US-GLOBEC NEP Phase IIIb-CGOA: Synthesis of Biophysical Observations at Multiple Trophic Levels Using Spatially Nested, Data-assimilating Models of the Coastal Gulf of Alaska

US-GLOBEC NEP 第三阶段 b-CGOA：使用阿拉斯加沿海湾的空间嵌套数据同化模型综合多个营养水平的生物物理观测结果

• 批准号: 0624776
• 负责人: Andrew Moore
• 金额: $ 35.51万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-05-15 至 2010-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0624776&HistoricalAwards=false
• 关键词: US; GLOBEC; NEP; Phase; IIIb

This core retrospective modeling and data assimilation project addresses broad GLOBEC program goals, in addition to the more tightly focused aims of the Northeast Pacific (NEP) GLOBEC program in the Coastal Gulf of Alaska (CGOA). This work aims to elucidate mechanisms that influence the observed production at multiple trophic levels (phytoplankton, zooplankton, and pink salmon) in the CGOA. Specific goals are to: (i) quantify how physical features in the CGOA and variability related to climate change impact zooplankton biomass, production, distribution, and the retention and loss of zooplankton from coastal regions; (ii) quantify the impact of key coastal physical and biological processes, such as freshwater runoff and cross-shelf transport; and (iii) compare the impacts of climate variability and change (such as El Nino-La Nina cycles and regime shifts) on marine animal populations (pink salmon) in the CGOA. The coupled models employ advanced data assimilation techniques to produce optimal merged data/model products, which will be delivered online for use by the GLOBEC NEP-CGOA synthesis effort.End-products include: 1) Synthesis of GLOBEC-CGOA field data through explicit, adjoint based, 3D physical data assimilation into nested circulation models; 2) Application of these improved circulation fields to lower trophic level (NPZ) simulations which include salmon prey items; 3) Development of an adjoint version of the combined circulation-NPZ model, for formal exploration of the sensitivities of derived indices to forcing functions; 4) Production of physical, NPZ, and salmon hindcasts of years with significant interannual climate variability, delivered online for use by other GLOBEC synthesis research programs and models; 5) Production of circulation and prey fields for an Individual-Based Model of pink salmon; 6) Implementation of an Eulerian model of pink salmon with other NPZ components; 7) Assimilation of CGOA biological field data into 1D NPZ models with adjoint techniques; 8) Development of an NPZ model suitable for the Northeast Pacific, to examine spatial patterns of response to climate variability; 9) Visualization of Eulerian and Lagrangian model results with online, interactive, immersive display technologies.The data assimilation and hindcast activities will benefit NOAA's Fisheries and the Environment (FATE) program, which is concerned with effective biophysical indices and other Fisheries Oceanography programs in the CGOA which require accurate circulation and NPZ hindcasts for retrospective studies. The data assimilation and sensitivity issues will contribute to the Alaska Ocean Observing System (AOOS) program. Multiple Ph.D. scientists and students will be trained. Educational outreach will take place via novel visualization techniques to display 3D model results.

除了阿拉斯加沿海湾 (CGOA) 的东北太平洋 (NEP) GLOBEC 计划的更严格目标之外，这一核心回顾性建模和数据同化项目还解决了广泛的 GLOBEC 计划目标。这项工作旨在阐明影响 CGOA 多个营养水平（浮游植物、浮游动物和粉红鲑鱼）观察到的产量的机制。具体目标是： (i) 量化 CGOA 的物理特征和与气候变化相关的变异性如何影响沿海地区浮游动物的生物量、生产、分布以及浮游动物的保留和损失； (ii) 量化主要沿海物理和生物过程的影响，例如淡水径流和跨大陆架运输； (iii) 比较气候变率和变化（如厄尔尼诺-拉尼娜周期和气候变化）对 CGOA 海洋动物种群（粉红鲑鱼）的影响。耦合模型采用先进的数据同化技术来生成最佳的合并数据/模型产品，这些产品将在线交付以供 GLOBEC NEP-CGOA 综合工作使用。最终产品包括： 1) 通过显式、基于伴随的 3D 物理数据同化到嵌套循环模型中； 2) 将这些改进的循环场应用于包括鲑鱼猎物在内的低营养级 (NPZ) 模拟； 3）开发联合循环-NPZ模型的伴随版本，用于正式探索派生指数对强迫函数的敏感性； 4) 产生具有显着年际气候变化的年份的物理、NPZ 和鲑鱼后报，在线提供以供其他 GLOBEC 综合研究计划和模型使用； 5）粉红鲑鱼个体模型的流通和猎物场的制作； 6) 与其他 NPZ 组件一起实施粉红鲑鱼的欧拉模型； 7）利用伴随技术将CGOA生物现场数据同化为一维NPZ模型； 8) 开发适用于东北太平洋的 NPZ 模型，以研究对气候变化响应的空间模式； 9) 通过在线、交互式、沉浸式显示技术实现欧拉和拉格朗日模型结果的可视化。数据同化和事后报告活动将有利于 NOAA 的渔业和环境 (FATE) 计划，该计划涉及有效的生物物理指数和其他渔业海洋学计划CGOA 需要准确的循环和 NPZ 后报来进行回顾性研究。资料同化和敏感性问题将有助于阿拉斯加海洋观测系统（AOOS）计划。多个博士学位科学家和学生将接受培训。教育推广将通过新颖的可视化技术来显示 3D 模型结果。