AccelNet-Implementation: Implementing a Deep Ocean Observing Strategy (iDOOS)
AccelNet-Implementation:实施深海观测策略 (iDOOS)
基本信息
- 批准号:2114717
- 负责人:
- 金额:$ 199.29万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-10-01 至 2025-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The deep ocean below 200 m is poorly known. This dynamic realm is a vast repository for biodiversity, provides critical climate regulation, and houses a wealth of hydrocarbon, mineral, and genetic resources. Observing the deep ocean at a level required to inform sustainable development and management faces significant technical and logistical challenges. To address these challenges, the iDOOS project will implement a Deep-Ocean Observing Strategy (DOOS) that brings together U.S. and international networks engaged in sustained deep-ocean observing, mapping, exploration, modeling, research, and management to leverage each other’s efforts, knowledge, and resources. This implementation project will boost the DOOS community-driven initiative, working under the umbrella of the Global Ocean Observing System (GOOS) and endorsed as a United Nations Ocean Decade Action. By connecting deep-ocean observers across disciplines, expanding the observing community to include non-traditional partners, and linking data providers to users, iDOOS will enhance the GOOS deep-ocean capabilities and target societal needs. Through engagement with policy makers, regulators, and science coordinators, iDOOS will raise awareness and support for deep-ocean science, and bring science into critical decisions regarding climate, biodiversity and sustainability. iDOOS will foster a community of future leaders informed in deep-ocean observing, modeling, and data science at a global level who are adept at communicating to regulators and policy makers as well as fellow scientists.iDOOS addresses three main themes: (1) requirement setting for deep ocean observing; (2) promoting the coordination and implementation of integrated observing to address Sustainable Development Goals and societal needs; and (3) translating knowledge and data to allow science-based decision-making, regulation and governance of the global deep ocean. These themes will be integrated and applied via the framework of regional demonstration projects. iDOOS will work with the GOOS disciplinary expert panels to refine Essential Ocean Variables in terms of deep ocean requirements, and with network partners to maximize their implementation and use. In addition, the project has two cross-cutting activities. A focus on data/informatics will contribute best practices and standards to the requirement-setting theme, support activities across the working groups, and offer tailored training to early-career researchers. The project aims to enable findable, accessible, interoperable, and reusable (FAIR) deep-sea data and a data-enabled, deep-sea workforce. A key element of iDOOS is the mentorship and training of the next generation. iDOOS will assemble a network of Deep Ocean Early career Researchers (DOERs) drawing from collaborating networks, the broader deep-ocean observing community, as well as from developing countries and indigenous communities. Through the theme working groups, the project will conduct training activities and meetings to substantially