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Kerrie L. Geil, Yolande L. Serra, and Xubin Zeng

that only 1 of 17 CMIP3 global models was able to realistically reproduce the NAMS precipitation annual cycle, interannual variability in precipitation, and key circulation patterns such as the monsoon high and the westward extension of the NASH with the associated low-level southerly flow. Stensrud et al. (1995) reproduced monsoon mesoscale circulation and the general features of deep convection with the Fourth-generation Pennsylvania State University–NCAR Mesoscale Model (MM4) limited

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Meng-Pai Hung, Jia-Lin Lin, Wanqiu Wang, Daehyun Kim, Toshiaki Shinoda, and Scott J. Weaver

1. Introduction Tropical convection is often organized into synoptic- to planetary-scale disturbances whose time scale is less than a season (~90 days) ( Wheeler and Kiladis 1999 , hereafter WK ; Wheeler and Weickmann 2001 ). This “subseasonal” variability plays an important role in the global climate system by modulating the location and timing of tropical deep convection and has been suggested as a key source of untapped predictability for the extended-range forecasts in both the tropics

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Brian A. Colle, Zhenhai Zhang, Kelly A. Lombardo, Edmund Chang, Ping Liu, and Minghua Zhang

explain the cyclone differences, such as low-level temperature gradients and the upper-level jet? Is there any indication of future cyclone change in terms of frequency, intensity, or spatial distribution? 2. Data and methods The Climate Forecast System Reanalysis (CFSR; Saha et al. 2010 ) at ~38-km grid spacing (64 vertical levels) was used to verify and compare the cyclone properties with the CMIP5 models for a few domains [East Coast land (ECL), East Coast water (ECW), and East Coast western and

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

during the period from 1998 to 2010. TRMM 3B42 rainfall is a global precipitation product based on multisatellite and rain gauge analyses. It provides precipitation estimates with 3-hourly temporal resolution on a 0.25° spatial resolution grid in a global belt between 50°S and 50°N. Daily wind fields during the period of the TRMM rainfall observations are obtained from the recent European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim, hereafter ERA-I) ( Dee et al

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Leila M. V. Carvalho and Charles Jones

unchanged or has little change and that the flow is unchanged, the poleward vapor transport and the pattern of evaporation minus precipitation ( E − P ) increases proportionally to the lower-tropospheric vapor. As a consequence, they postulated that wet regions will get wetter and dry regions will get drier in a warming planet. In a recent study, Jones and Carvalho (2013) analyzed the Climate Forecast System Reanalysis (CFSR) and phase 5 of the Coupled Model Intercomparison Project (CMIP5) ( Taylor

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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

storms that could potentially reach hurricane intensity are not excluded. Track density is calculated as the number of tracks in a 5° spherical cap per month while mean track strength is the mean vorticity of those tracks at each location. Comparisons of the CMIP5 track statistics with the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) for these same models were presented in Part II , which found that the best performing models within this subset are the

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Edmund K. M. Chang

show model-to-model variations, the projected percentage change in pp, averaged over the area 30°–55°N, 130°–70°W, is shown in Tables 2 and 3 for each CMIP5 and CMIP3 model, together with the multimodel mean. The climatological value for the average of pp over the region, normalized by the value based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) for DJF, is given in Table 4 (first row for each season). Table 4 shows that pp has a

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