Development of a Data Assimilation Capability Towards Ecological Forecasting in a Data-Rich Era

数据丰富时代生态预测的数据同化能力发展

• 批准号: 0850290
• 负责人: Yiqi Luo
• 金额: $ 107.95万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0850290&HistoricalAwards=false
• 关键词: Development; Data; Assimilation; Capability; Towards

The University of Oklahoma is awarded a grant to develop an Ecological Platform for Assimilation of Data (EcoPAD) for data assimilation and forecasting in ecology. EcoPAD will include components of (1) core computational algorithms (e.g., ecological models) that are specifically designed to solve ecological issues, (2) a variety of optimization techniques for data assimilation, (3) various data bases that will feed into EcoPAD, and (4) diverse functions of EcoPAD. The functions enable users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems (e.g., carbon sinks in USA), (iii) evaluate model structures, (iv) assess sampling strategies, and (v) conduct ecological forecasting. EcoPAD will be developed, tested, and applied at three spatial scales. First, EcoPAD will be developed against plot-level data from experiments in the Duke Forest and Oklahoma prairies to examine its capability of extract information on ecosystem responses to climate change. Second, the project will develop EcoPAD at the AmeriFlux network of eddy-flux measurements in the North America to examine its capability of forecasting diurnal, seasonal, and interannual dynamics of net ecosystem exchange. Third, EcoPAD's capability of forecasting future states of ecosystems and their services will be tested and evaluated at regional and continental scales. EcoPAD has the potential to become a powerful eco-informatics tool that assimilate data from measurement sensor networks and to generate data products that will be useful for policy making on resource management and climate change mitigation. This project will have integrated teaching, training, and learning through student and post-doc training, integrated courses in ecological modeling, and outreach to K-12 students and teachers. NEON and other sensor networks have been designed to provide better ecological service to the society. Data assimilation and ecological forecasting are key components for success of those networks. This project will develop EcoPAD to extract information from massive data for ecological forecasts, which can directly serve the society and be useful for policy making. Results from this project will be useful for education of public on ecosystem services. For further information see the PI's lab website at http://bomi.ou.edu/luo/.

俄克拉荷马州大学获得了一笔赠款，用于开发生态学数据同化和预测的数据同化生态平台（EcoPAD）。EcoPAD将包括（1）核心计算算法（例如，生态模型），专门设计用于解决生态问题，（2）各种优化技术的数据同化，（3）各种数据库，将饲料到EcoPAD，和（4）EcoPAD的各种功能。这些函数使用户能够（i）估计模型参数或状态变量，（ii）量化生态系统的估计参数和预测状态的不确定性（例如，美国的碳汇），（iii）评估模型结构，（iv）评估采样策略，（v）进行生态预测。EcoPAD将在三个空间尺度上开发、测试和应用。首先，将根据在杜克森林和俄克拉荷马州大草原进行的试验中获得的地块级数据开发EcoPAD，以检查其提取生态系统对气候变化反应的信息的能力。第二，该项目将在北美的AmeriFlux涡流通量测量网络上开发EcoPAD，以检查其预测净生态系统交换的日、季和年际动态的能力。第三，将在区域和大陆范围内测试和评价生态系统发展评估系统预测生态系统及其服务未来状况的能力。EcoPAD有可能成为一个强大的生态信息学工具，吸收来自测量传感器网络的数据，并生成有助于资源管理和减缓气候变化政策制定的数据产品。该项目将通过学生和博士后培训，生态建模综合课程以及K-12学生和教师的推广来整合教学，培训和学习。氖和其他传感器网络的设计是为了更好地为社会提供生态服务。数据同化和生态预报是这些网络取得成功的关键组成部分。该项目将开发EcoPAD，从大量数据中提取信息用于生态预测，这些信息可以直接服务于社会，并对政策制定有用。该项目的结果将有助于公众对生态系统服务的教育。欲了解更多信息，请参见PI实验室网站http://bomi.ou.edu/luo/。