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예상욱,Ben P. Kirtman 한국해양과학기술원 2006 Ocean science journal Vol.41 No.1
Total sea surface temperature (SST) in a coupled GCM is diagnosed by separating the variability into signal variance and noise variance. The signal and the noise is calculated from multi-decadal simulations from the COLA anomaly coupled GCM and the interactive ensemble model by assuming both simulations have a similar signal variance. The interactive ensemble model is a new coupling strategy that is designed to increase signal to noise ratio by using an ensemble of atmospheric realizations coupled to a single ocean model. The procedure for separating the signal and the noise variability presented here does not rely on any ad hoc temporal or spatial filter. Based on these simulations, we find that the signal versus the noise of SST variability in the North Pacific is significantly different from that in the equatorial Pacific. The noise SST variability explains the majority of the total variability in the North Pacific, whereas the signal dominates in the deep tropics. It is also found that the spatial characteristics of the signal and the noise are also distinct in the North Pacific and equatorial Pacific.
Yeh, Sang-Wook,Kirtman, Ben P. The Korean Society of Oceanography 2006 Ocean science journal Vol.41 No.1
Total sea surface temperature (SST) in a coupled GCM is diagnosed by separating the variability into signal variance and noise variance. The signal and the noise is calculated from multi-decadal simulations from the COLA anomaly coupled GCM and the interactive ensemble model by assuming both simulations have a similar signal variance. The interactive ensemble model is a new coupling strategy that is designed to increase signal to noise ratio by using an ensemble of atmospheric realizations coupled to a single ocean model. The procedure for separating the signal and the noise variability presented here does not rely on any ad hoc temporal or spatial filter. Based on these simulations, we find that the signal versus the noise of SST variability in the North Pacific is significantly different from that in the equatorial Pacific. The noise SST variability explains the majority of the total variability in the North Pacific, whereas the signal dominates in the deep tropics. It is also found that the spatial characteristics of the signal and the noise are also distinct in the North Pacific and equatorial Pacific.
A possible explanation on the changes in the spatial structure of ENSO from CMIP3 to CMIP5
Yeh, S. W.,Ham, Y. G.,Kirtman, B. P. AGU AMERICAN GEOPHYSICAL UNION 2014 Geophysical research letters Vol.41 No.1
This study examines changes in the structure of El Nino-Southern Oscillation (ENSO) amplitude using the historical climate simulations of the World Climate Research Program Coupled Model Intercomparison Project (CMIP) phase-3 and phase-5 coupled general circulation models (CGCMs). The analysis focuses on the so-called Bjerknes feedback. The Bjerknes feedback affects the sea surface temperature (SST) variability differently between the CMIP3 and CMIP5 models. In the CMIP5 models, the strength of the Bjerknes feedback is associated with the amplitude of ENSO, whereas the changes in the strength of Bjerknes feedback are not associated with changes in ENSO amplitude in CMIP3 CGCMs. The relationship between the Bjerknes feedback and the SST anomaly variance is suggested as a possible explanation for the eastward shift in the SST anomaly variance in CMIP5 relative to CMIP3.Key Points<list list-type='bulleted' id='grl51224-list-0001'> <list-item id='grl51224-li-0001'>Understanding of ENSO amplitude changes <list-item id='grl51224-li-0002'>Understanding of Bjerknes feedback in model <list-item id='grl51224-li-0003'>Identifying the difference in CMIP3 and CMIP5
Impact of the Indian Ocean on ENSO variability in a hybrid coupled model
Yeh, Sang-Wook,Wu, Renguang,Kirtman, Ben P. John WileySons, Ltd. 2007 Quarterly journal of the Royal Meteorological Soci Vol.133 No.623
<P>This study examines the impact of the Indian Ocean on El Niño and the Southern Oscillation (ENSO) variability through a series of numerical experiments with a hybrid coupled model. In the control run, an atmospheric general circulation model (AGCM) is coupled to the Zebiak–Cane simple ocean model in the tropical Pacific. Outside the tropical Pacific climatological sea surface temperatures are prescribed in the control simulation. In the first experiment, sea surface temperature anomalies (SSTAs) in the Indian Ocean are statistically predicted based on the state of the Pacific, and used to force the atmosphere. In the second experiment, a slab thermodynamic mixed layer model is coupled to the AGCM in the Indian Ocean. The Indian Ocean modifies the ENSO frequency via interactions with the Indian monsoon, but only when air–sea interactions in the Indian Ocean are included in the experimental design (i.e. the second experiment). The inclusion of the Indian Ocean, however, has little impact on the ENSO amplitude, which is at variance with other coupled simulations, suggesting that some missing dynamics or physics (i.e. Indian Ocean dynamics, Indonesian Throughflow, etc.) may play an important role. The Indian summer monsoon is more tightly coupled to ENSO in the second experiment than in the control run and the first experiment. The power spectrum of the Indian monsoon rainfall has a significant biennial time-scale of around 20–30 months in the second experiment, which may enhance the biennial time-scale of ENSO variability through a shift of the horizontal structure of zonal wind stress variability in the central equatorial Pacific. Copyright © 2007 Royal Meteorological Society</P>