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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

axes have been relabeled in linear AOD space for clarity. 3) Comparisons with aircraft observations The NASA Langley Research Center (LaRC) Differential Absorption Lidar (DIAL) system implements the High Spectral Resolution Lidar (HSRL) technique to retrieve aerosol extinction and AOD at 532 nm ( Hair et al. 2008 ). The instrument also retrieves aerosol backscatter coefficients and is sensitive to polarization at three wavelengths (355, 532, and 1064 nm), measuring both above and below the aircraft

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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

—the aerosol index (AI) and absorption AOD (AAOD)—compared with Ozone Monitoring Instrument (OMI) measurements. Next, we evaluate the vertical distribution of aerosols using lidar observations from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) and from airborne High Spectral Resolution Lidar (HSRL) instruments during atmospheric composition field campaigns over the United States. The last part of this section is a qualitative evaluation of MERRA-2 surface PM 2.5 on a global scale followed

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Allison B. Marquardt Collow and Mark A. Miller

the standard deviation of the daily averages. MERRA-2 is rather accurate in its assessment of the integrated water vapor, with MERRA-2 and the observations never deviating more than 0.15% of one another ( Fig. 1b ). MERRA-2 performs well for most months for cloud coverage as well. Cloud coverage is lower in the months of June and July in MERRA-2, with values that are more similar to CERES observations compared to observations from the micropulse lidar. This is not surprising considering both MERRA

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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

arises from differences between estimates from global models and satellite-based estimates ( Myhre 2009 ). However, as aerosol reanalyses like MERRA-2 continue to mature and incorporate additional observations (e.g., from lidars and multispectral sensors), we expect a narrowing of the gap between simulated and satellite-based estimates of the DRE. Table 4. Clear-sky DRE from reanalyses and observations. Observed median and std dev from satellite-derived estimates in Yu et al. (2006) , median and

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

MIPAS overestimates ozone below 50 hPa compared to ozonesondes and lidar observations, especially in the tropics, where the differences exceed 10% (see their Fig. 6), and report a much better agreement between SAGE II and independent data. Between 60 and 50 hPa, MERRA-2 is biased low compared to SAGE II, UARS MLS, and MIPAS observations. The key conclusions regarding the stratospheric ozone variability in MERRA-2 are summarized as follows: The difference standard deviations are within 20% between

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