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

(SAsia: 65°–85°E, 10°–25°N), Southeast Asia (SEA: 100°–120°E, 10°–25°N), and Australia (Aus: 130°–150°E, 10°–25°S). These regions are identified as boxes on the map in Fig. 3 , but only land points are used in the regional analyses. Note, however, that most of the analyses presented here employ Hovmöller plots that show the latitudinal extent of the monthly evolution of various fields. Only the bar chart in Fig. 2 utilizes area averages performed over the specified boxes. Precipitation results are

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

. 2012 ). Section 2 describes the data used and the techniques for estimating metrics and indices of land–atmosphere interaction from the model simulations. Results and synthesis are given in sections 3 and 4 . A discussion and conclusions are presented in section 5 . 2. Data and techniques Monthly-mean output fields from land and atmospheric datasets from 15 models are used. Table 1 lists all models examined in this study. The choice of models was predicated on several factors. Most important

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

relationship of the storm-track extension box average used above to a smaller-scale box average more typical of California land regions, and of the modeled and observed relationships between 200-mbar wind in the jet extension region to this index of California precipitation. This is undertaken for the CMIP5 models, for which the jet extension argument seems to be most relevant. Figure 8 shows relationships between precipitation averaged over the storm-track extension box to precipitation averaged over a

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Suzana J. Camargo

, these models are able to capture interannual variability associated with El Niño–Southern Oscillation (ENSO) and have been used successfully to develop dynamical ( Vitart and Stockdale 2001 ; Camargo and Barnston 2009 ) and statistical–dynamical ( Wang et al. 2009 ) seasonal forecasts of TC activity. More recently, multiyear hurricane forecasts have been developed using these models ( Smith et al. 2010 ; Vecchi et al. 2013 ). In the last few years, many centers have started to use high

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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

scenarios are evaluated in this study. The historical simulations are run in coupled atmosphere–ocean mode forced by historical estimates of changes in atmospheric composition from natural and anthropogenic sources, volcanoes, greenhouse gases (GHGs), and aerosols, as well as changes in solar output and land cover. Note that only anthropogenic GHGs and aerosols are prescribed common forcings to all models, and each model differs in the set of other forcings that it uses, such as land-use change. For

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Baird Langenbrunner and J. David Neelin

, measurable progress has been made in simulating ENSO dynamics and associated teleconnections within atmosphere–ocean coupled general circulation models (CGCMs) ( Neelin et al. 1992 ; Delecluse et al. 1998 ; Davey et al. 2001 ; Latif et al. 2001 ; DeWeaver and Nigam 2004 ; AchutaRao and Sperber 2006 ; Randall et al. 2007 ). A number of studies use the fully coupled GCMs to assess twentieth-century ENSO variability and teleconnections against observations ( Doherty and Hulme 2002 ; Capotondi et al

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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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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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