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

这笔赠款由NSF/信息技术研究-小额赠款计划和EAR/仪器和设施计划提供资金支持，将用于开发用于火山危险评估的第一代数据和模型同化系统。从本质上讲，该系统将使用贝叶斯预测技术来构建危险估计，包括先前的地质信息和近实时的数据类型。其主要目标是通过应用信息技术方法表明，即使在火山危机期间，这种不同的地质数据类型也可以顺利合并，以改进对危险和风险的估计。重点将放在与火山灰(火山灰)扩散和积累有关的危险上，这既是因为这一火山灾害的重要性，也是因为我们以前预测火山灰灾害的经验。模型将被用来将几个火山(科利马、塞罗内格罗、蒙特塞拉特、波波卡塔尔)的观测到的盖层地层学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)，将观测到的火山变形模式与特弗拉散落模型中使用的参数估计直接联系起来。该系统将使用并行算法构建，以开发廉价且广泛可用的PC集群。通过ITR赠款的赞助，我们计划首次清楚地展示通过系统地将地质记录、过程模型和近乎实时的监测结果联系起来实现的巨大优势。具体而言，这一方法将使人们更清楚地了解变形、岩浆过程和支配火山灰扩散和聚集的基本参数之间的联系。从这个意义上说，这里倡导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(非营利性组织)的合作提案进行。此外，与布里斯托尔大学的国际合作将为该项目带来特弗拉扩散模型方面的专门知识和蒙特塞拉特重要喷发的数据。学生将在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和向火山学社区提供实施PC集群的帮助，使该项目的结果广泛可用。***

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. ***