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

( u , υ , ω ) are the horizontal and vertical wind velocities, respectively; and S is referred to as the apparent water vapor sink in the literature ( Schumacher et al. 2008 ; Shige et al. 2008 ; Yanai et al. 1973 ) and differs from the conventional defined Q2 in the literature by a factor equal to the water latent heat of evaporation ( L ). The integrated S from the top of the atmosphere ( p t ) to the surface pressure ( p s ) (denoted as Σ) is approximately equal to P − E at the

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Yonghong Yi, John S. Kimball, Lucas A. Jones, Rolf H. Reichle, and Kyle C. McDonald

radiative transfer model accounts for surface emissivity variations caused by vegetation roughness and inland and coastal open water bodies and also for vertically integrated atmospheric water vapor, except for cloud liquid water effects. Differences in local timing of AMSR-E air temperature retrievals at ascending and descending overpasses and the timing of T max and T min are also accounted for ( Jones et al. 2010 ). The UM AMSR-E retrievals are provided over land under nonprecipitating and snow

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

precipitation (sum of convective, large-scale, and frozen forms). In the MERRA system, two nonphysical terms affect the moisture budget. Here F represents a very small amount of negative filling, ensuring positive water vapor content (less than 0.04% of precipitation or evaporation globally averaged). However, the ANA term represents the analysis increment of water vapor, which is on the order of magnitude of E − P . ANA is the water vapor forcing needed to constrain the evolution of the reanalysis steps

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Brian E. Mapes and Julio T. Bacmeister

in MERRA by the vertically integrated AT for water vapor, d 〈 q υ 〉/ dt ana ( Fig. 3 ). Positive AT values there suggest that the model physics has an overactive moisture sink (precipitation). We speculate that the convection scheme cues too strongly on surface-based parcel instability, which is closely tied to warm SST, and is too insensitive to the middle-level dry air, an important suppressing factor for convection in the AWP region. Fig . 3. Vertically integrated water vapor analysis

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

-Scaled Sonde Profiles (LSSONDE) datastream ( Turner et al. 1998 ). Because Vaisala RS-80 soundings have a known dry bias ( Turner et al. 2003 ), this datastream uses an empirical technique to scale sounding moisture profiles to match the microwave radiometer–derived atmospheric precipitable water vapor. b. ARM continuous forcing The ARM continuous forcing dataset developed for SCM/CRM applications is centered on the ARM SCF and is provided from January 1999 to December 2001. This forcing uses ARM surface

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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

generated by the DAS. The sea surface temperature and sea ice concentration boundary conditions are derived from the weekly 1° sea surface temperature product of Reynolds et al. (2002) , linearly interpolated in time to each model time step. The MERRA system also nudges the stratospheric water vapor to zonal-mean climatological values based on data from the Halogen Occultation Experiment (HALOE; Randel et al. 1998 ) and the Microwave Limb Sounder (MLS) on the Aura satellite. c. Production MERRA was

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

, including cloud optical depth and cloud height, should be investigated in the future as they also play key roles in determining the SW-down flux ( Dong and Mace 2003 ; Dong et al. 2010 ). Besides the cloud properties, the distribution of aerosol and other trace gases such as ozone and water vapor contained in the reanalyses can have a significant influence on the reanalyses' radiation parameterizations. Furthermore, the surface albedo can be an important factor in determining the amount of SW-down flux

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

increased rainout of assimilated water vapor and unrealistically high precipitation in the 40-yr ECMWF Re-Analysis (ERA-40). More exacting demands to accommodate the monitoring of decadal climate signals and the growing but ephemeral mix of remotely sensed data have spurred great progress in so-called bias aware methodologies ( Dee, 2005 ). Variationally constrained bias estimation strategies have been developed ( Derber and Wu 1998 ; Dee 2004 ) that embed the correction within the cost function

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Derek J. Posselt, Andrew R. Jongeward, Chuan-Yuan Hsu, and Gerald L. Potter

components, water vapor, clouds, and precipitation have proven more difficult to analyze accurately. The importance of characterizing cloud feedbacks in the climate system ( Stephens 2005 ) and increasing understanding of flood–drought cycles and extreme precipitation events has led to an increased focus on the realism of the hydrologic cycle in reanalyses ( Rienecker et al. 2011 ). The Modern-Era Retrospective Analysis for Research and Application (MERRA) is a reanalysis specifically designed to improve

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Franklin R. Robertson and Jason B. Roberts

describes the compositing methodology used to identify and frame intraseasonal signals. In section 3 , we review the behavior of some key quantities, primarily to provide context with earlier studies and to assure the quality of the temperature and moisture fields. The nature of the TOA radiative flux variability and its relationship to cloud behavior is addressed in section 4 . Section 5 examines atmospheric dry static energy and water vapor budgets and surface energy fluxes integrated over the

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