Python Package for Processing Earth Gravity Field Data

This package processes Earth gravity field data—provided as spherical harmonic coefficients—into gridded, domain-specific datasets. It also includes uncertainty estimation and the generation of regional mean time series.

Input

• Spherical harmonic coefficients, provided as one file per time step, in either:

  • ICGEM format (*.gfc)
  • SINEX format (*.snx)

• Configuration file steering the processing steps. Either:

  • Json format (*.json)
  • XML format (*.xml)

Output

• NetCDF files (*.nc) per domain containing gridded data
• CSV files (*.csv) per domain containing mean regional time series

Included Processing Steps

• Removal of the mean field
• Filtering of spherical harmonic coefficients:
  • DDK
  • Gaussian filter
  • VDK (requires SINEX input)
• Replacement of C20 and C30 with external data
• Subtraction of the GIA model
• Estimation and insertion of geocentre motion coefficients (C10, C11, S11)
• Subtraction of the 161-day aliased signal
• Spherical harmonic synthesis (land and ocean domains only)

Domain-Specific Processing

Land — Terrestrial Water Storage (TWS)

• Masking of the ocean
• Uncertainty estimation based on open-ocean noise

Ocean — Ocean Bottom Pressure (OBP)

• Separation of the ocean signal into:
  • Barystatic sea level, estimated via the sea-level equation
  • Residual circulation
• Uncertainty estimation based on residual time-series signals

Ice Sheets — Greenland and Antarctica

• Based on unfiltered spherical harmonic coefficients
• Gridded data estimated using the sensitivity-kernel approach
• Uncertainty estimation based on residual time-series signals