A Novel Data Assimilation System for Complex Dynamical Systems

这个项目是让PI参与开发一种新的数据同化系统，该系统将应用于美国国家环境预报中心(NCEP)的全球数值天气预报模式。与马里兰大学的同事们一起，PI已经实施了一个数据同化方案的初步版本，该方案将卡尔曼过滤器应用于一系列局部地区。在这个项目中，PI将作为马里兰大学学院公园气象系的全职访问教员在那里居住11个月，在那里他将学习大气科学和卫星数据分析。这次访问将使他能够应用他在动力系统、高性能计算和数据分析方面的现有技能，为数据同化项目做出实质性贡献。作为正在进行的大气科学研究生证书编制工作的一部分，数据同化研究所预计将开设一门数据同化研究生课程。后者是亚利桑那州立大学数学、机械和航天工程、化学、地理和物理系之间的跨学科合作。该IGMS项目由MPS多学科活动办公室(OMA)和数学科学部(DMS)联合支持。

This project is to have the PI participate in the development of a novel data assimilation system that will be applied to numerical global weather prediction models at the National Centers for Environmental Prediction (NCEP). With colleagues at the University of Maryland, the PI has implemented a preliminary version of a data assimilation scheme that applies the Kalman filter to a sequence of local regions. In this project, the PI will spend 11 months in residence as a full-time visiting faculty member in the Department of Meteorology at the University of Maryland at College Park, where he will study atmospheric science and satellite data analysis. This visit will allow him to apply his existing skills in dynamical systems, high performance computing, and data analysis to make substantive contributions to the data assimilation project. The PI expects to develop a graduate course in data assimilation as part of the ongoing development of a graduate Certificate in Atmospheric Sciences. The latter program is an interdisciplinary collaboration between the departments of mathematics, mechanical and aerospace engineering, chemistry, geography, and physics at ASU.This IGMS project is jointly supported by the MPS Office of Multidisciplinary Activities (OMA) and the Division of Mathematical Sciences (DMS).