This notebook is part of the $\omega radlib$ documentation: https://docs.wradlib.org.

Copyright (c) $\omega radlib$ developers. Distributed under the MIT License. See LICENSE.txt for more info.

import wradlib as wrl
import warnings
warnings.filterwarnings('ignore')
import numpy as np
import os
import metpy
import requests
import matplotlib.pyplot as pl
import matplotlib.patheffects as pe
import matplotlib.colors
from matplotlib.colors import Normalize
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
from metpy.plots import ctables
from osgeo import osr


from datetime import timedelta, datetime

import urllib
import io
import glob

try:
    get_ipython().magic("matplotlib inline")
except:
    pl.ion()

from html.parser import HTMLParser
try:
    import urlparse
    from urllib import urlencode
except: # For Python 3
    import urllib.parse as urlparse
    from urllib.parse import urlencode

def ceil_dt(dt, delta):
    return dt + (datetime.min - dt) % delta
    
now = datetime.utcnow()-timedelta(hours=0, minutes=20)
timenow_iso = now.strftime("%Y-%m-%dT%H%M00")

print(timenow_iso)
#print(ceil_dt(now, timedelta(minutes=30)))

2022-08-31T051500

import requests
from requests.structures import CaseInsensitiveDict

url = "https://partner-api.meteofrance.fr/partner/radar/europe/odyssey/1.1/realtime/composite/RAINFALL_RATE/"+timenow_iso+"Z?format=HDF5"

headers = CaseInsensitiveDict()
headers["accept"] = "application/x-hdf"
headers["apikey"] = "eyJ4NXQiOiJZV0kxTTJZNE1qWTNOemsyTkRZeU5XTTRPV014TXpjek1UVmhNbU14T1RSa09ETXlOVEE0Tnc9PSIsImtpZCI6ImdhdGV3YXlfY2VydGlmaWNhdGVfYWxpYXMiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.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.aT7jM5QdhebQWiuy2JKqPTnDHTbgXgTKruY9kh2f4wokyyZsphHlqLKww3Y3qGiO5Xw69P3iZGepuFEH2erEgYdzNmDdsd7kbO6BkinFNTaHn67rYfTAvujf0rktdgwOWpz_B6YWsvPk7G9x9cmg4ET81mNn3us1cpAB9AZ-2GJEIHvKS3p4sapXAPBOZ7XDXHa9rmKoCd399ee5SySp6EwQBfuDy604FNiKBOUmNehqeAl_3Ir9QBLCZpJwdsLG3E3awgDiNBM0bX7nTuYYMdmvT4IK5ymhjE0_TyROYYJ4kGOqyP7vEjca1mH5yrJmCfNGLoDkWSNhDpHPg-NNTw=="


resp = requests.get(url, headers=headers)

print(resp.status_code)


open('/home/lmathias/Documents/wradlib/opera/sfcrr_latest.hdf5', 'wb').write(resp.content)

resp = glob.glob('/home/lmathias/Documents/wradlib/opera/sfcrr_latest.hdf5')
resp=resp[-1]
print(resp)

vol = wrl.io.hdf.read_opera_hdf5(resp)


#print(vol)
import dateutil.parser
date = vol['dataset1/what']['enddate'].decode("utf-8")
print(date)
time = vol['dataset1/what']['endtime'].decode("utf-8")
print(time)
time = date+time
print(time)
time2 = datetime.strptime(time, "%Y%m%d%H%M%S")-timedelta(hours=0, minutes=5)
print(time2)

url2 = "https://partner-api.meteofrance.fr/partner/radar/europe/odyssey/1.1/realtime/composite/REFLECTIVITY/"+timenow_iso+"Z?format=HDF5"

headers = CaseInsensitiveDict()
headers["accept"] = "application/x-hdf"
headers["apikey"] = "eyJ4NXQiOiJZV0kxTTJZNE1qWTNOemsyTkRZeU5XTTRPV014TXpjek1UVmhNbU14T1RSa09ETXlOVEE0Tnc9PSIsImtpZCI6ImdhdGV3YXlfY2VydGlmaWNhdGVfYWxpYXMiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.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.aT7jM5QdhebQWiuy2JKqPTnDHTbgXgTKruY9kh2f4wokyyZsphHlqLKww3Y3qGiO5Xw69P3iZGepuFEH2erEgYdzNmDdsd7kbO6BkinFNTaHn67rYfTAvujf0rktdgwOWpz_B6YWsvPk7G9x9cmg4ET81mNn3us1cpAB9AZ-2GJEIHvKS3p4sapXAPBOZ7XDXHa9rmKoCd399ee5SySp6EwQBfuDy604FNiKBOUmNehqeAl_3Ir9QBLCZpJwdsLG3E3awgDiNBM0bX7nTuYYMdmvT4IK5ymhjE0_TyROYYJ4kGOqyP7vEjca1mH5yrJmCfNGLoDkWSNhDpHPg-NNTw=="


