The ensemble Kalman filter (EnKF) has now become a viable and popular method for data assimilation in various very large models, e.g., atmospheric, oceanic, and petroleum reservoirs systems. By bringing together leading technical experts, practitioners, researchers and students for presentations and informal interchange of information we aim at not only reviewing the state-of-the-art of EnKF but also at giving practitioners ideas of the possibilities of the methodology and the researchers feedba

Program

Download the workshop program here.

Venue

  • Location: Clarion Hotel Admiral, Bergen
  • Dates: May 18-20, 2010

Registration Fee

6,800 NOK - Includes two nights at hotel, two breakfasts, three lunches, dinner, and cultural arrangement.

Invited Speakers

Jeffrey Anderson
National Center for Atmospheric Research, USA 		Reducing the impact of sampling errors in ensemble filters
Craig Bishop
Naval Research Laboratory, USA 		Autonomous ensemble covariance moderation
Dennis McLaughlin
Massachusetts Institute of Technology, USA 		Reduced-order modeling for integrated ensemble estimation and control
Takemasa Miyoshi
University of Maryland, USA 		Adaptive localization and adaptive inflation methods with the LETKF
Dean Oliver
University of Oklahoma, USA 		Regularization for EnKF - Kalman gain versus ensemble covariance
Al Reynolds
University of Tulsa, USA 		Localization mitigates sampling error but is the data match good enough for Bayes?