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Philip J. Pegion and Arun Kumar

Centre Sea Ice and Sea Surface Temperature (HadISST) data set ( Rayner et al. 2003 ). The 15 leading EOFs were rotated using varimax rotation ( Kaiser 1958 ). To avoid contamination of sea ice points, the analysis was restricted to grid points that were completely ice free for the years 1901–2004. The leading mode of variability in this analysis is the trend of global SSTs, which explains 27.2% of the annual mean SST variance. The second leading mode is an ENSO like pattern and explains 20.5% of the

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Alfredo Ruiz-Barradas and Sumant Nigam

then obtained using the Hadley Centre’s Sea Ice and SST (HadISST) analysis that spans the time period 1870–2002 on a 1° grid ( Rayner et al. 2003 ), which is used on a coarser 5° × 2.5° grid. It is necessary to mention the following working definitions. Unless noted otherwise, climatology and long-term variability in the twentieth century are obtained for the 1902–99 base period. To avoid intraseasonal variability, the basic data is seasonal and defined in terms of the typical three-month means

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Renu Joseph and Ning Zeng

; Huffman et al. 1997 ) over land. The sea surface temperature (SST) reference dataset is the Hadley Center’s sea ice and SST analysis (HadISST data) ( Rayner et al. 2003 ). c. Methodology The timing of the three volcanic events (see Table 1 ) in this study is such that they all happened during periods when the El Niño also occurred. Therefore, while examining the associated climate response to volcanic events in observations, the natural variability associated with ENSO has to be removed. The method

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Scott J. Weaver, Siegfried Schubert, and Hailan Wang

the summary and discussion. 2. Datasets and methodology Several observationally based datasets are used to establish GPLLJ linkages to SST and precipitation. Atmospheric fields are gleaned from the NCEP–NCAR reanalysis ( Kalnay et al. 1996 ) and the North American Regional Reanalysis (NARR; Mesinger et al. 2006 ) on 2.5° × 2.5° and 1° × 1° latitude and longitude grids, respectively. The SST field is taken from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 5° × 2

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Yochanan Kushnir, Richard Seager, Mingfang Ting, Naomi Naik, and Jennifer Nakamura

that purpose, each with different SST forcing. Here we use one of these ensembles, consisting of 16 members and forced with observed global SST variability prescribed month by month, from 1856 to the present. This is the Global Ocean (forcing) Global Atmosphere (response; GOGA) experiment. For SST forcing we used a combination of the Lamont optimally smoothed SST dataset ( Kaplan et al. 1998 ) in the tropics and before 1870, and Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST

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Kirsten L. Findell and Thomas L. Delworth

.S. Weather Bureau, Washington, D.C., 58 pp . Priestley , C. H. S. , and R. J. Taylor , 1972 : On the assessment of surface heat flux and evaporation using large-scale parameters. Mon. Wea. Rev. , 100 , 81 – 92 . Rayner , N. A. , D. E. Parker , E. B. Horton , C. K. Folland , L. V. Alexander , D. P. Rowell , E. C. Kent , and A. Kaplan , 2003 : Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J

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Alfredo Ruiz-Barradas and Sumant Nigam

obtained using the Hadley Centre’s Sea Ice and SST analysis that spans the time period from 1870 to 2002 on a 1° grid ( Rayner et al. 2003 ), but is used on a coarser 5° × 2.5° grid. Unless noted otherwise, climatology and long-term variability of the twentieth, twenty-first, and twenty-second centuries span the following 99-yr base periods: 1901–99, 2001–99, and 2101–99. To avoid intraseasonal variability, the basic data is seasonal and defined in terms of the typical 3-month means: December

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Rachel R. McCrary and David A. Randall

shortwave radiation is a class C variable and is therefore completely model derived. It is used here as a comparison with the CGCMs. For SST data analysis, we use the UKMO Hadley Centre Sea Ice and SST dataset (HadISST; Rayner et al. 2003 ). HadISST has a 1° × 1° resolution and spans from 1870 to the present. Observations of hydrologic variables such as soil moisture and evapotranspiration are scarce. It is particularly difficult to find long-term data records (i.e., records longer than a few decades

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Randal D. Koster, Hailan Wang, Siegfried D. Schubert, Max J. Suarez, and Sarith Mahanama

temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. , 108 , 4407 . doi:10.1029/2002JD002670 . Schubert , S. , and Coauthors , 2009 : A U.S. CLIVAR project to assess and compare the responses of global climate models to drought-related SST forcing patterns: Overview and results. J. Climate , in press . Seneviratne , S. I. , D. Luthi , M. Litschi , and C. Schar , 2006 : Land–atmosphere coupling and climate change in Europe

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Siegfried Schubert, David Gutzler, Hailan Wang, Aiguo Dai, Tom Delworth, Clara Deser, Kirsten Findell, Rong Fu, Wayne Higgins, Martin Hoerling, Ben Kirtman, Randal Koster, Arun Kumar, David Legler, Dennis Lettenmaier, Bradfield Lyon, Victor Magana, Kingtse Mo, Sumant Nigam, Philip Pegion, Adam Phillips, Roger Pulwarty, David Rind, Alfredo Ruiz-Barradas, Jae Schemm, Richard Seager, Ronald Stewart, Max Suarez, Jozef Syktus, Mingfang Ting, Chunzai Wang, Scott Weaver, and Ning Zeng

. [Available from NOAA/NCEP/EMC, 5200 Auth Rd., Suitland, MD 20746] . Rayner , N. A. , D. E. Parker , E. B. Horton , C. K. Folland , L. V. Alexander , D. P. Rowell , E. C. Kent , and A. Kaplan , 2003 : Global analyses of SST, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. , 108 , 4407 . doi:10.1029/2002JD002670 . Richman , M. B. , 1986 : Rotation of principal components. J. Climatol. , 6 , 293 – 335 . Ruiz-Barradas , A

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