Correction of ‘Estimating observation impact without adjoint model in an ensemble Kalman filter’ | Zendy

Li Hong | Zendy; Liu Junjie | Zendy; Kalnay Eugenia | Zendy

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Correction of ‘Estimating observation impact without adjoint model in an ensemble Kalman filter’

Author(s) -

Li Hong,

Liu Junjie,

Kalnay Eugenia

Publication year - 2010

Publication title -

quarterly journal of the royal meteorological society

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.744

H-Index - 143

eISSN - 1477-870X

pISSN - 0035-9009

DOI - 10.1002/qj.658

Subject(s) - kalman filter , sensitivity (control systems) , forecast error , ensemble kalman filter , statistics , estimation , reduction (mathematics) , data assimilation , mathematics , systematic error , mean squared prediction error , filter (signal processing) , econometrics , computer science , algorithm , meteorology , extended kalman filter , geography , engineering , geometry , systems engineering , electronic engineering , computer vision

The ensemble sensitivity method proposed by Liu and Kalnay (2008) to estimate the impact of observations on reducing forecast error is shown to have a slight error and is corrected here. The corrected formula captures the actual forecast error reduction better and removes the positive bias in the estimation introduced by the original formula. Copyright © 2010 Royal Meteorological Society

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