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Jenny Lindvall, Gunilla Svensson, and Cecile Hannay

biogeochemical systems are mainly through near-surface variables. Thus, it is of interest to evaluate them in order to assess biases and possible model deficiencies. Few studies that evaluate the performance of planetary boundary layer (PBL) parameters in GCMs are found in the literature. Some very early studies include Boer et al. (1991) and Randall et al. (1992) . At the time of these intercomparisons, most models did not resolve the diurnal variation in solar insolation and only had a few vertical grid

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J. E. Kay, B. R. Hillman, S. A. Klein, Y. Zhang, B. Medeiros, R. Pincus, A. Gettelman, B. Eaton, J. Boyle, R. Marchand, and T. P. Ackerman

offers a compact visualization of model performance. As such, Taylor diagrams are particularly useful plots to evaluate climate model clouds with the numerous diagnostics available in COSP. We use Taylor diagrams ( Fig. 7 ) to summarize and reinforce the main conclusion of the preceding discussion, namely that the clouds in CAM5 are a closer match to satellite observations than are those in CAM4. Although the LWCF bias is larger for CAM5, the LWCF variability and correlation in CAM5 are closer to

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K. J. Evans, P. H. Lauritzen, S. K. Mishra, R. B. Neale, M. A. Taylor, and J. J. Tribbia

cost of the CCSM. CAM-EUL remains the most efficient model at low processor counts, achieving 0.8 simulated years per day (SYPD) on only 2048 cores. But as the number of cores is increased, the performance of CAM-EUL plateaus at 0.87 SYPD. CAM-SE and CAM-FV are similar in performance low processor counts, but CAM-SE has near-perfect scalability to 86 400 cores, achieving a top speed of 12.2 SYPD, whereas CAM-FV is less scalable and achieves its best performance of 2.49 SYPD on 53 248 cores. Fig . 2

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Kevin Raeder, Jeffrey L. Anderson, Nancy Collins, Timothy J. Hoar, Jennifer E. Kay, Peter H. Lauritzen, and Robert Pincus

estimate of analysis and forecast uncertainty. Climate model performance can also be evaluated in “observation space” by using the gridded model variables to compute estimates of available observations. Comparing these estimates to actual observations is referred to as evaluating performance in observation space. For observations such as a radiosonde temperature, this only requires spatial interpolation from the model grid, while observations such as a COSMIC radio occultation may require much more

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David M. Lawrence, Keith W. Oleson, Mark G. Flanner, Christopher G. Fletcher, Peter J. Lawrence, Samuel Levis, Sean C. Swenson, and Gordon B. Bonan

upon are included in section 5 . 2. Description of models and simulations a. CCSM4 and CLM4 CCSM4 is a global climate model consisting of atmosphere (R. Neale et al. 2011, unpublished manuscript), land, ocean ( Danabasoglu et al. 2012 ), and sea ice ( Holland et al. 2012 ) components. A general overview of CCSM4 and its performance relative to CCSM3 is provided in Gent et al. (2011) . The land component of CCSM4 is CLM4 ( Oleson et al. 2010b ; Lawrence et al. 2011 ). Biogeophysical processes

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Gijs de Boer, William Chapman, Jennifer E. Kay, Brian Medeiros, Matthew D. Shupe, Steve Vavrus, and John Walsh

deficiencies in this analysis, such as errors in the sea level pressure field, cloud phase, and boundary layer stability. Additional work needs to be completed to better understand causes of these and other errors discovered here, as well as to evaluate the performance of CCSM4 relative to other earth system models. In addition, to assure a fair comparison, continued efforts toward improving measurement datasets for model evaluation are required. Acknowledgments This research was supported by the Director

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Susan C. Bates, Baylor Fox-Kemper, Steven R. Jayne, William G. Large, Samantha Stevenson, and Stephen G. Yeager

force a number of different coupled ocean–sea ice models and the solutions are compared by Griffies et al. (2009) . The CORE fluxes are well suited for our purposes of evaluating coupled climate model mean fluxes and aspects of the variability because they satisfy the following requirements: they include global estimates of momentum, heat, and freshwater fluxes and their components; the net global heat and water fluxes are near zero, consistent with observations ( Large and Yeager 2009 ); the time

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Samantha Stevenson, Baylor Fox-Kemper, Markus Jochum, Richard Neale, Clara Deser, and Gerald Meehl

been paid recently to potential “switches” between modes having centers of action in the eastern and central Pacific ( Kao and Yu 2009 ; Yeh et al. 2009 ). And indeed physical changes to the tropical Pacific, such as alterations of heat content or the structure of the wind stress curl, must necessarily impact ENSO and the tropical heat budget—eventually. But understanding how and when that impact might be realized is not often discussed in the context of coupled model results. This paper will show

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Kerry H. Cook, Gerald A. Meehl, and Julie M. Arblaster

1. Introduction In this paper we document the West African, East African, North American, and South American monsoon regimes and associated processes for the Community Climate System Model, version 4 (CCSM4). This is the second of a two part series, with the first part ( Meehl et al. 2012 , hereafter Part I ) studying the Asian–Australian monsoon in CCSM4. Output from the fully coupled CCSM4 simulation is compared to the atmosphere-only the Community Atmosphere Model, version 4 (CAM4) runs

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Peter R. Gent, Gokhan Danabasoglu, Leo J. Donner, Marika M. Holland, Elizabeth C. Hunke, Steve R. Jayne, David M. Lawrence, Richard B. Neale, Philip J. Rasch, Mariana Vertenstein, Patrick H. Worley, Zong-Liang Yang, and Minghua Zhang

sequencing, processor concurrency, and exchange of state information and fluxes between components. In CPL7, all model components and the coupler itself can run on potentially overlapping processor subsets. This design permits the model system to have greatly increased flexibility to achieve the model component layout that optimizes the overall performance and efficiency of the model. The CCSM4 also includes a new scripting system that permits the user to easily specify the processor layout of the model

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