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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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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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Wilbert Weijer, Bernadette M. Sloyan, Mathew E. Maltrud, Nicole Jeffery, Matthew W. Hecht, Corinne A. Hartin, Erik van Sebille, Ilana Wainer, and Laura Landrum

than observed ( Danabasoglu et al. 2012 ): zonally averaged zonal wind stress T x peaks at about 0.20 N m −2 , as compared with approximately 0.15 N m −2 for the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) ( Fig. 3b ; Uppala et al. 2005 ). Fig . 3. Time series of (a) SAM, (b) maximum of the zonally averaged zonal wind stress, (c) the Niño-3.4 index, and (d) net SHF Q f averaged over the domain south of 55°S. Plotted are 11-yr running means for the

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Keith Oleson

( Roth 2007 ). The maximum UHI appears to depend slightly on latitude with values of 4°C in the tropics and about 6°C at midlatitudes, partly due to differences in anthropogenic heat generation and radiation balance ( Wienert and Kuttler 2005 ). Zhang et al. (2010) report remotely sensed globally averaged daytime skin temperature UHIs of 2.6°C in summer and 1.4°C in winter. Mesoscale models have been applied to the study of the UHI and more generally urban climate. Some of the earliest simulations

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

cases ( Taylor et al. 1997 ; Thomas and Loft 2002 ), three-dimensional dry dynamical test cases ( Taylor et al. 1998 ; Thomas and Loft 2005 ; Dennis et al. 2005 ; Taylor et al. 2007 ; Lauritzen et al. 2010 ), multicloud simulations ( Khouider et al. 2011 ), aquaplanet experiments that include full physics ( Taylor et al. 2008 ; Mishra et al. 2011a , b ), and realistic simulations with CAM2 physics ( Wang et al. 2007 ). The SE method has also been pursued for global forecast modeling, as in

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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

resolution of 1.25° × 0.9° in the 1° version, and half the number of grid points in both directions in the 2° version. CAM4 uses 26 layers in the vertical, which are distributed similarly to CAM3. The CAM4 is documented in R. B. Neale et al. (2011, unpublished manuscript). There have been several developments to the CCSM4 ocean component, which uses the Parallel Ocean Program version 2 ( Smith et al. 2010 ). How the parameterization for the effects of mesoscale eddies transitions from the nearly

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Samuel Levis, Gordon B. Bonan, Erik Kluzek, Peter E. Thornton, Andrew Jones, William J. Sacks, and Christopher J. Kucharik

Forecasts model is simulated better when accounting for interactive soil moisture and when soils start the summer season with sufficient soil moisture. In a study based on observations in the Canadian Prairies, Hanesiak et al. (2009) showed that areas with wetter soils tend to experience severe summer convective weather more frequently than areas with drier soils. In a meticulous investigation of the effects of initial soil moisture anomalies on subsequent precipitation over North America using the

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Ernesto Muñoz, Wilbert Weijer, Semyon A. Grodsky, Susan C. Bates, and Ilana Wainer

association between West African rainfall and U.S. landfall of intense hurricanes . Science , 249 , 1251 – 1256 . Griffies , S. M. , and Coauthors , 2009 : Coordinated Ocean-Ice Reference Experiments (COREs) . Ocean Modell. , 26 , 1 – 46 . Grodsky , S. A. , J. A. Carton , S. Nigam , and Y. M. Okumura , 2012 : Tropical Atlantic biases in CCSM4 . J. Climate , 25 , 3684 – 3701 . Hamill , T. M. , 2001 : Interpretation of rank histograms for verifying ensemble forecasts . Mon. Wea

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Jenny Lindvall, Gunilla Svensson, and Cecile Hannay

model simulations are also evaluated against global observation and reanalysis datasets. Two datasets for near-surface temperature are included in this study: the Willmott and Matsuura (2001) dataset version 3.02 for 1950–99 and Climate Research Unit (CRU) high-resolution climate data, version 2.1 ( Mitchell and Jones 2005 ) for the years 1961–90. Three reanalysis datasets are used. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim; Simmons et al

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