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

合作研究：使用耦合模型层次结构确定海洋动力学在大西洋表面温度变化中的作用

• 批准号: 2219707
• 负责人: Martha Buckley
• 金额: $ 31.96万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2219707&HistoricalAwards=false
• 关键词: Collaborative; Research; Determining; Role; Ocean

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.

观测和模式表明，大西洋海表温度（SST）表现出显着的低频（年际至十年）的变化，这些变化的很大一部分是与气候系统的内部变化。然而，这些内部大西洋SST变化的起源尚未完全了解。该项目将开发一系列耦合模型，其中各种海洋过程被禁用;比较模型对将使一维和三维海洋动力学的作用以及风和浮力作用力在造成动态海洋变化方面的作用能够被有力地分开。许多关于大西洋海温年代际变化的文献都集中在大西洋的多年代际变率（AMV）以及大气和海洋在其中的作用上。而不是专注于一种特定模式（例如，这项研究将在多个时间尺度上分离出整个大西洋海盆与特定海洋过程有关的大西洋SST变率模式。这种变化影响到区域和全球气候，包括北美和欧洲的气温、萨赫勒地区的降雨量以及大西洋飓风的频率和强度。提高对低频SST变率的认识对于在季节至十年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学在设定SST异常中的各自作用对SST的可预测性有影响，因为如果海洋动力学起主导作用，则预计可预测性更高，并且关于监测洋流作为十年预测系统的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NC State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。铅PI巴克利是指导物理海洋学妇女，以增加保留（MPOWIR）辅导组的共同领导人。PI还将通过担任当地公立学校年度科学展览会的导师和评委，参与K-12科学技术工程数学（STEM）教育。该项目的目标是解开大气强迫和各种海洋动力过程在大西洋SST变率和可预测性中的作用。为了实现这一目标，将利用共同体地球系统模型第二版（CESM 2）开发一系列耦合模型。模型层次将包括复杂程度不同的海洋模型组成部分，比较模型对将使小组能够定量确定海洋动力学的具体方面对驱动SST变率的作用，包括一维过程（垂直混合、年际混合层深度变化、卷吸）和三维海洋动力学（包括风和浮力驱动的过程）。一个严格的统计技术，称为协方差判别分析，将用于诊断模式对之间的主要差异，在大西洋SST方差，从而阐明特定的海洋过程对大西洋SST变率的影响。此外，大西洋SST的可预测性之间的模式在hierarchy的比较，将有助于阐明海洋过程中的可预测性的作用。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。