Collaborative Research: Dynamics of Eighteen Degree Water from CLIMODE Observations and its Climate Implications

副热带模式水(STMW)是在西部边界流(WBC)赤道一侧形成的一个等温层，响应冬季的冷却，它是理解中纬度地区气候变化的核心，因为它整合了海洋和大气的异常，有助于气候系统的记忆。STMW区域有很大的储热能力，其储热速率已被证明取决于海-气通量和海洋环流。短波的体积如此之大，仅靠几年的海-气相互作用不能将其消散；形成后，它在随后的冬季被部分卷积，再次与大气相互作用。已发现许多可能影响短波形成或随后的破坏的过程。NSF资助的CLIMODE(CLIVAR模式水实验)的一个主要目标是量化有助于北大西洋西部STMW演变的过程，由于其温度几乎恒定，通常被称为18度水(EDW)。在为期两年的现场方案中获得了一套广泛的测量结果；对观测周期的分析和建模有助于评估对EDW演变作出贡献的过程的相对重要性。一个主要的动机是CLIMODE分析将导致气候建模的改进。这项研究旨在提供CLIMODE特定分析、较长周期变异性与评估和验证气候模型的指标需求之间的联系。智力上的优势：EDW地区拥有大量的热量存储和海气通量，向极地可变的热量输送，以及充满能量的海洋环流，是大气-海洋系统记忆的主要候选者。拟议的研究是对EDW体积的年际至年代际变化、对其产生影响的过程及其对海-气相互作用的影响的研究。EDW演变中的一些相互竞争的过程(墨西哥湾流的暖水平流、混合和通过气-海通量的海洋热损失)具有与北大西洋涛动等气候指数有关的可变性。研究人员将检查是否可以使用代理变量来监测重要的过程，从而将现场计划的结果与更长的气候记录联系起来，以评估每个过程的重要性、EDW演变的可预测性以及EDW对气候记忆的贡献。广泛的影响：为了成功预测气候变异性和变化，模型必须能够模拟那些产生年际到年代际气候影响的过程。一个有效的气候观测系统必须监测描述这些基本过程所需的变量，并改进模型的参数化和模拟。例如，EDW地区是中纬度风暴迅速加强的中心，这些风暴可能对不断变化的海洋条件做出反应，特别是对海洋储热做出反应。气候预测的模拟和验证(如风暴强度的变化)取决于制定一系列衡量模型模拟重要过程(储热)情况的指标。对于对EDW演变及其气候影响很重要的过程，将确定关键测量，以便制定简单而适当的衡量标准来评估气候模型。该项目是对美国CLIVAR(气候可变性和可预测性)计划的贡献。

Subtropical Mode Water (STMW), an isothermal layer that forms on the equatorward side of western boundary current (WBC) in response to wintertime cooling, is central to understanding climate variability in mid-latitude regions because it integrates anomalies in both the ocean and atmospheric to contribute to climate system memory. The STMW region has a large capacity to store heat, and its heat storage rate has been shown to depend both on air-sea fluxes and on ocean circulation. The volume of STMW is so large that several years of air-sea interaction alone cannot dissipate it; after formation, it is partially re-entrained in subsequent winters to again interact with the atmosphere.Many processes have been identified that could affect STMW formation or its subsequent destruction. A primary goal of the NSF-funded CLIMODE (CLIVAR Mode Water Experiment) is to quantify the processes contributing to the evolution of the STMW of the western North Atlantic, commonly referred to as 18-degree-water (EDW) because of its nearly constant temperature. An extensive set of measurements has been obtained over the two-year field program; analyses and modeling of the observational period can help evaluate the relative importance of the processes contributing to EDW evolution. A primary motivation is that CLIMODE analyses will lead to improvements in climate modeling. This study aims to provide a link between the CLIMODE-specific analyses, longer period variability, and the need for metrics to evaluate and verify climate models. Intellectual merit: The EDW region with its large heat storage and air-sea fluxes, variable poleward heat transport, and energetic ocean circulation is a prime candidate for memory in the atmosphere-ocean system. The proposed research is an examination of the interannual-to-decadal variations in EDW volume, of the processes that contribute to it, and its impact on air-sea interaction. Some competing processes in EDW evolution (warm water advection by the Gulf Stream, mixing, and oceanic heat loss through air-sea fluxes) have variability linked to climate indices such as the North Atlantic Oscillation. The investigators will examine whether important processes can be monitored using proxy variables and thus link the field program results to the longer climate record to evaluate the importance of each process, the predictability of EDW evolution, and the ability of EDW to contribute to climate memory.Broader impacts: To be successful in predicting climate variability and change, models must be able to simulate those processes that produce interannual-to-decadal climate impact. An effective climate observing system must monitor the variables needed to characterize those fundamental processes and improve model parameterization and simulation. For example, the EDW region is a center of rapid intensification of mid-latitude storms that may be responding to changing ocean conditions, in particular, to ocean heat storage. Simulation and verification of climate predictions (such as changes in storm intensity) depend on developing a series of metrics that measure how well the model simulates important processes (heat storage). For the processes that are important to EDW evolution and its climate impact, critical measurements will be identified in order to develop simple and appropriate metrics with which to evaluate climate models.This project is a contribution to the U.S. CLIVAR (CLImate VARiability and predictability) program.