The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)

Ronald Gelaro Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Will McCarty Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Max J. Suárez Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
Universities Space Research Association, Columbia, Maryland

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Ricardo Todling Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Andrea Molod Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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

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Cynthia A. Randles Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
Morgan State University, Baltimore, Maryland

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

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Michael G. Bosilovich Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Rolf Reichle Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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

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

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Richard Cullather Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland

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Clara Draper Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
Universities Space Research Association, Columbia, Maryland

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

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Virginie Buchard Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
Universities Space Research Association, Columbia, Maryland

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

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

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

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Gi-Kong Kim Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Randal Koster Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Robert Lucchesi Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
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William Putman Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Michele Rienecker Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Siegfried D. Schubert Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
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Meta Sienkiewicz Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
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Bin Zhao Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
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Abstract

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), is the latest atmospheric reanalysis of the modern satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO). MERRA-2 assimilates observation types not available to its predecessor, MERRA, and includes updates to the Goddard Earth Observing System (GEOS) model and analysis scheme so as to provide a viable ongoing climate analysis beyond MERRA’s terminus. While addressing known limitations of MERRA, MERRA-2 is also intended to be a development milestone for a future integrated Earth system analysis (IESA) currently under development at GMAO. This paper provides an overview of the MERRA-2 system and various performance metrics. Among the advances in MERRA-2 relevant to IESA are the assimilation of aerosol observations, several improvements to the representation of the stratosphere including ozone, and improved representations of cryospheric processes. Other improvements in the quality of MERRA-2 compared with MERRA include the reduction of some spurious trends and jumps related to changes in the observing system and reduced biases and imbalances in aspects of the water cycle. Remaining deficiencies are also identified. Production of MERRA-2 began in June 2014 in four processing streams and converged to a single near-real-time stream in mid-2015. MERRA-2 products are accessible online through the NASA Goddard Earth Sciences Data Information Services Center (GES DISC).

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

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

Current affiliation: I.M. System Group, Inc., Rockville, Maryland.

Corresponding author: Ronald Gelaro, ron.gelaro@nasa.gov

Abstract

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), is the latest atmospheric reanalysis of the modern satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO). MERRA-2 assimilates observation types not available to its predecessor, MERRA, and includes updates to the Goddard Earth Observing System (GEOS) model and analysis scheme so as to provide a viable ongoing climate analysis beyond MERRA’s terminus. While addressing known limitations of MERRA, MERRA-2 is also intended to be a development milestone for a future integrated Earth system analysis (IESA) currently under development at GMAO. This paper provides an overview of the MERRA-2 system and various performance metrics. Among the advances in MERRA-2 relevant to IESA are the assimilation of aerosol observations, several improvements to the representation of the stratosphere including ozone, and improved representations of cryospheric processes. Other improvements in the quality of MERRA-2 compared with MERRA include the reduction of some spurious trends and jumps related to changes in the observing system and reduced biases and imbalances in aspects of the water cycle. Remaining deficiencies are also identified. Production of MERRA-2 began in June 2014 in four processing streams and converged to a single near-real-time stream in mid-2015. MERRA-2 products are accessible online through the NASA Goddard Earth Sciences Data Information Services Center (GES DISC).

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

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

Current affiliation: I.M. System Group, Inc., Rockville, Maryland.

Corresponding author: Ronald Gelaro, ron.gelaro@nasa.gov
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  • Adler, R. F., and Coauthors, 2003: The Version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167, doi:10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Akella, S., R. Todling, and M. Suárez, 2016: Assimilation for skin SST in the NASA GEOS atmospheric data assimilation system. Quart. J. Roy. Meteor. Soc., 143, 10321046, doi:10.1002/qj.2988.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Andrews, D. G., J. R. Holton, and C. B. Leovy, 1987: Middle Atmosphere Dynamics. Academic Press, 489 pages.

  • Bacmeister, J. T., and G. Stephens, 2011: Spatial statistics of likely convective clouds in CloudSat data. J. Geophys. Res., 116, D04104, doi:10.1029/2010JD014444.

