cryoswath

cryoswath is a python package containing processing pipelines, a tool library, and some pre-assembled data to retrieve and study CryoSat-2 data.

Adaptability lies at its core. The user can access many options simply by passing arguments to functions; everything else can be customized changing the concerned function or adding a new one.

🌱 state

cryoswath is being developed. Branch main contains the "pip"-installable package, scripts contains tutorials, and data contains auxiliary data and the required directory structure. You can have everything setup automatically (see "getting started"). Other branches are for development.

✨ features

• find all CryoSat-2 tracks passing over your region of interest
• download L1b data from ESA
• retrieve swath elevation estimates
• aggregate point data to gridded data
• fill data gaps using tested methods
• calculate change rates

🚀 getting started

There is a number of ways you can start off. I will give detailed instructions for UNIX systems. Make sure to use python 3.11 or higher. Further, I recommend to use a virtual environment and will involve python-venv in the instructions (however, conda works similar).

All of the following instructions consist of three main steps:

1. making cryoswath available
2. setting up a project directory
3. initializing cryoswath

The instructions will use the variable $proj_dir for the project directory. Please set it to a path that suits you like proj_dir=altimetry-project.

In all cases, consider to download the data dependencies ArcticDEM and the RGI glacier and complex shape files into the $proj_dir/data/auxiliary/DEM and $proj_dir/data/auxiliary/RGI directories (more in the docs).

with git 🐙

advantage: easy pulling bugfixes

git clone https://github.com/j-haacker/cryoswath.git $proj_dir
cd $proj_dir
python3.11 -m venv .venv
source .venv/bin/activate
pip install -e .
cryoswath-init

with pip 📦

advantage: easy installation

mkdir $proj_dir
cd $proj_dir
python3.11 -m venv .venv
source .venv/bin/activate
pip install cryoswath
cryoswath-init

with conda 🐍

advantage: most stable dependency resolution

First, choose an environment name and either define $env_name, e.g., env_name=cryoswath, or adapt the create and activate commands accordingly.

conda create -n $env_name conda-forge::cryoswath
conda activate $env_name
mkdir $proj_dir
cd $proj_dir
cryoswath-init

with Docker 🐳

advantage: will almost always work

note: the first time running the docker image require to download ~ 1 Gb

1. docker run -it -p 8888:8888 -v $proj_dir$:/home/jovyan cryoswath/jupyterlab:v0.2.1
2. You will receive an address including a token with which you can connect to the jupyterlab using your browser
3. In jupyterlab, open a regular shell and execute cryoswath-init
4. Open the scripts folder in the explorer and select one of the notebooks or create your own (inside the scripts folder)

multiple projects

For each project, run cryoswath-init from the project directory.

📖 documentation

j-haacker.github.io/cryoswath

dependencies

• requirements.txt
• reference elevation model
• glacier outlines

cryoswath will point you to the required resources.

🐛 known issues

• projected RGI basins sometimes "invalid" -> add .make_valid() if it is missing somewhere

• it has mostly been tested for the Arctic

  Further: see open issues.

citation and attribution

You can cite this package using bibtex:

@software{cryoswath,
  author       = {Haacker, Jan},
  title        = {cryoswath: v0.2.1},
  month        = feb,
  year         = 2025,
  publisher    = {Zenodo},
  version      = {v0.2.1},
  doi          = {10.5281/zenodo.14837018}
}

Please mind that you likely used other resources on the way.

• ESA provides the L1b data under these Terms and Conditions
• RGI data is distributed under CC-BY-4.0 license
• if you (likely) used DEMs of the PGC, see their Acknowledgement Policy
• the many python packages and libraries this package depends on; some of which are indispensable.

📜 license

MIT. See LICENSE.txt.