improve justice, equity, diversity, inclusion, and belonging among the participating networks and more broadly within deep-ocean science.The Accelerating Research through International Network-to-Network Collaborations (AccelNet) program is designed to accelerate the process of scientific discovery and prepare the next generation of U.S. researchers for multiteam international collaborations. The AccelNet program supports strategic linkages among U.S. research networks and complementary networks abroad that will leverage research and educational resources to tackle grand scientific challenges that require significant coordinated international efforts.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.
200米以下的深海鲜为人知。 这个动态的领域是生物多样性的巨大宝库,提供关键的气候调节,并拥有丰富的碳氢化合物,矿物和遗传资源。 在为可持续发展和管理提供信息所需的水平上观测深海面临着重大的技术和后勤挑战。 为了应对这些挑战,iDOOS项目将实施一项深海观测战略(DOOS),将美国和国际上从事持续深海观测、测绘、勘探、建模、研究和管理的网络聚集在一起,以利用彼此的努力、知识和资源。 这一实施项目将推动海洋观测系统社区驱动的倡议,在全球海洋观测系统(海观系统)的保护伞下开展工作,并被批准为联合国海洋十年行动。 通过将各学科的深海观测者联系起来,扩大观测界以包括非传统伙伴,并将数据提供者与用户联系起来,iDOOS将加强全球海洋观测系统的深海能力,并满足社会需求。 通过与决策者、监管机构和科学协调员的合作,iDOOS将提高对深海科学的认识和支持,并将科学纳入有关气候、生物多样性和可持续性的关键决策。 iDOOS将在全球范围内培养一批精通深海观测、建模和数据科学的未来领导者,他们善于与监管机构和政策制定者以及其他科学家进行沟通。iDOOS涉及三个主题:(1)制定深海观测要求;(2)促进综合观测的协调和实施,以满足可持续发展目标和社会需求;(3)促进全球海洋观测的发展。以及(3)转化知识和数据,以便对全球深海进行科学决策、监管和治理。 这些主题将通过区域示范项目的框架加以整合和应用。 iDOOS将与全球海洋观测系统学科专家小组合作,根据深海要求完善基本海洋变量,并与网络伙伴合作,最大限度地实施和使用这些变量。 此外,该项目还有两项贯穿各领域的活动。 对数据/信息学的关注将为需求设定主题提供最佳实践和标准,支持各工作组的活动,并为早期职业研究人员提供量身定制的培训。 该项目旨在实现可查找、可访问、可互操作和可重复使用(FAIR)的深海数据和数据支持的深海劳动力。 iDOOS的一个关键要素是指导和培训下一代。 iDOOS将从合作网络、更广泛的深海观测界以及发展中国家和土著社区汇集一个深海早期职业研究人员网络。 通过专题工作组,该项目将开展培训活动和会议,以大幅改善正义、公平、多样性、包容性,通过国际网络间合作加速研究该计划旨在加速科学发现的进程,并为下一代美国研究人员进行多团队国际合作做好准备。该奖项反映了NSF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。
项目成果
期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Designing, generating, and translating deep-ocean observations for and with international policy makers
为国际政策制定者并与国际政策制定者一起设计、生成和翻译深海观测结果
- DOI:10.1093/icesjms/fsac143
- 发表时间:2022
- 期刊:
- 影响因子:3.3
- 作者:Levin, Lisa A.;Cimoli, Laura;Gjerde, Kristina;Harden-Davies, Harriet;Heimbach, Patrick;LaScala-Gruenewald, Diana;Pachiadaki, Maria;Pillar, Helen R.;Smith, Leslie M.;Stocks, Karen
- 通讯作者:Stocks, Karen
Deep sea nature-based solutions to climate change
- DOI:10.3389/fclim.2023.1169665
- 发表时间:2023-07
- 期刊:
- 影响因子:0
- 作者:Nathalie Hilmi;M. Sutherland;S. Farahmand;G. Haraldsson;Erik van Doorn;Ekkehard Ernst;M. Wisz;Astrid Claudel Rusin;Laura G. Elsler;L. Levin
- 通讯作者:Nathalie Hilmi;M. Sutherland;S. Farahmand;G. Haraldsson;Erik van Doorn;Ekkehard Ernst;M. Wisz;Astrid Claudel Rusin;Laura G. Elsler;L. Levin
SMART Cables Observing the Oceans and Earth
观测海洋和地球的智能电缆
- DOI:10.4031/mtsj.56.5.3
- 发表时间:2022
- 期刊:
- 影响因子:0.8
- 作者:Rowe, Charlotte A.;Howe, Bruce M.;Fouch, Matthew J.;Angove, Michael;Aucan, Jerome;Barnes, Christopher R.;Bayliff, Nigel;Becker, Nathan C.;Carrilho, Fernando;Fry, Bill
- 通讯作者:Fry, Bill
The Deep Ocean Observing Strategy: Addressing Global Challenges in the Deep Sea Through Collaboration
深海观测战略:通过合作应对深海全球挑战
- DOI:10.4031/mtsj.56.3.11
- 发表时间:2022
- 期刊:
- 影响因子:0.8
- 作者:Smith, Leslie M.;Cimoli, Laura;LaScala-Gruenewald, Diana;Pachiadaki, Maria;Phillips, Brennan;Pillar, Helen;Stopa, Justin E.;Baumann-Pickering, Simone;Beaulieu, Stace E.;Bell, Katherine L.C.
- 通讯作者:Bell, Katherine L.C.
