Collaborative Research: Determining the Role of Ocean Dynamics in Atlantic Sea Surface Temperature Variations Using a Hierarchy of Coupled Models

观测和模式表明，大西洋海表温度（SSTs）表现出显著的低频（年际至年代际）变率，这些变化的很大一部分与气候系统的内部变化有关。然而，这些大西洋内部海温变化的起源尚未完全了解。该项目将开发一个耦合模型的层次结构，其中各种海洋过程被禁用；比较模式对将使一维和三维海洋动力学的作用以及风和浮力强迫在形成海洋动力变化中的独立作用强有力地分离开来。许多关于大西洋海温年代际变化的文献都集中在大西洋多年代际变率（AMV）和其中大气和海洋的作用上。而不是专注于一个特定的模式(例如，（AMV），本研究将在多个时间尺度上分离出整个大西洋盆地与特定海洋过程相关的大西洋海温变化模式。这种变化影响着区域和全球气候，包括北美和欧洲的气温、萨赫勒地区的降雨以及大西洋飓风的频率和强度。提高对低频海温变率的认识对于在季节到年代际时间尺度上进行气候预测的努力至关重要。了解大气强迫和海洋动力在设定海温异常中的各自作用，有助于提高海温的可预测性，因为如果海洋动力起主导作用，预计海温的可预测性会更高，以及有关监测洋流作为年代际预测系统一部分的重要性的实际问题。该项目还将通过向更广泛的社区提供协方差判别分析代码，推进气候数据分析的统计方法。该提案将支持WHOI的一名研究生和北卡罗来纳州立大学的一名博士后研究员各一年。该提案还将支持2名女性早期职业pi。巴克利（PI Buckley）是指导物理海洋学女性提高保留率（MPOWIR）指导小组的共同负责人。他们还将担任当地公立学校年度科学博览会的导师和评委，参与K-12科学-技术-工程-数学（STEM）教育。该项目的目标是在年际至年代际时间尺度上，解开大气强迫和各种海洋动力过程在大西洋海温变率和可预测性中的作用。为了实现这一目标，将使用社区地球系统模型版本2 （CESM2）开发一个耦合模型的层次结构。模式层次将包括不同复杂性的海洋模式组件，比较模式对将使小组能够定量地确定海洋动力学特定方面的作用，包括一维过程（垂直混合、年际混合层深度变化、夹带）和三维海洋动力学（包括风和浮力驱动的过程），在驱动海温变率方面的作用。将采用一种称为协方差判别分析的严格统计技术来诊断模式对之间大西洋海温方差的主要差异，从而阐明特定海洋过程对大西洋海温变率的影响。此外，对不同模式间大西洋海温的可预测性进行比较，将有助于阐明海洋过程在可预测性中的作用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Observations and models indicate that Atlantic sea surface temperatures (SSTs) exhibit significant low- frequency (interannual to decadal) variability, and a significant portion of these variations is related to internal variations of the climate system. However, the origin of these internal Atlantic SST variations is yet to be fully understood. This project will develop a hierarchy of coupled models in which various oceanic processes are disabled; comparing model pairs will enable the role of one-dimensional and three-dimensional ocean dynamics to be separated robustly, as well the separate roles of wind and buoyancy forcing in creating dynamical ocean variations. Much of the literature on decadal Atlantic SST variations is focused rather narrowly on the Atlantic Multidecadal Variability (AMV) and the role of the atmosphere and the ocean therein. Instead of focusing on one specific mode (e,g., the AMV), this research will isolate the modes of Atlantic SST variability related to specific oceanic processes, throughout the Atlantic basin on multiple time scales. This variability impacts regional and global climate, including temperatures across North America and Europe, rainfall in the Sahel region, and frequency and intensity of Atlantic hurricanes. Improved knowledge of low-frequency SST variability is essential for efforts aimed at climate predictions on seasonal to decadal time scales. Understanding the respective roles of atmospheric forcing and ocean dynamics in setting SST anomalies has implications for predictability of SSTs, as higher predictability is expected if ocean dynamics play a dominant role, and practical questions regarding the importance of monitoring ocean currents as part of a decadal prediction system. This project will also advance statistical methods for analysis of climate data by providing codes for covariance discriminant analysis to the broader community. This proposal will support a graduate student at WHOI and a postdoctoral researcher at NC State for a year each. The proposal will also support 2 female early career PIs. Lead PI Buckley is a Co-Leader of a mentoring group for Mentoring Physical Oceanography Women to Increase Retention (MPOWIR). The PIs will also engage in K-12 Science-Technology- Engineering-Math (STEM) education by serving as mentors and judges for the local public school annual science fairs.The goal of this project is to disentangle the roles of atmospheric forcing and various ocean dynamical processes in Atlantic SST variability and predictability on interannual-to-decadal time scales. In order to achieve this goal, a hierarchy of coupled models will be developed using the Community Earth System Model version 2 (CESM2). The model hierarchy will include ocean model components of varying complexity and comparing model pairs will enable the team to quantitatively determine the roles of specific aspects of ocean dynamics, including one-dimensional processes (vertical mixing, interannual mixed layer depth variations, entrainment) and three-dimensional ocean dynamics (including wind and buoyancy-driven processes), on driving SST variability. A rigorous statistical technique, called covariance discriminant analysis, will be applied to diagnose the leading differences in Atlantic SST variance between model pairs, thus elucidating the impact of specific ocean processes on Atlantic SST variability. Additionally, a comparison of the predictability of Atlantic SST between models in the hierarchy, will help elucidate the role of oceanic processes in predictability.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.