NSFGEO-NERC: Collaborative Research: Using Time-series Field Observations to Constrain an Ocean Iron Model

NSFGEO-NERC：合作研究：利用时间序列现场观测来约束海洋铁模型

• 批准号: 1829777
• 负责人: Kristen Buck
• 金额: $ 33.86万
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1829777&HistoricalAwards=false
• 关键词: NSFGEO; NERC; Collaborative; Research; Using

Iron is an essential nutrient for the growth of phytoplankton in the oceans. As such, iron plays key roles in regulating marine primary production and the cycling of carbon. It is thus important that models of ocean biology and chemistry consider iron, in order to explore past, present and future variations in marine productivity and the role of the ocean in the global carbon cycle. In this joint project involving researchers in the U.S. and the U.K., supported by both NSF and the Natural Environment Research Council (U.K.), field data from the Bermuda Atlantic Time-series Study (BATS) region will be combined with an established, state-of-the-art ocean biogeochemical model. By leveraging the known seasonal-scale physical, chemical and biological changes in the BATS region, the oceanographic context provided by the BATS core data, and an existing model of the regional physical circulation, the proposed study will yield process-related information that is of general applicability to the open ocean. In particular, the proposed research will focus on understanding the atmospheric input, biological uptake, regeneration and scavenging removal of dissolved iron in the oceanic water column, which have emerged as major uncertainties in the ocean iron cycle. The project will include significant educational and training contributions at the K-12, undergraduate, graduate and postdoctoral levels, as well as public outreach efforts that aim to explain the research and its importance.The ability of ocean models to simulate iron remains crude, owing to an insufficient understanding of the mechanisms that drive variability in dissolved iron, particularly the involvement of iron-binding ligands, colloids and particles in the surface input, biological uptake, regeneration and scavenging of dissolved iron in the upper ocean. Basin-scale data produced by the GEOTRACES program provide an important resource for testing and improving models and, by extension, our mechanistic understanding of the ocean iron cycle. However such data provide only quasi-synoptic 'snapshots', which limits their utility in isolating and identifying the processes that control dissolved iron in the upper ocean. The proposed research aims to provide mechanistic insight into these governing processes by combining time-series data from the BATS region with numerical modeling experiments. Specifically, seasonally resolved data on the vertical (upper 2,000 meters) and lateral (tens of kilometers) distributions of particulate, dissolved, colloidal, soluble and ligand-bound iron species will be obtained from the chemical analysis of water column samples collected during five cruises, spanning a full annual cycle, shared with the monthly BATS program cruises. These data, along with ancillary data from the BATS program, will be used to test and inform numerical modeling experiments, and thus derive an improved understanding of the mechanisms that control the distribution and dynamics of dissolved iron in the oceanic water column.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.

铁是海洋中浮游植物生长的必需营养素。因此，铁在调节海洋初级生产和碳循环方面发挥着关键作用。因此，海洋生物学和化学模型必须考虑铁，以便探索海洋生产力过去、现在和未来的变化以及海洋在全球碳循环中的作用。在这个由美国和英国研究人员参与的联合项目中，在 NSF 和自然环境研究委员会（英国）的支持下，来自百慕大大西洋时间序列研究 (BATS) 地区的现场数据将与已建立的国家数据相结合。最先进的海洋生物地球化学模型。通过利用 BATS 区域已知的季节尺度物理、化学和生物变化、BATS 核心数据提供的海洋学背景以及现有的区域物理环流模型，拟议的研究将产生与过程相关的信息，这些信息普遍适用于公海。特别是，拟议的研究将侧重于了解海洋水体中溶解铁的大气输入、生物吸收、再生和清除去除，这些已成为海洋铁循环中的主要不确定因素。该项目将包括对 K-12、本科生、研究生和博士后级别的重大教育和培训贡献，以及旨在解释该研究及其重要性的公共宣传工作。海洋模型模拟铁的能力仍然很粗糙，因为对驱动溶解铁变化的机制了解不足，特别是对上层海洋中溶解铁的表面输入、生物吸收、再生和清除中铁结合配体、胶体和颗粒的参与。 GEOTRACES 计划产生的流域规模数据为测试和改进模型提供了重要资源，进而为我们对海洋铁循环的机械理解提供了重要资源。然而，此类数据仅提供准天气“快照”，这限制了它们在分离和识别控制上层海洋溶解铁的过程方面的效用。拟议的研究旨在通过将 BATS 区域的时间序列数据与数值建模实验相结合，提供对这些控制过程的机械洞察。具体而言，将对五次航行期间收集的水柱样本进行化学分析，获得颗粒、溶解、胶体、可溶性和配体结合铁物种的垂直（2,000米以上）和横向（数十公里）分布的季节性解析数据，跨越整个年度周期，与每月 BATS 计划巡游共享。这些数据以及 BATS 计划的辅助数据将用于测试数值模拟实验并为其提供信息，从而更好地了解控制海洋水体中溶解铁的分布和动态的机制。该奖项反映了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，NSF 的法定使命被认为值得支持。