Editorial Type:
Article
Article Type:
Research Article

The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part II: Evaluation and Case Studies

V. Buchard Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
Goddard Earth Sciences Technology and Research/Universities Space Research Association, Columbia, Maryland

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C. A. Randles Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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A. M. da Silva Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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A. Darmenov Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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P. R. Colarco Atmospheric Chemistry and Dynamics Lab, NASA Goddard Space Flight Center, Greenbelt, Maryland

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R. Govindaraju Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
Science Systems and Applications, Inc., Lanham, Maryland

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R. Ferrare NASA Langley Research Center, Hampton, Virginia

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J. Hair NASA Langley Research Center, Hampton, Virginia

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A. J. Beyersdorf NASA Langley Research Center, Hampton, Virginia

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L. D. Ziemba NASA Langley Research Center, Hampton, Virginia

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H. Yu Climate and Radiation Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland
Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland

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Print Publication:
01 Sep 2017
Collections:
Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2)
DOI:
https://doi.org/10.1175/JCLI-D-16-0613.1
Page(s):
6851–6872
Restricted access

Abstract

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), is NASA’s latest reanalysis for the satellite era (1980 onward) using the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. MERRA-2 provides several improvements over its predecessor (MERRA-1), including aerosol assimilation for the entire period. MERRA-2 assimilates bias-corrected aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer and the Advanced Very High Resolution Radiometer instruments. Additionally, MERRA-2 assimilates (non bias corrected) AOD from the Multiangle Imaging SpectroRadiometer over bright surfaces and AOD from Aerosol Robotic Network sunphotometer stations. This paper, the second of a pair, summarizes the efforts to assess the quality of the MERRA-2 aerosol products. First, MERRA-2 aerosols are evaluated using independent observations. It is shown that the MERRA-2 absorption aerosol optical depth (AAOD) and ultraviolet aerosol index (AI) compare well with Ozone Monitoring Instrument observations. Next, aerosol vertical structure and surface fine particulate matter (PM2.5) are evaluated using available satellite, aircraft, and ground-based observations. While MERRA-2 generally compares well to these observations, the assimilation cannot correct for all deficiencies in the model (e.g., missing emissions). Such deficiencies can explain many of the biases with observations. Finally, a focus is placed on several major aerosol events to illustrate successes and weaknesses of the AOD assimilation: the Mount Pinatubo eruption, a Saharan dust transport episode, the California Rim Fire, and an extreme pollution event over China. The article concludes with a summary that points to best practices for using the MERRA-2 aerosol reanalysis in future studies.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-16-0613.s1.

Current affiliation: ExxonMobil Research and Engineering Company, Annandale, New Jersey.

Corresponding author: V. Buchard, virginie.buchard@nasa.gov

This article is included in the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) special collection.

Abstract

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), is NASA’s latest reanalysis for the satellite era (1980 onward) using the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. MERRA-2 provides several improvements over its predecessor (MERRA-1), including aerosol assimilation for the entire period. MERRA-2 assimilates bias-corrected aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer and the Advanced Very High Resolution Radiometer instruments. Additionally, MERRA-2 assimilates (non bias corrected) AOD from the Multiangle Imaging SpectroRadiometer over bright surfaces and AOD from Aerosol Robotic Network sunphotometer stations. This paper, the second of a pair, summarizes the efforts to assess the quality of the MERRA-2 aerosol products. First, MERRA-2 aerosols are evaluated using independent observations. It is shown that the MERRA-2 absorption aerosol optical depth (AAOD) and ultraviolet aerosol index (AI) compare well with Ozone Monitoring Instrument observations. Next, aerosol vertical structure and surface fine particulate matter (PM2.5) are evaluated using available satellite, aircraft, and ground-based observations. While MERRA-2 generally compares well to these observations, the assimilation cannot correct for all deficiencies in the model (e.g., missing emissions). Such deficiencies can explain many of the biases with observations. Finally, a focus is placed on several major aerosol events to illustrate successes and weaknesses of the AOD assimilation: the Mount Pinatubo eruption, a Saharan dust transport episode, the California Rim Fire, and an extreme pollution event over China. The article concludes with a summary that points to best practices for using the MERRA-2 aerosol reanalysis in future studies.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-16-0613.s1.

Current affiliation: ExxonMobil Research and Engineering Company, Annandale, New Jersey.

