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Paul A. Dirmeyer, Yan Jin, Bohar Singh, and Xiaoqin Yan

regions with the onset of industrialization, the aggressive expansion of agriculture over the center of the continent, and other regional precipitation changes that appear to be occurring as the general circulation of atmosphere and ocean respond to the global radiative changes. The models concur that a reduction in precipitation has taken place across subtropical North America since preindustrial conditions. There is also evidence for a response over the middle of the continent in spring that is

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Zaitao Pan, Xiaodong Liu, Sanjiv Kumar, Zhiqiu Gao, and James Kinter

the climatic warming gradient exists, 2) at low-level jet termini where warm moist air converges, and 3) in intense agricultural regions where the deep crop roots can extract soil moisture. The midcontinental cooling goes against the common belief that the middle of continents, far from oceans, should warm faster than coastal regions. Also, it was a challenge for the great majority of models in phase 3 of the Coupled Model Intercomparison Project (CMIP3) to reproduce the WHs ( Kunkel et al. 2006

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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

from the early part of the record, during which the retrospective forecast system did indicate a rapid decrease in hurricane frequency initialized in the middle to late 1960s, as was seen in the observations (the correlation over the first 12 yr is 0.91 and −0.4 thereafter). In this reply, we have focused on the analysis of the hurricane predictions described in S13 , which were not available to us at the time of the original V13 manuscript was prepared. We note that the analyses described in

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Jeanne M. Thibeault and Anji Seth

along the eastern coast of North America from south of the Canadian Maritimes to the Gulf of Mexico west of Florida ( Fig. 2c ), implying that wet summers are associated with a westward shift or expansion of the NASH. Fig . 2. Regressions of observed and simulated twentieth-century (1981–2000) northeast-region JJA precipitation anomalies with (left) precipitation and 850-hPa wind, (middle) 500-hPa wind and geopotential height, and (right) SLP. All regression coefficients are shown for geopotential

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

data, (middle) the best model composite, and (bottom) the worst model composite for (left) the development stage month of June, (center) the mature stage month of August, and (right) the decay stage month of October. The composite of the three best models ( Fig. 6 , middle) illustrates most of the circulation features seen in the observations during the development and mature stages and demonstrates that current CGCM's are capable of realistically representing the NAMS, even at horizontal

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

). All indices are calculated for each model and observations. The clouds are classified by cloud-top height. The high-level clouds are 400 hPa or over, the middle-level clouds 400–600 hPa, and the low-level clouds 600 hPa or less as a rough standard. The cloud factions of the model outputs are integrated over these three layers separately to represent the low-level, middle-level, and high-level cloud amount. Wavelet software for spectrum analysis was provided by C. Torrence and G. Compo ( Torrence

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Justin Sheffield, Suzana J. Camargo, Rong Fu, Qi Hu, Xianan Jiang, Nathaniel Johnson, Kristopher B. Karnauskas, Seon Tae Kim, Jim Kinter, Sanjiv Kumar, Baird Langenbrunner, Eric Maloney, Annarita Mariotti, Joyce E. Meyerson, J. David Neelin, Sumant Nigam, Zaitao Pan, Alfredo Ruiz-Barradas, Richard Seager, Yolande L. Serra, De-Zheng Sun, Chunzai Wang, Shang-Ping Xie, Jin-Yi Yu, Tao Zhang, and Ming Zhao

current climate conditions and reducing uncertainty in future projections. Table 1 provides an overview of the models used. The specific models used vary for each individual analysis because of data availability at the time of this study, and so the model names are provided within the results section where appropriate. Table 1. CMIP5 models evaluated and their attributes. b. Overview of methods Data from the historical CMIP5 scenario are evaluated, which is a coupled atmosphere–ocean mode

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Justin Sheffield, Andrew P. Barrett, Brian Colle, D. Nelun Fernando, Rong Fu, Kerrie L. Geil, Qi Hu, Jim Kinter, Sanjiv Kumar, Baird Langenbrunner, Kelly Lombardo, Lindsey N. Long, Eric Maloney, Annarita Mariotti, Joyce E. Meyerson, Kingtse C. Mo, J. David Neelin, Sumant Nigam, Zaitao Pan, Tong Ren, Alfredo Ruiz-Barradas, Yolande L. Serra, Anji Seth, Jeanne M. Thibeault, Julienne C. Stroeve, Ze Yang, and Lei Yin

uncertainty in future projections. Table 1 provides an overview of the models used. Table 1. CMIP5 models evaluated and their attributes. Model types are atmosphere–ocean coupled (AO), ocean–atmosphere–chemistry coupled (ChemOA), Earth system model, and Earth system model chemistry coupled. To provide a consistent evaluation across the various analyses, we focus on a core set of 17 models, which are highlighted in the table by asterisks. The core set was chosen to span a diverse set of modeling centers

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Sanjiv Kumar, James Kinter III, Paul A. Dirmeyer, Zaitao Pan, and Jennifer Adams

interdecadal Pacific oscillation (IPO), the Pacific decadal oscillation (PDO), and the Atlantic multidecadal oscillation (AMO; Robinson et al. 2002 ; Kunkel et al. 2006 ; Wang et al. 2009 ; Meehl et al. 2012a ; Weaver 2013 ), other studies have highlighted the role of regional-scale hydrologic processes and land–atmosphere interaction (e.g., Pan et al. 2004 ; Liang et al. 2006 ; Misra et al. 2012 ). The most common feature of these studies is investigating the temperature trends for a fixed time

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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

gradient approximation ( Sobel and Bretherton 2000 ). An Atlantic SST warming that is larger than that of the tropical average, with a tropospheric warming in the Atlantic that follows tropical-mean SST, would lead to a large-scale destabilization of the atmosphere in the Atlantic, to changes in the large-scale vorticity, shear, and atmospheric humidity, and to increases in tropical cyclone (TC) potential intensity (e.g., Latif et al. 2007 ; Vecchi and Soden 2007a ; Gualdi et al. 2008 ; Sugi et al

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