系统的支流上，研究小组将评估拟议中的海洋隧道对气候的重要性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。