    • Search Google Scholar
    • Export Citation
  • Ballish, B. A., and V. K. Kumar, 2008: Systematic differences in aircraft and radiosonde temperatures. Bull. Amer. Meteor. Soc., 89, 16891707, doi:10.1175/2008BAMS2332.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bauer, P., A. J. Geer, P. Lopez, and D. Salmond, 2010: Direct 4D-Var assimilation of all-sky radiances. Part I: Implementation. Quart. J. Roy. Meteor. Soc., 136, 18681885, doi:10.1002/qj.659.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bellouin, N., J. Quaas, J.-J. Morcrette, and O. Boucher, 2013: Estimates of aerosol radiative forcing from the MACC re-analysis. Atmos. Chem. Phys., 13, 20452062, doi:10.5194/acp-13-2045-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berrisford, P., P. Kallberg, S. Kobayashi, D. Dee, S. Uppala, A. J. Simmons, P. Poli, and H. Sato, 2011: Atmospheric conservation properties in ERA-Interim. Quart. J. Roy. Meteor. Soc., 137, 13811399, doi:10.1002/qj.864.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bloom, S., L. Takacs, A. DaSilva, and D. Ledvina, 1996: Data assimilation using incremental analysis updates. Mon. Wea. Rev., 124, 12561271, doi:10.1175/1520-0493(1996)124<1256:DAUIAU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bocquet, M., and Coauthors, 2015: Data assimilation in atmospheric chemistry models: Current and future prospects for coupled chemistry meteorology models. Atmos. Chem. Phys., 15, 53255358, doi:10.5194/acp-15-5325-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bosilovich, M. G., 2013: Regional climate and variability in NASA MERRA and recent reanalyses: U.S. summertime precipitation and temperature. J. Appl. Meteor. Climatol., 52, 19391951, doi:10.1175/JAMC-D-12-0291.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bosilovich, M. G., F. R. Robertson, and J. Chen, 2011: Global energy and water budgets in MERRA. J. Climate, 24, 57215739, doi:10.1175/2011JCLI4175.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bosilovich, M. G., and Coauthors, 2015: MERRA-2: Initial evaluation of the climate. Technical Report Series on Global Modeling and Data Assimilation, Vol. 43, NASA Tech. Rep. NASA/TM–2015–104606, 139 pp. [Available online at https://gmao.gsfc.nasa.gov/pubs/docs/Bosilovich803.pdf.]

  • Bosilovich, M. G., R. Lucchesi, and M. Suarez, 2016: MERRA-2: File specification. GMAO Office Note 9, 73 pp. [Available online at https://gmao.gsfc.nasa.gov/pubs/docs/Bosilovich785.pdf.]

  • Bosilovich, M. G., F. Robertson, L. Takacs, A. Molod, and D. Mocko, 2017: Atmospheric water balance and variability in the MERRA-2 reanalysis. J. Climate, 30, 11771196, doi:10.1175/JCLI-D-16-0338.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Box, J. E., and A. Rinke, 2003: Evaluation of Greenland Ice Sheet surface climate in the HIRHAM regional climate model using automatic weather station data. J. Climate, 16, 13021319, doi:10.1175/1520-0442-16.9.1302.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brassington, G. B., and Coauthors, 2015: Progress and challenges in short- to medium- range coupled prediction. J. Oper. Oceanogr., 8, 239258, doi:10.1080/1755876X.2015.1049875.

    • 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, 57435760, doi:10.5194/acp-15-5743-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cardinali, C., L. Isaksen, and E. Anderson, 2003: Use and impact of automated aircraft data in a global 4DVAR data assimilation system. Mon. Wea. Rev., 131, 18651877, doi:10.1175//2569.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, Y., F. Weng, Y. Han, and Q. Liu, 2008: Validation of the Community Radiative Transfer Model (CRTM) by using CloudSat data. J. Geophys. Res., 113, 21562202, doi:10.1029/2007JD009561.