resp2 = requests.get(url2, headers=headers)

print(resp2.status_code)


open('/home/lmathias/Documents/wradlib/opera/maxdbz_latest.hdf5', 'wb').write(resp2.content)

resp2=glob.glob('/home/lmathias/Documents/wradlib/opera/maxdbz_latest.hdf5')
resp2=resp2[-1]
print(resp2)

vol2 = wrl.io.hdf.read_opera_hdf5(resp2)

#print(vol)
import dateutil.parser
date = vol2['dataset1/what']['enddate'].decode("utf-8")
print(date)
time = vol2['dataset1/what']['endtime'].decode("utf-8")
print(time)
time = date+time
print(time)
time2 = datetime.strptime(time, "%Y%m%d%H%M%S")-timedelta(hours=0, minutes=5)
print(time2)

200
/home/lmathias/Documents/wradlib/opera/sfcrr_latest.hdf5
20220831
052000
20220831052000
2022-08-31 05:15:00
200
/home/lmathias/Documents/wradlib/opera/maxdbz_latest.hdf5
20220831
052000
20220831052000
2022-08-31 05:15:00

from pyproj import Proj,transform
import matplotlib.colors as mcolors
import numpy.ma as ma


myProj = Proj("+proj=laea +lat_0=55.0 +lon_0=10.0 +x_0=1950000.0 +y_0=-2100000.0 +units=m +ellps=WGS84")
projdef = "+proj=laea +lat_0=55.0 +lon_0=10.0 +x_0=1950000.0 +y_0=-2100000.0 +units=m +ellps=WGS84"
proj_stereo = wrl.georef.proj4_to_osr(projdef)
#print(proj_stereo)

 
opera_proj = Proj(projparams=projdef)  
wgs_proj = Proj(init='EPSG:4326')  # WGS84

LL_lon = vol['where']['LL_lon']
UL_lon = vol['where']['UL_lon']
UR_lon = vol['where']['UR_lon']
LR_lon = vol['where']['LR_lon']
LL_lat = vol['where']['LL_lat']
UL_lat = vol['where']['UL_lat']
UR_lat = vol['where']['UR_lat']
LR_lat = vol['where']['LR_lat']

x0, y0 = transform(wgs_proj, opera_proj, UL_lon, UL_lat)
x1, y1 = transform(wgs_proj, opera_proj, LR_lon, LR_lat)

xscale = 2000.0 
yscale = 2000.0

x = np.linspace(x0, x1, 1900)
y = np.linspace(y0, y1, 2200)
xv, yv = np.meshgrid(x, y)

lon, lat = transform(opera_proj, wgs_proj, xv, yv)

