Scientific Computing Seminar

Date:

Friday, January 6, 2005

Time:

1:00pm-2:00pm

Location:

50A-5132

Seminar Speaker:

Eugenia Kalnay
Department of Meteorology
University of Maryland
http://www.atmos.umd.edu/~ekalnay/

Title:

Advanced data assimilation: 4D-VAR or Ensemble Kalman Filter?

Abstract:

We consider the advantages and disadvantages of Ensemble Kalman Filter (EnKF) and 4D-Var, in view of experiments with the Lorenz (1963) model exploring the impact of tuning parameters such as the assimilation window in 4D-Var, and variance inflation in EnKF. Results obtained with a more realistic PE model (using both perfect model and reanalysis observations) provide guidance on several aspects of the practical implementation of EnKF, including model error, and observation localization as an alternative to background error covariance localization to reduce long-distance sampling problems. A table by Lorenc (2004) summarizing the pros and cons of the two methods is modified and commented.
About the speaker:

Eugenia Kalnay is a Distinguished University Professor, Department of Meteorology, University of Maryland; Member of the National Academy of Engineering (1996); foreign member of the Academia Europaea (2000); Distinguished University Professor, U MD, 2001; corresponding member of the Argentine National Academy of Physical Sciences(2003); Fellow of AGU (2005); former Robert E. Lowry Chair, School of Meteorology, U. of Oklahoma; former Director of the Environmental Modeling Center at NCEP.

Sponsor of Seminar:

Helen He

Scientific Computing

Contact Esmond G. Ng EGNg@lbl.gov