Showing a 15-panel figure on an (A4) paper is not very convenient. Each individual panel will be very small. It might be better to put such figures in supplementing info, potentially on an interactive web page / dashboard (see #58).
I think one of the main roles of the all-method image is to convey the idea that "we collected data form many methods and can plot them in a consistent way". To this end, we could also stack the panels, a bit like this:
Where in our case the x- and z-axes would be lat/lon, whereas the y-axis is the method/ensemble member. The right panel could be the ensemble mean/std.
I very quickly tried to make something like this in python:
This is the corresponding source code:
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm
X, Y = np.meshgrid(ds.lon, ds.lat)
Z = np.zeros_like(X)
# Plot
fig = plt.figure()
ax = fig.add_subplot(projection="3d")
for n, (name, da) in enumerate(ds.data_vars.items()):
ax.plot_surface(X, Z+n, Y, facecolors=cm.GnBu(da))
Showing a 15-panel figure on an (A4) paper is not very convenient. Each individual panel will be very small. It might be better to put such figures in supplementing info, potentially on an interactive web page / dashboard (see #58).
I think one of the main roles of the all-method image is to convey the idea that "we collected data form many methods and can plot them in a consistent way". To this end, we could also stack the panels, a bit like this:
https://blog.i2s.fr/en/hyperspectral-imaging-an-invisible-revolution-in-quality-control-and-non-contactanalysis-with-extended-power/
Where in our case the x- and z-axes would be lat/lon, whereas the y-axis is the method/ensemble member. The right panel could be the ensemble mean/std.
I very quickly tried to make something like this in python:
This is the corresponding source code: