A Python interface to perform wave analysis from satellite altimeter data.

pip install radwave==1.0.8


RADWave - Wave analysis from Altimeter data

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RADWave documentation is found at radwave.readthedocs.io

RADWave is a python package built to characterise wave conditions based on altimeter data.

Satellite radar altimeters can be used to determine significant wave height and wind speed [Young et al., 2011]. Since the first launch of the GEOSAT (GEOdetic SATellite) altimeter in 1985, there has been almost continuous data collection. From these measurements one can calculate wave conditions namely wave height, period and power [Young and Donelan, 2018]. Analysis of this long-term, high resolution spatio-temporal record brings new insights into inter-annual, seasonal and decadal variations of regional wave climates.


RADWave is Python package that provides a mechanism to access altimeter datasets through web-enabled data services (THREDDS). The package capabilities are illustrated based on the the Australian Ocean Data Network (AODN database that spans from 1985-present and that has already been calibrated and validated by [Ribal and Young, 2019]. RADWave allows the user to query over a range of spatial and temporal scales altimeter parameters in specific geographical regions and subsequently calculates significant wave heights, periods, group velocities, average wave energy densities and wave energy fluxes.

RADWave can be used to easily calculate past wave conditions and infers long term wave climate variability, providing new insights on wave modal conditions, seasonal changes, long-term trends and associated modulation by climate oscillations.

Designed for researchers and industry partners focusing on offshore wave conditions globally, RADWave enhances the ease of access and analysis of altimeter data.



You will need Python 3.5+. Also, the following packages are required:

Installing using pip

You can install RADWave using the pip package manager with your version of Python:

python3 -m pip install radwave

Installing using conda

You can install RADWave using conda by downloading the repository from GitHub. Then you will use the environment.yml to create the environment. Open a terminal on Linux/Mac or Anaconda Prompt on Windows:

cd RADWave/Notebooks
conda env create -f environment.yml
conda env update --file environment.yml
conda activate radwave
jupyter notebook

Installing using Docker

A more straightforward installation which does not depend on specific compilers relies on the docker virtualisation system.

To install the docker image and test it is working:

   docker pull pyreefmodel/radwave:latest
   docker run --rm pyreefmodel/radwave:latest help

To build the dockerfile locally, we provide a script. First ensure you have checked out the source code from github and then run the script in the Docker directory. If you modify the dockerfile and want to push the image to make it publicly available, it will need to be retagged to upload somewhere other than the GEodels repository.

git checkout https://github.com/pyReef-model/RADWave.git
cd RADWave
source Docker/build-dockerfile.sh


Binder & docker container

Launch the demonstration at mybinder.org



Another option will be to use the Docker container available through Kitematic pyreefmodel/radwave.

Docker Cloud Automated build


How to contribute?

We welcome all kinds of contributions! Please get in touch if you would like to help out.

Everything from code to notebooks to examples and documentation are all equally valuable so please don't feel you can't contribute.

To contribute please fork the project make your changes and submit a pull request. We will do our best to work through any issues with you and get your code merged into the main branch.

If you found a bug, have questions, or are just having trouble with bioLEC, you can:

Where to find support?

Please feel free to submit new issues to the issue-log to request new features, document new bugs, or ask questions.


This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this program. If not, see http://www.gnu.org/licenses/lgpl-3.0.en.html.


  1. Ribal, A. and Young, I. R., 2019. 33 years of globally calibrated wave height and wind speed data based on altimeter observations. Scientific Data 6(77), p.100.

  2. Young, I. R., Zieger, S. and Babanin, A. V., 2011. Global trends in wind speed and wave height. Science 332(6028), p451–455.

  3. Young, I. R. and Donelan, M., 2018. On the determination of global ocean wind and wave climate from satellite observations. Remote Sensing of Environment 215, 228–241.