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contributor authorHamrud, Mats
contributor authorBonavita, Massimo
contributor authorIsaksen, Lars
date accessioned2017-06-09T17:32:41Z
date available2017-06-09T17:32:41Z
date copyright2015/12/01
date issued2015
identifier issn0027-0644
identifier otherams-87015.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230638
description abstracthe desire to do detailed comparisons between variational and more scalable ensemble-based data assimilation systems in a semioperational environment has led to the development of a state-of-the-art EnKF system at ECMWF. A broad description of the ECMWF EnKF is given in this paper, focusing on highlighting differences compared to standard EnKF practice. In particular, a discussion of the novel algorithm used to control imbalances between the mass and wind fields in the EnKF analysis is given. The scalability and computational properties of the EnKF are reviewed and the implementation choices adopted at ECMWF described. The sensitivity of the ECMWF EnKF to ensemble size, horizontal resolution, and representation of model errors is also discussed. A comparison with 4DVar will be found in Part II of this two-part study.
publisherAmerican Meteorological Society
titleEnKF and Hybrid Gain Ensemble Data Assimilation. Part I: EnKF Implementation
typeJournal Paper
journal volume143
journal issue12
journal titleMonthly Weather Review
identifier doi10.1175/MWR-D-14-00333.1
journal fristpage4847
journal lastpage4864
treeMonthly Weather Review:;2015:;volume( 143 ):;issue: 012
contenttypeFulltext


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