def gh500_uv850_mslp(initial_time, fhour=0, model='ECMWF'):
"""
Analysis 500hPa geopotential height, 850hPa wind barbs, and
mean sea level pressure.
:param initial_time: initial time, string or datetime ojbect.
like '18042008' or datetime(2018, 4, 20, 8).
:param fhour: forecast hour.
:param model: model name.
:return: None.
"""
# micaps data directory
data_dirs = {
'ECMWF': [
'ECMWF_LR/HGT/500', 'ECMWF_LR/UGRD/850', 'ECMWF_LR/VGRD/850',
'ECMWF_LR/PRMSL'
],
'GRAPES': [
'GRAPES_GFS/HGT/500', 'GRAPES_GFS/UGRD/850', 'GRAPES_GFS/VGRD/850',
'GRAPES_GFS/PRMSL'
],
'NCEP': [
'NCEP_GFS/HGT/500', 'NCEP_GFS/UGRD/850', 'NCEP_GFS/VGRD/850',
'NCEP_GFS/PRMSL'
]
}
try:
data_dir = data_dirs[model.strip().upper()]
except KeyError:
raise ValueError('Unknown model, choose ECMWF, GRAPES or NCEP.')
# get filename
filename = model_filename(initial_time, fhour)
# retrieve data from micaps server
gh500 = get_model_grid(data_dir[0], filename=filename)
if gh500 is None:
return
init_time = gh500.coords['init_time'].values[0]
u850 = get_model_grid(data_dir[1], filename=filename)
if u850 is None:
return
v850 = get_model_grid(data_dir[2], filename=filename)
if v850 is None:
return
mslp = get_model_grid(data_dir[3], filename=filename)
if mslp is None:
return
# prepare data
gh500 = {
'lon': gh500.coords['lon'].values,
'lat': gh500.coords['lat'].values,
'data': gh500.values
}
uv850 = {
'lon': u850.coords['lon'].values,
'lat': u850.coords['lat'].values,
'udata': u850.values,
'vdata': v850.values
}
mslp = {
'lon': mslp.coords['lon'].values,
'lat': mslp.coords['lat'].values,
'data': mslp.values
}
# draw figure
fig = plt.figure(figsize=(10.5, 6))
plotcrs = ccrs.AlbersEqualArea(central_latitude=45.,
central_longitude=100.,
standard_parallels=[30., 60.])
gs = mpl.gridspec.GridSpec(1,
2,
width_ratios=[1, .02],
bottom=.07,
top=.99,
hspace=0.01,
wspace=0.01)
# draw main figure
ax = plt.subplot(gs[0], projection=plotcrs)
add_model_title('500-hPa Heights (m), 850-hPa Winds, MSLP (hPa)',
init_time,
model=model,
fhour=fhour,
fontsize=14)
plots = metp.draw_gh500_uv850_mslp(ax,
mslp=mslp,
gh500=gh500,
uv850=uv850,
map_extent=[50, 150, 0, 65],
regrid_shape=20)
# add color bar
cax = plt.subplot(gs[1])
cb = plt.colorbar(plots['mslp'],
cax=cax,
orientation='vertical',
extendrect='True',
ticks=plots['mslp'].levels)
cb.set_label('Mean sea level pressure', size=12)
# add logo
add_logo(fig, alpha=0.7)
# show figure
gs.tight_layout(fig)
plt.show()
def cref_uv850(initial_time, fhour=0, model='ShangHai',
map_center=(117, 39), map_width=12, draw_wind=False):
"""
Analysis composite reflectivity and 850hPa wind.
Arguments:
initial_time {string or datetime}} --
initial time, string or datetime ojbect.
like '18042008' or datetime(2018, 4, 20, 8).
Keyword Arguments:
fhour {int} -- forecast hour (default: {0})
model {str} -- model name (default: {'ShangHai'})
map_center {tuple} -- map center (default: {(117, 39)})
map_width {int} -- map width (default: {12})
draw_wind {bool} -- draw 850hPa wind or not (default: {False})
Raises:
ValueError -- [description]
"""
# micaps data directory
data_dirs = {
'SHANGHAI': ['SHANGHAI_HR/COMPOSITE_REFLECTIVITY/ENTIRE_ATMOSPHERE',
'SHANGHAI_HR/UGRD/850', 'SHANGHAI_HR/VGRD/850'],
'BEIJING': ['BEIJING_MR/COMPOSITE_REFLECTIVITY/ENTIRE_ATMOSPHERE',
'BEIJING_MR/UGRD/850', 'BEIJING_MR/VGRD/850'],
'GRAPES_MESO': ['GRAPES_MESO_HR/RADAR_COMBINATION_REFLECTIVITY',
'GRAPES_MESO_HR/UGRD/850', 'GRAPES_MESO_HR/VGRD/850'],
'GRAPES_3KM': ['GRAPES_3KM/RADAR_COMBINATION_REFLECTIVITY',
'GRAPES_3KM/UGRD/850', 'GRAPES_3KM/VGRD/850']}
try:
data_dir = data_dirs[model.strip().upper()]
except KeyError:
raise ValueError('Unknown model, choose ShangHai, BeiJing, Grapes_meso of Grapes_3km.')
