This software is licensed under the terms of the Apache Licence Version 2.0 which can be obtained at http://www.apache.org/licenses/LICENSE-2.0. In applying this licence, ECMWF does not waive the privileges and immunities granted to it by virtue of its status as an intergovernmental organisation nor does it submit to any jurisdiction.

POF Plotter¶

Importing all the necessary python libraries

import matplotlib
import matplotlib.pyplot as plt
from matplotlib import colors
from matplotlib import cm
from matplotlib.colors import Normalize
import numpy as np
import xarray as xr
import matplotlib as mpl
from cartopy import config
import cartopy.crs as ccrs
import cartopy as cart
import sys
import datetime
from matplotlib.colors import ListedColormap,LinearSegmentedColormap

Open Prediction Netcdf

year=2019
month=12


fire= xr.open_dataset(f"./outputs/POF_prediction_{year}_{month:02d}.nc")
fire = fire.assign_coords(longitude=((fire.longitude + 360) % 360)).sortby('longitude')
lats = fire.latitude.values
lons = fire.longitude.values
fire

Define a subregion to plot

lat1 = -10
lat2 = -45
lon1 = 110
lon2 = 155

sub_ds = fire.sel(
    latitude=slice(lat1, lat2), 
    longitude=slice(lon1, lon2)
)

sub_ds

Create colour pallete

cols = ['#4a5a60','#edcc00','#edcc00','#e57d0f','#e57d0f','#e57d0f','#e57d0f','#e57d0f','#e57d0f','#e21819','#e21819','#e21819','#e21819','#e21819','#000000','#000000']
test = ListedColormap(cols)

Define levels

index=0 # Which index to plot (1st of the month)

fires = sub_ds.fire_probability[index].values
plot_title = f"Probability of Fire Forecast for {sub_ds.time.values[index].strftime('%d %B %Y') }"

fires[fires>0.006]=0.006 # 1km

levels = np.arange(16)/2500 # 1km

print(np.shape(fires))
print(np.nanmax(fire.fire_probability.values))
print(np.nanmin(fire.fire_probability.values))
print(np.nanmean(fire.fire_probability.values))

(350, 451)
0.7821691036224365
7.712809946269772e-08
0.00037181633024126437

Plot

ax = plt.axes(projection=ccrs.PlateCarree())
ax.coastlines(linewidth=1)

fig = ax.contourf(sub_ds.longitude, sub_ds.latitude, fires,levels=levels,vmin=0,vmax=0.006,transform=ccrs.PlateCarree(),cmap=test)

ax.add_feature(cart.feature.OCEAN,zorder=1,edgecolor='k',color='white')
ax.add_feature(cart.feature.BORDERS,linewidth=0.5,color='white')
ax.add_feature(cart.feature.LAKES,color='white', edgecolor='k', linewidth=0.2, zorder=2)

states_provinces = cart.feature.NaturalEarthFeature(
        category='cultural',
        name='admin_1_states_provinces_lines',
        scale='50m',
        edgecolor='black'
)

for spine in ax.spines.values():
   spine.set_visible(False)

cbar = plt.colorbar(fig,ticks=[0.0002,0.0008,0.0022,0.0044,0.0056],fraction=0.025, pad=0.04)
cbar.ax.set_yticklabels(['Low', 'Medium','High', 'Very High', 'Extreme'])

plt.title(plot_title, fontsize=16)

plt.tight_layout()

plt.savefig('./outputs/My_PoF_Plot.png', dpi=300)

/opt/homebrew/Caskroom/miniforge/base/envs/POF_BOOK/lib/python3.14/site-packages/cartopy/mpl/feature_artist.py:143: UserWarning: facecolor will have no effect as it has been defined as "never".
  warnings.warn('facecolor will have no effect as it has been '
/opt/homebrew/Caskroom/miniforge/base/envs/POF_BOOK/lib/python3.14/site-packages/cartopy/io/__init__.py:242: DownloadWarning: Downloading: https://naturalearth.s3.amazonaws.com/50m_physical/ne_50m_lakes.zip
  warnings.warn(f'Downloading: {url}', DownloadWarning)