def plot_borders2(ax):
    filename = wrl.util.get_wradlib_data_file('geo/gadm36_LUX_0.shp')
    filename2 = wrl.util.get_wradlib_data_file('geo/gadm36_ITA_0.shp')
    filename3 = wrl.util.get_wradlib_data_file('geo/gadm36_BEL_0.shp')
    filename4 = wrl.util.get_wradlib_data_file('geo/gadm36_FRA_0.shp')
    filename5 = wrl.util.get_wradlib_data_file('geo/gadm36_DEU_0.shp')
    filename6 = wrl.util.get_wradlib_data_file('geo/gadm36_GBR_0.shp')
    filename7 = wrl.util.get_wradlib_data_file('geo/gadm36_NLD_0.shp')
    filename8 = wrl.util.get_wradlib_data_file('geo/gadm36_ESP_0.shp')
    filename9 = wrl.util.get_wradlib_data_file('geo/gadm36_CZE_0.shp')
    filename10 = wrl.util.get_wradlib_data_file('geo/gadm36_CHE_0.shp')
    filename11 = wrl.util.get_wradlib_data_file('geo/gadm36_DNK_0.shp')
    filename12 = wrl.util.get_wradlib_data_file('geo/gadm36_AUT_0.shp')
    filename13 = wrl.util.get_wradlib_data_file('geo/gadm36_POL_0.shp')
    filename14 = wrl.util.get_wradlib_data_file('geo/gadm36_SVN_0.shp')
    filename15 = wrl.util.get_wradlib_data_file('geo/gadm36_HRV_0.shp')
    dataset, inLayer = wrl.io.open_vector(filename)
    dataset2, inLayer2 = wrl.io.open_vector(filename2)
    dataset3, inLayer3 = wrl.io.open_vector(filename3)
    dataset4, inLayer4 = wrl.io.open_vector(filename4)
    dataset5, inLayer5 = wrl.io.open_vector(filename5)
    dataset6, inLayer6 = wrl.io.open_vector(filename6)
    dataset7, inLayer7 = wrl.io.open_vector(filename7)
    dataset8, inLayer8 = wrl.io.open_vector(filename8)
    dataset9, inLayer9 = wrl.io.open_vector(filename9)
    dataset10, inLayer10 = wrl.io.open_vector(filename10)
    dataset11, inLayer11 = wrl.io.open_vector(filename11)
    dataset12, inLayer12 = wrl.io.open_vector(filename12)
    dataset13, inLayer13 = wrl.io.open_vector(filename13)
    dataset14, inLayer14 = wrl.io.open_vector(filename14)
    dataset15, inLayer15 = wrl.io.open_vector(filename15)
    borders, keys = wrl.georef.get_vector_coordinates(inLayer)
    borders2, keys2 = wrl.georef.get_vector_coordinates(inLayer2)
    borders3, keys3 = wrl.georef.get_vector_coordinates(inLayer3)
    borders4, keys4 = wrl.georef.get_vector_coordinates(inLayer4)
    borders5, keys5 = wrl.georef.get_vector_coordinates(inLayer5)
    borders6, keys6 = wrl.georef.get_vector_coordinates(inLayer6)
    borders7, keys7 = wrl.georef.get_vector_coordinates(inLayer7)
    borders8, keys8 = wrl.georef.get_vector_coordinates(inLayer8)
    borders9, keys9 = wrl.georef.get_vector_coordinates(inLayer9)
    borders10, keys10 = wrl.georef.get_vector_coordinates(inLayer10)
    borders11, keys11 = wrl.georef.get_vector_coordinates(inLayer11)
    borders12, keys12 = wrl.georef.get_vector_coordinates(inLayer12)
    borders13, keys13 = wrl.georef.get_vector_coordinates(inLayer13)
    borders14, keys14 = wrl.georef.get_vector_coordinates(inLayer14)
    borders15, keys15 = wrl.georef.get_vector_coordinates(inLayer15)
    wrl.vis.add_lines(ax, borders, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders2, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders3, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders4, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders5, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders6, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders7, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders8, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders9, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders10, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders11, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders12, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders13, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders14, color='black', lw=1.5, zorder=4)
    wrl.vis.add_lines(ax, borders15, color='black', lw=1.5, zorder=4)



cmap = ctables.colortables.get_colortable('NWSStormClearReflectivity')
cmap2 = ctables.colortables.get_colortable('NWSReflectivity')

newcmap = ListedColormap(cmap(np.linspace(0.25, 0.92, 28)))

sfcrr = vol['dataset1/data1/data']

sfcdbz = 10*np.log10(200*sfcrr**(1.6))
sfcdbz = ma.masked_where(sfcdbz < 0, sfcdbz)
sfcrr = ma.masked_where(sfcrr < 0.5, sfcrr)

maxdbz = vol2['dataset1/data1/data']

maxdbz = ma.masked_where(maxdbz < 0, maxdbz)
sfcrr = ma.masked_where(sfcrr < 0.5, sfcrr)

#maxdbz_int = griddata(lon,lat, maxdbz, method='linear')

# fig = pl.figure(figsize=(15,11))
# ax = pl.subplot(111)
# pm = ax.pcolormesh(lon, lat, sfcrr, cmap=newcmap, vmin=10, vmax=70)
# cb = pl.colorbar(pm, ax=ax, shrink=0.9, ticks=[0,10,20,30,40,50,60,70],orientation='vertical')
# cb.set_label("dBZ",fontsize=16)
# cb.ax.tick_params(labelsize=14)
# pl.xlabel("Longitude ",fontsize=16) 
# pl.ylabel("Latitude",fontsize=16)
# pl.title(time2.strftime("%d.%m.%Y %H:%M UTC"),fontsize=22)
# pl.xticks(fontsize=12)
# pl.yticks(fontsize=12)
# pl.grid(linewidth=0.5, color='gray', alpha=0.5, linestyle='--')
# pl.xlim(-5, 16)
# pl.ylim(42, 55)
# plot_borders2(ax)
# t = pl.gcf().text(0.135, 0.84, 'Product: Maximum Reflectivity (OPERA)\nData: EUMETNET', fontsize=10)
# t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='black'))

