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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

that climate projections for the twenty-first century at the local and regional levels remain a substantial challenge. The present study provides a summary of projected twenty-first-century NA climate change in the updated state-of-the-art climate and Earth system models used in CMIP5. The results contained herein are contributed by members of the CMIP5 Task Force of the National Oceanographic and Atmospheric Administration (NOAA) Modeling, Analysis, Predictions and Projections Program (MAPP

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Leila M. V. Carvalho and Charles Jones

associated atmospheric radiative forcing has dramatically increased in the last decades ( Forster et al. 2007 ). Changes in atmospheric forcing modify the distribution of the atmospheric heating with consequences to the hydrological cycle. The atmospheric moisture content increases in response to global warming following the Clausius–Clapeyron relationship, but the rate of precipitation increase is slower as predicted by climate models ( Allen and Ingram 2002 ; Richter and Xie 2008 ; Cherchi et al

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J. David Neelin, Baird Langenbrunner, Joyce E. Meyerson, Alex Hall, and Neil Berg

California coast at approximately 35°N, resulting in the climatological precipitation at the California coast being smaller than at comparable latitudes in the central Pacific. Fig . 1. DJF precipitation change measures in CMIP5 models for the end of the century (2070–99 average) relative to a base period of 1961–90 under the RCP8.5 forcing scenario. (a) Multimodel ensemble mean (15 models) precipitation change (mm day −1 ). Red line shows the 3 mm day −1 contour from the MME mean base period

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

members) for the RCP4.5 experiments, and 16 CMIP5 climate models (39 ensemble members) for the RCP8.5 experiments. Model selection for each experiment was primarily driven by the data availability at the time this study was conducted. The historical experiments are standard all-forcings climate simulations including anthropogenic greenhouse gas concentrations/emissions, volcanic aerosols, and land use changes for the period 1850–2005 ( Taylor et al. 2012 ). In 2100, CO 2 -equivalent concentrations are

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Baird Langenbrunner and J. David Neelin

. (2005) compare two uncoupled atmospheric GCMs forced with identically prescribed SSTs, finding noticeable variations between the two models in the response of extratropical 500-mb height and regional precipitation. They force these models with climatological SST fields and SSTs representative of a response to a Coupled Model Intercomparison Project (CMIP) phase 2 (CMIP2) CO 2 doubling experiment. They find that precipitation difference patterns between the two models are similar for either case

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Suzana J. Camargo

Observatory of Columbia University and Michael Tippett for suggestions on the manuscript. SJC is supported by the National Oceanic and Atmospheric Administration/Modeling Analysis and Prediction Program (MAPP) under Grant NA11OAR4310093 and is part of the NOAA/MAPP CMIP5 Task Force. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Tables 1 and 2 ) for producing and making

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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

at daily to seasonal time scales, as well as selected climate features that have regional importance. Part II covers aspects of climate variability, such as intraseasonal variability in the tropical Pacific, the El Niño–Southern Oscillation (ENSO), and the Atlantic multidecadal oscillation, which play major roles in driving North American climate variability. This study draws from individual work by investigators within the CMIP5 Task Force of the National Oceanic and Atmospheric Administration

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

Projections (MAPP) Program as part of the CMIP5 Task Force under Grant GC10-400, the NASA MAP Program, and NSF Grant ATM-0745872. D. Kim was supported by NASA Grant NNX09AK34G. T. Shinoda is supported by NOAA CPO MAPP and ESS (GC10-400, NA11OAR4310110) and the ONR/LASP project (Program Element 601153N). REFERENCES Bergman , J. W. , H. H. Hendon , and K. M. Weickmann , 2001 : Intraseasonal air–sea interactions at the onset of El Niño . J. Climate , 14 , 1702 – 1719 . Bessafi , M. , and M. C

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

influences, solar forcing, concentrations of short-lived species and aerosols from both natural and anthropogenic sources, and land use ( Taylor et al. 2009 ). For details regarding CMIP5 experimental design, the reader is referred to Taylor et al. (2009 , 2012 ). Table 1 provides information on the 21 CGCMs used for this study, which have atmospheric components ranging in horizontal grid resolution from 0.56° × 0.56° in longitude by latitude to 3.75° × 2.47° and oceanic horizontal grids ranging from

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

Modeling, Analysis, Predictions and Projections (MAPP) Program as part of the CMIP5 Task Force under Grant NA11OAR4310104, the DOE Office of Science through its Office of Biological and Environmental Sciences, and the National Sea Grant College Program of NOAA (NYSG R/RCP-17). We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making

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