11th International Ensemble Kalman Filter Workshop
The ensemble Kalman filter (EnKF) and its many variants have been proven effective for data assimilation in large models, including those in atmospheric, oceanic, hydrologic, and petroleum reservoir systems. By bringing together technical experts, practitioners, researchers and students for presentations and informal interchange of information, we aim to share research results and suggest important challenges that have yet to be addressed. Read more here.
The 11th International EnKF workshop is arranged by International Research Institute of Stavanger (IRIS) in collaboration with the Nansen Environmental and Remote Sensing Center (NERSC), the Uni Research CIPR (Centre for Integrated Petroleum Research) and Statoil.
June 20. - 22. 2016
Brakanes Hotel, Ulvik (Hardanger)
Call for abstracts:
We welcome abstracts on both new developments of the EnKF and related data assimilation methods and realistic applications. The applications are encouraged to discuss limitations and suggest further developments of the method. The accepted abstracts will be scheduled for either oral presentation or poster presentation. This workshop does not publish full papers, so submission of full paper is not required.
Randi Valestrand (IRIS)
Xiaodong Luo (IRIS)
Alberto Carassi (MCRN and NERSC)
Dean Oliver (Uni Research CIPR)
Remus Hanea (Statoil)
The registration fee will include hotel and meals during the workshop, and a round trip on bus (about 2 hrs one way) from Bergen city to Ulvik, a place located in the famous Hardangerfjord of Norway. For more information please see the EnKF workshop web page: http://www.iris.no/enkf/enkf-homepage. This web page will be continuously updated as the planning progresses.
Deadline for registration: April 25th 2016.
See website for updates
- Arnold Heemink, TU Delft, Netherland; "Ensemble methods for variational data assimilation"
- Alexander Barth, University of Liège, Belgium; "Local ensemble assimilation scheme with global constraints and conservation"
- John Harlim, The Pennsylvania State University, USA; "Model Error in Data Assimilation"
- Raul Tempone, KAUST, Saudi Arabia
- Remus Hanea, Statoil (tentative)