Prediction of global patterns of dominant quasi-biweekly oscillation by the NCEP Climate Forecast System version 2

被引:0
作者
Xiaolong Jia
Song Yang
Xun Li
Yunyun Liu
Hui Wang
Xiangwen Liu
Scott Weaver
机构
[1] China Meteorological Administration,National Climate Center
[2] Sun Yat-sen University,School of Environmental Science and Engineering
[3] NOAA Climate Prediction Center,Hainan Meteorological Service
[4] China Meteorological Administration,undefined
来源
Climate Dynamics | 2013年 / 41卷
关键词
Quasi-biweekly oscillation; Prediction skill; Monsoons; ENSO;
D O I
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中图分类号
学科分类号
摘要
Daily output from the hindcasts by the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) is analyzed to understand the skill of forecasting atmospheric variability on quasi-biweekly (QBW) time scale. Eight dominant quasi-biweekly oscillation (QBWO) modes identified by the extended empirical orthogonal function analysis are focused. In the CFSv2, QBW variability exhibits a significant weakening tendency with lead time for all seasons. For most QBWO modes, the variance drops to only 50 % of the initial value at lead time of 11–15 days. QBW variability has better prediction skill in the winter hemisphere than in the summer hemisphere. Skillful forecast can reach about 10–15 days for most modes but those in the winter hemisphere have better forecast skills. Among the eight QBWO modes, the North Pacific mode and the South Pacific (SP) mode have the highest forecast skills while the Asia–Pacific mode and the Central American mode have the lowest skills. For the Asia–Pacific and Central American modes, the forecasted QBWO phase shows an obvious eastward shift with increase in lead time compared to observations, indicating a smaller propagating speed. However, the predicted feature for the SP mode is more realistic. Air–sea coupling on the QBW time scale is perhaps responsible for the different prediction skills for different QBWO modes. In addition, most QBWO modes have better forecasting skills in El Niño years than in La Niña years. Different dynamical mechanisms for various QBWO modes may be partially responsible for the differences in prediction skill among different QBWO modes.
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页码:1635 / 1650
页数:15
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共 120 条
[1]  
Agudelo PA(2009)Application of a serial extended forecast experiment using the ECMWF model to interpret the predictive skill of tropical intraseasonal variability Clim Dyn 32 855-872
[2]  
Hoyos CD(1993)The 10–20-day mode of the 1979 Indian monsoon: its relation with the time variation of monsoon rainfall Mon Weather Rev 121 2465-2482
[3]  
Webster PJ(1995)An observational study of the South China Sea monsoon during the 1979 summer: onset and life cycle Mon Weather Rev 123 2295-2318
[4]  
Curry JA(2000)Interaction between the summer monsoons in East Asia and the South China Sea: intraseasonal monsoon modes J Atmos Sci 57 1373-1392
[5]  
Chen TC(1979)Lanczos filtering in one and two dimensions J Appl Meteorol 18 1016-1022
[6]  
Chen JM(2003)Coupling between northward-propagating intraseasonal oscillations and sea surface temperature in the Indian Ocean J Atmos Sci 60 1733-1753
[7]  
Chen TC(1999)10–25 day intraseasonal variations of convection and circulation over East Asia and western North Pacific during early summer J Meteorol Soc Jpn 77 753-769
[8]  
Chen JM(2002)Tropical–extratropical interaction associated with the 10–25 day oscillation over the western Pacific during the northern summer J Meteorol Soc Jpn 80 311-331
[9]  
Chen TC(2003)Clustering of synoptic activity by Indian summer monsoon intraseasonal oscillations Geophys Res Lett 30 1431-1258
[10]  
Yen MC(2010)A framework for assessing operational model MJO forecasts: a project of the CLIVAR Madden–Julian oscillation working group Bull Am Meteorol Soc 91 1247-661