Skip to content

Creation and analysis of MPAS-WRF meshes by Vortex

Notifications You must be signed in to change notification settings

gba-oliveira/vtx-mpas-meshes

 
 

Repository files navigation

vtx-mpas-meshes

Creation and analysis of MPAS-WRF meshes by Vortex

Work under progress. Example of regional mesh: example_mesh.png

Created by Marta Gil Bardají. Contact email: [email protected]

Installation Guide

To obtain a local copy of the code, clone this github repository meshes. Note that you need permission to do so.

$ git clone [email protected]:marta-gil/vtx-mpas-meshes.git

The necessary conda environment can be created using the environment.yml file present in the vtx-mpas-meshes repository cloned from github:

$ conda env create -n <envname> -f <path-to-environment.yml-file>

The conda environment contains:

  • mpas-tools & jigsaw for mesh creation
  • xarray, geopy, cartopy for mesh visualization
  • packages for documentation
  • jupyter notebook

The environment should be activated to run the scripts in this repository.

$ conda activate <envname>

Then you can install the scripts of this repository by installing the vtxmpasmeshes source files using the setup.py file.

(<envname>) $ pyhton setup.py install

To be able to run the Jupyter Notebooks, add the environment to ipykernel:

(<envname>) $ python -m ipykernel install --user --name=<envname>

and a successful message similar to this should appear:

Installed kernelspec <envname> in /home/<username>/.local/share/jupyter/kernels/<envname>

Mesh generation

Creates global and regional MPAS meshes based on global latlon resolution maps. The focus is on symmetric resolutions that are highest at a certain area of the planet and decrease radially.

example_resolution.png

Based on https://github.com/pedrospeixoto/MPAS-PXT/blob/master/grids/utilities/jigsaw/spherical_grid.py by Pedro S. Peixoto [email protected].

It uses:

About

Creation and analysis of MPAS-WRF meshes by Vortex

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 90.7%
  • Python 9.3%