Internal seminar

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Bi-weekly Tuesday NERSC Internal seminars

Dynamically constrained uncertainty for the Kalman filter covariance in the presence of model error

Colin James Grudzien
Seminar Date: 
4. April 2017 - 11:15 - 11:45

The forecasting community has long understood the impact of dynamic instability on the uncertainty of predictions in physical systems and this has led to innovative filtering design to take advantage of the knowledge of process models. The advantages of this combined approach to filtering, including both a dynamic and statistical understanding, have included dimensional reductions and robust feature selection in the observational design of filters.

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