Regridding datasets#

Options:

Interpolating using Xarray
- https://docs.xarray.dev/en/stable/user-guide/interpolation.html
Reproject match using Rioxarray
- https://corteva.github.io/rioxarray/stable/examples/reproject_match.html
- https://rasterio.readthedocs.io/en/stable/api/rasterio.enums.html#rasterio.enums.Resampling
xESMF’s regridder
- https://xesmf.readthedocs.io/en/latest/notebooks/Dataset.html

import os
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import rasterio as rio
import xarray as xr
import xesmf as xe
import climag.climag as cplt

def plot_map(data, var, x, y, transform, cmap="Spectral_r", contour=False):
    """
    Helper function for plotting maps
    """

    plt.figure(figsize=(9, 7))
    ax = plt.axes(projection=cplt.projection_hiresireland)
    if contour:
        data.isel(time=180)[var].plot.contourf(
            ax=ax,
            x=x,
            y=y,
            levels=10,
            robust=True,
            transform=transform,
            cmap=cmap,
        )
    else:
        data.isel(time=180)[var].plot(
            ax=ax,
            x=x,
            y=y,
            levels=10,
            robust=True,
            transform=transform,
            cmap=cmap,
        )
    ax.gridlines(
        draw_labels=dict(bottom="x", left="y"),
        color="lightslategrey",
        linewidth=0.5,
        x_inline=False,
        y_inline=False,
    )
    ax.coastlines(resolution="10m", color="darkslategrey", linewidth=0.75)
    ax.set_title(str(data.isel(time=180)["time"].values))
    plt.tight_layout()
    plt.show()