Corresponding author: V. Buchard, virginie.buchard@nasa.gov

This article is included in the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) special collection.

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  • Aquila, V., L. D. Oman, R. S. Stolarski, P. R. Colarco, and P. A. Newman, 2012: Dispersion of the volcanic sulfate cloud from a Mount Pinatubo–like eruption. J. Geophys. Res., 117, D06216, doi:10.1029/2011JD016968.

    • Search Google Scholar
    • Export Citation

  • Balkanski, Y., M. Schulz, T. Claquin, and S. Guibert, 2007: Reevaluation of mineral aerosol radiative forcings suggests a better agreement with satellite and AERONET data. Atmos. Chem. Phys., 7, 81–95, doi:10.5194/acp-7-81-2007.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Benedetti, A., and Coauthors, 2009: Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation. J. Geophys. Res., 114, D13205, doi:10.1029/2008JD011115.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Buchard, V., and Coauthors, 2014: Evaluation of GEOS-5 sulfur dioxide simulations during the Frostburg, MD 2010 field campaign. Atmos. Chem. Phys., 14, 1929–1941, doi:10.5194/acp-14-1929-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Buchard, V., and Coauthors, 2015: Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA aerosol reanalysis. Atmos. Chem. Phys., 15, 5743–5760, doi:10.5194/acp-15-5743-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Buchard, V., and Coauthors, 2016: Evaluation of the surface PM2.5 in version 1 of the NASA MERRA aerosol reanalysis over the United States. Atmos. Environ., 125, 100–111, doi:10.1016/j.atmosenv.2015.11.004.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Carn, S. A., L. Clarisse, and A. J. Prata, 2016: Multi-decadal satellite measurements of global volcanic degassing. J. Volcanol. Geotherm. Res., 311, 99–134, doi:10.1016/j.jvolgeores.2016.01.002.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chen, D., Z. Liu, C. Schwartz, H.-C. Lin, J. Cetola, Y. Gu, and L. Xue, 2014: The impact of aerosol optical depth assimilation on aerosol forecasts and radiative effects during a wild fire event over the United States. Geosci. Model Dev., 7, 2709–2715, doi:10.5194/gmd-7-2709-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chiapello, I., C. Moulin, and J. M. Prospero, 2005: Understanding the long-term variability of African dust transport across the Atlantic as recorded in both Barbados surface concentrations and large-scale Total Ozone Mapping Spectrometer (TOMS) optical thickness. J. Geophys. Res., 110, D18S10, doi:10.1029/2004JD005132.

    • Search Google Scholar
    • Export Citation

  • Chin, M., and Coauthors, 2002: Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements. J. Atmos. Sci., 59, 461–483, doi:10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Colarco, P. R., O. B. Toon, O. Torres, and P. J. Rasch, 2002: Determining the UV imaginary index of refraction of Saharan dust particles from Total Ozone Mapping Spectrometer data using a three-dimensional model of dust transport. J. Geophys. Res., 107, 4289, doi:10.1029/2001JD000903.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Colarco, P. R., M. Schoeberl, B. Doddridge, L. Marufu, O. Torres, and E. Welton, 2004: Transport of smoke from Canadian forest fires to the surface near Washington, DC: Injection height, entrainment, and optical properties. J. Geophys. Res., 109, D06203, doi:10.1029/2003JD004248.

    • Search Google Scholar
    • Export Citation

  • Colarco, P. R., A. da Silva, M. Chin, and T. Diehl, 2010: Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth. J. Geophys. Res., 115, D14207, doi:10.1029/2009JD012820.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Colarco, P. R., E. P. Nowottnick, C. A. Randles, B. Yi, P. Yang, K.-M. Kim, J. A. Smith, and C. G. Bardeen, 2014: Impact of radiatively interactive dust aerosols in the NASA GEOS-5 climate model: Sensitivity to dust particle shape and refractive index. J. Geophys. Res. Atmos., 119, 753–786, doi:10.1002/2013JD020046.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Darmenov, A. S., and A. da Silva, 2015: The Quick Fire Emissions Dataset (QFED)—Documentation of versions 2.1, 2.2 and 2.4. Technical Report Series on Global Modeling and Data Assimilation, NASA//TM-2015-104606, Vol. 38, 212 pp. [Available online at https://gmao.gsfc.nasa.gov/pubs/docs/Darmenov796.pdf.]

