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Improving the use of observations to calibrate ensemble spread
Author(s) -
Flowerdew Jonathan,
Bowler Neill E.
Publication year - 2011
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.744
Subject(s) - kalman filter , data assimilation , ensemble kalman filter , calibration , meteorology , variance inflation factor , variance (accounting) , computer science , environmental science , climatology , mathematics , statistics , extended kalman filter , geography , geology , economics , regression analysis , accounting , multicollinearity
Abstract The Met Office Global and Regional Ensemble Prediction System (MOGREPS) uses an online inflation factor calculation to calibrate the spread of the ensemble in space and time and counteract the tendency of the Ensemble Transform Kalman Filter (ETKF) to underestimate analysis uncertainty. Until 2008, this calibration mechanism relied entirely on sonde and wind profiler data, and was only applied locally in the Extratropics. By producing more appropriate estimates of the error variance of ATOVS brightness temperature observations, it has become possible to include these in the inflation factor calculation. This in turn provides sufficient data to apply localisation uniformly over the globe. The new scheme improves the latitudinal distribution of spread in comparison to forecast error, especially in the Tropics. Issues remain with the vertical distribution of spread, which are addressed by work to be reported in a future paper. © 2011 Crown Copyright, the Met Office. Published by John Wiley & Sons, Ltd.