# base_filename='opera_maxdbz_'
# suffix='.png'
# my_file = base_filename+time2.strftime("%Y%m%d%H%M")+suffix
# print(my_file)
# pl.savefig(my_file, bbox_inches='tight', dpi=300)

# fig = pl.figure(figsize=(15,11))
# ax = pl.subplot(111)
# pm = ax.pcolormesh(lon, lat, sfcdbz, cmap=newcmap, vmin=0, vmax=70)
# cb = pl.colorbar(pm, ax=ax, shrink=0.9, orientation='vertical')
# cb.set_label("dBZ",fontsize=16)
# cb.ax.tick_params(labelsize=14)
# pl.xlabel("Longitude ",fontsize=16) 
# pl.ylabel("Latitude",fontsize=16)
# pl.title(time2.strftime("%d.%m.%Y %H:%M UTC"),fontsize=22)
# pl.xticks(fontsize=12)
# pl.yticks(fontsize=12)
# pl.grid(linewidth=0.5, color='gray', alpha=0.5, linestyle='--')
# pl.xlim(-5, 16)
# pl.ylim(42, 55)
# plot_borders2(ax)
# t = pl.gcf().text(0.135, 0.84, 'Product: Low-Level Reflectivity\nData: OPERA/EUMETNET', fontsize=10)
# t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='black'))

# base_filename='opera_sfcrr_'
# suffix='.png'
# my_file = base_filename+time2.strftime("%Y%m%d%H%M")+suffix
# print(my_file)
# pl.savefig(my_file, bbox_inches='tight', dpi=80)

fig = pl.figure(figsize=(15,11))
ax = pl.subplot(111)
pm = ax.pcolormesh(lon, lat, sfcdbz, cmap=newcmap, vmin=0, vmax=70)
cb = pl.colorbar(pm, ax=ax, shrink=0.9, orientation='vertical')
cb.set_label("dBZ",fontsize=16)
cb.ax.tick_params(labelsize=14)
pl.xlabel("Longitude ",fontsize=16) 
pl.ylabel("Latitude",fontsize=16)
pl.title(time2.strftime("%d.%m.%Y %H:%M UTC"),fontsize=22)
pl.xticks(fontsize=12)
pl.yticks(fontsize=12)
pl.grid(linewidth=0.5, color='gray', alpha=0.5, linestyle='--')
pl.xlim(3.7, 8)
pl.ylim(48.5, 51)
plot_borders2(ax)
t = pl.gcf().text(0.135, 0.84, 'Product: Low-Level Reflectivity\nData: OPERA/EUMETNET', fontsize=10)
t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='black'))

base_filename='opera_sfcdbz_'
suffix='.jpeg'
my_file = base_filename+time2.strftime("%Y%m%d%H%M")+suffix
print(my_file)
pl.savefig(my_file, bbox_inches='tight', dpi=80)

opera_sfcdbz_202208310515.jpeg

---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
File ~/.conda/envs/wradlib/lib/python3.8/site-packages/IPython/core/formatters.py:339, in BaseFormatter.__call__(self, obj)
    337     pass
    338 else:
--> 339     return printer(obj)
    340 # Finally look for special method names
    341 method = get_real_method(obj, self.print_method)

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/IPython/core/pylabtools.py:151, in print_figure(fig, fmt, bbox_inches, base64, **kwargs)
    148     from matplotlib.backend_bases import FigureCanvasBase
    149     FigureCanvasBase(fig)
--> 151 fig.canvas.print_figure(bytes_io, **kw)
    152 data = bytes_io.getvalue()
    153 if fmt == 'svg':

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/backend_bases.py:2295, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2289     renderer = _get_renderer(
   2290         self.figure,
   2291         functools.partial(
   2292             print_method, orientation=orientation)
   2293     )
   2294     with getattr(renderer, "_draw_disabled", nullcontext)():
-> 2295         self.figure.draw(renderer)
   2297 if bbox_inches:
   2298     if bbox_inches == "tight":

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/artist.py:74, in _finalize_rasterization.<locals>.draw_wrapper(artist, renderer, *args, **kwargs)
     72 @wraps(draw)
     73 def draw_wrapper(artist, renderer, *args, **kwargs):
---> 74     result = draw(artist, renderer, *args, **kwargs)
     75     if renderer._rasterizing:
     76         renderer.stop_rasterizing()

