Short Name:

tavgM_2d_mld_Nx: MERRA Simulated 2D Incremental Analysis Update (IAU) MERRA-Land reanalysis, GEOSldas-MERRALand, Time Average Monthly Mean 0.667 x 0.5 degree V5.2.0 (MSTMNXMLD) at GES DISC

The Modern-Era Retrospective Analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis data product that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. A supplemental and improved set of land surface hydrological fields (MERRA-Land) was generated by re-running a revised version of the land component of the MERRA system (Reichle et al., 2012). Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the global gauge-based NOAA Climate Prediction Center Unified (CPCU) precipitation product and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies. The MERRA-Land product, MSTMNXMLD or tavgM_2d_mld_Nx, is a simulated 2-Dimensional monthly mean at the native resolution. All collections from this group are at reduced horizontal resolution. The data are on the GEOS-5 native 540 x 361 grid with 0.667 degree longitude x 0.5 degree latitude resolution. Data are archived in the HDF-EOS2 (Grid) format, based on HDF4. Sign Up for the MERRA-2 Mailing List Sign up for the MERRA-2 listserv to receive announcements on the latest data information, tools and services that become available, data announcements from GMAO and more! Contact the GES DISC User Services ( to be added to the list. MERRA-2 Science Data and Data Processing Questions Do you have a question about MERRA/MERRA-2? Take a look at the File Specification Document and if that doesn't answer your question, users can contact staff with questions on the data, data processing and science. Send questions to

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