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Gabriele Villarini, David A. Lavers, Enrico Scoccimarro, Ming Zhao, Michael F. Wehner, Gabriel A. Vecchi, Thomas R. Knutson, and Kevin A. Reed

combination of changes in both CO 2 and SST because of the potentially opposite effects associated with the changes in these two forcings. One of the main objectives of the U.S. CLIVAR working group, and these experiments, is to quantify changes in tropical cyclone characteristics in a warming climate. This paper is organized as follows. The next section contains a description of the data, methods, and models used. Section 3 presents the results, and is followed by section 4 , in which we summarize

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Enrico Scoccimarro, Silvio Gualdi, Gabriele Villarini, Gabriel A. Vecchi, Ming Zhao, Kevin Walsh, and Antonio Navarra

Group dataset. More specifically, we use the following four experiments: CLIM: This is a climatological run obtained by repeating the SST climatology over the period 1982–2005 [based on the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST); Rayner et al. 2003 ] for 10 years. It is used to provide a baseline to contrast with the perturbation studies. Ozone and aerosol forcings are climatological as provided by the IPCC. Also, radiative gas concentrations are defined according to

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Chao Wang and Liguang Wu

wind, SST, and precipitation data of the three experiments [historical and representative concentration pathway 4.5 and 8.5 (RCP4.5 and RCP8.5) experiments] from CMIP5 models are used in this study. The historical experiment is forced by observed conditions, including changes in atmospheric composition, solar forcing, natural or anthropogenic aerosols, and so on. The radiative forcing in the RCP4.5 (RCP8.5) experiments stabilizes at 4.5 (8.5) W m −2 in 2100 ( Taylor et al. 2012 ). The output of

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Suzana J. Camargo, Michael K. Tippett, Adam H. Sobel, Gabriel A. Vecchi, and Ming Zhao

better skill in simulating the environmental fields than in simulating TC-like structures themselves (e.g., Camargo 2013 ), these strategies make better use of the climate models. One possibility is to use the large-scale fields of the global models to force regional climate models ( Landman et al. 2005 ; Camargo et al. 2007a ; Knutson et al. 2008 ). Another possibility is to use a hybrid dynamical–statistical model (e.g., Vecchi et al. 2011 ) as well as a dynamical downscaling model that

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Michael Wehner, Prabhat, Kevin A. Reed, Dáithí Stone, William D. Collins, and Julio Bacmeister

, called SSTplus2_2xCO2, combines the uniform addition of 2°C to the 1990 climatological SST and 660 ppm value of atmospheric CO 2 . Sulfate and other trace aerosol concentrations are fixed to 2000 climatological values from a related coupled model simulation and are the same for all experiments. Analyses in this paper are confined to global measures of tropical storm behavior. While the potential for different responses to forcing changes in different basins is significant, such differences are likely

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Christina M. Patricola, R. Saravanan, and Ping Chang

, and AMM and Atlantic TC activity, followed by a description of the data and methodology used in this study. The questions posed above are then investigated by analyzing composites of observed Atlantic TC activity according to ENSO and AMM phases. We also evaluate Atlantic TC activity during rare extreme events that are conceivably absent from the data record due to its brevity by forcing a regional climate model with constructed pairs of strong ENSO and AMM phases. 2. Background Proper guidance

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Malcolm J. Roberts, Pier Luigi Vidale, Matthew S. Mizielinski, Marie-Estelle Demory, Reinhard Schiemann, Jane Strachan, Kevin Hodges, Ray Bell, and Joanne Camp

general circulation models (CGCMs) implemented at horizontal resolutions that allow multicentennial integrations under a variety of forcing scenarios, often with full Earth system biogeochemistry components. To address such issues, a long-standing collaboration exists between the Met Office and the University of Reading to develop “weather resolving” climate models, which are able to capture typical weather features such as fronts and atmospheric rivers (as found in a weather forecast) while also

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Wei Mei, Shang-Ping Xie, and Ming Zhao

produce significant differences in the simulated interannual variation of basinwide hurricane counts. To extract a reproducible signal associated with the external forcing (i.e., observed SSTs), we use three-member ensemble simulations that are different only in initial conditions. The ensemble mean is considered as the forced response to the prescribed SSTs from observations. The deviation of each member from the ensemble mean represents internal variability of the model. To further advance our

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Michael Horn, Kevin Walsh, Ming Zhao, Suzana J. Camargo, Enrico Scoccimarro, Hiroyuki Murakami, Hui Wang, Andrew Ballinger, Arun Kumar, Daniel A. Shaevitz, Jeffrey A. Jonas, and Kazuyoshi Oouchi

series for both the present-day and altered forcing experiments are given in Table 3 . All correlations are statistically significant. The highest correlation in the present-day experiments (0.78) is obtained between the CSIRO and the CMCC-INGV group scheme in the CMCC-INGV data. This is unsurprising, as the CMCC-INGV group used a variant of the CSIRO scheme. Correlations are lower between the other tracking scheme pairs for the CMCC-INGV data. The CSIRO–Zhao correlation for the NCEP model is high

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John G. Dwyer, Suzana J. Camargo, Adam H. Sobel, Michela Biasutti, Kerry A. Emanuel, Gabriel A. Vecchi, Ming Zhao, and Michael K. Tippett

patterns generated by the CMIP3 and CMIP5 ensembles, compared with a control simulation run with observed, climatological SST from 1981 to 2005. The future simulations use the SST perturbation from the end of the twenty-first century in the CMIP suites added to the twentieth-century-observed SST pattern, as described in detail in Zhao et al. (2009) and Zhao and Held (2012) . For CMIP5, we look at the multimodel mean SST warming in the RCP4.5 scenario (about half of the forcing strength of the RCP8

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