Integrating Multidisciplinary Observations in Vent Environments (IMOVE): Decadal Progress in Deep-Sea Observatories at Hydrothermal Vents
- DOI:10.3389/fmars.2022.866422
- 发表时间:2022-05
- 期刊:
- 影响因子:0
- 作者:M. Matabos;T. Barreyre;S. Juniper;M. Cannat;D. Kelley;Joan M. Alfaro-Lucas;V. Chavagnac;A. Colaço;J. Escartín;E. Escobar;D. Fornari;J. Hasenclever;J. Huber;A. Laës-Huon;N. Lantéri;L. Levin;S. Mihaly;E. Mittelstaedt;F. Pradillon;P. Sarradin;J. Sarrazin;B. Tomasi;R. Venkatesan;C. Vic
- 通讯作者:M. Matabos;T. Barreyre;S. Juniper;M. Cannat;D. Kelley;Joan M. Alfaro-Lucas;V. Chavagnac;A. Colaço;J. Escartín;E. Escobar;D. Fornari;J. Hasenclever;J. Huber;A. Laës-Huon;N. Lantéri;L. Levin;S. Mihaly;E. Mittelstaedt;F. Pradillon;P. Sarradin;J. Sarrazin;B. Tomasi;R. Venkatesan;C. Vic
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Patrick Heimbach其他文献
MITgcm-AD v2: Open source tangent linear and adjoint modeling framework for the oceans and atmosphere enabled by the Automatic Differentiation tool Tapenade
- DOI:
10.1016/j.future.2024.107512 - 发表时间:
2025-02-01 - 期刊:
- 影响因子:
- 作者:
Shreyas Sunil Gaikwad;Sri Hari Krishna Narayanan;Laurent Hascoët;Jean-Michel Campin;Helen Pillar;An Nguyen;Jan Hückelheim;Paul Hovland;Patrick Heimbach - 通讯作者:
Patrick Heimbach
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
North Atlantic warming and the retreat of Greenland's outlet glaciers
北大西洋变暖与格陵兰岛出口冰川的消退
- DOI:
10.1038/nature12854 - 发表时间:
2013-12-04 - 期刊:
- 影响因子:48.500
- 作者:
Fiammetta Straneo;Patrick Heimbach - 通讯作者:
Patrick Heimbach
Patrick Heimbach的其他文献
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{{ truncateString('Patrick Heimbach', 18)}}的其他基金
Collaborative Research: Frameworks: Convergence of Bayesian inverse methods and scientific machine learning in Earth system models through universal differentiable programming
协作研究:框架:通过通用可微编程将贝叶斯逆方法和科学机器学习在地球系统模型中融合
- 批准号:
2103942 - 财政年份:2021
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
NSFGEO-NERC: Collaborative Research: Subpolar North Atlantic Processes - Dynamics and pRedictability of vAriability in Gyre and OverturNing (SNAP-DRAGON)
NSFGEO-NERC:合作研究:北大西洋次极过程 - 环流和翻转变化的动力学和可预测性 (SNAP-DRAGON)
- 批准号:
2038422 - 财政年份:2020
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
Collaborative Research: Leveraging the AMOC arrays and models to understand heat and freshwater transports in the North Atlantic
合作研究:利用 AMOC 阵列和模型了解北大西洋的热量和淡水输送
- 批准号:
1924546 - 财政年份:2019
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
Paleochronometry as a control problem for recovering holocene climate variations over the Greenland Ice Sheet
古年代学作为恢复格陵兰冰盖全新世气候变化的控制问题
- 批准号:
1903596 - 财政年份:2019
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
Collaborative Research: From Adjoints for the Few to Adjoints for the Many: Integrating the Use of Adjoint Methods in Earth System Modeling
协作研究:从少数人的伴随到多人的伴随:在地球系统建模中整合伴随方法的使用
- 批准号:
1751120 - 财政年份:2017
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
Collaborative Research: Submarine Melting and Freshwater Export in Greenland's Glacial Fjords: The Role of Subglacial Discharge, Fjord Topography and Shelf Properties
合作研究:格陵兰岛冰川峡湾的海底融化和淡水输出:冰下排放、峡湾地形和陆架特性的作用
- 批准号:
1737759 - 财政年份:2017
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
Collaborative Research: Understanding the controls on spatial and temporal variability in ice discharge using a Greenland-wide ice sheet model
合作研究:使用格陵兰冰盖模型了解冰排放时空变化的控制
- 批准号:
1603854 - 财政年份:2016
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
Collaborative Research: A Bering Strait Ocean Observing System for the Pacific Inflow to the Arctic - a fundamental part of the Arctic Observing Network
合作研究:白令海峡太平洋流入北极海洋观测系统——北极观测网络的基本组成部分
- 批准号:
1640357 - 财政年份:2016
- 资助金额:
$ 199.29万 - 项目类别:
Continuing Grant
Collaborative Research: Submarine Melting of Greenland's Glaciers: What are the relevant ocean dynamics?
合作研究:格陵兰岛冰川海底融化:相关的海洋动力学是什么?
- 批准号:
1550290 - 财政年份:2015
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
Collaborative Research: Submarine Melting and Freshwater Export in Greenland's Glacial Fjords: The Role of Subglacial Discharge, Fjord Topography and Shelf Properties
合作研究:格陵兰岛冰川峡湾的海底融化和淡水输出:冰下排放、峡湾地形和陆架特性的作用
- 批准号:
1434149 - 财政年份:2014
- 资助金额:
$ 199.29万 - 项目类别:
Standard Grant
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