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

/CAM ensemble mean. Errors in forecasts from the DART ensemble reanalysis are larger than from the ECWMF conditions (and in extratropical regions, the differences are larger still) due to some combination of reduced model resolution and smaller numbers of observations used in the analyses. This comparison illustrates the ability of DART to readily provide a direct comparison of different models (or versions) against the same set of observations. We plan to increase the DART/CAM resolution to 1° and extend

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Alicia R. Karspeck, Steve Yeager, Gokhan Danabasoglu, Tim Hoar, Nancy Collins, Kevin Raeder, Jeffrey Anderson, and Joseph Tribbia

-mean ocean-state estimate relative to an identically forced ocean model simulation. Most of this improvement is in the upper 1000 m of the ocean. Because the simulation is only 8 years in length, we do not present an assessment of the variability. Simulations of greater than 30 years, which are currently planned, will allow us to robustly determine how data assimilation alters the seasonal cycle and variability in the ocean model. Identifiable issues notwithstanding, the results of this first endeavor

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

two stable control simulations is used. The first is the 1300-yr preindustrial control ( Gent et al. 2011 ) carried out under 1850 AD CO 2 concentrations. The next is the so-called extension run for RCP4.5, designed to describe the climate from 2100–2300 after CO 2 concentrations have stabilized. Extension runs are planned for all RCPs, but as of yet the others have not yet been completed. Note that the extension runs are themselves not sufficiently long to provide robust ENSO statistics; a

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

resolved wavenumber as the value of k where the smoothing has reduced E ( k ) by 50% from its original unsmoothed value. By this measure, CAM-FV has the roughest topography, resolving k < 71, while CAM-EUL and CAM-SE use significantly smoother topography, with k < 40 and k < 33, respectively. In the future we plan on using an improved remapping algorithm to generate topography datasets tailored for CAM-SE and with less smoothing. Fig . 15. Zonally averaged vertical velocity for CAM-SE, CAM

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David M. Lawrence, Andrew G. Slater, and Sean C. Swenson

weakness in the model and is an active area of model development, the results of which will be reported in a forthcoming study. Additional areas of planned development include the incorporation of a representation of excess soil ice [pockets of ice that are commonly found in permafrost ground that are present in excess of the available soil pore space ( Zhang et al. 2000 )], improvements to the CLM soil biogeochemistry to resolve the low northern high-latitude soil carbon bias, and an explicit

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William H. Lipscomb, Jeremy G. Fyke, Miren Vizcaíno, William J. Sacks, Jon Wolfe, Mariana Vertenstein, Anthony Craig, Erik Kluzek, and David M. Lawrence

ice sheet topography. We also plan to couple Glimmer-CISM to the CESM ocean model, with the ultimate goal of simulating interactions of ice sheets with all other components of the climate system. Acknowledgments We thank Gail Gutowski and Charles Jackson for valuable interactions and advice during model testing. We also thank Janneke Ettema, Jonathan Gregory, Magnus Hagdorn, Matthew Hoffman, David Holland, Jesse Johnson, Tony Payne, Stephen Price, Jeff Ridley, Ian Rutt, and Michiel van den Broeke

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