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

allows for covariability between ocean variables. For prediction purposes, they also have the natural benefit of delivering an ensemble of states that can potentially be used as initial conditions for probabilistic forecasts. And, in contrast to 4DVAR global ocean-state estimation systems, filters assimilate only past observations, making their historical state estimates appropriate for testing and calibrating ocean-initialized retrospective climate forecasts. In this initial effort, the ocean

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

1. Introduction Data assimilation (DA) has long been recognized as an indispensable tool in numerical weather forecasting for generating realistic initial and boundary conditions, for melding diverse observations into gridded analyses that have been used for model forecast verification ( Lynch 2006 ) and for added quality control of observational systems. Until recently, its usefulness for climate model development has not been compelling enough to warrant the effort of implementing the best

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Stephen Yeager, Alicia Karspeck, Gokhan Danabasoglu, Joe Tribbia, and Haiyan Teng

1. Introduction Society would benefit tremendously if climate scientists could produce reliable forecasts, years to decades in advance, of changes in regional hurricane activity, rainfall, or the likelihood of extreme events such as severe heat waves. In the relatively new field of decadal climate prediction, work is under way to assess the feasibility of using coupled general circulation models (CGCMs) to generate such forecasts, but significant scientific challenges must be overcome if this

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Shih-Yu Wang, Michelle L'Heureux, and Jin-Ho Yoon

–ENSO connection, if GHGs are increasing the WNP–ENSO relationship then this may suggest potentially more skillful ENSO forecasts at 1-yr lead and increased confidence in seasonal predictions during the decades to come. Acknowledgments Critical and valuable comments offered by Tony Barnston, Bruce Anderson, and Karthik Balaguru are highly appreciated. This study was supported under Grants NNX13AC37G, MOTC-CWB-101-M-15, and the Utah State University Agricultural Experiment Station (approved as journal paper

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Richard B. Neale, Jadwiga Richter, Sungsu Park, Peter H. Lauritzen, Stephen J. Vavrus, Philip J. Rasch, and Minghua Zhang

multicentennial spinup period when subject to preindustrial (circa 1850) major climate forcings. b. Observational data Comparisons are made to standard observational satellite, in situ and reanalysis datasets including the 15-yr European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-15; Gibson et al. 1997 ), 40-yr ECMWF Re-Analysis (ERA-40; Uppala et al. 2005 ), ECMWF Interim Re-Analysis (ERA-Interim; Dee et al. 2011 ), the NASA Modern-Era Retrospective Analysis for Research and

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Stephen J. Vavrus, Marika M. Holland, Alexandra Jahn, David A. Bailey, and Benjamin A. Blazey

extensive at depth, causing temperatures to be too high below 400 m. Within the atmosphere, the model’s surface air temperature is slightly too cold over the Arctic in all months compared with the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40; generally <2 K), but the spatial patterns and temporal variability are well simulated. The sea level pressures are generally too low Arctic-wide, with a severe undersimulation of the Beaufort high during spring and autumn

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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

to use 0.5° resolution for the new, shorter decadal forecasts. This was based on the large improvements in sea surface temperatures (SSTs) in the major upwelling regions going from 2° to 0.5° atmosphere resolution in CCSM3.5, documented in Gent et al. (2010) . However, it was found in CCSM4 that a majority of the upwelling region SST improvement between 2° and 0.5° resolution was obtained by using 1° atmosphere resolution; see section 4a . Given this SST improvement, and other benefits in the

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Clara Deser, Adam S. Phillips, Robert A. Tomas, Yuko M. Okumura, Michael A. Alexander, Antonietta Capotondi, James D. Scott, Young-Oh Kwon, and Masamichi Ohba

Simple Ocean Data Assimilation (SODA) reanalysis version 2.1.6 for the period 1958–2007 on a 0.5° latitude–0.5° longitude grid and 40 levels in the vertical (14 in the upper 200 m) ( Carton and Giese 2008 ). The SODA reanalysis is driven by winds from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis Project (ERA-40). 3. Results a. ENSO 1) Niño-3.4 SST variability The simulation of the climatological annual mean SST distribution in the Indo-Pacific, in particular the

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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

clouds for τ > 1.3. For the active instruments ( CloudSat , CALIPSO), studies such as those by B08 and C08 influence our evaluation strategy. B08 used CloudSat observations to evaluate the Met Office (UKMO) weather forecast model, and their findings motivated our midlevel cloud and precipitation bias evaluation using CloudSat . B08 showed that the UKMO model lacks midlevel CloudSat clouds, reaffirming a common climate model bias found in ISCCP-based studies. C08 evaluated climate

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

agreement with the CMAP data on that product’s coarser resolution, and that the TRMM data provide additional detail needed for validating the 1° CCSM4 output. The primary standard of comparison used here for circulation, geopotential height, and temperature fields is the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA)-Interim reanalyses ( Simmons et al. 2006 ), calculated from daily values for 1990–2005 at 1.5° resolution. It is a different time period than that used for

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