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

铁是海洋浮游植物生长所必需的营养物质。因此，铁在调节海洋初级生产力和碳的循环方面发挥着关键作用。因此，重要的是，海洋生物和化学模型应考虑铁，以便探索海洋生产力的过去、现在和未来的变化以及海洋在全球碳循环中的作用。在这项由美国和英国研究人员参与的联合项目中，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最先进的海洋生物地球化学模型相结合，该项目得到了NSF和自然环境研究理事会(UK)的支持。通过利用BATS区域已知的季节尺度的物理、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式，拟议的研究将产生对公海具有普遍适用性的与过程有关的信息。特别是，拟议的研究将侧重于了解海洋水柱中溶解铁的大气输入、生物吸收、再生和清除清除，这些已成为海洋铁循环中的主要不确定因素。该项目将包括在K-12、本科生、研究生和博士后各级的重大教育和培训贡献，以及旨在解释这项研究及其重要性的公共宣传努力。由于对驱动溶解铁变化的机制，特别是铁结合配体、胶体和颗粒参与表层输入、生物吸收、再生和清除上层海洋中的溶解铁的机制了解不足，海洋模型模拟铁的能力仍然很低。GEOTRACES计划产生的盆地范围的数据为测试和改进模型提供了重要的资源，进而为我们从机制上理解海洋铁循环提供了重要的资源。然而，这些数据只能提供准天气学的“快照”，这限制了它们在分离和识别控制上层海洋中溶解的铁的过程中的作用。这项拟议的研究旨在通过将BATS地区的时间序列数据与数值模拟实验相结合，从机制上深入了解这些控制过程。具体地说，关于颗粒铁、溶解铁、胶体铁、可溶性铁和配体结合铁的垂直(高度2,000米)和横向(数十公里)分布的季节性解析数据将从五个航次收集的水柱样本的化学分析中获得，这些水柱样本跨越一个完整的年度周期，与每月的BATS计划航次共享。这些数据，以及来自BATS计划的辅助数据，将被用来测试和提供数值模拟实验的信息，从而更好地理解控制海洋水柱中溶解铁的分布和动态的机制。

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.