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Franklin R. Robertson, Michael G. Bosilovich, Junye Chen, and Timothy L. Miller

increments and relate these forcings to the stepwise evolution in passive microwave sensing associated with the AMSU-A and Special Sensor Microwave Imager (SSM/I) ( section 3 ). Section 4 provides some diagnostics on what aspects of climate variability within the 30-yr period survive or are distorted by these artifacts. We then use principal component analysis to characterize space–time variability of the increment terms. In section 5 we show how applying a statistical regression methodology to

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

assimilation technology. Because the errors of reanalyses and their underlying models are relatively unknown, their benefit for answering more complex questions involving the climate is questionable. For this reason, reanalyses have been used sparingly to generate forcing that provides initial and boundary conditions for single-column model (SCM) and cloud-resolving model (CRM) studies that can help develop improvements for general circulation models (GCMs). To circumnavigate these issues, extensive work

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Siegfried Schubert, Hailan Wang, and Max Suarez

1. Introduction The boreal summer extratropical circulation lacks the strong jets and large-amplitude stationary waves that typify the boreal winter climate. This, together with the presence of pervasive tropical easterlies that inhibit remote forcing from the tropics, tends to limit boreal summer middle-latitude variability to more local/regional processes, with mesoscale convective weather systems and land–atmosphere coupling playing important roles (e.g., Parker and Johnson 2000 ; Koster

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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

conditions, reanalysis products also provide estimates of land surface fields, including surface meteorological forcing data (such as precipitation, radiation, air temperature, and humidity) as well as land surface states and fluxes (such as soil moisture, snow, and runoff). Reanalysis estimates can be used for a large variety of research and applications, for example, the generation of enhanced land surface meteorological datasets ( Berg et al. 2005 ; Guo et al. 2006 ; Sheffield et al. 2006 ), the

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Franklin R. Robertson and Jason B. Roberts

second kind (wave-CISK; Lau and Peng 1987 ; Wang and Rui 1990 ; Salby et al. 1994 ), stochastic forcing by tropical ( Salby and Garcia 1987 ), and extratropical ( Blade and Hartmann 1993 ; Compo et al. 1999 ) sources, and an array of air–sea interaction processes controlling lower-tropospheric moisture ( Emanuel 1987 ; Neelin et al. 1987 ; Blade and Hartmann 1993 ; Kemball-Cook and Weare 2001 ; Raymond and Fuchs 2009 ). Second, even acknowledging recent novel advances in climate modeling (e

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Mark Decker, Michael A. Brunke, Zhuo Wang, Koichi Sakaguchi, Xubin Zeng, and Michael G. Bosilovich

cycle that is much too large over land during the warm seasons ( Janowiak et al. 1998 ). Similarly, Berg et al. (2003) found that the NCEP–NCAR reanalysis and ERA-40 have substantial biases in 2-m air and dewpoint temperatures, surface radiative fluxes, and precipitation over land in North America as compared with various gridded datasets. Aside from the atmospheric fields used to force land surface models, evapotranspiration during the warm season over the U.S. Great Plains region has also been

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Kyle F. Itterly and Patrick C. Taylor

timing and intensity unrealistically force the surface water and energy budget, leading to errors in surface runoff and evaporation ( Del Genio and Wu 2010 ). Decker et al. (2012) found significant errors in the diurnal cycle of surface turbulent fluxes in reanalysis models as well. Slingo et al. (2003) evaluated the diurnal cycle of the Hadley Centre Coupled Model, version 3 (HadCM3) GCM over the tropics and found the largest differences between the GCM and observations occur over the Maritime

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

centers such as the European Centre for Medium-Range Weather Forecasts (ECMWF), the National Centers for Environmental Prediction (NCEP), and the Japan Meteorological Agency (JMA). In addition, a set of experiments was performed to investigate the forcings contributing to the AEJ structure and position. WA09 results confirmed in part previous findings by Thorncroft and Blackburn (1999) , on the importance of low-level heating in controlling the AEJ, and by Cook (1999) , on the prominent role of

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

example, different reanalyses respond to global forcing with different circulation perturbations ( Chen et al. 2008a ). With several generations of reanalyses to consider, the various datasets generated from these efforts show large variance in the processes of the global water and energy budgets ( Chen et al. 2008a , b ; TFK09 ; Bosilovich et al. 2008 , 2009 ). Kalnay et al. (1996) , Uppala et al. (2005) , and Onogi et al. (2007) provide some of the most important overviews of existing long

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

are used for a variety of applications, including as a source for the development and verification of climate models, forcing data for numerous user models, examining forecast skill, estimation of renewable energy resources, investigation of extreme weather and climatic events, and health risk assessments. These datasets may also be an essential tool for performing studies in data-sparse regions such as the Arctic. Given its unique environmental characteristics and extreme surface conditions

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