MJO Prediction Skill of the Subseasonal-to-Seasonal Prediction Models
Author(s) -
Yuna Lim,
SeokWoo Son,
Daehyun Kim
Publication year - 2018
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli-d-17-0545.1
Subject(s) - madden–julian oscillation , outgoing longwave radiation , climatology , predictability , forecast skill , environmental science , extratropical cyclone , longwave , coupled model intercomparison project , tropics , convection , atmospheric sciences , meteorology , climate model , geography , geology , radiation , mathematics , climate change , statistics , physics , oceanography , quantum mechanics , fishery , biology
The Madden–Julian oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides a major source of tropical and extratropical predictability on a subseasonal time scale. This study conducts a quantitative evaluation of the MJO prediction skill in state-of-the-art operational models, participating in the subseasonal-to-seasonal (S2S) prediction project. The relationship of MJO prediction skill with model biases in the mean moisture fields and in the longwave cloud–radiation feedbacks is also investigated.The S2S models exhibit MJO prediction skill out to a range of 12 to 36 days. The MJO prediction skills in the S2S models are affected by both the MJO amplitude and phase errors, with the latter becoming more important at longer forecast lead times. Consistent with previous studies, MJO events with stronger initial MJO amplitude are typically better predicted. It is found that the sensitivity to the initial MJO phase varies notably from model to model.In most models, a notable ...
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