pyTMD

Python-based tidal prediction software for estimating ocean, load, solid Earth and pole tides

About

Version:
Citation:
Tests:
Data:
License:

For more information: see the documentation at pytmd.readthedocs.io

Installation

From PyPI:

python3 -m pip install pyTMD

To include all optional dependencies:

python3 -m pip install pyTMD[all]

Using conda or mamba from conda-forge:

conda install -c conda-forge pytmd

mamba install -c conda-forge pytmd

Development version from GitHub:

python3 -m pip install git+https://github.com/pyTMD/pyTMD.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/pyTMD/pyTMD.git

3. Move into the pyTMD directory

cd pyTMD

4. Install dependencies and start JupyterLab:

pixi run start

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

Dependencies

• h5netcdf: Pythonic interface to netCDF4 via h5py
• lxml: processing XML and HTML in Python
• numpy: Scientific Computing Tools For Python
• platformdirs: Python module for determining platform-specific directories
• pyproj: Python interface to PROJ library
• scipy: Scientific Tools for Python
• timescale: Python tools for time and astronomical calculations
• xarray: N-D labeled arrays and datasets in Python

Alternative Software

perth5 from NASA Goddard Space Flight Center:
https://codeberg.org/rray/perth5

pyfes from the Centre National d'Études Spatiales (CNES):
https://github.com/CNES/aviso-fes

Matlab Tide Model Driver from Earth & Space Research:
https://github.com/EarthAndSpaceResearch/TMD_Matlab_Toolbox_v2.5

Fortran OSU Tidal Prediction Software:
https://www.tpxo.net/otps

Download

The program homepage is:
https://github.com/pyTMD/pyTMD

A zip archive of the latest version is available directly at:
https://github.com/pyTMD/pyTMD/archive/main.zip

Disclaimer

This package includes software developed at NASA Goddard Space Flight Center (GSFC) and the University of Washington Applied Physics Laboratory (UW-APL). It is not sponsored or maintained by the Universities Space Research Association (USRA), AVISO, CNES or NASA. The software is provided here for your convenience but with no guarantees whatsoever. It should not be used for coastal navigation or any application that may risk life or property.

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.

Credits

The Tidal Model Driver (TMD) Matlab Toolbox was developed by Laurie Padman, Lana Erofeeva and Susan Howard. An updated version of the TMD Matlab Toolbox (TMD3) was developed by Chad Greene. The OSU Tidal Inversion Software (OTIS) and OSU Tidal Prediction Software (OTPS) were developed by Lana Erofeeva and Gary Egbert (copyright OSU, licensed for non-commercial use). The NASA Goddard Space Flight Center (GSFC) PREdict Tidal Heights (PERTH3) software was developed by Richard Ray and Remko Scharroo. An updated and more versatile version of the NASA GSFC tidal prediction software (PERTH5) was developed by Richard Ray. The pyFES prediction software was funded and supported by CNES and the FES model is distributed by AVISO.

References

T. C. Sutterley, S. L. Howard, L. Padman, and M. R. Siegfried, "pyTMD: Python-based tidal prediction software". Journal of Open Source Software, 10(116), 8566, (2025). doi: 10.21105/joss.08566

T. C. Sutterley, T. Markus, T. A. Neumann, M. R. van den Broeke, J. M. van Wessem, and S. R. M. Ligtenberg, "Antarctic ice shelf thickness change from multimission lidar mapping", The Cryosphere, 13, 1801-1817, (2019). doi: 10.5194/tc-13-1801-2019

L. Padman, M. R. Siegfried, and H. A. Fricker, "Ocean Tide Influences on the Antarctic and Greenland Ice Sheets", Reviews of Geophysics, 56, 142-184, (2018). doi: 10.1002/2016RG000546

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.