Intercomparisons of 4D-Variational Assimilation and the Ensemble Kalman Filter
Driven largely by interest in weather prediction and ocean monitoring, methods for performing geophysical data analysis and assimilation have developed rapidly since the middle of the last century. By the early 1990's, a general consensus had developed in the data assimilation community in favor of variational methods and, in particular, the 4D-variational approach (4D-Var). More recently there has been much interest in an alternative approach, the ensemble Kalman filter (EnKF), inspired by the Kalman filter. In November 2008, an international workshop was held in Buenos Aires to consider the two methods, intercompare them both theoretically and in various practical contexts, and hopefully lead to a better understanding of the potential of both methods. There was special emphasis on atmospheric data assimilation with the aim of providing a solid scientific basis for supporting practical decisions eventually to be taken by meteorological agencies. The papers in this special collection are based on the presentations at the workshop, and are listed below as they are published. Click here to view the full preface for this special collection.
The workshop website can be accessed here: http://4dvarenkf.cima.fcen.uba.ar/
Dr. Herschel Mitchell