Time-variable gravity (TVG) is of great significance in understanding various aspects of the dynamic Earth system, and you won’t want to miss the famous GRACE (Gravity Recovery and Climate Experiment) monthly gravity models if you are interested in TVG. Unfortunately, everyday I had to face and chose one from different versions of them (many institutes have their own GRACE solutions), and then corrected a number of defects in them before using them. Many additional data were needed to overcome some of these defects. Soon, I got tired of these boring and trivial corrections and arose the thought: “Why not try to create a corrected and refined version of GRACE data?” Our group discussed the basic idea and related issues, and finally turned the idea to our multiple-data-based product LDCmgm90. The paper was published in Scientific Data (access our paper) yesterday with the data link access the LDCmgm90 data.

Briefly, LDCmgm90 is a monthly geopotential model set complete from degree and order 2 to 90, derived from various GRACE/SLR (Satellite Laser Ranging) monthly geopotential + Various GCM (General Circulation Model) outputs + ERP (Earth Rotational Parameter) measurement constraints using the Least Difference Combination (LDC) method. Therefore, LDCmgm90 has the same functions of the GRACE monthly geopotential model sets as released by different institutes, such as Center for Space Research (CSR), Deutsches GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL) and Graz University of Technology (TUG), but with a number of defects or limitations in GRACE data removed. Some of the defects are listed below:
1. Problematic C20
2. Strong longitudinal stripe-pattern errors
3. Excess 161-day signals in original GRACE data
4. Two jumps at Jan. 2006 and Jan. 2010 due to updates of ECMWF model
5. Long-period pole tides due to the IERS2010 nonlinear mean pole model
e.t.c.

For a full description about how LDCmgm90 overcomes the defects in common GRACE data, one can refer to this presentation given at the TibXS2019 meeting.

We hope researchers from relevant branches find this data set helpful and welcome any feedback to us.