    • 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, 461483, doi:10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chýlek, P., and J. A. Coakley, 1974: Aerosol and climate. Science, 183, 7577, doi:10.1126/science.183.4120.75.

  • Colarco, P., 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
  • Collow, A. B. M., and M. A. Miller, 2016: The seasonal cycle of the radiation budget and cloud radiative effect in the Amazon rain forest of Brazil. J. Climate, 29, 77037722, doi:10.1175/JCLI-D-16-0089.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collow, A. B. M., M. G. Bosilovich, and R. D. Koster, 2016: Large-scale influences on summertime extreme precipitation in the northeastern United States. J. Hydrometeor., 17, 30453061, doi:10.1175/JHM-D-16-0091.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colony, R., I. Appel, and I. Rigor, 1992: Surface air temperature observations in the Arctic Basin. Applied Physics Laboratory, University of Washington Tech. Memo. TM 1-92, 120 pp.

  • Compo, G. P., and Coauthors, 2011: The Twentieth Century Reanalysis Project. Quart. J. Roy. Meteor. Soc., 137, 128, doi:10.1002/qj.776.

  • Coy, L., K. Wargan, A. M. Molod, W. R. McCarty, and S. Pawson, 2016: Structure and dynamics of the quasi-biennial oscillation in MERRA-2. J. Climate, 29, 53395354, doi:10.1175/JCLI-D-15-0809.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cullather, R. I., and M. G. Bosilovich, 2012: The energy budget of the polar atmosphere in MERRA. J. Climate, 25, 524, doi:10.1175/2011JCLI4138.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cullather, R. I., S. M. J. Nowicki, B. Zhao, and M. J. Suárez, 2014: Evaluation of the surface representation of the Greenland Ice Sheet in a general circulation model. J. Climate, 27, 48354856, doi:10.1175/JCLI-D-13-00635.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Darmenov, A., 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, Vol. 32, NASA Tech. Rep. NASA/TM–2015–104606, 201 pp. [Available online at https://gmao.gsfc.nasa.gov/pubs/docs/Darmenov796.pdf.]

  • Decker, M., M. A. Brunke, Z. Wang, K. Sakaguchi, X. Zeng, and M. G. Bosilovich, 2011: Evaluation of the reanalysis products from GSFC, NCEP, and ECMWF using flux tower observations. J. Climate, 24, 221249, doi:10.1175/JCLI-D-11-00004.1.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and A. M. da Silva, 2003: The choice of variable for atmospheric moisture analysis. Mon. Wea. Rev., 131, 155171, doi:10.1175/1520-0493(2003)131<0155:TCOVFA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and S. Uppala, 2009: Variational bias correction of satellite radiance data in the ERA-Interim reanalysis. Quart. J. Roy. Meteor. Soc., 135, 18301841, doi:10.1002/qj.493.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Derber, J. C., and W.-S. Wu, 1998: The use of TOVS cloud-cleared radiances in the NCEP SSI analysis system. Mon. Wea. Rev., 126, 22872299, doi:10.1175/1520-0493(1998)126<2287:TUOTCC>2.0.CO;2.

