CIRA » Home » Research » Non-Gaussian Framework
Most existing data assimilation systems are based on the Gaussian probability density function (PDF) assumptions. However, many variables and observations, especially those related to clouds and microphysics, belong to a skewed probability distribution and are inadequately represented by Gaussian PDF assumptions. This research is addressing the development and application of non-Gaussian framework for data assimilation and ensemble forecasting.
This research topic is a component of other research topics
and research projects
- Ensemble data assimilation system based on control theory
- Ensemble Kalman filtering for Army-scale meteorology
- Impact of fundamental assumptions of probabilistic data assimilation/ensemble forecasting: condition mode vs. conditional mean