Ensemble Data Assimilation and Prediction

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International Conference on Ensemble Methods in Geophysical Sciences (November 12-16, 2012, Toulouse, France)

  • Apodaca, K., M. Zupanski, M. Zhang, M. DeMaria, J. A. Knaff, G. DeMaria, and L. D. Grasso, 2012: Evaluating the potential impact of lightning data assimilation utilizing hybrid variational-ensemble methods.
  • Zhang, M., M. Zupanski, M.-J. Kim, J. Knaff, and K. Apodaca, 2012: Extracting maximum information from satellite observations using an ensemble-based data assimilation method.
  • Zupanski, M., 2012: Towards the development of hybrid variational-ensemble data assimilation: Minimization, Hessian preconditioning, and static error covariance model.

International Frontiers in Computational Physics: Modeling the Earth Systems (December 16-20, 2012, Boulder, CO)

  • Zupanski, M., 2012: Challenges of hybrid data assimilation methods.

2013 AMS Annual Meeting (6-10 January 2013, Austin, TX)
  • Apodaca, K., M. Zupanski, M. Zhang, M. DeMaria, J. Knaff, G. DeMaria, and L. Grasso, 2013: Evaluating the potential impact of assimilating satellite lightning data utilizing hybrid variational-ensemble methods.
  • Zhang, M., M. Zupanski, J. A. Knaff, and K. Apodaca, 2013: Impact studies of GOES-R Instruments for the TC Core Region Data Assimilation: Assimilating MSG SEVIRI Radiances as GOES-R ABI Proxy Data

2013 Warn-on-Forecast and High Impact Weather Workshop (February 5 - 7, 2013, Norman, OK)

  • Zupanski, M., and K. Apodaca, 2013: Utility of GOES-R geostationary lightning mapper (GLM) using hybrid variational-ensemble data assimilation in regional applications.

2013 SIAM Conference on Computational Science and Engineering (February 25 - March 1, 2013, Boston, MA)

  • Zupanski, M., 2013: A Hybrid Variational-ensemble Data Assimilation Method. (Data Assimilation and PDE-Constrained Optimization - MS215)

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