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gravity-toolkit

Python tools for obtaining and working with Level-2 spherical harmonic coefficients from the NASA/DLR Gravity Recovery and Climate Experiment (GRACE) and the NASA/GFZ Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) missions

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For more information: see the documentation at gravity-toolkit.readthedocs.io

Installation

From PyPI:

python3 -m pip install gravity-toolkit

To include all optional dependencies:

python3 -m pip install gravity-toolkit[all]

Using conda or mamba from conda-forge:

conda install -c conda-forge gravity-toolkit
mamba install -c conda-forge gravity-toolkit

Development version from GitHub:

python3 -m pip install git+https://github.com/tsutterley/gravity-toolkit.git

Running with Pixi

Alternatively, you can use Pixi for a streamlined workspace environment:

  1. Install Pixi following the installation instructions
  2. Clone the project repository:
git clone https://github.com/tsutterley/gravity-toolkit.git
  1. Move into the gravity-toolkit directory
cd gravity-toolkit
  1. Install dependencies and start JupyterLab:
pixi run start

This will automatically create the environment, install all dependencies, and launch JupyterLab in the notebooks directory.

Resources

Dependencies

Download

The program homepage is:
https://github.com/tsutterley/gravity-toolkit

A zip archive of the latest version is available directly at:
https://github.com/tsutterley/gravity-toolkit/archive/main.zip

Disclaimer

This package includes software developed at the University of California at Irvine (UCI), the NASA Jet Propulsion Laboratory (JPL), NASA Goddard Space Flight Center (GSFC) and the University of Washington Applied Physics Laboratory (UW-APL). This program is not sponsored or maintained by the Universities Space Research Association (USRA), the Center for Space Research at the University of Texas (UTCSR), the Jet Propulsion Laboratory (JPL), the German Research Centre for Geosciences (GeoForschungsZentrum, GFZ) or NASA. The software is provided here for your convenience but with no guarantees whatsoever.

Contributing

This project contains work and contributions from the scientific community. If you would like to contribute to the project, please have a look at the contribution guidelines, open issues and discussions board.

References

T. C. Sutterley, I. Velicogna, and C.-W. Hsu, "Self-Consistent Ice Mass Balance and Regional Sea Level From Time-Variable Gravity", Earth and Space Science, 7, (2020). doi: 10.1029/2019EA000860

T. C. Sutterley and I. Velicogna, "Improved estimates of geocenter variability from time-variable gravity and ocean model outputs", Remote Sensing, 11(18), 2108, (2019). doi: 10.3390/rs11182108

J. Wahr, S. C. Swenson, and I. Velicogna, "Accuracy of GRACE mass estimates", Geophysical Research Letters, 33(6), L06401, (2006). doi: 10.1029/2005GL025305

J. Wahr, M. Molenaar, and F. Bryan, "Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible > detection using GRACE", Journal of Geophysical Research: Solid Earth, 103(B12), (1998). doi: 10.1029/98JB02844

D. Han and J. Wahr, "The viscoelastic relaxation of a realistically stratified earth, and a further analysis of postglacial rebound", Geophysical Journal International, 120(2), (1995). doi: 10.1111/j.1365-246X.1995.tb01819.x

Data Repositories

T. C. Sutterley, I. Velicogna, and C.-W. Hsu, "Ice Mass and Regional Sea Level Estimates from Time-Variable Gravity", (2020). doi: 10.6084/m9.figshare.9702338

T. C. Sutterley and I. Velicogna, "Geocenter Estimates from Time-Variable Gravity and Ocean Model Outputs", (2019). doi: 10.6084/m9.figshare.7388540

License

The content of this project is licensed under the Creative Commons Attribution 4.0 Attribution license and the source code is licensed under the MIT license.

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Python tools for working with time-variable gravity fields

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