CAREER: Evolution of Ocean Mesoscale Turbulence in a Changing Climate
职业:气候变化中海洋中尺度湍流的演变
基本信息
- 批准号:1553593
- 负责人:
- 金额:$ 76.29万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-02-15 至 2022-01-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Once the large-scale ocean circulation was viewed as a sluggish continuous flow. Thanks to new satellite and in situ observations, powerful numerical models, and advances in theory, it is now understood that ocean mesoscale turbulence, the highly energetic, nonlinear jumble of waves, eddies, and jets which characterizes ocean currents on scales of 20-500 km, is an essential component of ocean circulation, transport, and marine ecosystems. Because this turbulence draws its energy from instabilities of the large-scale flow, its properties are themselves sensitive to changes in climate. This project seeks to answer the question: how, and on what timescales, do large-scale changes in global climate affect the properties of ocean mesoscale turbulence? As such, the proposed work has the potential to transform how the climate community views mesoscale turbulence. Because most ocean climate models are too coarse to resolve the mesoscale, the effects of mesoscale turbulence are parameterized. As a result, mesoscale turbulence is reduced to a "parameter" to be tuned, rather than an emergent, dynamic part of the Earth system. The project is aimed at deepening basic physical understanding of the processes that regulate the properties of mesoscale turbulence and the timescales on which these properties respond to changes in climate. Consideration of this two-way interaction will lead to a richer understanding of the role of the ocean in the climate system, opening the door to new mechanisms for climate feedbacks. The project will also lead to methodological advances in Big Data computational tools for oceanography. The curriculum development will address the need for students to develop strong computational skills and, in particular, the capability to handle Big Data, to meet the emerging challenges of 21st century science. It will also promote active learning and the use of data in the oceanography classroom. The open-source nature of the teaching materials will encourage wide adoption. Strong interaction between research and education is guaranteed, because the same tools used in the research will be incorporated into the curriculum, both evolving together throughout the project.The research component of this CAREER award will examine the link between climate change, baroclinic instability, mesoscale eddy properties (kinetic energy and length scales), and mesoscale mixing, using a hierarchy of models and observations. Idealized process models will build a theoretical foundation of understanding of how changes in surface wind and buoyancy forcing lead to changes in mesoscale turbulence. Decadal variability in mesoscale statistics and baroclinic instability will also be examined in satellite and hydrographic observations. Finally, the theoretical framework and statistical analysis will be applied to global, eddy-resolving climate model simulations of greenhouse warming. To facilitate this work, Python-based computational tools for rapid data processing will be developed. These tools will be integrated into education through development of an open-source curriculum in "Big Data Oceanography," in which the computational skills necessary to study global, high-resolution datasets are taught side-by-side with core ocean science concepts. These modules will be deployed and assessed in an undergraduate course and disseminated widely online and at education conferences.
大尺度的海洋环流曾经被看作是一种缓慢的连续流动。由于新的卫星和现场观测,强大的数值模型和理论的进步,现在人们已经认识到,海洋中尺度湍流是20-500公里尺度上的海流特征,是海洋环流,运输和海洋生态系统的重要组成部分。由于这种湍流从大尺度流动的不稳定性中汲取能量,因此其性质本身对气候变化很敏感。该项目旨在回答这样一个问题:全球气候的大尺度变化如何以及在什么样的时间尺度上影响海洋中尺度湍流的性质?因此,拟议的工作有可能改变气候界对中尺度湍流的看法。由于大多数海洋气候模式过于粗糙,无法解决中尺度问题,中尺度湍流的影响被参数化。因此,中尺度湍流被简化为一个需要调整的“参数”,而不是地球系统中出现的动态部分。该项目旨在加深对调节中尺度湍流特性的过程以及这些特性对气候变化作出反应的时间尺度的基本物理认识。对这种双向互动的考虑将导致对海洋在气候系统中的作用有更深入的了解,为气候反馈的新机制打开大门。该项目还将推动海洋学大数据计算工具的方法学进步。课程开发将满足学生发展强大的计算技能的需求,特别是处理大数据的能力,以应对21世纪世纪科学的新兴挑战。它还将促进在海洋学课堂上积极学习和使用数据。教材的开放源码性质将鼓励广泛采用。研究和教育之间的强互动是有保证的,因为研究中使用的相同工具将被纳入课程,两者在整个项目中一起发展。该CAREER奖的研究部分将使用一系列模式和观测来研究气候变化,斜压不稳定,中尺度涡动特性(动能和长度尺度)和中尺度混合之间的联系。理想化的过程模式将为理解地面风和浮力强迫的变化如何导致中尺度湍流的变化奠定理论基础。还将在卫星和水文观测中研究中尺度统计数据的十年变率和斜压不稳定性。最后,理论框架和统计分析将应用于全球,涡分辨气候模式模拟温室效应。为了便利这项工作,将开发基于Python的快速数据处理计算工具。这些工具将通过开发“大数据海洋学”的开放源码课程纳入教育,在该课程中,研究全球高分辨率数据集所需的计算技能将与核心海洋科学概念同时教授。这些模块将在本科课程中部署和评估,并在网上和教育会议上广泛传播。
项目成果
期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Impacts of ice-shelf melting on water mass transformation in the Southern Ocean from E3SM simulations
E3SM 模拟显示冰架融化对南大洋水团转化的影响
- DOI:10.1175/jcli-d-19-0683.1
- 发表时间:2020
- 期刊:
- 影响因子:4.9
- 作者:Jeong, Hyein;Asay-Davis, Xylar S.;Turner, Adrian K.;Comeau, Darin S.;Price, Stephen F.;Abernathey, Ryan P.;Veneziani, Milena;Petersen, Mark R.;Hoffman, Matthew J.;Mazloff, Matthew R.
