课题基金 / 基金详情

Improving estimates of ocean productivity and carbon sequestration through a combination of autonomous observation- and model-based approaches

Improving estimates of ocean productivity and carbon sequestration through a combination of autonomous observation- and model-based approaches
通过结合自主观测和基于模型的方法改进对海洋生产力和碳封存的估计
批准号:
RGPIN-2022-02975
负责人:
Fennel, Katja
金额:
$4.44万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

项目摘要

项目成果

Fennel, Katja的其他基金

相似基金

相关文献

中文摘要
翻译
海洋正在迅速变暖并变得更加分层,这抑制了在海面上维持光合作用初级生产所必需的溶解营养物质的垂直交换。初级生产支持海洋食物网,并在调节地球气候方面发挥重要作用,作为海洋内部封存二氧化碳的途径。准确量化海洋初级生产和碳固存及其对气候变暖的响应是一项紧迫的科学挑战,但受到生物地球化学观测相对稀少的阻碍。科考船的测量虽然可以进行最广泛的直接测量,但由于成本和工作量的限制,只能进行几个点的测量。卫星可以提供高空间分辨率的天气性全球覆盖,但观测到的唯一生物地球化学性质是表面叶绿素。由此产生的差距阻碍了我们充分认识海洋生物地球化学变化、了解潜在过程以及测试和改进模型的能力。最近自主平台和小型化生物地球化学传感器的成熟为克服长期存在的海洋生物地球化学采样不足提供了机会,使我们能够通过卫星和船舶等传统观测手段来观察变化。自主平台允许以经济有效的方式在全球范围内以三维空间收集许多重要的海洋生物地球化学特性的高分辨率,无偏和持续测量。利用快速扩展的自主海洋观测网络,特别是生物地球化学(BGC) Argo计划,本研究计划的目标是:1)开发和应用新的方法来估计自主观测的海洋生产力和碳输出;2)使用新出现的数据严格测试和完善海洋生物地球化学模型,以提高模型能力;3)开发和应用统计方法,将自主生物地球化学观测与模型相结合,以获得对海洋状态变化的最佳估计。对拟议的估算海洋生产力和碳输出方法的成功演示,将从根本上改变观察这些过程的国际努力,将加强将带有BGC传感器的自主平台持续纳入全球海洋观测系统的案例,并将为未来几十年探测气候引起的变化奠定基础。对生物地球化学模型进行严格和系统的评估将减少全球气候预测的不确定性。提供约束良好的数据同化模型产品将直接使北大西洋西北地区的各种利益相关者受益。所有这些成果对于合理缓解气候变化影响和实现净零碳的有效步骤都是非常宝贵的。
英文摘要
The ocean is rapidly warming and becoming more stratified, which inhibits the vertical exchange of dissolved nutrients essential for maintaining photosynthetic primary production at the sea surface. Primary production supports the marine food web and plays a major role in regulating Earth's climate as a pathway for sequestering CO2 in the ocean's interior. Accurate quantification of ocean primary production and carbon sequestration, and their response to a warming climate are urgent scientific challenges but are hindered by the relative sparsity of biogeochemical observations. Measurements from research ships, while allowing for the broadest suite of direct measurements, are limited to a few point measurements due to the cost and effort required. Satellites can provide synoptic global coverage at high spatial resolution, but the only biogeochemical property observed is surface chlorophyll. The resulting gaps are hampering our ability to fully recognize changes in ocean biogeochemistry, to understand the underlying processes, and to test and improve models. The recent maturation of autonomous platforms and miniaturized biogeochemical sensors provides an opportunity to overcome the long-standing biogeochemical undersampling of the ocean, enabling us to observe changes by complementing traditional means of observation via satellites and ships. Autonomous platforms allow collection of highly resolved, unbiased, and sustained measurements of many essential biogeochemical ocean properties on the global scale in 3-dimensional space and in a cost-effective manner. Taking advantage of rapidly expanding autonomous ocean observation networks, in particular the biogeochemical (BGC) Argo program, the objectives of this research program are to 1) develop and apply new approaches for estimating ocean productivity and carbon export from autonomous observations, 2) rigorously test and refine ocean biogeochemical models using the newly emerging data to improve model capabilities, and 3) develop and apply statistical methods for blending autonomous biogeochemical observations and models to obtain the best possible estimates of the changing ocean state. A successful demonstration of the proposed approaches for estimating ocean productivity and carbon export will fundamentally transform international efforts to observe these processes, will strengthen the case for a sustained inclusion of autonomous platforms with BGC sensors in the global ocean observing system, and will lay the groundwork for enabling detection of climate-induced changes in the coming decades. A rigorous and systematic assessment of biogeochemical models will reduce uncertainties in global climate projections. Provision of well-constrained data-assimilative model products will directly benefit a variety of stakeholders in the northwest North Atlantic region. All of these outcomes are invaluable for sound mitigation of climate change impacts and effective steps toward net-zero carbon.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Marine environmental prediction through improved biogeochemical models
  • 批准号:
    RGPIN-2014-03938
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.44万
  • 财政年份:
    2021
  • 负责人:
    Fennel, Katja
  • 依托单位:
Assessment and Verification Tools for Ocean-based Carbon Dioxide Removal (CDR)
  • 批准号:
    570525-2021
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $21.1万
  • 财政年份:
    2021
  • 负责人:
    Fennel, Katja
  • 依托单位:
Marine environmental prediction through improved biogeochemical models
  • 批准号:
    RGPIN-2014-03938
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.44万
  • 财政年份:
    2020
  • 负责人:
    Fennel, Katja
  • 依托单位:
Marine environmental prediction through improved biogeochemical models
  • 批准号:
    RGPIN-2014-03938
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.44万
  • 财政年份:
    2017
  • 负责人:
    Fennel, Katja
  • 依托单位:
海外基金