This dataset is a time series of mass variability averaged over all of the global ocean. It provides the non-steric or mass only sea level changes over time. The mass variability are derived from JPL GRACE Mascon Ocean, Ice, and Hydrology Equivalent Water Height CRI Filtered RL063Mv04 dataset, which can be found at https://podaac.jpl.nasa.gov/dataset/TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06.3_V4. A more 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. The mass variability are provided as an ASCII table.

This dataset is a time series of mass variability averaged over all of the global ocean. It provides the non-steric or mass only sea level changes over time. The mass variability are derived from JPL GRACE Mascon Ocean, Ice, and Hydrology Equivalent Water Height CRI Filtered RL06.3Mv04 dataset, which can be found at https://doi.org/10.5067/TEMSC-3JC634. A more 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. The mass variability is provided as an ASCII table.

This dataset is a time series of mass variability averaged over all of the global ocean. It provides the non-steric or mass only sea level changes over time. The mass variability are derived from JPL GRACE Mascon Ocean, Ice, and Hydrology Equivalent Water Height CRI Filtered RL06.3Mv04 dataset, which can be found at https://podaac.jpl.nasa.gov/dataset/TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06.3_V3. A more 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. The mass variability is provided as an ASCII table.

This dataset is a time series of mass variability averaged over all of the global ocean. It provides the non-steric or mass only sea level changes over time. The mass variability are derived from JPL GRACE Mascon Ocean, Ice, and Hydrology Equivalent Water Height CRI Filtered RL06.1Mv04 dataset, which can be found at https://podaac.jpl.nasa.gov/dataset/TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06.3_V4. A more 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. The mass variability is provided as an ASCII table.

This dataset is a time series of mass variability averaged over all of the global ocean. It provides the non-steric or mass only sea level changes over time. The mass variability are derived from JPL GRACE Mascon Ocean, Ice, and Hydrology Equivalent Water Height CRI Filtered RL06.1Mv04 dataset, which can be found at https://doi.org/10.5067/TEMSC-3JC634. A more 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. The mass variability is provided as an ASCII table.

Data pertain to analysis of GRACE time series of mass change in both gridded and basin format. The GRACE data are based on the COST-G solution obtained from http://gravis.gfz-potsdam.de/home. Both 50km regular gridded data and basin-level time series are included, as well as the SAM and ENSO climate indices on which the regressions were based. The gridded datasets provided here include derived quantities from the regressions such as trends, uncertainties, and regression coefficients in NetCDF format.

Glacial isostatic adjustment (GIA) is an ongoing geophysical process and is measured by gravimetry satellites like GRACE and GRACE-FO. To isolate signals of contemporary surface mass loss in the cumulative satellite gravimetry measurements, contemporary GIA rates are computed and subtracted from the satellite gravimetry observations. The GIA correction models provided here are filtered such that they are compatible with Level-3 post-processing filters applied to GRACE(-FO) data as indicated in the [product_id]. In this way, user can effectively assess the impact of the applied GIA correction, and substitute different GIA models should that be desired. This GIA dataset is mapped into 1.0-degree global grid in netCDF format.

Glacial isostatic adjustment (GIA) is an ongoing geophysical process and is measured by gravimetry satellites like GRACE and GRACE-FO. To isolate signals of contemporary surface mass loss in the cumulative satellite gravimetry measurements, contemporary GIA rates are computed and subtracted from the satellite gravimetry observations. The GIA correction models provided here are filtered such that they are compatible with Level-3 post-processing filters applied to GRACE(-FO) data as indicated in the [product_id]. In this way, user can effectively assess the impact of the applied GIA correction, and substitute different GIA models should that be desired. This GIA dataset is mapped into 1.0-degree global grid in netCDF format.

Glacial isostatic adjustment (GIA) is an ongoing geophysical process and is measured by gravimetry satellites like GRACE and GRACE-FO. To isolate signals of contemporary surface mass loss in the cumulative satellite gravimetry measurements, contemporary GIA rates are computed and subtracted from the satellite gravimetry observations. The GIA correction models provided here are filtered such that they are compatible with Level-3 post-processing filters applied to GRACE(-FO) data as indicated in the [product_id]. In this way, user can effectively assess the impact of the applied GIA correction, and substitute different GIA models should that be desired. This GIA dataset is mapped into 0.5-degree global grid compatible with the JPL Mascon solution, provided in netCDF format.

This data set contains the monthly Global Ocean Mass Anomalies (goma) since 04/2002, as measured by the GRACE and GRACE Follow-On (G/GFO) satellite missions. The data are averaged over the global ocean domain, at monthly intervals (note: data gaps exist). This file contains the goma time series based on the spherical harmonic gravity fields provided by the G/GFO SDS centers: JPL, CSR, GFZ. The data are frequently updated as new monthly observations are acquired by the GFO mission. The processing of the spherical harmonics gravity field coefficients is as follows: (1) GAD + GSM: the monthly de-aliasing product GAD is added back to the GSM L2 gravity fields; (2) [GSM + GAD] coefficients are averaged over the global ocean with a coastal buffer of 300 km (to avoid land-ocean leakage); (3) the spatial mean of atmospheric loading of the entire global ocean domain is removed (via the GAA L2 data product). A GIA correction using the ICE-6GD model (Peltier et al., 2018) is applied.