In [3]:
# To parse the full dataset, we can call parse_cf without an argument, and assign the returned Dataset.
data = data.metpy.parse_cf()
x, y = data['tp'].metpy.coordinates('x', 'y')
time = data['tp'].metpy.time
timeinit = time[0]
timeinit = datetime.utcfromtimestamp(timeinit.item()/1e9)-timedelta(hours=1)
print(timeinit)
lon = data['tp'].metpy.longitude
lat = data['tp'].metpy.latitude
dx, dy = mpcalc.lat_lon_grid_deltas(lon, lat)
dx = dx[None, :]
dy = dy[None, :]
tp = data['tp']
tg = data['t']
ww = data['WW']
t = data['t2m']
td = data['d2m']
r = data['r2']
u = data['u10']
fg = data['gust']
v = data['v10']
hs = data['sde']
clcl = data_clcl['ccl']
clcm = data_clcm['ccl']
clch = data_clch['ccl']
lat = 49.62
lon = 6.2
#msl = msl.metpy.loc[{'latitude': lat, 'longitude': lon}]/100 #convert to hPa
t = t.metpy.loc[{'latitude': lat, 'longitude': lon}]-273.15
td = td.metpy.loc[{'latitude': lat, 'longitude': lon}]-273.15
tg = tg.metpy.loc[{'latitude': lat, 'longitude': lon}]-273.15 #convert to °C
u = u.metpy.loc[{'latitude': lat, 'longitude': lon}]
fg = fg.metpy.loc[{'latitude': lat, 'longitude': lon}]
v = v.metpy.loc[{'latitude': lat, 'longitude': lon}]
tp = tp.metpy.loc[{'latitude': lat, 'longitude': lon}]
#sp = sp.metpy.loc[{'latitude': lat, 'longitude': lon}]
r = r.metpy.loc[{'latitude': lat, 'longitude': lon}]
ww = ww.metpy.loc[{'latitude': lat, 'longitude': lon}]
clcl = clcl.metpy.loc[{'latitude': lat, 'longitude': lon}]
clcm = clcm.metpy.loc[{'latitude': lat, 'longitude': lon}]
clch = clch.metpy.loc[{'latitude': lat, 'longitude': lon}]
hs = hs.metpy.loc[{'latitude': lat, 'longitude': lon}]*100 # convert to cm
dd = mpcalc.wind_direction(u*units('m/s'), v*units('m/s'), convention='from')
ff = mpcalc.wind_speed(u*units('m/s'), v*units('m/s'))
td_calc = mpcalc.dewpoint_from_relative_humidity(t*units.degC,r)
#print(td.data.magnitude)
size = np.size(t)
plt.rcParams['axes.xmargin'] = 0
import matplotlib.dates as mdates
myFmt = mdates.DateFormatter('%d/%m\n%Hh')
loc = mdates.HourLocator(np.arange(0,24,2))
loc2 = mdates.HourLocator(np.arange(1,25,2))
fig, (ax1, ax2, ax3, ax4, ax5, ax6) = plt.subplots(6,1,figsize=(15,15))
ax1.plot(time[0:size], t[0:size], '-r', linewidth=3,zorder=5)
ax1.plot(time[0:size], td[0:size], '-g', linewidth=3)
ax1.set_ylabel('°C', fontsize=14)
ax1.set_yticks(np.arange(np.round(np.min(td))-2, np.round(np.max(t))+2,2))
ax1.set_ylim(np.round(np.min(td)-1),np.round(np.max(t)+2))
ax1.xaxis.set_major_locator(loc)
ax1.xaxis.set_minor_locator(loc2)
ax1.xaxis.set_major_formatter(myFmt)
ax1.tick_params(axis='both', which='major', labelsize=12)
ax1.legend(['Température 2 m','Point de rosée 2 m'],bbox_to_anchor=(0,1.02,1,0.2), loc="lower left",
fancybox=True, shadow=True, borderaxespad=0, ncol=3, fontsize=11)
ax1.grid(which='both', linestyle='--', linewidth='1',zorder=1)
#ax2.plot(time[6:size], td[6:size], '-g', linewidth=3)
ax2.plot(time[0:size], tg[0:size], 'tab:brown', linewidth=3,zorder=5)
ax2.set_ylabel('°C', fontsize=14)
ax2.set_ylim(np.round(np.min(tg)-2),np.round(np.max(tg)+2))