  • Dee, D. P., L. Rukhovets, R. Todling, A. M. Da Silva, and J. W. Larson, 2001: An adaptive buddy check for observational quality control. Quart. J. Roy. Meteor. Soc., 127, 2451–2471, doi:10.1002/qj.49712757714.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • de Graaf, M., and P. Stammes, 2005: SCIAMACHY Absorbing Aerosol Index—Calibration issues and global results from 2002–2004. Atmos. Chem. Phys., 5, 2385–2394, doi:10.5194/acp-5-2385-2005.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Diehl, T., A. Heil, M. Chin, X. Pan, D. Streets, M. Schultz, and S. Kinne, 2012: Anthropogenic, biomass burning, and volcanic emissions of black carbon, organic carbon, and SO2 from 1980 to 2010 for hindcast model experiments. Atmos. Chem. Phys. Discuss., 12, 24 895–24 954, doi:10.5194/acpd-12-24895-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Duncan, B. N., R. V. Martin, A. C. Staudt, R. Yevich, and J. A. Logan, 2003: Interannual and seasonal variability of biomass burning emissions constrained by satellite observations. J. Geophys. Res., 108, 4040, doi:10.1029/2002JD002378.

    • Search Google Scholar
    • Export Citation

  • EANET, 2001: Quality Assurance/Quality Control (QA/QC) program for the air concentration monitoring in East Asia. Acid Deposition Monitoring Network in East Asia, 25 pp. [Available online at http://www.eanet.cc/product/qaqc/qaqcair.pdf.]

  • EANET, 2006: Data report on the acid deposition in the East Asian region 2005. Acid Deposition Monitoring Network in East Asia, 255 pp. [Available online at www.eanet.asia/product/datarep/.]

  • Freitas, S. R., and Coauthors, 2007: Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models. Atmos. Chem. Phys., 7, 3385–3398, doi:10.5194/acp-7-3385-2007.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gelaro, R., and Coauthors, 2017: The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). J. Climate, 30, 5419–5454, doi:10.1175/JCLI-D-16-0758.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hair, J. W., and Coauthors, 2008: Airborne high spectral resolution lidar for profiling aerosol optical properties. Appl. Opt., 47, 6734–6752, doi:10.1364/AO.47.006734.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hammer, M. S., R. V. Martin, A. van Donkelaar, V. Buchard, O. Torres, D. A. Ridley, and R. J. D. Spurr, 2016: Interpreting the ultraviolet aerosol index observed with the OMI satellite instrument to understand absorption by organic aerosols: Implications for atmospheric oxidation and direct radiative effects. Atmos. Chem. Phys., 16, 2507–2523, doi:10.5194/acp-16-2507-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hand, J., and Coauthors, 2011: Spatial and seasonal patterns and temporal variability of haze and its constituents in the United States: Report V June 2011. Cooperative Institute for Research in the Atmosphere, Colorado State University, 507 pp. [Available online at http://vista.cira.colostate.edu/Improve/spatial-and-seasonal-patterns-and-temporal-variability-of-haze-and-its-constituents-in-the-united-states-report-v-june-2011/.]

