Session 10A |
| | Advanced Methods for Data Assimilation I |
| | Chair: Kayo Ide, University of Maryland, College Park, MD
|
| 4:00 PM | 10A.1 | Regularization of error covariance with the Gaussian graphical model
Genta Ueno, The Institute of Statistical Mathematics, Tokyo, Japan; and T. Tsuchiya |
| 4:15 PM | 10A.2 | A Bayesian method for estimating stochastic parameters
Xiaosong Yang, NOAA/GFDL, Princeton, NJ; and T. DelSole |
| 4:30 PM | 10A.3 | Improve Ensemble-Based State Estimation and Forecasting with Simultaneous Parameter Estimation
Xiao-Ming Hu, The University of Oklahoma, Norman, OK; and J. W. Nielsen-Gammon and F. Zhang |
| 4:45 PM | 10A.4 | On the use of model physics parameters as control variables in data assimilation systems
Derek J. Posselt, University of Michigan, Ann Arbor, MI |
| 5:00 PM | 10A.5 | Impact of “variable localization” in the background error covariance matrix within the Local Ensemble Transform Kalman Filter
Eugenia Kalnay, Univ. of Maryland, College Park, MD; and J. S. Kang and K. Ide |
| 5:15 PM | 10A.6 | What constrains the growth of spread in ensemble Kalman filters?
Tom Hamill, NOAA/ESRL, Boulder, CO; and J. Whitaker |