    • 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 89524 954, doi:10.5194/acpd-12-24895-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Donlon, C. J., M. Martin, J. Stark, J. Roberts-Jones, E. Fiedler, and W. Wimmer, 2012: The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system. Remote Sens. Environ., 116, 140158, doi:10.1016/j.rse.2010.10.017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duynkerke, P., and S. de Roode, 2001: Surface energy balance and turbulence characteristics observed at the SHEBA Ice Camp during FIRE III. J. Geophys. Res., 106, 15 31315 322, doi:10.1029/2000JD900537.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Farman, J., B. Gardiner, and J. Shanklin, 1985: Large losses of total ozone in Antarctica reveal seasonal ClOx/NOx interaction. Nature, 315, 207210, doi:10.1038/315207a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fettweis, X., 2007: Reconstruction of the 1979–2006 Greenland ice sheet surface mass balance using the regional climate model MAR. Cryosphere, 1, 2140, doi:10.5194/tc-1-21-2007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Flemming, J., and Coauthors, 2017: The CAMS interim reanalysis of carbon monoxide, ozone and aerosol for 2003–2015. Atmos. Chem. Phys., 17, 19451983, doi:10.5194/acp-17-1945-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Froidevaux, L., and Coauthors, 2006: Early validation analyses of atmospheric profiles from EOS MLS on the Aura satellite. IEEE Trans. Geosci. Remote Sens., 44, 11061121, doi:10.1109/TGRS.2006.864366.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • GMAO, 2015a: MERRA-2 inst1_2d_asm_Nx: 2d, 3-hourly, instantaneous, single-level, assimilation, single-level diagnostics V5.12.4. GES DISC, accessed June 2016, doi:10.5067/3Z173KIE2TPD.

    • Crossref
    • Export Citation
  • GMAO, 2015b: MERRA-2 inst1_2d_int_Nx: 2d, 1-hourly, instantaneous, single-level, assimilation, vertically integrated diagnostics V5.12.4. GES DISC, accessed June 2016, doi:10.5067/G0U6NGQ3BLE0.

    • Crossref
    • Export Citation
  • GMAO, 2015c: MERRA-2 inst3_3d_asm_Np: 3d, 3-hourly, instantaneous, pressure-level, assimilation, assimilated meteorological fields, V5.12.4. Goddard Space Flight Center Distributed Active Archive Center, accessed June 2016, doi:10.5067/QBZ6MG944HW0.

    • Crossref
    • Export Citation
  • GMAO, 2015d: MERRA-2 tavg1_2d_flx_Nx: 2d, 1-hourly, time-averaged, single-level, assimilation, surface flux diagnostics V5.12.4. GES DISC, accessed June 2016, doi:10.5067/7MCPBJ41Y0K6.

    • Crossref
    • Export Citation
  • GMAO, 2015e: MERRA-2 tavg1_2d_int_Nx: 2d, 1-hourly, time-averaged, single-level, assimilation, vertically integrated diagnostics V5.12.4. GES DISC, accessed June 2016, doi:10.5067/Q5GVUVUIVGO7.

    • Crossref
    • Export Citation
  • GMAO, 2015f: MERRA-2 tavg1_2d_slv_Nx: 2d, 1-hourly, time-averaged, single-level, assimilation, single-level diagnostics V5.12.4. GES DISC, accessed June 2016, doi:10.5067/VJAFPLI1CSIV.

    • Crossref
    • Export Citation
  • GMAO, 2015g: MERRA-2 tavgM_2d_aer_Nx: 2d, monthly mean, time-averaged, single-level, assimilation, aerosol diagnostics V5.12.4. Goddard Space Flight Center Distributed Active Archive Center, accessed June 2016, doi:10.5067/FH9A0MLJPC7N.

    • Crossref
    • Export Citation
  • GMAO, 2015h: MERRA-2 tavgM_2d_flx_Nx: 2d, monthly mean, time-averaged, single-level, assimilation, surface flux diagnostics V5.12.4. GES DISC, accessed June 2016, doi:10.5067/0JRLVL8YV2Y4.

    • Crossref
    • Export Citation
  • GMAO, 2015i: MERRA-2 tavgM_2d_glc_Nx: 2d, monthly mean, land ice surface diagnostics, V5.12.4. Goddard Space Flight Center Distributed Active Archive Center, accessed June 2015, doi:10.5067/5W8Q3I9WUFGX.

    • Crossref
    • Export Citation
  • GMAO, 2015j: MERRA-2 tavgM_2d_lnd_Nx: 2d, monthly mean, land surface diagnostics, V5.12.4. Goddard Space Flight Center Distributed Active Archive Center, accessed June 2015, doi:10.5067/8S35XF81C28F.