  • Herman, J., P. Bhartia, O. Torres, C. Hsu, C. Seftor, and E. Celarier, 1997: Global distribution of UV-absorbing aerosols from Nimbus 7/TOMS data. J. Geophys. Res., 102, 16 911–16 922, doi:10.1029/96JD03680.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hess, M., P. Koepke, and I. Schult, 1998: Optical properties of aerosols and clouds: The software package OPAC. Bull. Amer. Meteor. Soc., 79, 831–844, doi:10.1175/1520-0477(1998)079<0831:OPOAAC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Holben, B., and Coauthors, 1998: AERONET—A federated instrument network and data archive for aerosol characterization. Remote Sens. Environ., 66, 1–16, doi:10.1016/S0034-4257(98)00031-5.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hsu, N. C., and Coauthors, 1999: Comparisons of the TOMS aerosol index with sun-photometer aerosol optical thickness: Results and applications. J. Geophys. Res., 104, 6269–6279, doi:10.1029/1998JD200086.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ji, D., and Coauthors, 2014: The heaviest particulate air-pollution episodes occurred in northern China in January, 2013: Insights gained from observation. Atmos. Environ., 92, 546–556, doi:10.1016/j.atmosenv.2014.04.048.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kinne, S., and Coauthors, 2006: An AeroCom initial assessment—Optical properties in aerosol component modules of global models. Atmos. Chem. Phys., 6, 1815–1834, doi:10.5194/acp-6-1815-2006.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kleist, D. T., D. F. Parrish, J. C. Derber, R. Treadon, W.-S. Wu, and S. Lord, 2009: Introduction of the GSI into the NCEP Global Data Assimilation System. Wea. Forecasting, 24, 1691–1705, doi:10.1175/2009WAF2222201.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Levelt, P. F., E. Hilsenrath, G. W. Leppelmeier, G. H. van den Oord, P. K. Bhartia, J. Tamminen, J. F. de Haan, and J. P. Veefkind, 2006: Science objectives of the Ozone Monitoring Instrument. IEEE Trans. Geosci. Remote Sens., 44, 1199–1208, doi:10.1109/TGRS.2006.872336.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Li, Z., Z. Zang, Q. B. Li, Y. Chao, D. Chen, Z. Ye, Y. Liu, and K. N. Liou, 2013: A three-dimensional variational data assimilation system for multiple aerosol species with WRF-Chem and an application to PM2.5 prediction. Atmos. Chem. Phys., 13, 4265–4278, doi:10.5194/acp-13-4265-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lynch, P., and Coauthors, 2016: An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences. Geosci. Model Dev., 9, 1489–1522, doi:10.5194/gmd-9-1489-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mahowald, N. M., and Coauthors, 2009: Atmospheric iron deposition: Global distribution, variability, and human perturbations. Annu. Rev. Mar. Sci., 1, 245–278, doi:10.1146/annurev.marine.010908.163727.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Malm, W. C., J. F. Sisler, D. Huffman, R. A. Eldred, and T. A. Cahill, 1994: Spatial and seasonal trends in particle concentration and optical extinction in the United States. J. Geophys. Res., 99, 1347–1370, doi:10.1029/93JD02916.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Malm, W. C., B. A. Schichtel, and M. L. Pitchford, 2011: Uncertainties in PM2.5 gravimetric and speciation measurements and what we can learn from them. J. Air Waste Manage. Assoc., 61, 1131–1149, doi:10.1080/10473289.2011.603998.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mauldin, L., N. Zaun, M. McCormick Jr., J. Guy, and W. Vaughn, 1985: Stratospheric Aerosol and Gas Experiment II instrument: A functional description. Opt. Eng., 24, 242307, doi:10.1117/12.7973473.

    • Crossref
    • Export Citation

  • McHenry, J. N., J. M. Vukovich, and N. C. Hsu, 2015: Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing. J. Air Waste Manag. Assoc., 65, 1395–1412, doi:10.1080/10962247.2015.1096862.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Meng, Z., P. Yang, G. W. Kattawar, L. Bi, K. N. Liou, and I. Laszlo, 2010: Single-scattering properties of tri-axial ellipsoidal mineral dust aerosols: A database for application to radiative transfer calculations. J. Aerosol Sci., 41, 501–512, doi:10.1016/j.jaerosci.2010.02.008.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mergenthaler, J., J. Kumer, and A. Roche, 1995: CLAES observations of Mt. Pinatubo stratospheric aerosol. Geophys. Res. Lett., 22, 3497–3500, doi:10.1029/95GL02787.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Molod, A. M., L. L. Takas, M. Suarez, and J. Bacmeister, 2015: Development of the GEOS-5 atmospheric general circulation model: Evolution from MERRA to MERRA-2. Geosci. Model Dev., 8, 1339–1356, doi:10.5194/gmd-8-1339-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Nowottnick, E. P., P. R. Colarco, E. J. Welton, and A. da Silva, 2015: Use of the CALIOP vertical feature mask for evaluating global aerosol models. Atmos. Meas. Tech., 8, 3647–3669, doi:10.5194/amt-8-3647-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Pérez, C., and Coauthors, 2011: Atmospheric dust modeling from meso to global scales with the online NMMB/BSC-Dust model—Part 1: Model description, annual simulations and evaluation. Atmos. Chem. Phys., 11, 13 001–13 027, doi:10.5194/acp-11-13001-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Peterson, D. A., E. J. Hyer, J. R. Campbell, M. D. Fromm, J. W. Hair, C. F. Butler, and M. A. Fenn, 2015: The 2013 Rim Fire: Implications for predicting extreme fire spread, pyroconvection, and smoke emissions. Bull. Amer. Meteor. Soc., 96, 229–247, doi:10.1175/BAMS-D-14-00060.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Pope, C. A., and D. W. Dockery, 2013: Air pollution and life expectancy in China and beyond. Proc. Natl. Acad. Sci. USA, 110, 12 861–12 862, doi:10.1073/pnas.1310925110.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Pope, C. A., M. Ezzati, and D. W. Dockery, 2009: Fine-particulate air pollution and life expectancy in the United States. N. Engl. J. Med., 360, 376–386, doi:10.1056/NEJMsa0805646.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Prospero, J. M., and R. T. Nees, 1986: Impact of the North African drought and El Niño on mineral dust in the Barbados trade winds. Nature, 320, 735–738, doi:10.1038/320735a0.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Prospero, J. M., and P. J. Lamb, 2003: African droughts and dust transport to the Caribbean: Climate change implications. Science, 302, 1024–1027, doi:10.1126/science.1089915.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Prospero, J. M., W. M. Landing, and M. Schulz, 2010: African dust deposition to Florida: Temporal and spatial variability and comparisons to models. J. Geophys. Res., 115, D13304, doi:10.1029/2009JD012773.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Randerson, J. T., and Coauthors, 2006: The impact of boreal forest fire on climate warming. Science, 314, 1130–1132, doi:10.1126/science.1132075.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Randles, C. A., and Coauthors, 2016: Aerosols in MERRA-2. Technical Report Series on Global Modeling and Data Assimilation 44, NASA Global Modeling and Assimilation Office. [Available online at https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/docs/.]