ax2.set_yticks(np.arange(np.round(np.min(tg))-2, np.round(np.max(tg))+2,2))
ax2.xaxis.set_major_locator(loc)
ax2.xaxis.set_minor_locator(loc2)
ax2.xaxis.set_major_formatter(myFmt)
ax2.tick_params(axis='both', which='major', labelsize=12)
ax2.legend(['Température près du sol'],bbox_to_anchor=(0,1.02,1,0.2), loc="lower left",
fancybox=True, shadow=True, borderaxespad=0, ncol=3, fontsize=11)
ax2.grid(which='both', linestyle='--', linewidth='1',zorder=1)
# ax3.plot(time[0:size], ff[0:size]*1.94384, '-k', linewidth=3,zorder=5)
# ax3.plot(time[0:size], fg[0:size]*1.94384, '--k', linewidth=3, zorder=5)
# ax3.set_ylabel('noeuds', fontsize=14)
# #ax3.set_yticks(np.arange(np.round(np.min(ff)), np.round(np.max(fg)),2))
# ax3.set_ylim(0,np.round(np.max(fg)+1))
# ax3.xaxis.set_major_locator(loc)
# ax3.xaxis.set_minor_locator(loc2)
# ax3.xaxis.set_major_formatter(myFmt)
# ax3.tick_params(axis='both', which='major', labelsize=12)
# ax3.legend(['Vent moyen 10 m','Rafales 10 m'],bbox_to_anchor=(0,1.02,1,0.2), loc="lower left",
# fancybox=True, shadow=True, borderaxespad=0, ncol=3, fontsize=11)
# ax3.grid(which='both', linestyle='--', linewidth='1', zorder=1)
for i in range(0,48):
ax3.bar(time[i], clcl[i], width=0.02, color='dimgrey',zorder=5)
ax3.bar(time[i], clcm[i], width=0.02, color='darkgrey',zorder=4)
ax3.bar(time[i], clch[i], width=0.02, color='lightgrey',zorder=3)
ax3.set_ylabel('%', fontsize=14)
#ax3.set_yticks([0,10,20,30,40,50,60,70,80,90,100])
ax3.set_yticks([0,20,40,60,80,100])
ax3.xaxis.set_major_locator(loc)
ax3.xaxis.set_minor_locator(loc2)
ax3.xaxis.set_major_formatter(myFmt)
ax3.tick_params(axis='both', which='major', labelsize=12)
ax3.legend(['Nébulosité basse (0-2 km)','Nébulosité moyenne (2-7 km)','Nébulosité haute (> 7 km)'],bbox_to_anchor=(0,1.02,1,0.2), loc="lower left",
fancybox=True, shadow=True, borderaxespad=0, ncol=3, fontsize=11)
ax3.grid(which='both', linestyle='--', linewidth='1',zorder=1)
rr = np.array(0)
for i in range(0,size):
if i==0:
ax4.bar(time[i], tp[i], width=0.02, color='b',zorder=5)
else:
rr = np.append(rr, tp[i]-tp[i-1])
ax4.bar(time[i], tp[i]-tp[i-1], width=0.02, color='b',zorder=5)
rr.astype(float)
print(np.nanmax(rr))
ax4.set_ylabel('mm', fontsize=14)
ax4.set_ylim(0,np.ceil(np.nanmax(rr)))
ax4.xaxis.set_major_locator(loc)
ax4.xaxis.set_minor_locator(loc2)
ax4.xaxis.set_major_formatter(myFmt)
ax4.tick_params(axis='both', which='major', labelsize=12)
ax4.legend(['Précipitations'],bbox_to_anchor=(0,1.02,1,0.2), loc="lower left",
fancybox=True, shadow=True, borderaxespad=0, ncol=3, fontsize=11)
ax4.grid(which='both', linestyle='--', linewidth='1',zorder=1)
ax5.plot(time[0:size], hs[0:size], 'purple', linewidth=3)
ax5.set_ylabel('cm', fontsize=14)
ax5.set_ylim(0,np.round(np.max(hs)+1))
#ax2.set_yticks([0,10,20,30,40,50,60,70,80,90,100])
ax5.xaxis.set_major_locator(loc)
ax5.xaxis.set_minor_locator(loc2)
ax5.xaxis.set_major_formatter(myFmt)
ax5.tick_params(axis='both', which='major', labelsize=12)
