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CIRA » Home » Research » Theme » 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

• Extreme Weather and Climate
• Satellite Observations
• Clouds and Microphysics

This theme is addressed in the following projects:

• NSF Ensemble DA System Based on Control Theory
• NASA Assimilation and downscaling of the GPM-like satellite precipitation

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