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 Phase IIIb-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级的生物物理观测结果

• 批准号: 0606575
• 负责人: Emanuele Di Lorenzo
• 金额: $ 18.67万
• 依托单位: Georgia Tech Research Corporation
• 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: 2006-04-15 至 2010-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0606575&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.

这个核心的回顾性建模和数据同化项目解决了广泛的GLOBEC计划目标，除了东北太平洋（NEP）阿拉斯加沿海海湾（CGOA）的GLOBEC计划的更紧密的重点目标。这项工作的目的是阐明机制，影响所观察到的生产在多个营养级（浮游植物，浮游动物，和粉红鲑鱼）在CGOA。具体目标是：（i）量化CGOA中的物理特征和与气候变化有关的可变性如何影响浮游动物生物量、生产、分布以及沿海地区浮游动物的保留和损失;（ii）量化关键的沿海物理和生物过程的影响，如淡水径流和跨大陆架迁移;（iii）比较气候变率和变化（如厄尔尼诺-拉尼娜周期和状态转换）对CGOA海洋动物种群（粉红鲑鱼）的影响。耦合模式采用先进的资料同化技术产生最佳的合并资料/模式产品，这些产品将在线提供给GLOBECNEP-CGOA合成工作使用，最终产品包括：1）通过显式的、基于伴随的三维物理资料同化将GLOBEC-CGOA场资料合成为嵌套环流模式; 2）将这些改进的环流场应用于包括鲑鱼猎物项目的低营养级（NPZ）模拟; 3）发展一个伴随的环流-NPZ组合模式，正式探讨导出的指数对强迫函数的敏感性; 4）生产的物理，NPZ，和鲑鱼年的显着年际气候变率的后报，提供在线使用的其他GLOBEC综合研究计划和模式; 5）生产的流通和猎物领域的个人为基础的模式粉红鲑鱼; 6）实施欧拉模式的粉红鲑鱼与其他NPZ组件; 7）利用伴随技术将CGOA生物场资料同化到一维NPZ模式中：8）发展一个适合于东北太平洋的NPZ模式，以检验对气候变率响应的空间格局; 9）欧拉和拉格朗日模型结果的可视化，沉浸式显示技术。数据同化和后报活动将有利于NOAA的渔业和环境（FATE）计划，该项目涉及有效的生物物理指标和CGOA的其他渔业海洋学项目，这些项目需要准确的环流和NPZ后报进行回顾性研究。数据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。教育推广将通过新的可视化技术来显示3D模型结果。