ITR/AP(Geo): Collaborative Proposal For First Generation Model And Data Assimilation System To Reduce Volcanic Hazards

ITR/AP(Geo)：减少火山灾害的第一代模型和数据同化系统的合作提案

• 批准号: 0130602
• 负责人: Charles Connor
• 金额: $ 19.57万
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2006-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0130602&HistoricalAwards=false
• 关键词: ITR; AP; Geo; Collaborative; Proposal

0130602ConnorThis grant, supported through funds from the NSF/Information Technology Research - Small Grants Program and the EAR/Instrumentation and Facilities Program, will enable the development of a first-generation data and model assimilation system for volcanic hazard assessment. Essentially, this system will use Bayesian forecasting techniques to construct hazard estimates that incorporate both prior geologic information and near-real-time data types. The primary goal is to demonstrate, through the application of information technology methodologies, that such disparate geologic data types can be combined smoothly, even during volcanic crises, to yield improved estimates of hazard and risk. The focus will be on hazards associated with the dispersion and accumulation of volcanic tephra (volcanic ash), both because of the importance of this volcanic hazard and our previous experience in forecasting tephra hazards. Models will be used to relate observed tephra-stratigraphies at several volcanoes (Colima, Cerro Negro, Montserrat, Popocateptal) to sets of input parameters, including eruption duration, initial gas content, and meteorological conditions. We plan to explore several techniques (inversion, simplified models, database development) to relate observed patterns of volcano deformation directly to the parameter estimates used in tephra fallout models. The system will be constructed using parallel algorithms to exploit inexpensive and widely available PC clusters. Through the auspices of an ITR grant, we plan to clearly demonstrate the huge advantages realized by, for the first time, systematically linking the geologic record, process models, and near-real time monitoring results. For tephra accumulation hazards specifically, this approach will further lead to a clear understanding of the links between deformation, magma processes, and the fundamental parameters governing tephra dispersion and accumulation. In this sense, the results of the systematic approach advocated here will provide guidance about the volcanological research most likely to results in volcanic hazard reduction. This research will be conducted as a collaborative proposal between the University of Miami, the University of South Florida, and Southwest Research Institute (nonprofit). In addition, international collaboration with the University of Bristol will bring expertise on tephra dispersion modeling and data on the important Montserrat eruptions to the project. Students will contribute to all phases of the project, including geological research, model development, and software development. After appropriate testing, we plan to make the results of this project widely available by open-sourcing the codes and providing assistance in implementation of PC clusters to the volcanological community. ***

0130602Connor 这项赠款由 NSF/信息技术研究 - 小额赠款计划和 EAR/仪器和设施计划的资金支持，将有助于开发用于火山灾害评估的第一代数据和模型同化系统。 本质上，该系统将使用贝叶斯预测技术来构建包含先前地质信息和近实时数据类型的灾害估计。主要目标是通过应用信息技术方法来证明，即使在火山危机期间，这些不同的地质数据类型也可以顺利组合，以产生改进的灾害和风险估计。重点将放在与火山灰（火山灰）扩散和积累相关的灾害上，这既是因为这种火山灾害的重要性，也是因为我们以前在预测火山灰灾害方面的经验。 模型将用于将几座火山（科利马火山、塞罗内格罗火山、蒙特塞拉特火山、波波卡特普塔尔火山）观测到的火山地层与一组输入参数联系起来，包括喷发持续时间、初始气体含量和气象条件。 我们计划探索几种技术（反演、简化模型、数据库开发），将观察到的火山变形模式直接与火山灰沉降模型中使用的参数估计联系起来。该系统将使用并行算法构建，以利用廉价且广泛使用的 PC 集群。 通过 ITR 拨款的支持，我们计划首次清楚地展示通过系统地链接地质记录、过程模型和近实时监测结果所实现的巨大优势。特别是对于火山灰堆积危害，这种方法将进一步使人们清楚地了解变形、岩浆过程以及控制火山灰分散和堆积的基本参数之间的联系。从这个意义上说，这里提倡的系统方法的结果将为最有可能减少火山灾害的火山学研究提供指导。 这项研究将作为迈阿密大学、南佛罗里达大学和西南研究所（非营利组织）之间的合作提案进行。此外，与布里斯托大学的国际合作将为该项目带来火山灰扩散模型的专业知识和重要的蒙特塞拉特火山喷发的数据。学生将为项目的所有阶段做出贡献，包括地质研究、模型开发和软件开发。经过适当的测试后，我们计划通过开源代码并向火山学界提供 PC 集群实施方面的帮助来广泛使用该项目的结果。 ***