CAREER: A change in the forecast: Ocean biogeochemistry over the next decade

职业：预测的变化：未来十年的海洋生物地球化学

• 批准号: 1752724
• 负责人: Nicole Lovenduski
• 金额: $ 79.99万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1752724&HistoricalAwards=false
• 关键词: CAREER; change; forecast; Ocean; biogeochemistry

The pressing need for societally-relevant information about the physical climate system in the near future (the coming years to decades) has generated extensive research in the field of decadal climate prediction. Recent work highlights the ability of climate models to predict such things as regional surface air temperature, precipitation, Arctic sea ice extent, and ocean heat content with several years lead time; such predictions are of great use to those who manage infrastructure and resources. The use of models for predictions of regional changes in ocean chemistry and biology on these timescales is much less common but could also be very useful to managers, policy makers, and the scientific enterprise. In this CAREER award, the investigator will use a model to make regional predictions of changes in ocean chemistry and biology on one- to ten-year timescales; these predictions will be tested against real-world observations to assess and understand the skill of the predictions. The major educational goal of this project is to prepare undergraduate students from underrepresented groups for graduate study in the field of oceanography. This will be achieved by partnering with the Summer Multicultural Access to Research Training (SMART) program to provide five undergraduate students with transformative learning and mentoring experiences that will expand their pathways to competitive graduate programs. The SMART program has well-established recruiting strategies and assessment protocols and has achieved tremendous success in reducing the disparities between majority and minority PhD recipients in STEM fields. It is anticipated that this project will give rise to increased numbers of underrepresented students achieving doctoral degrees in chemical and physical oceanography. The PI is strongly committed to moving diverse undergraduate STEM students forward into graduate programs by providing genuine research experiences and mentorship to these students and has a history of successful student placement into graduate programs. The project leader is strongly committed to moving diverse undergraduate STEM students forward into graduate programs by providing genuine research experiences and mentorship to these students and has a history of successful student placement into graduate programs. The project will also support the education and training of a graduate student and postdoctoral researcher. The project team proposes to analyze ocean biogeochemistry predictions using output from an Earth System Model with fully resolved ocean biogeochemistry and observations from satellite, hydrographic, and autonomous platforms. From annual to decadal timescales, the team will quantify predictability and predictive skill in key ocean biogeochemical parameters, including surface ocean pH, partial pressure and air-sea flux of carbon dioxide, and upper-ocean aragonite saturation state, net primary production, and oxygen concentration. The model-based predictability study will probe the limits of skillful ocean biogeochemical prediction and investigate the mechanisms involved. Detailed analysis of sustained ocean biogeochemical events in the recent past will inform understanding of their predictability in the coming decade.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.

在不久的将来（接下来的几十年）对与社会气候系统相关的社会相关信息的迫切需求已在际气候预测的领域进行了广泛的研究。最近的工作突出了气候模型预测区域表面空气温度，降水，北极海冰范围和海洋热含量等事物的能力。这样的预测对管理基础架构和资源的人有很大的帮助。使用模型预测这些时间尺度上海洋化学和生物学的区域变化的预测要少得多，但对于经理，政策制定者和科学企业来说也可能非常有用。在本职业奖中，研究人员将使用模型来对一到十年时间尺度的海洋化学和生物学变化进行区域预测；这些预测将针对现实世界的观察结果进行测试，以评估和理解预测的技能。该项目的主要教育目标是为来自代表性不足的小组的本科生做好准备，以在海洋学领域进行研究生学习。这将通过与夏季多元文化访问研究培训（SMART）计划合作，为五个本科生提供变革性的学习和指导经验，以将其途径扩展到竞争激烈的研究生课程。 SMART计划具有良好的招聘策略和评估协议，并在减少STEM领域中多数和少数博士学位接受者之间的差异方面取得了巨大的成功。预计该项目将导致越来越多的代表性的学生获得化学和物理海洋学博士学位。 PI强烈致力于通过为这些学生提供真正的研究经验和指导，并在研究生课程中获得成功的历史，将多样化的本科STEM学生转向研究生课程。该项目负责人强烈致力于通过为这些学生提供真正的研究经验和指导，并在研究生课程中获得成功的历史，从而将多样化的本科STEM学生转向研究生课程。该项目还将支持研究生和博士后研究员的教育和培训。该项目团队建议使用具有完全分辨的海洋生物地球化学和卫星，水文和自治平台的观察结果的地球系统模型的输出来分析海洋生物地球化学预测。从年度到十年的时间尺度，团队将量化关键海洋生物地球化学参数的可预测性和预测能力，包括二氧化碳碳含量的表面海洋pH，部分压力和空气通量，以及上海后饱和状态，净初级产生和氧气浓度。基于模型的可预测性研究将探测熟练的海洋生物地球化学预测的限制，并研究所涉及的机制。最近对持续海洋地球化学事件的详细分析将为您在未来十年的可预测性中提供理解。该奖项反映了NSF的法定任务，并且使用基金会的智力优点和更广泛的影响评估标准，认为值得通过评估来获得支持。

项目成果

Observational Needs Supporting Marine Ecosystems Modeling and Forecasting: From the Global Ocean to Regional and Coastal Systems

• DOI: 10.3389/fmars.2019.00623
• 发表时间: 2019-10-15
• 期刊: FRONTIERS IN MARINE SCIENCE
• 影响因子: 3.7
• 作者: Capotondi, Antonietta;Jacox, Michael;Pesant, Stephane
• 通讯作者: Pesant, Stephane

Predicting near-term variability in ocean carbon uptake

预测海洋碳吸收的近期变化

• DOI: 10.5194/esd-10-45-2019
• 发表时间: 2019
• 期刊: Earth System Dynamics
• 影响因子: 7.3
• 作者: Lovenduski, Nicole S.;Yeager, Stephen G.;Lindsay, Keith;Long, Matthew C.
• 通讯作者: Long, Matthew C.

Alternate History: A Synthetic Ensemble of Ocean Chlorophyll Concentrations

架空历史：海洋叶绿素浓度的合成整体

• DOI: 10.1029/2020gb006924
• 发表时间: 2021
• 期刊: Global Biogeochemical Cycles
• 影响因子: 5.2
• 作者: Elsworth, Geneviève W.;Lovenduski, Nicole S.;McKinnon, Karen A.
• 通讯作者: McKinnon, Karen A.

Initialized Earth System prediction from subseasonal to decadal timescales

• DOI: 10.1038/s43017-021-00155-x
• 发表时间: 2021-04
• 期刊: Nature Reviews Earth & Environment
• 影响因子: 42.1
• 作者: G. Meehl;J. Richter;H. Teng;A. Capotondi;K. Cobb;F. Doblas-Reyes;M. Donat;M. England;J. Fyfe

High predictability of terrestrial carbon fluxes from an initialized decadal prediction system

初始化的十年预测系统对陆地碳通量的高预测性

• DOI: 10.1088/1748-9326/ab5c55
• 发表时间: 2019
• 期刊: Environmental Research Letters
• 影响因子: 6.7
• 作者: Lovenduski, Nicole S.;Bonan, Gordon B.;Yeager, Stephen G.;Lindsay, Keith;Lombardozzi, Danica L.
• 通讯作者: Lombardozzi, Danica L.