Climatological Lagrangian Coherent Structure calculation using python based on the code developed by Rodrigo Duran for Matlab.
This repository contains the scripts needed to deploy a series of particle releases using OpenDrift and calculate the associated climatological Lagrangian Coherent Structures. The user can define a variety of parameters, for more information see the jupyter notebook example. Support of quad-triangular unstructured grids such as SCHISM outputs is supported (hydro+waves, stokes drift only). The main objective of this repository is to calculate climatological LCSs, however options are provided if the user is interested in calculating non-climatological LCSs.
To use this package OpenDrift is necessary. To facilitate and make the installation faster please use mamba. Example of how to install on Unix-like platforms (Mac OS & Linux):
curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh
bash Miniforge3-$(uname)-$(uname -m).sh
*Accessed: December 2023
Once mamba is installed we can proceed.
This research was part of the Moana Project, therefore the reader used for OpenDrift is especific to a reader developed by Simon Weppe for the project use. However, unless working with the same dataset or a data related to the Moana project I invite you to download the repository directly from OpenDrift
OpenDrift original repo
git clone https://github.com/OpenDrift/opendrift.git
Branch developed by Simon Weppe
git clone https://github.com/simonweppe/opendrift.git
The environment.yml file contains all the dependencies needed to run opendrift and cLCS scripts.
cd ../
git clone https://github.com/MireyaMMO/cLCS.git
cd cLCS
mamba env create --name cLCS --file=environment.yml
pip install -e .
cd ../opendrift
pip install -e .
To build a local docker image:
docker build -f Dockerfile -t clcs:$tag .
To pull a working docker image from the current repository
Moana Version (developed by Simon Weppe)
docker pull mmontao/clcs:MOANA-v1.0.0
OpenDrift
docker pull mmontao/clcs:v1.0.0
And run. $tag can be v1.0.0, MOANA-v1.0.0 or if built locally the chosen tag
docker run -ti mmontao/clcs:$tag bash
- mean_C.py contains the mean_CG class that deploys particles throughout the grid using OpenDrift and computes monthly averages Cauchy-Green tensors for a defined month (See Duran, et al., 2018 for more details on the methods).
- make_cLCS.py contains the class compute_cLCS_squeezelines which uses the provided Cauchy-Green tensors obtained from mean_CG to compute the squeezelines associated to cLCS.
- plotting_cLCS.py using the squeezelines obtained from compute_cLCS_squeezeline
plotting_cLCScan help to visualise the resulting cLCS using cartopy.cLCSrho_cartopy_colourto plot the cLCS and the strength associated to them represented by a colourmap.cLCSrho_cartopy_monochrometo visualise the cLCS in one colour. - utils.py contains some utility functions used accross the different classes such as
sp2xy,xy2sphandget_colourmap. The latter contains personalised colourmap options for a different variety of colourmaps (see Additional info).
- 01_cLCS_ROMS.ipynb This jupyter notebook displays an example of how to compute the cLCS calculation using the data from the thesis referenced below.
- 02_LCS_SCHISM.ipynb This jupyter notebook displays an example of how to compute the LCS calculation using an unstructured-hydrodynamic model (SCHISM) and a wave model.
- 03_LCS_SCHISM_stokes_only.ipynb This jupyter notebook displays an example of how to compute the LCS calculation only considering stokes drift.
cLCS description and matlab toolbox
OpenDrift
Moana Project - BoP Study
Montano Orozco, M. M. (2023). Hydrodynamics and coastal dispersion from the Bay of Plenty, Aotearoa, New Zealand: A 25-year numerical modelling perspective (Thesis, Doctor of Philosophy). University of Otago. Retrieved from http://hdl.handle.net/10523/16243.
For a better formatted version of the thesis (working embedded links) please click here
Moana Project THREDDS
