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Joshua-Xiouhua Fu, Wanqiu Wang, Yuejian Zhu, Hong-Li Ren, Xiaolong Jia, and Toshiaki Shinoda


Six sets of hindcasts conducted with the NCEP GFS have been used to study the SST-feedback processes and assess the relative contributions of atmospheric internal dynamics and SST feedback on the October and November MJO events observed during the DYNAMO IOP (Oct- and Nov-MJO). The hindcasts are carried out with three variants of the Arakawa–Shubert cumulus scheme under TMI and climatological SST conditions. The positive intraseasonal SST anomaly along with its convergent Laplacian produces systematic surface disturbances, which include enhanced surface convergence, evaporation, and equivalent potential temperature no matter which cumulus scheme is used. Whether these surface disturbances can grow into a robust response of MJO convection depends on the characteristics of the cumulus schemes used. If the cumulus scheme is able to amplify the SST-initiated surface disturbances through a strong upward–downward feedback, the model is able to produce a robust MJO convection response to the underlying SST anomaly; otherwise, the model will not produce any significant SST feedback. A new method has been developed to quantify the “potential” and “practical” contributions of the atmospheric internal dynamics and SST feedback on the MJOs. The present results suggest that, potentially, the SST feedback could have larger contributions than the atmospheric internal dynamics. Practically, the contributions to the Oct- and Nov-MJO events are, respectively, dominated by atmospheric internal dynamics and SST feedback. Averaged over the entire period, the contributions from the atmospheric internal dynamics and SST feedback are about half and half.

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Jian Ling, Chongyin Li, Tim Li, Xiaolong Jia, Boualem Khouider, Eric Maloney, Frederic Vitart, Ziniu Xiao, and Chidong Zhang
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Rongqing Han, Hui Wang, Zeng-Zhen Hu, Arun Kumar, Weijing Li, Lindsey N. Long, Jae-Kyung E. Schemm, Peitao Peng, Wanqiu Wang, Dong Si, Xiaolong Jia, Ming Zhao, Gabriel A. Vecchi, Timothy E. LaRow, Young-Kwon Lim, Siegfried D. Schubert, Suzana J. Camargo, Naomi Henderson, Jeffrey A. Jonas, and Kevin J. E. Walsh


An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño–Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation.

Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño—namely, eastern Pacific (EP) and central Pacific (CP) El Niño—and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño.

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