  • Randles, C. A., and Coauthors, 2017: The MERRA-2 aerosol reanalysis, 1980 onward, Part I: System description and data assimilation evaluation. J. Climate, 30, 6823–6850, doi:10.1175/JCLI-D-16-0609.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rienecker, M. M., and Coauthors, 2008: The GEOS-5 Data Assimilation System—Documentation of versions 5.0.1, 5.1.0, and 5.2.0. NASA/TM-2008-104606, Vol. 27, NASA Global Modeling and Assimilation Office, 101 pp. [Available online at https://gmao.gsfc.nasa.gov/pubs/docs/Rienecker369.pdf.]

  • Rienecker, M. M., and Coauthors, 2011: MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 3624–3648, doi:10.1175/JCLI-D-11-00015.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rubin, J. I., and Coauthors, 2016: Development of the Ensemble Navy Aerosol Analysis Prediction System (ENAAPS) and its application of the Data Assimilation Research Testbed (DART) in support of aerosol forecasting. Atmos. Chem. Phys., 16, 3927–3951, doi:10.5194/acp-16-3927-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Saide, P. E., J. Kim, C. H. Song, M. Choi, Y. Cheng, and G. R. Carmichael, 2014: Assimilation of next generation geostationary aerosol optical depth retrievals to improve air quality simulations. Geophys. Res. Lett., 41, 9188–9196, doi:10.1002/2014GL062089.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Schwartz, C. S., Z. Liu, H.-C. Lin, and J. D. Cetola, 2014: Assimilating aerosol observations with a “hybrid” variational-ensemble data assimilation system. J. Geophys. Res. Atmos., 119, 4043–4069, doi:10.1002/2013JD020937.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sekiyama, T., T. Tanaka, A. Shimizu, and T. Miyoshi, 2010: Data assimilation of CALIPSO aerosol observations. Atmos. Chem. Phys., 10, 39–49, doi:10.5194/acp-10-39-2010.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Spurr, R., 2006: VLIDORT: A linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media. J. Quant. Spectrosc., 102, 316–342, doi:10.1016/j.jqsrt.2006.05.005.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sun, Y., Q. Jiang, Z. Wang, P. Fu, J. Li, T. Yang, and Y. Yin, 2014: Investigation of the sources and evolution processes of severe haze pollution in Beijing in January 2013. J. Geophys. Res., 119, 4380–4398, doi:10.1002/2014JD021641.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tagliabue, A., L. Bopp, and O. Aumont, 2009: Evaluating the importance of atmospheric and sedimentary iron sources to Southern Ocean biogeochemistry. Geophys. Res. Lett., 36, L13601, doi:10.1029/2009GL038914.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tanaka, T. Y., K. Orito, T. T. Sekiyama, K. Shibata, M. Chiba, and H. Tanaka, 2003: MASINGAR, a global tropospheric aerosol chemical transport model coupled with MRI/JMA98 GCM: Model description. Pap. Meteor. Geophys., 53, 119–138, doi:10.2467/mripapers.53.119.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Textor, C., and Coauthors, 2006: Analysis and quantification of the diversities of aerosol life cycles within AeroCom. Atmos. Chem. Phys., 6, 1777–1813, doi:10.5194/acp-6-1777-2006.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Thomason, L. A., and T. Peter, Eds., 2006: SPARC Assessment of Stratospheric Aerosol Properties (ASAP). SPARC Tech. Rep., WCRP-124, WMO/TD-No. 1295, 322 pp. [Available online at www.sparc-climate.org/publications/sparc-reports/.]

