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Ensemble Data Assimilation and Prediction

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• Basic development of ensemble data assimilation

• Applications with complex models (climate, global, regional, microscale, carbon, GFS, GOES-5, BUGS, GCE, WRF, RAMS, SSIB)

• Applications with simple models (KdVB, shallow-water, column, Lorenz63)

• Clouds and Microphysics

• Carbon Data Assimilation

• Non-Gaussian framework

• Information content and measures

• Model error and bias

• Parameter estimation

• Extreme weather and climate

• Minimization

• Satellite observations

• Dimension reduction in dynamical systems

• Predictability

• Multiple sensors

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