- 通讯作者:Mazloff, Matthew R.
Water mass transformation variability in the Weddell Sea in Ocean Reanalyses
海洋再分析中威德尔海的水团转化变化
- DOI:10.5194/egusphere-2022-129
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Bailey, Shanice Tseng;Jones, Spencer;Abernathey, Ryan Patrick;Gordon, Arnold L.;Yuan, Xiaojun
- 通讯作者:Yuan, Xiaojun
Density-compensated overturning in the Labrador Sea
- DOI:10.1038/s41561-019-0517-1
- 发表时间:2020-01
- 期刊:
- 影响因子:18.3
- 作者:Sijia Zou;M. Lozier;Feili Li;R. Abernathey;L. Jackson
- 通讯作者:Sijia Zou;M. Lozier;Feili Li;R. Abernathey;L. Jackson
Drivers of Local Ocean Heat Content Variability in ECCOv4
- DOI:10.1175/jcli-d-20-0058.1
- 发表时间:2020-02
- 期刊:
- 影响因子:4.9
- 作者:Jan‐Erik Tesdal;R. Abernathey
- 通讯作者:Jan‐Erik Tesdal;R. Abernathey
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Ryan Abernathey其他文献
Open Code Policy for NASA Space Science: A Perspective from NASA-Supported Ocean Modeling and Ocean Data Analysis
NASA 空间科学的开放代码政策:NASA 支持的海洋建模和海洋数据分析的视角
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
S. Gille;Ryan Abernathey;T. Chereskin;B. Cornuelle;Patrick Heimbach;M. Mazloff;Cesar B. Rocha;Saulo Soares;Maike Sonnewald;Bia Villas Boas;Jinbo Wang - 通讯作者:
Jinbo Wang
Rapid changes in terrestrial carbon dioxide uptake captured in near-real time from a geostationary satellite: The ALIVE framework
地球静止卫星近实时捕捉到的陆地二氧化碳吸收的快速变化:ALIVE框架
- DOI:
10.1016/j.rse.2025.114759 - 发表时间:
2025-07-01 - 期刊:
- 影响因子:11.400
- 作者:
Danielle Losos;Sadegh Ranjbar;Sophie Hoffman;Ryan Abernathey;Ankur R. Desai;Jason Otkin;Helin Zhang;Youngryel Ryu;Paul C. Stoy - 通讯作者:
Paul C. Stoy
THE PANGEO BIG DATA ECOSYSTEM AND ITS USE AT CNES
PANGEO 大数据生态系统及其在 CNES 的使用
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Guillaume Eynard;Ryan Abernathey;Joseph Hamman;Aurelien Ponte;Willi Rath - 通讯作者:
Willi Rath
Ryan Abernathey的其他文献
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{{ truncateString('Ryan Abernathey', 18)}}的其他基金
EarthCube Data Capabilities: A Cloud-Native Data Repository for the Geoscience Community
EarthCube 数据功能:地球科学社区的云原生数据存储库
- 批准号:
2026932 - 财政年份:2020
- 资助金额:
$ 76.29万 - 项目类别:
Standard Grant
Collaborative Research: Ocean Transport and Eddy Energy
合作研究:海洋运输和涡流能
- 批准号:
1912325 - 财政年份:2019
- 资助金额:
$ 76.29万 - 项目类别:
Standard Grant
Collaborative Research: Framework: Data: Toward Exascale Community Ocean Circulation Modeling
合作研究:框架:数据:迈向百万兆亿级社区海洋环流建模
- 批准号:
1835778 - 财政年份:2018
- 资助金额:
$ 76.29万 - 项目类别:
Standard Grant
Collaborative Proposal: EarthCube Integration: Pangeo: An Open Source Big Data Climate Science Platform
合作提案:EarthCube 集成:Pangeo:开源大数据气候科学平台
- 批准号:
1740648 - 财政年份:2017
- 资助金额:
$ 76.29万 - 项目类别:
Standard Grant
Collaborative Research: The Upper Branch of the Southern Ocean Overturning in the Southern Ocean State Estimate: Water Mass Transformation and the 3-D Residual Circulation
合作研究:南大洋上游支流翻转 南大洋状态估计:水团转化和 3-D 剩余环流
- 批准号:
1357133 - 财政年份:2014
- 资助金额:
$ 76.29万 - 项目类别:
Standard Grant
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