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/artist.py:51, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     48     if artist.get_agg_filter() is not None:
     49         renderer.start_filter()
---> 51     return draw(artist, renderer)
     52 finally:
     53     if artist.get_agg_filter() is not None:

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/figure.py:2845, in Figure.draw(self, renderer)
   2842         # ValueError can occur when resizing a window.
   2844 self.patch.draw(renderer)
-> 2845 mimage._draw_list_compositing_images(
   2846     renderer, self, artists, self.suppressComposite)
   2848 for sfig in self.subfigs:
   2849     sfig.draw(renderer)

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/image.py:132, in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    130 if not_composite or not has_images:
    131     for a in artists:
--> 132         a.draw(renderer)
    133 else:
    134     # Composite any adjacent images together
    135     image_group = []

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/artist.py:51, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     48     if artist.get_agg_filter() is not None:
     49         renderer.start_filter()
---> 51     return draw(artist, renderer)
     52 finally:
     53     if artist.get_agg_filter() is not None:

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/axes/_base.py:3091, in _AxesBase.draw(self, renderer)
   3088         a.draw(renderer)
   3089     renderer.stop_rasterizing()
-> 3091 mimage._draw_list_compositing_images(
   3092     renderer, self, artists, self.figure.suppressComposite)
   3094 renderer.close_group('axes')
   3095 self.stale = False

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/image.py:132, in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    130 if not_composite or not has_images:
    131     for a in artists:
--> 132         a.draw(renderer)
    133 else:
    134     # Composite any adjacent images together
    135     image_group = []

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/artist.py:51, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     48     if artist.get_agg_filter() is not None:
     49         renderer.start_filter()
---> 51     return draw(artist, renderer)
     52 finally:
     53     if artist.get_agg_filter() is not None:

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/collections.py:2175, in QuadMesh.draw(self, renderer)
   2172     ys = self.convert_yunits(offsets[:, 1])
   2173     offsets = np.column_stack([xs, ys])
-> 2175 self.update_scalarmappable()
   2177 if not transform.is_affine:
   2178     coordinates = self._coordinates.reshape((-1, 2))

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/collections.py:905, in Collection.update_scalarmappable(self)
    903         # pcolormesh, scatter, maybe others flatten their _A
    904         self._alpha = self._alpha.reshape(self._A.shape)
--> 905     self._mapped_colors = self.to_rgba(self._A, self._alpha)
    907 if self._face_is_mapped:
    908     self._facecolors = self._mapped_colors

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/cm.py:456, in ScalarMappable.to_rgba(self, x, alpha, bytes, norm)
    454 if norm:
    455     x = self.norm(x)
--> 456 rgba = self.cmap(x, alpha=alpha, bytes=bytes)
    457 return rgba

File ~/.conda/envs/wradlib/lib/python3.8/site-packages/matplotlib/colors.py:641, in Colormap.__call__(self, X, alpha, bytes)
    638 else:
    639     lut = self._lut.copy()  # Don't let alpha modify original _lut.
--> 641 rgba = np.empty(shape=xa.shape + (4,), dtype=lut.dtype)
    642 lut.take(xa, axis=0, mode='clip', out=rgba)
    644 if alpha is not None:

MemoryError: Unable to allocate 128. MiB for an array with shape (4180000, 4) and data type float64

<Figure size 1500x1100 with 2 Axes>

fig = pl.figure(figsize=(15,11))
ax = pl.subplot(111)
pm = ax.pcolormesh(lon, lat, maxdbz, cmap=newcmap, vmin=0, vmax=70)
cb = pl.colorbar(pm, ax=ax, shrink=0.9, orientation='vertical')
cb.set_label("dBZ",fontsize=16)
cb.ax.tick_params(labelsize=14)
pl.xlabel("Longitude ",fontsize=16) 
pl.ylabel("Latitude",fontsize=16)
pl.title(time2.strftime("%d.%m.%Y %H:%M UTC"),fontsize=22)
pl.xticks(fontsize=12)
pl.yticks(fontsize=12)
pl.grid(linewidth=0.5, color='gray', alpha=0.5, linestyle='--')
pl.xlim(3.7, 8)
pl.ylim(48.5, 51)
plot_borders2(ax)
t = pl.gcf().text(0.135, 0.84, 'Product: Maximum Reflectivity\nData: OPERA/EUMETNET', fontsize=10)
t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='black'))

base_filename='opera_maxdbz_'
suffix='.jpeg'
my_file = base_filename+time2.strftime("%Y%m%d%H%M")+suffix
print(my_file)
pl.savefig(my_file, bbox_inches='tight', dpi=80)

opera_maxdbz_202208310515.jpeg