2016
DOI: 10.1007/s00024-016-1269-0
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The Local Ensemble Transform Kalman Filter (LETKF) with a Global NWP Model on the Cubed Sphere

Abstract: Abstract-We develop an ensemble data assimilation system using the four-dimensional local ensemble transform kalman filter (LEKTF) for a global hydrostatic numerical weather prediction (NWP) model formulated on the cubed sphere. Forecast-analysis cycles run stably and thus provide newly updated initial states for the model to produce ensemble forecasts every 6 h. Performance of LETKF implemented to the global NWP model is verified using the ECMWF reanalysis data and conventional observations. Global mean value… Show more

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Cited by 24 publications
(20 citation statements)
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“…We test the use of ESVs as additive inflation using the LETKF data assimilation system implemented in the global NWP model at KIAPS (Shin et al ., ). The use of ESVs as an additive inflation was first suggested by Yang et al .…”
Section: Discussionmentioning
confidence: 97%
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“…We test the use of ESVs as additive inflation using the LETKF data assimilation system implemented in the global NWP model at KIAPS (Shin et al ., ). The use of ESVs as an additive inflation was first suggested by Yang et al .…”
Section: Discussionmentioning
confidence: 97%
“…We choose a prior variance of the inflation parameter which allows a relatively strong temporal smoothing, since it results in a better performance of the LETKF (see more details in Shin et al . ()).…”
Section: Methodsmentioning
confidence: 94%
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“…To obtain the ensemble forecasts every 6 h, we exploit the Local Ensemble Transform Kalman Filter at KIAPS (LETKF: Hunt et al ., ; Shin et al ., ; ). We use the four‐dimensional version of LETKF formulation and set 50 ensemble members for this study, which assimilates observations in a similar way to H4DEV in the aspect of using ensemble trajectory (Hunt et al ., ).…”
Section: Methods and Datamentioning
confidence: 99%