ax5.legend(['Couche de neige au sol'],bbox_to_anchor=(0,1.02,1,0.2), loc="lower left",
fancybox=True, shadow=True, borderaxespad=0, ncol=3, fontsize=11)
ax5.grid(which='both', linestyle='--', linewidth='1',zorder=1)
for i in range(0,size):
if np.round(ww[i])==71 or np.round(ww[i])==73 or np.round(ww[i])==75 or np.round(ww[i])==85 or np.round(ww[i])==86 :
ax6.plot(time[i], 0, color='purple', marker='.', markersize=25, zorder=5)
elif np.round(ww[i])==66 or np.round(ww[i])==67 or np.round(ww[i])==56 or np.round(ww[i])==57 :
ax6.plot(time[i], 0, color='red', marker='.', markersize=25, zorder=5)
elif np.round(ww[i])==61 or np.round(ww[i])==63 or np.round(ww[i])==65 or np.round(ww[i])==51 or np.round(ww[i])==53 or np.round(ww[i])==55 or np.round(ww[i])==80 or np.round(ww[i])==81 or np.round(ww[i])==82 :
ax6.plot(time[i], 0, color='green', marker='.', markersize=25, zorder=5)
elif np.round(ww[i])==45:
ax6.plot(time[i], 0, color='gold', marker='.', markersize=25, zorder=5)
elif np.round(ww[i])==48:
ax6.plot(time[i], 0, color='darkorange', marker='.', markersize=25, zorder=5)
else:
ax6.plot(time[i], 0, color='white', marker='.', markersize=25, zorder=1)
#ax6.plot(time[0:size], ww[0:size], color='k', marker='.', markersize=15, zorder=5)
ax6.set_ylabel('SIGWW', fontsize=14)
ax6.set_ylim(-0.1,0.1)
ax6.xaxis.set_major_locator(loc)
ax6.xaxis.set_minor_locator(loc2)
ax6.xaxis.set_major_formatter(myFmt)
ax6.tick_params(axis='both', which='major', labelsize=12)
ax6.set_yticks([])
from matplotlib.lines import Line2D
colors = ['green', 'red', 'purple', 'gold','darkorange']
lines = [Line2D([0], [0], color=c, marker='.', markersize=15, linestyle='None') for c in colors]
labels = ['Pluie/Bruine', 'Pluie/Bruine verglaçante', 'Neige', 'Brouillard', 'Brouillard givrant']
ax6.legend(lines,labels,bbox_to_anchor=(0,1.02,1,0.2), loc="lower left",
fancybox=True, shadow=True, borderaxespad=0, ncol=3, fontsize=11)
ax6.grid(which='both', linestyle='--', linewidth='1', zorder=1)
ax6.set_xlabel('Date/Heure (UTC)', fontsize=14)
ax7 = fig.add_axes([0.05,0.9,0.20,0.25])
ax7.axis('off')
ax7.imshow(im, aspect='equal', origin='upper', zorder=6)
ax1.set_title(timeinit.strftime('Base de données: Modèle ICON-D2 (Deutscher Wetterdienst) | ' + timeinit.strftime('Init: %d.%m.%Y %H:%M UTC')+'\nCoordonnées: 49.62°N, 6.2°E (Aéroport Luxembourg-Findel)\n'), fontsize=18)
fig.tight_layout()
plt.savefig('icond2_winterops.jpeg', format="jpeg", bbox_inches='tight', dpi=100)
plt.savefig('icond2_winterops.pdf', format="pdf", bbox_inches='tight', dpi=100)
Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable Found valid latitude/longitude coordinates, assuming latitude_longitude for projection grid_mapping variable
2023-07-13 03:00:00 0.0
/tmp/ipykernel_10677/4036542127.py:136: UserWarning: Attempting to set identical bottom == top == 0 results in singular transformations; automatically expanding. ax4.set_ylim(0,np.ceil(np.nanmax(rr))) /tmp/ipykernel_10677/4036542127.py:195: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect. fig.tight_layout()
