MERRA-2 System Characteristics

System

  • System name (version): Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) (using Goddard Earth Observing System version 5.12.4)
  • Date of implementation: Oct 12, 2015
  • Project overview paper: Gelaro et al. (2017)

Configuration

  • Earth system components included in the analysis system (e.g., ocean, sea-ice, land, etc.): Catchment Land Surface Model with Observation Corrected Precipitation. Assimilated and Interactive Aerosols
  • Horizontal resolution of the model, with indication of grid spacing in km (for the different Earth system component included in the model): The model is run on a cubed sphere grid. Data are provided at 0.625° longitude 0.5° latitude by (576 by 361 gridpoints, approximately 50km2)
  • Number of levels in the different Earth system components (for the different Earth system component included in the model): 72 native model levels, also interpolated to 42 pressure levels
  • Frequency of the outputs: 2D variables at 1 hourly frequency, 3D variables at 3 hourly frequency, Analysis variables at 6 hourly frequency
  • Top of the atmospheric model: 0.01 hPa
  • Number of analysis cycle per day: 4
  • Earliest start date: 00Z 01 JAN 1980
  • Integration time step: 900sec
  • Length and frequency of the longest forecast: 6 hours, only for the analysis cycle
  • Dataset latency: Data is available by the 15th of the next month
  • Documentation: https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/docs

Analysis system

  • Length of the analysis window: 6 hours
  • Number of ensemble members and their resolution: NA
  • Additional comments: Uses Incremental Analysis Update (Bloom et al. 1996) and global mass constraint (Takacs et al. 2016)
  • Data assimilation method: Grid Point Statistical Interpolation (GSI) – Gelaro et al (2017)

Externally prescribed boundary conditions

  • Sea surface temperature: SST and Sea Ice are prescribed from observations; (Bosilovich et al. 2015)
  • Sea-ice: As with SST above, but sea ice albedo is discussed by Cullather et al. (2014)
  • Snow: Reichle et al. (2017); Cullather et al. (2014)
  • Vegetation: Reichle et al. (2017)
  • Land use (and its evolution in time): Reichle et al. (2017)
  • Aerosols: Aerosols are assimilated and interactive with the radiation (Randles et al. 2016)
  • Green House Gases: Follows RCP 4.5
  • Solar forcing: Follows CMIP5

Details of model

  • Dynamical core (e.g., semi-Lagrangian): Finite Volume (Putman and Lin, 2007)
  • Grid structure: cubed sphere (Putman and Lin, 2007)
  • Hydrostatic or nonhydrostatic: Nonhydrostatic (Putman and Lin, 2007)
  • Radiations parameterization: Molod et al. (2015)
  • Boundary layer parameterization: Molod et al. (2015)
  • Convection parameterization: Molod et al. (2015)
  • Cloud parameterization scheme: Molod et al. (2015)
  • Land surface parameterization scheme: Reichle et al. (2017)

Further information


Observational data used


References

  • Bloom, S., L. Takacs, A. DaSilva, and D. Ledvina, 1996: Data assimilation using incremental analysis updates. Mon. Wea. Rev., 124, 1256–1271. doi:10.1175/1520-0493(1996)124,1256:DAUIAU.2.0.CO;2.
  • Bosilovich, Michael G., Santha Akella, Lawrence Coy, Richard Cullather, Clara Draper, Ronald Gelaro, Robin Kovach, Qing Liu, Andrea Molod, Peter Norris, Krzysztof Wargan, Winston Chao, Rolf Reichle, Lawrence Takacs, Yury Vikhliaev, Steve Bloom, Allison Collow, Stacey Firth, Gordon Labow, Gary Partyka, Steven Pawson, Oreste Reale, Siegfried D. Schubert, and Max Suárez, 2015. MERRA-2: Initial Evaluation of the Climate. NASA/TM–2015–104606, Vol. 43, 139 pp. Link
  • Bosilovich, M. G., R. Lucchesi, and M. Suárez, 2016: MERRA-2: File Specification. GMAO Office Note No. 9 (Version 1.1), 73 pp. Link
  • 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, 4835–4856, doi: 10.1175/JCLI-D-13-00635.1.
  • Gelaro, R., and Coauthors, 2017: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1
  • McCarty, Will, Lawrence Coy, Ronald Gelaro, Albert Huang, Dagmar Merkova, Edmond B. Smith, Meta Seinkiewicz, and Krzysztof Wargan, 2016. MERRA-2 Input Observations: Summary and Assessment. NASA Technical Report Series on Global Modeling and Data Assimilation, NASA/TM-2016-104606, Vol. 46, 61 pp https://gmao.gsfc.nasa.gov/pubs/docs/McCarty885.pdf
  • Molod, A., Takacs, L., Suárez, M., and Bacmeister, J.: Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2, Geosci. Model Dev., 8, 1339–1356, https://doi.org/10.5194/gmd-8-1339-2015, 2015.
  • Putman, W.M. and Lin, S.J., 2007. Finite-volume transport on various cubed-sphere grids. Journal of Computational Physics, 227(1), pp.55-78. 10.1016/j.jcp.2007.07.022
  • Randles, C. A., A. M. da Silva, V. Buchard, A. Darmenov, P. R. Colarco, V. Aquila, H. Bian, E. P. Nowottnick, X. Pan, A. Smirnov, H. Yu, and R. Govindaraju, 2016. The MERRA-2 Aerosol Assimilation. NASA Technical Report Series on Global Modeling and Data Assimilation, NASA/TM-2016-104606, Vol. 45, 143 pp. https://gmao.gsfc.nasa.gov/pubs/docs/Randles887.pdf
  • Reichle, R. H., C. S. Draper, Q. Liu, M. Girotto, S. P. P. Mahanama, R. D. Koster, and G. J. M. De Lannoy (2017), Assessment of MERRA-2 land surface hydrology estimates, Journal of Climate, 30, 2937-2960, doi:10.1175/JCLI-D-16-0720.1.
  • Takacs, L.L., Suárez, M.J. and Todling, R. (2016), Maintaining atmospheric mass and waterbalance in reanalyses. Q.J.R. Meteorol. Soc., 142: 1565- 1573.https://doi.org/10.1002/qj.2763