XORCA

What is this about?

XORCA brings XGCM and Xarray to the ORCA grid. (It actually brings all this to NEMO output. But xnemo was already taken.)

It allows for opening all output files from a model run into one Xarray dataset that is understood by XGCM. With this, grid-aware differentiation / differencing and integration / summation is possible.

Example: Calculate the barotropic stream function in 2 lines

After a short preamble which imports the package and loads the data:

import xarray as xr
import xgcm
from xorca.lib import load_xorca_dataset

ds = load_xorca_dataset(data_files=list_of_all_model_output_files,
                        aux_files=list_of_mesh_mask_files)
grid = xgcm.Grid(ds, periodic=["Y", "X"])

This is all that's needed to define and calculate the barotropic stream function for all time steps:

U_bt = (ds.vozocrtx * ds.e3u).sum("z_c")
psi = grid.cumsum(- U_bt * ds.e2u, "Y") / 1.0e6

And this triggers the actual computation and produces the image:

psi.mean("t").plot(size=9);

More examples

See the example notebook for hints on where this might end: notebooks/xorca_demo_ORCA05.ipynb.

Installation

First, install all dependencies (assuming you have conda installed and in the path):

curl \
    https://raw.githubusercontent.com/willirath/xorca/master/environment.yml \
    -o xorca_environment.yml
conda env create -n xorca_env -f xorca_environment.yml

Then install XORCA:

source activate xorca_env
pip install git+https://github.com/willirath/xorca.git@master

To use, source activate xorca_env before, e.g., starting jupyter notebook.