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C. A. Randles, A. M. da Silva, V. Buchard, P. R. Colarco, A. Darmenov, R. Govindaraju, A. Smirnov, B. Holben, R. Ferrare, J. Hair, Y. Shinozuka, and C. J. Flynn

Reichle et al. (2017) that better represents diurnal precipitation changes compared to observations. Aerosol hygroscopic growth depends on simulated relative humidity and is considered in computations of particle fall velocity, deposition velocity, and optical parameters. Numerous studies have demonstrated the skill of the GOCART aerosol module in simulating AOD and other observable aerosol properties (e.g., Colarco et al. 2010 ; Nowottnick et al. 2010 , 2011 ; Bian et al. 2013 ). b. Emissions

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V. Buchard, C. A. Randles, A. M. da Silva, A. Darmenov, P. R. Colarco, R. Govindaraju, R. Ferrare, J. Hair, A. J. Beyersdorf, L. D. Ziemba, and H. Yu

et al. 2017 , hereafter Part I ). In recent years, to better understand the role of aerosols in the climate system and their impacts on air quality, significant efforts have been made to greatly increase both space- and ground-based observations of aerosols. Simultaneously, global aerosol models are becoming more complex while better representing many important observed aerosol properties [especially aerosol optical depth (AOD); Kinne et al. 2006 ]. Satellite observations have sparse

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Allison B. Marquardt Collow and Mark A. Miller

:// .] Rosário , N. E. , M. A. Yamasoe , H. Brindley , T. F. Eck , J. Schafer , 2011 : Downwelling solar irradiance in the biomass burning region of the southern Amazon: Dependence on aerosol intensive optical properties and role of water vapor . J. Geophys. Res. , 116 , D18304 , doi: 10.1029/2011JD015956 . Rutan , D. A. , and Coauthors , 2015 : CERES synoptic product: Methodology and validation of surface radiant flux . J. Atmos. Oceanic Technol. , 32 , 1121 – 1143

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Laura M. Hinkelman

and Southeast Asia, where dust is part of the overall aerosol mix. These improvements were noted in Buchard et al.’s (2017) study of the impacts of assimilating aerosol into MERRA and attributed to better dust optical properties and the inclusion of MISR aerosol data over bright desert areas. Although CSWDN has decreased over the tropical forests of Africa, no improvement is seen over the Amazon or the tropical islands of Southeast Asia. At the same time, the deficits over Greenland and

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Ronald Gelaro, Will McCarty, Max J. Suárez, Ricardo Todling, Andrea Molod, Lawrence Takacs, Cynthia A. Randles, Anton Darmenov, Michael G. Bosilovich, Rolf Reichle, Krzysztof Wargan, Lawrence Coy, Richard Cullather, Clara Draper, Santha Akella, Virginie Buchard, Austin Conaty, Arlindo M. da Silva, Wei Gu, Gi-Kong Kim, Randal Koster, Robert Lucchesi, Dagmar Merkova, Jon Eric Nielsen, Gary Partyka, Steven Pawson, William Putman, Michele Rienecker, Siegfried D. Schubert, Meta Sienkiewicz, and Bin Zhao

summed product of each species mass and its extinction coefficient based on aerosol optical properties derived largely from the OPAC dataset [see Randles et al. (2017) and references therein]. Emissions of both dust and sea salt are wind-driven for each of five size bins, parameterized following Marticorena and Bergametti (1995) and Gong (2003) , respectively. Sulfate and carbonaceous aerosol emissions derive from both natural and anthropogenic sources, as described in Randles et al. (2017

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Richard I. Cullather and Sophie M. J. Nowicki

that alters downwelling infrared flux properties, and/or by influencing turbulent fluxes and surface winds. It is widely acknowledged that the GrIS climate experiences considerable spatial variability (e.g., Chen et al. 1997 ; Vernon et al. 2013 ; Velicogna et al. 2014 ). The geographical proximity of an ice sheet location to anomalous circulation may produce localized conditions which enhance or inhibit melt. It is of interest to understand the conditions present during extreme melt events and

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Krzysztof Wargan, Gordon Labow, Stacey Frith, Steven Pawson, Nathaniel Livesey, and Gary Partyka

. 2004 ) from the OMI onboard EOS Aura . The dataset contains the climatological heights of the “optical centroid pressure,” which reflect how deep a UV photon, on average, will penetrate into the cloud. With this more accurate cloud height climatology, the errors produced by extrapolating ozone amounts under a cloud are minimized. Instrument noise for the majority of measurements is less than 0.5% ( DeLand et al. 2012 ). Bhartia et al. (2013) describes the V8.6 algorithm and related uncertainties

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