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Full catalog/TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06.3_V4
TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06.3_V4·vRL06.3Mv04·dataset

Where Earth's water mass shifts month to month (GRACE)

JPL GRACE and GRACE-FO Mascon Ocean, Ice, and Hydrology Equivalent Water Height Coastal Resolution Improvement (CRI) Filtered Release 06.3 Version 04
hydrosphere NASA POCLOUD Level 3 netCDF-4
In plain English

What it measures. Monthly maps of where water mass on Earth shifts compared to a long-term average, expressed as the equivalent thickness of water gained or lost in each area, with coastlines sharpened to reduce blurring.

How it's made. Derived from the GRACE and GRACE-FO satellite pair, which detects tiny changes in Earth's gravity, processed at JPL using the mascon method that intrinsically removes noise without extra smoothing.

How & where you'd use it. Tracks changes in groundwater, ice sheets, glaciers, and ocean mass, making it a key tool for studying droughts, water resources, and sea-level change.

What's measured

TERRESTRIAL HYDROSPHERE › WATER BUDGET › TERRESTRIAL WATER STORAGETERRESTRIAL HYDROSPHERE › GROUND WATERCRYOSPHERE › GLACIERS/ICE SHEETS › GLACIER MASS BALANCE/ICE SHEET MASS BALANCE

Coverage & cadence

  • Time span2002-04-04 → ongoing
  • Measured byGRACE-FO (GRACE-FO MWI, GRACE-FO LRI, GRACE-FO ACC, GRACE-FO SCA) · GRACE (KBR, GRACE LRR, GRACE ACC, GRACE SCA)
  • Processing levelLevel 3
  • Spatial extent-180, -90, 180, 90
  • FormatsnetCDF-4
  • StatusACTIVE

What you can do with it

  • Follow rainfall, floods and surface-water extent
  • Track soil moisture and the onset of drought
  • Monitor lakes, rivers and groundwater storage
Official description

This dataset contains gridded monthly global water storage/height anomalies relative to a time-mean, derived from GRACE and GRACE-FO and processed at JPL using the Mascon approach (RL06.3Mv04). A Coastal Resolution Improvement (CRI) filter has been applied to this data set to reduce signal leakage errors across coastlines. For most land hydrology, oceanographic as well as land-ice applications this is the recommend data set for the analysis of surface mass changes. The data are provided in a single data file in netCDF format, with water storage/height anomalies in equivalent water thickness units (cm). The data are derived from solving for monthly gravity field variations on geolocated spherical cap mass concentration functions, rather than global spherical harmonic coefficients. Additionally, realistic geophysical information is introduced during the computation to intrinsically remove correlated errors. Thus, these Mascon grids do not need to be de-correlated or smoothed, like traditional spherical harmonic gravity solutions. The complete Mascon solution consists of 4,551 independent estimates of surface mass change that have been derived using an equal-area 3-degree grid of individual mascons. A subset of these individual mascons span coastlines, and contain mixed land and ocean mass change signals. In a post-processing step, the CRI filter is applied to those mixed land/ocean Mascons to separate land and ocean mass. The land mask used to perform this separation is provided in the same directory as this dataset, as are uncertainty values, and the gridded mascon-ID number to enable further analysis. Since the individual mascons act as an inherent smoother on the gravity field, a set of optional gain factors (or scale factors) is provided within the netCDF and can be applied to the solution to study mass change signals at sub-mascon resolution (e.g. for continental hydrology applications). For use-case examples and further background on the gain factors, please see Wiese, Landerer & Watkins, 2016, https://doi.org/10.1002/2016WR019344. This RL06.3Mv04 is an updated version of the previous Tellus JPL Mascon RL06.1Mv03 (DOI, 10.5067/TEMSC-3JC63). For a detailed description on the Mascon solution, including the mathematical derivation, implementation of geophysical constraints, and solution validation, please see Watkins et al., 2015, doi: 10.1002/2014JB011547. For a detailed description of the CRI filter implementation, please see Wiese et al., 2016, doi:10.1002/2016WR019344.

Get the data

tellus_grac-grfo_mascon_cri_grid_rl06.3_v4_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06.3_V4",
    version="RL06.3Mv04",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from POCLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.