Collaborative Research: CMG: Data Assimilation by Synchronization of Truth and Model

这个项目探索了一种基于同步两个混沌系统的方法的数据同化方法的想法，一个是真实大气系统，另一个是大气的数值预报模式。研究将从简单的低维模式向更具天气模式特征的模式发展。其中一种同步方法将基于培育的矢量。提高环境预报系统效率或有效性的数据同化创新可能会有一些重要的应用，如陆地和空间天气、沿海洋流和生态系统的预报，或地表和次表层水文学。

This project explores the idea of developing an approach to data assimilation based on methods for synchronizing two chaotic systems, one being the real atmosphere and the other being a numerical forecast model of the atmosphere. The research will progress from simple low-dimensional models to models more characteristic of weather models. One of the synchronization methods will be based on bred vectors.Innovations in data assimilation that increase the efficiency or effectiveness of environmental forecasting systems might have a number of important applications such as the prediction of terrestrial and space weather, coastal ocean currents and ecosystems, or surface and sub-surface hydrology.