    • Crossref
    • Export Citation
  • GMAO, 2015k: MERRA-2 tavgM_2d_int_Nx: 2d, monthly mean, time-averaged, single-level, assimilation, vertically integrated diagnostics V5.12.4. GES DISC, accessed June 2015, doi:10.5067/FQPTQ4OJ22TL.

    • Crossref
    • Export Citation
  • GMAO, 2015l: MERRA-2 tavgM_3d_qdt_Np: 3d, monthly mean, time-averaged, pressure-level, assimilation, moist tendencies V5.12.4. GES DISC, accessed June 2016, doi:10.5067/2ZTU87V69ATP.

    • Crossref
    • Export Citation
  • GMAO, 2015m: MERRA-2 tavgM_2d_slv_Nx: 2d, monthly mean, single-level diagnostics, V5.12.4. Goddard Space Flight Center Distributed Active Archive Center, accessed April 2015, doi:10.5067/AP1B0BA5PD2K.

    • Crossref
    • Export Citation
  • GMAO, 2015n: MERRA-2 tavgM_3d_tdt_Np: 3d, monthly mean, time-averaged, pressure-level, assimilation, temperature tendencies V5.12.4. GES DISC, accessed June 2016, doi:10.5067/VILT59HI2MOY.

    • Crossref
    • Export Citation
  • Gong, S. L., 2003: A parameterization of sea-salt aerosol source function for sub- and super-micron particles. Global Biogeochem. Cycles, 17, 1097, doi:10.1029/2003GB002079.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Greuell, W., and T. Konzelmann, 1994: Numerical modelling of the energy balance and englacial temperature of the Greenland Ice Sheet. Calculations for the ETH-Camp location (West Greenland, 1155 m a.s.l.). Global Planet. Change, 9, 91114, doi:10.1016/0921-8181(94)90010-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ham, Y.-G., S. Schubert, Y. Vikhliaev, and M. J. Suárez, 2014: An assessment of the ENSO forecast skill of GEOS-5 system. Climate Dyn., 43, 2415, doi: 10.1007/s00382-014-2063-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Han, Y., P. van Delst, Q. Liu, F. Weng, B. Yan, R. Treadon, and J. Derber, 2006: JCSDA Community Radiative Transfer Model (CRTM)–Version 1. NOAA Tech. Rep. 122, 33 pp. [Available online at https://docs.lib.noaa.gov/noaa_documents/NESDIS/TR_NESDIS/TR_NESDIS_122.pdf.]

  • Heidinger, A. K., C. Cao, and J. T. Sullivan, 2002: Using Moderate Resolution Imaging Spectrometer (MODIS) to calibrate Advanced Very High Resolution Radiometer reflectance channels. J. Geophys. Res., 107, 4702, doi:10.1029/2001JD002035.

    • Search Google Scholar
    • Export Citation
  • Hoch, S. W., 2005: Radiative flux divergence in the surface boundary layer. A study based on observations at Summit, Greenland. Ph.D. dissertation, Swiss Federal Institute of Technology, 164 pp.

  • Holben, B., and Coauthors, 1998: AERONET—A federated instrument network and data archive for aerosol characterization. Remote Sens. Environ., 66, 116, doi:10.1016/S0034-4257(98)00031-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holm, E. V., 2003: Revision of the ECMWF humidity analysis: Construction of a Gaussian control variable. Proc. ECMWF/GEWEX Workshop on Humidity Analysis, Reading, United Kingdom, ECMWF/GEWEX, 6 pp. [Available online at http://www.ecmwf.int/sites/default/files/elibrary/2003/9998-revision-ecmwf-humidity-analysis-construction-gaussian-control-variable.pdf.]

  • Inness, A. F., and Coauthors, 2013: The MACC reanalysis: An 8 yr data set of atmospheric composition. Atmos. Chem. Phys., 13, 40734109, doi:10.5194/acp-13-4073-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kahn, R. A., B. J. Gaitley, J. V. Martonchik, D. J. Diner, K. A. Crean, and B. Holben, 2005: Multiangle Imaging Spectroradiometer (MISR) global aerosol optical depth validation based on 2 years of coincident Aerosol Robotic Network (AERONET) observations. J. Geophys. Res., 110, D10S04, doi:10.1029/2004JD004706.

