MSPA-CSE: Novel A Posteriori Analysis of Ecological Models: The Carbon Cycle

MSPA-CSE：生态模型的新颖后验分析：碳循环

• 批准号: 0434354
• 负责人: Donald Estep
• 金额: --
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard 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=0434354&HistoricalAwards=false
• 关键词: MSPA; CSE; Novel; Posteriori; Analysis

Many ecological models, such as the Integrated Regional Carbon Cycle Model describing the cycling of mass and energy and exchange of materials at the earth's surface, are characterized by complex, nonlinear interactions between different physical sub-systems acting on a vast range of scales. The investigators will develop and apply new tools for quantifying and controlling the effects of the uncertainty in a differential equation model, such as those that arise from experimental measurement, and for fitting such models to physical measurements. The new tools will be based on a combination of an a posteriori analysis technique that has been used with wide success in engineering and statistical methodology used for complex data sets. Models of the biosphere are becoming indispensable in the analysis and prediction of large-scale environmental change, including global warming. However, the complexity of modern models demands new approaches for analysis that combine deterministic and statistical mathematics in order to allow the rapid incorporation of new scientific understanding (e.g., new relevant processes) and data sources (e.g. new satellite technologies) and to quantify the effects of uncertainties in the representation of terrestrial systems. The combination of the power of the mathematical and statistical tools being employed in this project and the interdisciplinary mode of collaboration between the investigators yields substantial promise of significant advances on critically important issues in ecological modeling.

许多生态模型，如描述地球表面质量和能量循环以及物质交换的区域碳循环综合模型，其特点是不同物理子系统之间在大范围尺度上的复杂、非线性相互作用。研究人员将开发和应用新的工具来量化和控制微分方程模型中不确定性的影响，例如那些来自实验测量的不确定性，以及将这些模型拟合到物理测量中。新工具将基于后验分析技术的结合，后验分析技术已在工程和用于复杂数据集的统计方法中取得了广泛的成功。在分析和预测包括全球变暖在内的大规模环境变化方面，生物圈模型正变得不可或缺。然而，现代模式的复杂性要求采用新的分析方法，将确定性数学和统计数学结合起来，以便能够迅速结合新的科学认识（例如，新的相关过程）和数据来源（例如，新的卫星技术），并对地面系统表示中的不确定性的影响进行量化。在这个项目中使用的数学和统计工具的力量以及研究人员之间的跨学科合作模式的结合，在生态建模的关键重要问题上产生了重大进展的实质性承诺。