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David E. Rupp, Philip W. Mote, Nathaniel L. Bindoff, Peter A. Stott, and David A. Robinson

experiment, “historicalNat,” used natural external forcings only, which include solar irradiance and volcanic gases. The second experiment, “historical,” used both natural and anthropogenic forcing; the latter includes long-lived greenhouse gases, aerosols and chemically active gases, though not all models include the identical suite of anthropogenic forcing agents. Simulated monthly SCE that excluded any time-varying forcing came from long-duration runs under the CMIP5 preindustrial control experiment

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

-driven (versus concentration driven) earth system model (ESM) simulations exploring the sensitivity of the carbon cycle feedback, and time-evolving land use runs allowing for the dynamic vegetation feedback ( Taylor et al. 2012 ). The core long-term CMIP5 simulations include historical and projection experiments. The historical experiments include all-forcing (historical), greenhouse gas (GHG) forcing only (historicalGHG), natural forcing only (historicalNat), and other specific forcing (such as aerosols

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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

forcing (greenhouse gases, aerosols, volcanoes, and solar) have been made (e.g., Oouchi et al. 2006 ; Knutson et al. 2008 ; Emanuel et al. 2008 ; Gualdi et al. 2008 ; Vecchi et al. 2008 ; Sugi et al. 2009 , 2012 ; Zhao et al. 2009 ; Bender et al. 2010 ; Knutson et al. 2010 ; Villarini et al. 2011b ; Zhao and Held 2011 ; Villarini and Vecchi 2012b , 2013a ). The basis for these projections is the possibility that radiatively forced climate change could influence the climatic conditions to

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Lin Chen, Yongqiang Yu, and De-Zheng Sun

warming. For one thing, the surface temperature is not likely to increase uniformly across the globe ( Xie et al. 2010 ). Another methodology used to examine the cloud and water vapor feedbacks in climate models involves examining the response of cloud and water vapor to SST changes on the time scales of El Niño–Southern Oscillation (ENSO) ( Sun et al. 2003 , 2006 ; S09 ; Lloyd et al. 2009 , 2011 , 2012 ; among others). By comparing the response of cloud and water vapor to the ENSO forcing in

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

the weak bias of the southerly wind along the African coast are also discussed by Richter and Xie (2008) , Hu et al. (2008) , and Doi et al. (2010) . Tozuka et al. (2011) showed that the tropical Atlantic bias is highly sensitive to the choices of deep convection parameterization. Another issue related to model performance and assessment is the extent to which the models reproduce the observed manner in which climate modes appear to force changes in the AWP. Much more of the NTA variability

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Anji Seth, Sara A. Rauscher, Michela Biasutti, Alessandra Giannini, Suzana J. Camargo, and Maisa Rojas

evaporation in both energy and water budgets ( Neelin and Held 1987 ). Based on Giannini (2010) , two competing mechanisms were examined, involving the differing responses of simulated precipitation to greenhouse gas forcing: remote (or top down) and local (or bottom up). A schematic of these mechanisms is provided in Fig. 1 . In the remote mechanism, SST warming leads to large-scale tropospheric warming, enhances vertical stability in the global tropics ( Sobel et al. 2002 ; Chiang and Sobel 2002

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Edmund K. M. Chang

relatively high-resolution modeling study. These contrasting impacts from changes in the upper and lower troposphere renders quantitative understanding of storm-track changes difficult and may account for the large spread in model projections of storm-track changes shown later in this study. Around the United States, Teng et al. (2008) examined the projected changes in winter cyclone activity based on an experiment made with the Community Climate System Model, version 3 (CCSM3), with forcing based on

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

al. 2012 ). In this study, we assess CMIP5 model fidelity in representing ISV over the ENP and neighboring areas by analyzing 16 GCMs participating in CMIP5. This work is a part of the collective efforts coordinated by the CMIP5 Task Force of the National Oceanic and Atmospheric Administration (NOAA) Modeling, Analysis, Predictions, and Projections (MAPP) program. The outline of this paper is as follows. In section 2 , the CMIP5 models and observational datasets used for this study are briefly

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

Intercomparison Project (CMIP5) ( Taylor et al. 2012 ) provides an opportunity to address these questions in a multimodel framework. This study has been conducted under the aegis of the “CMIP5 Task Force” coordinated under the Modeling, Analysis, Prediction, and Projection (MAPP) program of the National Oceanic and Atmospheric Administration Climate Program Office. The overall goal of the task force is to evaluate CMIP5 simulations of the twentieth-century climate specifically over North America, as well as

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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

Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and other global, regional, and national assessments. The goal of this study is to provide a broad evaluation of CMIP5 models in their depiction of North American climate variability. It draws from individual work by investigators within the CMIP5 Task Force of the U.S. National Oceanic and Atmospheric Administration (NOAA) Modeling Analysis and Prediction Program (MAPP) and is part of a Journal of Climate special collection on

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