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Hailong Liu, Chunzai Wang, Sang-Ki Lee, and David Enfield

multidecadal influence of the AMO on Atlantic tropical cyclone activity ( Goldenberg et al. 2001 ) may operate through the mechanism of the AWP-induced atmospheric changes. In CMIP3, the global SST difference pattern between large AWP years and small AWP years on the multidecadal time scale resembles the geographic pattern of the AMO for most coupled models ( LWLE12 ). Many studies have been conducted to evaluate the performance of CGCMs in the World Climate Research Program (WCRP) CMIP3 multimodel dataset

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Xianan Jiang, Eric D. Maloney, Jui-Lin F. Li, and Duane E. Waliser

smallest RMS because of its better skill in simulating the spatial standard deviations of summer mean rainfall over the ENP. In addition, four other GCMs, including CSIRO-Mk3, MPI-ESM-LR, CanESM2, and CNRM-CM5, also exhibit relatively good pattern correlation scores relative to other GCMs. Performance in simulating summer mean rainfall in a GCM is largely consistent with that for the circulation pattern at 850 hPa. In general, models with relatively higher skill in simulating the summer mean rainfall

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Eric D. Maloney, Suzana J. Camargo, Edmund Chang, Brian Colle, Rong Fu, Kerrie L. Geil, Qi Hu, Xianan Jiang, Nathaniel Johnson, Kristopher B. Karnauskas, James Kinter, Benjamin Kirtman, Sanjiv Kumar, Baird Langenbrunner, Kelly Lombardo, Lindsey N. Long, Annarita Mariotti, Joyce E. Meyerson, Kingtse C. Mo, J. David Neelin, Zaitao Pan, Richard Seager, Yolande Serra, Anji Seth, Justin Sheffield, Julienne Stroeve, Jeanne Thibeault, Shang-Ping Xie, Chunzai Wang, Bruce Wyman, and Ming Zhao

). Hence, this variability in the annual cycle represents a climatological intraseasonal oscillation, akin to those found in other regions of the globe (e.g., Wang and Xu 1997 ). A previous assessment of CMIP3 model performance at simulating the MSD and future projections ( Rauscher et al. 2008 ) suggested that many CMIP3 models are capable of simulating the MSD despite an overall dry bias and that the MSD is projected to become stronger with an earlier onset. An updated evaluation of this feature

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Suzana J. Camargo

: Description and basic evaluation . Climate Dyn. , 40 , 2091 – 2121 , doi:10.1007/s00382-011-1259-y . Volodin , E. M. , N. A. Dianskii , and A. V. Gusev , 2010 : Simulating present-day climate with INMCM4.0 coupled model of the atmospheric and oceanic general circulations . Izv. Atmos. Oceanic Phys. , 46 , 414 – 431 . Walsh , K. J. E. , M. Fiorino , C. W. Landsea , and K. L. McInnes , 2007 : Objectively determined resolution-dependent threshold criteria for the detection of

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Edmund K. M. Chang

– 841 . Colle , B. A. , Z. Zhang , K. A. Lombardo , E. K. M. Chang , P. Liu , and M. Zhang , 2013 : Historical evaluation and future prediction of eastern North America and western Atlantic extratropical cyclones in the CMIP5 models during the cool season . J. Climate , 26 , 6882 – 6903 . Dee , D. P. , and Coauthors , 2011 : The ERA-Interim reanalysis: Configuration and performance of the data assimilation system . Quart. J. Roy. Meteor. Soc. , 137 , 553 – 597 . Donohoe

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Gabriel A. Vecchi, Rym Msadek, Whit Anderson, You-Soon Chang, Thomas Delworth, Keith Dixon, Rich Gudgel, Anthony Rosati, Bill Stern, Gabriele Villarini, Andrew Wittenberg, Xiasong Yang, Fanrong Zeng, Rong Zhang, and Shaoqing Zhang

of the sensitivity of hurricane frequency to SST changes in the Zhao et al. (2009 , 2010 ) high-resolution atmospheric model was trained across a broad range of climate states, including multiple realizations of the historical period and various projections of twenty-first-century SST change. This statistical model's performance against the observed record satisfies a necessary condition for its application to interannual to decadal predictions ( Vecchi et al. 2011 ). The parameters in this

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Leila M. V. Carvalho and Charles Jones

GFDL-ESM2M and CanESM2 (0.02° and 0.025°C yr −1 , respectively). To assess the performance of the CMIP5 models in simulating the observed trends in T850 p85 regardless of existing biases in T850, the intercept of the linear fit of all CMIP5 model simulations was removed and the resulting temperature anomalies (plus trends) are displayed in Fig. 2a . The intercepts do not differ significantly from the mean values over the historic period for NCEP–NCAR and CMIP5 models. Nonetheless, since all CMIP5

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