System name (version): Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) (using Goddard Earth Observing System version 5.12.4)• 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.): Assimilated and Interactive Aerosols. Observation-based precipitation driving the land surface and aerosol wet deposition except in the high latitudes (Reichle et al. 2017a).
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 by 0.5° latitude (576 by 361 grid points, approximately 50km by 50km)
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 usually available by the 15th of the following month
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: 3D variational analysis (3D-Var), with the first-guess at the appropriate time of the observations (FGAT) and variational bias correction
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: Seasonally-varying climatology of satellite leaf-area index; Reichle et al. (2017)
Land use (and its evolution in time): Time invariant satellite land cover; Reichle et al. (2017)
Aerosols: Emissions (Section 2.2 of Randles et al. 2016); Aerosols are assimilated and interactive with the radiation
Green House Gases:Follows RCP 4.5
Solar forcing: NOAA Climate Data Record (CDR) of Solar Spectral Irradiance (SSI), NRLSSI Version 2.1 (Coddington et al. 2017). There is lag in the release of latest data, so the near -real time analysis uses an extrapolation of the solar cycle.
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: Hydrostatic (Putman and Lin, 2007)
Radiations parameterization: Chou-Suarez (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: Catchment land surface model (Koster et al. 2000; Reichle et al. 2017b)
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. https://gmao.gsfc.nasa.gov/pubs/docs/Bosilovich803.pdf
Coddington O., J. L. Lean, D. Lindholm, P. Pilewskie, M. Snow, and NOAA CDR Program (2017): NOAA Climate Data Record (CDR) of Solar Spectral Irradiance (SSI), NRLSSI Version 2.1. NOAA National Centers for Environmental Information. https://doi.org/10.7289/V53776SW
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
Koster, R. D., M. J. Suarez, A. Ducharne, M. Stieglitz, and P. Kumar, 2000: A catchment-based approach to modeling land surface processes in a general circulation model: 1. Model structure. J. Geophys. Res., 105, 24 809–24 822, doi:10.1029/2000JD900327.
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., Q. Liu, R. D. Koster, C. S. Draper, S. P. P. Mahanama, and G. S. Partyka, 2017a: Land surface precipitation in MERRA-2, Journal of Climate, 30, 1643-1664, doi:10.1175/JCLI-D-16-0570.1.
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