    • 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, 18151834, doi:10.5194/acp-6-1815-2006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kleist, D. T., D. F. Parrish, J. C. Derber, R. Treadon, R. M. Errico, and R. Yang, 2009a: Improving incremental balance in the GSI 3DVAR analysis system. Mon. Wea. Rev., 137, 10461060, doi:10.1175/2008MWR2623.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kleist, D. T., D. F. Parrish, J. C. Derber, R. Treadon, W.-S. Wu, and S. Lord, 2009b: Introduction of the GSI into the NCEPs Global Data Assimilation System. Wea. Forecasting, 24, 16911705, doi:10.1175/2009WAF2222201.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kobayashi, S., M. Matricardi, D. Dee, and S. Uppala, 2009: Toward a consistent reanalysis of the upper stratosphere based on radiance measurements from SSU and AMSU-A. Quart. J. Roy. Meteor. Soc., 135, 20862099, doi:10.1002/qj.514.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kobayashi, S., and Coauthors, 2015: The JRA-55 reanalysis: General specifications and basic characteristics. J. Meteor. Soc. Japan, 93, 548, doi:10.2151/jmsj.2015-001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., G. Walker, G. J. Collatz, and P. E. Thornton, 2014: Hydroclimatic controls on the means and variability of vegetation phenology and carbon uptake. J. Climate, 27, 56325652, doi:10.1175/JCLI-D-13-00477.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kunkel, K. E., and Coauthors, 2013: Monitoring and understanding trends in extreme storms: State of knowledge. Bull. Amer. Meteor. Soc., 94, 499514, doi:10.1175/BAMS-D-11-00262.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Levy, R. C., L. A. Remer, S. Mattoo, E. F. Vermote, and Y. J. Kaufman, 2007: Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. J. Geophys. Res., 112, D13211, doi:10.1029/2006JD007811.

    • Search Google Scholar
    • Export Citation
  • Lim, Y.-K., R. Kovach, S. Pawson, and G. Vernieres, 2017: The 2015/16 El Niño event in context of the MERRA-2 reanalysis: A comparison of the tropical Pacific with 1982/83 and 1997/98. J. Climate, doi:10.1175/JCLI-D-16-0800.1, in press.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, Q., and S. Boukabara, 2014: Community Radiative Transfer Model (CRTM) applications in supporting the Suomi National Polar-Orbiting Partnership (SNPP) mission validation and verification. Remote Sens. Environ., 140, 744754, doi:10.1016/j.rse.2013.10.011.

    • 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, 14891522, doi:10.5194/gmd-9-1489-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lynch-Stieglitz, M., 1994: The development and validation of a simple snow model for the GISS GCM. J. Climate, 7, 18421855, doi:10.1175/1520-0442(1994)007<1842:TDAVOA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Manney, G. L., and Coauthors, 2008: The evolution of the stratopause during the 2006 major warming: Satellite data and assimilated meteorological analyses. J. Geophys. Res., 113, D11115, doi:10.1029/2007JD009097.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marticorena, B., and G. Bergametti, 1995: Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme. J. Geophys. Res., 100, 16 41516 430, doi:10.1029/95JD00690.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McCarty, W., L. Coy, R. Gelaro, A. Huang, D. Merkova, E. B. Smith, M. Sienkiewicz, and K. Wargan, 2016: MERRA-2 input observations: Summary and initial assessment. Technical Report Series on Global Modeling and Data Assimilation, Vol. 46, NASA Tech. Rep. NASA/TM–2016–104606, 61 pp. [Available online at https://gmao.gsfc.nasa.gov/pubs/docs/McCarty885.pdf.]

  • McPeters, R., and Coauthors, 2008: Validation of the Aura Ozone Monitoring Instrument total column ozone product. J. Geophys. Res., 113, D15S14, doi:10.1029/2007JD008802.

