Define a standard gridΒΆ
Building models is much easier with standardized data. So define a standard grid (geographical projection, longitude range [-180,180], 0.25 degree resolution). All data will be regridded to this grid before use.
There is one user-accessible variable in this file
E5sCube - an iris cube on the standard grid (use as the target in regridding)
# Define common grids
# Models are grid specific, so it's easier to regrid early on
# and do everything on the common grid
import numpy as np
import iris
import iris.cube
import iris.util
import iris.analysis
import iris.coord_systems
# Define a standard-cube to work with
# Identical to that used in ERA5, except that the longitude cut is moved
# to mid pacific (-180) instead of over the UK (0)
resolution = 0.25
xmin = -180
xmax = 180
ymin = -90
ymax = 90
pole_latitude = 90
pole_longitude = 180
npg_longitude = 0
cs = iris.coord_systems.RotatedGeogCS(pole_latitude, pole_longitude, npg_longitude)
lat_values = np.arange(ymin, ymax + resolution, resolution)
latitude = iris.coords.DimCoord(
lat_values, standard_name="grid_latitude", units="degrees_north", coord_system=cs
)
lon_values = np.arange(xmin, xmax, resolution)
longitude = iris.coords.DimCoord(
lon_values, standard_name="grid_longitude", units="degrees_east", coord_system=cs
)
dummy_data = np.ma.MaskedArray(np.zeros((len(lat_values), len(lon_values))), False)
E5sCube = iris.cube.Cube(
dummy_data, dim_coords_and_dims=[(latitude, 0), (longitude, 1)]
)
E5scs = cs