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Behnjamin J. Zib, Xiquan Dong, Baike Xi, and Aaron Kennedy

–random overlapped. More information about the 20CR system is documented in Compo et al. (2011) . 4) CFSR reanalysis NCEP's CFSR dataset is a global, high-resolution coupled atmosphere–ocean–land surface–sea ice model that was recently completed over the 31-yr period from 1979 to 2009. This reanalysis intends to provide initial conditions for historical forecasts and address calibration applications for the operational NCEP climate forecasts while also helping to provide accurate estimates of the earth

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Michael G. Bosilovich, Franklin R. Robertson, and Junye Chen

. Data a. Reanalyses There exist several atmospheric reanalyses for the period of 1979 through current time. The Japanese 25-yr Reanalysis (JRA-25), released for use in March 2006 ( Onogi et al. 2005 , 2007 ); the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40; Uppala et al. 2005 ), which stops in August 2002; and the National Centers for Atmospheric Research–Department of Energy second reanalysis (NCEP–DOE R2; Kanamitsu et al. 2002 ) represent the second generation

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Michele M. Rienecker, Max J. Suarez, Ronald Gelaro, Ricardo Todling, Julio Bacmeister, Emily Liu, Michael G. Bosilovich, Siegfried D. Schubert, Lawrence Takacs, Gi-Kong Kim, Stephen Bloom, Junye Chen, Douglas Collins, Austin Conaty, Arlindo da Silva, Wei Gu, Joanna Joiner, Randal D. Koster, Robert Lucchesi, Andrea Molod, Tommy Owens, Steven Pawson, Philip Pegion, Christopher R. Redder, Rolf Reichle, Franklin R. Robertson, Albert G. Ruddick, Meta Sienkiewicz, and Jack Woollen

1. Introduction Reanalyses combine model fields with observations distributed irregularly in space and time into a spatially complete gridded meteorological dataset, with an unchanging model and analysis system spanning the historical data record. The earlier generations of reanalyses from the National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction (NOAA/NCEP), the European Centre for Medium-Range Weather Forecasts (ECMWF), and the Japan Meteorological

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Michael A. Brunke, Zhuo Wang, Xubin Zeng, Michael Bosilovich, and Chung-Lin Shie

-Interim. The ERA-40 data were downloaded from the NCAR Research Data Archive (RDA) Web site ( http://dss.ucar.edu ), and the ERA-Interim data were downloaded from the mass storage on NCAR’s supercomputers. c. NCEP reanalyses The NCEP reanalyses compared here include NCEP–NCAR, NCEP–DOE, and the CFSR. NCEP–NCAR (also referred to as NCEP-I) was originally a 40-yr product ( Kalnay et al. 1996 ) but has been extended to near–real time. Its model is NCEP’s operational global forecasting model of the mid-1990s

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David H. Bromwich, Julien P. Nicolas, and Andrew J. Monaghan

). Furthermore, reanalyses may be contaminated by artificial trends in the data, such as caused by a temporal drift of satellite radiances ( Dee and Uppala 2008 , 2009 ). The most recent reanalyses have benefited from advances in operational weather forecasting and guidance from previous reanalysis efforts ( Bengtsson et al. 2007 ). A variational bias correction, allowing for an automatic and adaptive handling of biases in satellite radiances, has been implemented in ERA-Interim, MERRA, and CFSR. Improved

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Rolf H. Reichle, Randal D. Koster, Gabriëlle J. M. De Lannoy, Barton A. Forman, Qing Liu, Sarith P. P. Mahanama, and Ally Touré

study of the land surface water budget, including streamflow, droughts, soil moisture, and snow processes ( Dai and Trenberth 2002 ; Su and Lettenmaier 2009 ; Sheffield and Wood 2008 ; Burke et al. 2010 ; Brown et al. 2010 ), the estimation of the land carbon budget ( Zhao et al. 2006 ; Yi et al. 2011 ), and, possibly, the calibration and verification of seasonal climate forecasting systems ( Saha et al. 2006 ) and the generation of climate data records ( Thorne and Vose 2010 ; Dee et al. 2010

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Sun Wong, Eric J. Fetzer, Brian H. Kahn, Baijun Tian, Bjorn H. Lambrigtsen, and Hengchun Ye

.25° resolution, and extend globally from 50°S to 50°N. The GPCP 1DD data product is a 1° × 1° resolution daily precipitation dataset. It is based on the GPCP version 2.1 satellite-gauge product, which merges global precipitation-gauge analyses with precipitation retrievals from satellites including SSM/I, Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS), AIRS, and others ( Huffman et al. 2009 and references therein). In this study, the P fields are averaged daily

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Man-Li C. Wu, Oreste Reale, Siegfried D. Schubert, Max J. Suarez, and Chris D. Thorncroft

between midlatitude activity and tropical dynamics. That the ITCZ periodically breaks and reforms and that pulses of enhanced and reduced organized convection unrelated to AEW activity are observed in that latitude range is known to operational weather forecasting in the tropical Atlantic: with this work it is suggested that this is more than chaotic variability, but that it may be the result of the interaction between midlatitude activity and tropical dynamics. Over the African monsoon region and the

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Benjamin A. Schenkel and Robert E. Hart

are only affected by changes in the observing system ( Thorne and Vose 2010 ). Previous climate-scale studies of TCs utilizing reanalyses have included Hart et al. (2007) who used the 40-year European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40; Uppala et al. 2005 ) to quantify the environmental “memory” of TC passage. The ERA-40 was also used by Sriver and Huber (2006) to calculate TC power dissipation ( Emanuel 2005 ) to argue that increases in sea surface

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Aaron D. Kennedy, Xiquan Dong, Baike Xi, Shaocheng Xie, Yunyan Zhang, and Junye Chen

has been done to derive forcing using constrained variational analysis from observations during intensive observation periods (IOPs) at the Department of Energy (DOE) Atmospheric Radiation Measurement Program (ARM) sites ( Zhang and Lin 1997 ; Zhang et al. 2001 ). More recently, Xie et al. (2003) evaluated the forcing datasets derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) during three IOPs at the ARM Southern Great Plains (SGP) site. They found that although the

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