Controlling overestimation of error covariance in ensemble Kalman filters with sparse observations: A variance limiting Kalman filter

Details Controlling overestimation of error covariance in ensemble Kalman filters with sparse observations: A variance limiting Kalman filter Controlling overestimation of error covariance in ensemble Kalman filters with sparse observations: A variance limiting Kalman filter

2011-08-30

arxiv.org/abs/1108.5801v1

Monthly Weather Review, 139(8), pp. 2650-2667, 2011

Physics

Data Analysis, Statistics and Probability

32 pages, 11 figures

Scientific paper

10.1175/2011MWR3557.1

We consider the problem of an ensemble Kalman filter when only partial observations are available. In particular we consider the situation where the observational space consists of variables which are directly observable with known observational error, and of variables of which only their climatic variance and mean are given. To limit the variance of the latter poorly resolved variables we derive a variance limiting Kalman filter (VLKF) in a variational setting. We analyze the variance limiting Kalman filter for a simple linear toy model and determine its range of optimal performance. We explore the variance limiting Kalman filter in an ensemble transform setting for the Lorenz-96 system, and show that incorporating the information of the variance of some un-observable variables can improve the skill and also increase the stability of the data assimilation procedure.

Affiliated with

Also associated with

No associations

Rating

Controlling overestimation of error covariance in ensemble Kalman filters with sparse observations: A variance limiting Kalman filter does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Controlling overestimation of error covariance in ensemble Kalman filters with sparse observations: A variance limiting Kalman filter, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Controlling overestimation of error covariance in ensemble Kalman filters with sparse observations: A variance limiting Kalman filter will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-728701