Toward an Operational Particle Filter-Based Ensemble Data Assimilation System.

摘要

The primary goal of this project was to use a Markov chain Monte Carlo (MCMC) algorithm to examine the strengths and limitations of ensemble data assimilation algorithms, when applied to estimation of convective cloud system properties. MCMC methods return an exact solution, and as such are powerful tools for the evaluation of approximate data assimilation algorithms. The research was successful in advancing ensemble data assimilation theory, and has directly led to two peer reviewed journal articles, a peer reviewed book chapter, and 11 conference presentations.