TITLE

Ensemble Square Root Filters

AUTHOR(S)
Tippett, Michael K.; Anderson, Jeffrey L.; Bishop, Craig H.; Hamill, Thomas M.; Whitaker, Jeffrey S.
PUB. DATE
July 2003
SOURCE
Monthly Weather Review;Jul2003, Vol. 131 Issue 7, p1485
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Ensemble data assimilation methods assimilate observations using state-space estimation methods and low-rank representations of forecast and analysis error covariances. A key element of such methods is the transformation of the forecast ensemble into an analysis ensemble with appropriate statistics. This transformation may be performed stochastically by treating observations as random variables, or deterministically by requiring that the updated analysis perturbations satisfy the Kalman filter analysis error covariance equation. Deterministic analysis ensemble updates are implementations of Kalman square root filters. The nonuniqueness of the deterministic transformation used in square root Kalman filters provides a framework to compare three recently proposed ensemble data assimilation methods.
ACCESSION #
10131991

 

Related Articles

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics