EUNJOO LEE, Korea Meteorological Administration
Data Assimilation for KMA local model with extended domain
CoauthorsHyun-Cheol Shin, Eunhee Lee, Jung-Rim Lee, Sangwon Joo
Abstract: Korea Meteorological Administration(KMA) runs operationally Local Data
Assimilation and Prediction System(LDPS) which uses its lateral boundary
conditions from KMA Global Data Assimilation and Prediction System(GDPS).
(KMA operational models are based on Unified Model(UM) of UK Metoffice.)
Normally, limited area model has several issues related to forecast performance
such as high resolution observation data assimilation and lateral boundary
condition from bigger model with low resolution.
KMA has focused on the improvement of KMA LDPS forecast performance since
To capture better synop-scale features and reduce the impact of discontinuity at
lateral boundary, model domain is extended. More observations in the western part
of extended LDPS model domain are assimilated and so the extended LDPS is
expected to produce better initial condition of synoptic flow which is approaching
to Korean Peninsula. Also, the assimilation of high resolution satellite data and
ground GNSS data is developed for extended LDPS.