clouddrift 0.1.1

Accelerating the use of Lagrangian data for atmospheric, oceanic, and climate sciences

CloudDrift

The CloudDrift project aims at accelerating the use of Lagrangian data for atmospheric, oceanic, and climate sciences. It is currently funded by the NSF EarthCube program through EarthCube Capabilities Grant No. 2126413. The lead Principal Investigator of the project is Shane Elipot and its development is led by Philippe Miron.

This project is generating the clouddrift library as an open source software written in python. This software requires a number of modules that need to exist within your working python environment. The list of necessary modules is contained in the YAML file environment.yml. This file can be used with a package manager such as conda to create the necessary python environment. From the command line, run

conda env create --file environment.yml

Once the library is in a beta stage, a conda/pip packages will be available to simplify the installation process.

This repository is organized as follows:

• clouddrift/: modules of the clouddrift library.
• data/: processing scripts for various Lagrangian datasets, including the GDP historical dataset.
• docs/: documentation in-progress available at cloud-drift.github.io/clouddrift.
• examples/: series of Jupyter Notebooks showcasing the library use cases.
• tests/: test-suite.
• dev/: development Jupyter Notebooks use to brainstorm new ideas and discussions.