    • Search Google Scholar
    • Export Citation
  • Meng, J., R. Yang, H. Wei, M. Ek, G. Gayno, P. Xie, and K. Mitchell, 2012: The Land Surface Analysis in the NCEP Climate Forecast System Reanalysis. J. Hydrometeor., 13, 16211630, doi:10.1175/JHM-D-11-090.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360, doi:10.1175/BAMS-87-3-343.

  • Molina, M. J., and F. S. Rowland, 1974: Stratospheric sink for chlorofluoromethanes: Chlorine atom-catalysed destruction of ozone. Nature, 249, 810812, doi:10.1038/249810a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Molod, A., L. Takacs, M. Suárez, and J. Bacmeister, 2015: Development of the GEOS-5 atmospheric general circulation model: Evolution from MERRA to MERRA2. Geosci. Model Dev., 8, 13391356, doi:10.5194/gmd-8-1339-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moorthi, S., and M. J. Suárez, 1992: Relaxed Arakawa–Schubert: A parameterization of moist convection for general circulation models. Mon. Wea. Rev., 120, 9781002, doi:10.1175/1520-0493(1992)120<0978:RASAPO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Myhre, G., 2009: Consistency between satellite-derived and modeled estimates of the direct aerosol effect. Science, 325, 187190, doi:10.1126/science.1174461.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, P. A., and E. R. Nash, 2005: The unusual Southern Hemisphere stratosphere winter of 2002. J. Atmos. Sci., 62, 614628, doi:10.1175/JAS-3323.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 17471763, doi:10.1175/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Poli, P., and Coauthors, 2013: The data assimilation system and initial performance evaluation of the ECMWF pilot reanalysis of the 20th-century assimilating surface observations only (ERA-20C). ERA Tech. Rep. 14, 59 pp. [Available online at http://www.ecmwf.int/en/elibrary/11699-data-assimilation-system-and-initial-performance-evaluation-ecmwf-pilot-reanalysis.]

  • Putman, W., and S.-J. Lin, 2007: Finite-volume transport on various cubed-sphere grids. J. Comput. Phys., 227, 5578, doi:10.1016/j.jcp.2007.07.022.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Randles, C. A., and Coauthors, 2016: The MERRA-2 aerosol assimilation. Technical Report Series on Global Modeling and Data Assimilation, Vol. 45, NASA Tech. Rep. NASA/TM–2016–104606, 143 pp. [Available online at https://gmao.gsfc.nasa.gov/pubs/docs/Randles887.pdf.]

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reichle, R. H., and Q. Liu, 2014: Observation-corrected precipitation estimates in GEOS-5. Technical Report Series on Global Modelling and Data Assimilation, Vol. 35, NASA Tech. Rep. NASA/TM–2014–104606, 24 pp. [Available online at https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20150000725.pdf.]

  • Reichle, R. H., R. D. Koster, G. J. M. De Lannoy, B. A. Forman, Q. Liu, S. Mahanama, and A. Toure, 2011: Assessment and enhancement of MERRA land surface hydrology estimates. J. Climate, 24, 63226338, doi:10.1175/JCLI-D-10-05033.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reichle, R. H., Q. Liu, R. D. Koster, C. S. Draper, S. P. P. Mahanama, and G. S. Partyka, 2017a: Land surface precipitation in MERRA-2. J. Climate, 30, 16431664, doi:10.1175/JCLI-D-16-0570.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reichle, R. H., C. S. Draper, Q. Liu, M. Girotto, S. P. P. Mahanama, R. D. Koster, and G. J. M. De Lannoy, 2017b: Assessment of MERRA-2 land surface hydrology estimates. J. Climate, 30, 29372960, doi:10.1175/JCLI-D-16-0720.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Remer, L. A., and Coauthors, 2005: The MODIS aerosol algorithm, products, and validation. J. Atmos. Sci., 62, 947973, doi:10.1175/JAS3385.1.