Skip to main content

Tide Model Driver to read OTIS, GOT and FES formatted tidal solutions and make tidal predictions

Project description

Language License PyPI Version Anaconda-Server Documentation Status codecov zenodo

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

Ocean and load tidal predictions using OTIS, GOT and FES formatted tidal solutions

Radial solid Earth and pole tide displacements following IERS conventions

Dependencies

References

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, H. A. Fricker, “Ocean Tide Influences on the Antarctic and Greenland Ice Sheets”, Reviews of Geophysics, 56, 142-184, (2018). doi: 10.1002/2016RG000546

Download

The program homepage is:
A zip archive of the latest version is available directly at:

Software

Matlab Tide Model Driver from Earth & Space Research is available at:
Fortran OSU Tidal Prediction Software OTPS is available at:
Incorporated into the NASA Cryosphere Altimetry Processing Toolkit at:

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 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.

Credits

This project contains work and contributions from the scientific community. The Tidal Model Driver (TMD) Matlab Toolbox was developed by Laurie Padman, Lana Erofeeva and Susan Howard. 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.

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyTMD-2.0.4.tar.gz (7.4 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyTMD-2.0.4-py3-none-any.whl (7.5 MB view details)

Uploaded Python 3

File details

Details for the file pyTMD-2.0.4.tar.gz.

File metadata

  • Download URL: pyTMD-2.0.4.tar.gz
  • Upload date:
  • Size: 7.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.3

File hashes

Hashes for pyTMD-2.0.4.tar.gz
Algorithm Hash digest
SHA256 ab6f0d362bfd5c31d341af81fa8a145c2d71eea5f668038e5a694b25bdeb6919
MD5 90a97a8047fbb556ca5dbb2967450413
BLAKE2b-256 c3cc0d74f96320fa10a49ef78f166ee71b45181f39b2af0feb14620b927b4b50

See more details on using hashes here.

File details

Details for the file pyTMD-2.0.4-py3-none-any.whl.

File metadata

  • Download URL: pyTMD-2.0.4-py3-none-any.whl
  • Upload date:
  • Size: 7.5 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.3

File hashes

Hashes for pyTMD-2.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 821d12fbbca943eef4b549ab8c5a89a8e40f2633f1826bba052012dbe4902ebe
MD5 84a01f70df29e8aef8ea22a3c815ae5d
BLAKE2b-256 4bc914f6dca36e49561b6010119ab3dc44059b71d58690c3ac5583a23901d02d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page