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Ensemble data assimilation (EnsDA) activities of the GOES-R project Progress report Dusanka Zupanski CIRA/CSU GOES-R meeting 8 September 2004 Dusanka Zupanski,

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Presentation on theme: "Ensemble data assimilation (EnsDA) activities of the GOES-R project Progress report Dusanka Zupanski CIRA/CSU GOES-R meeting 8 September 2004 Dusanka Zupanski,"— Presentation transcript:

1 Ensemble data assimilation (EnsDA) activities of the GOES-R project Progress report Dusanka Zupanski CIRA/CSU GOES-R meeting 8 September 2004 Dusanka Zupanski, CIRA/CSU Zupanski@CIRA.colostate.edu

2 Dusanka Zupanski, CIRA/CSU Zupanski@CIRA.colostate.edu -Develop Ensemble Data Assimilation (EnsDA) algorithm for RAMS (and later for WRF) model - Apply EnsDA methodology to assimilate synthetic GOES-R observations - Perform twin data assimilation experiments (using RAMS and WRF models) to examine the impact of simulated GOES-R observations Long term GOALS of the GOES-R data assimilation component

3 Dusanka Zupanski, CIRA/CSU Zupanski@CIRA.colostate.edu - EnsDA experience with complex, non-linear atmospheric models (such as RAMS) is very limited - Model error estimation and correction is a critical component - How to assimilate numerous observations, with many degrees of freedom, while keeping the ensemble size reasonably small Submitted to the AMS conference: Zupanski D., M. Zupanski, M. DeMaria and L. Grasso: “Critical issues of ensemble data assimilation in application to GOES-R risk reduction program” Critical issues

4 Dusanka Zupanski, CIRA/CSU Zupanski@CIRA.colostate.edu - 3-d RAMS model is incorporated into the EnsDA algorithm (still in the debugging phase) - Including model error estimation component - Starting experiments with synthetic observations - Addressing the issue of many observations Current progress

5 Dusanka Zupanski, CIRA/CSU Zupanski@CIRA.colostate.edu  1-d KdVB model (M. Zupanski, D. Zupanski)  1-d NASA’s GEOS column precipitation model (D. Zupanski)  1-d RAMS model (W. Cotton, D. Zupanski, NASA)  1-d Cloud model (G. Stephens, M. Zupanski, NASA)  2-d CSU Geodesic Shallow Water model (M. Zupanski, D. Randall, NSF)  3-d NCEP’s Global Forecast System model (M. Zupanski, NOAA/THORPEX)  3-d RAMS model (D. Zupanski, NOAA/GOES-R)  3-d Purdue University micro-scale model (M. Zupanski, DoD)  3-d RAMS model + SiB-CASA (D. Zupanski, S. Denning, NASA) EnsDA algorithm applications

6 Dusanka Zupanski, CIRA/CSU Zupanski@CIRA.colostate.edu


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