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Getting Started

Welcome to the documentation for NEMO initial conditions (pyIC)

Introduction

pyIC is a python package to generate initial conditions for regional NEMO model configurations.

Dependecies 🌐

pyIC is insatlled under a conda/mamba environment to aid wider distribution and to facilitate development. The key dependecies are listed below:

  • cf_xarray
  • netcdf4
  • numpy
  • xarray
  • xesmf
  • xgcm

Quick Start 🚀

Installation

To get started, check out and set up an instance of the pyIC GitHub repository:

export PYIC_DIR=$PWD/pyIC
git clone git@github.com:NOC-MSM/pyIC.git
Helpful Tip...
  • It is not advised to checkout the respository in your home directory.

Creating a specific conda virtual environment is highly recommended (click here for more about virtual enviroments). Load conda (e.g. through anaconda/miniforge) and create the environment through the provided environment.yml file.

cd $PYIC_DIR
conda env create -n pyic -f environment.yml

Activate the new environment

conda activate pyic

Install pyIC

pip install -e .

Usage

pyIC revolves around its GRID class, which takes a gridded data set as input (such as a netCDF, or any other file that can be opened using xarray). Then we use the Regridder within xesmf to regrid data on one GRID to another.

A basic example is included within the pyic_exe.py script and can be run from the command line. Further arguments are required to specify x, y, depth if they are not on a list of commonly inferred ones.

python pyic_exe.py --source /path/to/source/grid.nc --destination /path/to/destination/grid.nc --in_data /path/to/source/data.nc --out_path /path/to/destination/regridded_data.nc

These flags can be simplified to -s, -d, -i and -o respectively.

--out_path is optional and will be assumed to be regridded.nc if it is not passed to pyic_exe.py.

Example scripts

Several example python scripts can be found in the examples/ subdirectory. These are split into two rough categories: synthetic data (with scripts to create said data) and data from NEMO and other models.