CMG Collaborative Research: Structures of Uncertainty in Coupled Phys-Bio-Biological EstimStructures of Uncertainty in Coupled Physical-Biological Estimation in the Coastal Ocean

CMG 合作研究：物理-生物-生物耦合估计中的不确定性结构沿海海洋耦合物理-生物估计中的不确定性结构

• 批准号: 0417769
• 负责人: Daniel Lynch
• 金额: $ 55.16万
• 依托单位: Dartmouth College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0417769&HistoricalAwards=false
• 关键词: CMG; Collaborative; Research; Structures; Uncertainty

AbstractThis investigation addresses phenomena in the Coastal Ocean that present a directed structure of causation and inference. It will focus on the interface between biological and physical phenomena, where the causal structure is one-way, physics affecting biology via advection, temperature, salt, light, and turbulence. The transfer of physical uncertainty toward biological phenomena is of primary concern. Rigorous representations of that transfer, and its implications for state and parameter estimation, will be developed. Examples will be drawn from contemporary experience with observational programs and simulations. Due to their huge complexity, these site-specific, coupled problems favor careful problem formulation which is compatible with concurrent oceanographic measurement programs. Both Eulerian and Lagrangian (Individual-Based) models will be used, operating in spatially-explicit environments. Essential nonlinearities will be accommodated with ensemble (Monte Carlo) methods in algorithm design; and with maximum likelihood estimation where simpler least-squares approaches are not justified. General problems of Environmental and Natural Resource Management are now being appreciated globally, and particularly in the coastal ocean. Access to transportation, oil and gas, marine fisheries, recreation, and waste disposal are increasingly dominant there; and the USA has created numerous public management requirements for those resources and activities. This work addresses contemporary US coastal ocean problems that are multi-disciplinary in nature. The proposed collaboration unites expertise in Probability and Statistics, Ocean Science, and Computational Science. The problems selected are at the forefront of the interfaces among these disciplines. As presented in the ocean, these problems are big and complex. Progress at their interface is needed in which workable computational algorithms, sound mathematical formulations, and useful scientific reduction collaborate in intellectually lasting ways. The PI's have standing in their disciplines and at their interfaces. Progress of relevance to major ongoing coastal management programs will be balanced across the collaborating disciplines and focused on the interdisciplinary Coastal Ocean.

摘要本研究探讨了沿海海洋中呈现出因果关系和推理关系的直接结构的现象。它将关注生物和物理现象之间的界面，其中因果结构是单向的，物理通过平流、温度、盐、光和湍流影响生物。物理不确定性向生物现象的转移是主要关注的问题。将开发这种转移的严格表示及其对状态和参数估计的含义。范例将取自当代观测程序和模拟的经验。由于它们的巨大复杂性，这些特定地点的耦合问题需要仔细的问题制定，以便与并行的海洋测量程序兼容。欧拉和拉格朗日（基于个体）模型都将被使用，在空间明确的环境中运行。在算法设计中，必要的非线性将被集成（蒙特卡罗）方法所容纳；在最大似然估计中，更简单的最小二乘方法是不合理的。环境和自然资源管理的一般问题现在正在全球范围内得到重视，特别是在沿海海域。交通、石油和天然气、海洋渔业、娱乐和废物处理在那里日益占主导地位；美国为这些资源和活动制定了许多公共管理要求。这项工作解决了当代美国沿海海洋问题，本质上是多学科的。拟议的合作联合了概率与统计、海洋科学和计算科学方面的专业知识。所选择的问题是在这些学科之间的接口的前沿。在海洋中，这些问题既大又复杂。需要在它们的界面上取得进展，使可行的计算算法、合理的数学公式和有用的科学还原以智力持久的方式合作。PI在他们的学科和界面上都有地位。与正在进行的主要沿海管理计划相关的进展将在合作学科之间进行平衡，并集中在跨学科的沿海海洋。