CIRA » Home » Research » Extreme Weather and Climate
Successful application of data assimilation to extreme events in weather and climate requires correct assimilation of extreme event observations. Current data assimilation methods, based on the Gaussian probability density function (PDF) assumption, are designed to reject extreme event observations, and thus neglect important information. This implies a specific development of a non- Gaussian framework for data assimilation, which includes extreme value probability density function (PDF), as well as other "regular" PDFs, such as the Gaussian and Lognormal PDFs. This research is focusing on development of methodologies that improve the efficiency and utility of extreme event observations in data assimilation.
This research topic is a component of other research topics
and research projects
- Ensemble data assimilation system based on control theory