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http://dx.doi.org/10.14191/Atmos.2012.22.4.455

Development of 12-month Ensemble Prediction System Using PNU CGCM V1.1  

Ahn, Joong-Bae (Division of Earth Environmental System, Pusan National University)
Lee, Su-Bong (Division of Earth Environmental System, Pusan National University)
Ryoo, Sang-Boom (Global Environment System Research Lab., National Institute of Meteorological Research)
Publication Information
Atmosphere / v.22, no.4, 2012 , pp. 455-464 More about this Journal
Abstract
This study investigates a 12 month-lead predictability of PNU Coupled General Circulation Model (CGCM) V1.1 hindcast, for which an oceanic data assimilated initialization is used to generate ocean initial condition. The CGCM, a participant model of APEC Climate Center (APCC) long-lead multi-model ensemble system, has been initialized at each and every month and performed 12-month-lead hindcast for each month during 1980 to 2011. The 12-month-lead hindcast consisted of 2-5 ensembles and this study verified the ensemble averaged hindcast. As for the sea-surface temperature concerns, it remained high level of confidence especially over the tropical Pacific and the mid-latitude central Pacific with slight declining of temporal correlation coefficients (TCC) as lead month increased. The CGCM revealed trustworthy ENSO prediction skills in most of hindcasts, in particular. For atmospheric variables, like air temperature, precipitation, and geopotential height at 500hPa, reliable prediction results have been shown during entire lead time in most of domain, particularly over the equatorial region. Though the TCCs of hindcasted precipitation are lower than other variables, a skillful precipitation forecasts is also shown over highly variable regions such as ITCZ. This study also revealed that there are seasonal and regional dependencies on predictability for each variable and lead.
Keywords
CGCM; ocean data assimilation; seasonal forecasting; ensemble prediction; ENSO;
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