  • Torres, O., P. Bhartia, J. Herman, Z. Ahmad, and J. Gleason, 1998: Derivation of aerosol properties from satellite measurements of backscattered ultraviolet radiation: Theoretical basis. J. Geophys. Res., 103, 17 099–17 110, doi:10.1029/98JD00900.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Torres, O., A. Tanskanen, B. Veihelmann, C. Ahn, R. Braak, P. K. Bhartia, P. Veefkind, and P. Levelt, 2007: Aerosols and surface UV products from Ozone Monitoring Instrument observations: An overview. J. Geophys. Res., 112, D24S47, doi:10.1029/2007JD008809.

    • Search Google Scholar
    • Export Citation

  • Torres, O., C. Ahn, and Z. Chen, 2013: Improvements to the OMI near-UV aerosol algorithm using A-Train CALIOP and AIRS observations. Atmos. Meas. Tech., 6, 3257–3270, doi:10.5194/amt-6-3257-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • van der Werf, G. R., J. T. Randerson, L. Giglio, G. J. Collatz, P. S. Kasibhatla, and A. F. Arellano, 2006: Interannual variability in global biomass burning emissions from 1997 to 2004. Atmos. Chem. Phys., 6, 3423–3441, doi:10.5194/acp-6-3423-2006.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • van Donkelaar, A., R. V. Martin, M. Brauer, R. Kahn, R. Levy, C. Verduzco, and P. J. Villeneuve, 2010: Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: Development and application. Environ. Health Perspect., 118, 847–855, doi:10.1289/ehp.0901623.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Winker, D. M., W. H. Hunt, and M. J. McGill, 2007: Initial performance assessment of CALIOP. Geophys. Res. Lett., L19803, doi:10.1029/2007GL030135.

  • Winker, D. M., M. A. Vaughan, A. Omar, Y. Hu, K. A. Powell, Z. Liu, W. H. Hunt, and S. A. Young, 2009: Overview of the CALIPSO mission and CALIOP data processing algorithms. J. Atmos. Oceanic Technol., 26, 2310–2323, doi:10.1175/2009JTECHA1281.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wu, W.-S., R. J. Purser, and D. F. Parrish, 2002: Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon. Wea. Rev., 130, 2905–2916, doi:10.1175/1520-0493(2002)130<2905:TDVAWS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Yu, H., L. A. Remer, R. A. Kahn, M. Chin, and Y. Zhang, 2013: Satellite perspective of aerosol intercontinental transport: From qualitative tracking to quantitative characterization. Atmos. Res., 124, 73–100, doi:10.1016/j.atmosres.2012.12.013.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zhang, J., J. S. Reid, D. L. Westphal, N. L. Baker, and E. J. Hyer, 2008: A system for operational aerosol optical depth data assimilation over global oceans. J. Geophys. Res., 113, D10208, doi:10.1029/2007JD009065.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zheng, B., and Coauthors, 2015: Heterogeneous chemistry: A mechanism missing in current models to explain secondary inorganic aerosol formation during the January 2013 haze episode in north China. Atmos. Chem. Phys., 15, 2031–2049, doi:10.5194/acp-15-2031-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ziemba, L. D., and Coauthors, 2016: Airborne observations of bioaerosol over the southeast United States using a Wideband Integrated Bioaerosol Sensor (WIBS-4A). J. Geophys. Res. Atmos., 121, 8506–8524, doi:10.1002/2015JD024669.

    • Crossref
    • Search Google Scholar
    • Export Citation
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