# get filename
filename = model_filename(initial_time, fhour)
# retrieve data from micaps server
cref = get_model_grid(data_dir[0], filename=filename)
if cref is None:
return
init_time = cref.coords['init_time'].values[0]
if draw_wind:
u850 = get_model_grid(data_dir[1], filename=filename)
if u850 is None:
return
v850 = get_model_grid(data_dir[2], filename=filename)
if v850 is None:
return
# prepare data
data = np.ma.masked_array(cref.values)
data[data == 9999] = np.ma.masked
data[data < 10] = np.ma.masked
cref_data = {'lon':cref.coords['lon'].values,
'lat':cref.coords['lat'].values,
'data':np.squeeze(data)}
if draw_wind:
uv850 = {'lon': u850.coords['lon'].values,
'lat': u850.coords['lat'].values,
'udata': np.squeeze(u850.values),
'vdata': np.squeeze(v850.values)}
# set up map projection
datacrs = ccrs.PlateCarree()
plotcrs = ccrs.AlbersEqualArea(
central_latitude=map_center[1], central_longitude=map_center[0],
standard_parallels=[30., 60.])
# set up figure
fig = plt.figure(figsize=(12, 9))
gs = mpl.gridspec.GridSpec(
1, 2, width_ratios=[1, .03],
bottom=.01, top=.99, hspace=0.01, wspace=0.01)
ax = plt.subplot(gs[0], projection=plotcrs)
# add model title
add_model_title(
'CREF (dBz), 850-hPa Winds', init_time, model=model,
fhour=fhour, fontsize=18, multilines=True)
# add map background
map_extent = (
map_center[0] - map_width/2.0, map_center[0] + map_width/2.0,
map_center[1] - map_width/3.0, map_center[1] + map_width/3.0)
ax.set_extent(map_extent, crs=datacrs)
add_china_map_2cartopy(
ax, name='province', edgecolor='black',
lw=2, zorder=100)
# draw composite reflectivity
x, y = np.meshgrid(cref_data['lon'], cref_data['lat'])
norm, cmap = colortables.get_with_steps('NWSReflectivity', 12, 4)
pm = ax.pcolormesh(x, y, cref_data['data'], norm=norm, cmap=cmap, transform=datacrs)
cax = plt.subplot(gs[1])
cb = plt.colorbar(pm, cax=cax, orientation='vertical', extendrect='True')
cb.set_label('Composite reflectivity', size=12)
# draw wind vector
if draw_wind:
x, y = np.meshgrid(uv850['lon'], uv850['lat'])
ax.quiver(x, y, uv850['udata'], uv850['vdata'],
transform=datacrs, regrid_shape=25)
# show figure
gs.tight_layout(fig)
plt.show()
def qpf_24h(initial_time,
fhour=0,
model='ECMWF',
map_center=(117, 39),
map_width=12):
"""
Draw 24h accumulated QPF.
Arguments:
initial_time {string or datetime object} -- model initital time,
like '18042008' or datetime(2018, 4, 20, 8).
Keyword Arguments:
fhour {int} -- model initial time (default: {0})
model {str} -- model name (default: {'ECMWF'})
"""
# micaps data directory
data_dirs = {'ECMWF': ['ECMWF_HR/RAIN24']}
try:
data_dir = data_dirs[model.strip().upper()]
except KeyError:
raise ValueError('Unknown model, choose ECMWF, GRAPES or NCEP.')
# get file name
filename = model_filename(initial_time, fhour)
# retrieve data from micaps server
rain24 = get_model_grid(data_dir[0], filename=filename)
if rain24 is None:
print('Can not retrieve {} from Micaps server.'.format(filename))
return
init_time = rain24.coords['init_time'].values[0]
rain24 = {
'lon': rain24.coords['lon'].values,
'lat': rain24.coords['lat'].values,
'data': np.squeeze(rain24.values)
}
# set up map projection
datacrs = ccrs.PlateCarree()
plotcrs = ccrs.AlbersEqualArea(central_latitude=map_center[1],
central_longitude=map_center[0],
standard_parallels=[30., 60.])
# set up figure
fig = plt.figure(figsize=(10, 8))
ax = fig.add_axes([0, 0, 1, 1], projection=plotcrs)
# add model title
add_model_title('24h accumulated QPF',
init_time,
model=model,
fhour=fhour,
fontsize=18,
multilines=True,
atime=24)
# add map background
map_extent = (map_center[0] - map_width / 2.0,
map_center[0] + map_width / 2.0,
map_center[1] - map_width / 2.0,
map_center[1] + map_width / 2.0)
ax.set_extent(map_extent, crs=datacrs)
land_50m = cfeature.NaturalEarthFeature('physical',
'land',
'50m',
edgecolor='face',
facecolor=cfeature.COLORS['land'])
ax.add_feature(land_50m)
add_china_map_2cartopy(ax,
name='province',
edgecolor='darkcyan',
lw=1,
zorder=100)
# draw QPF
clevs = [0.1, 10, 25, 50, 100, 250]
colors = ["#88F492", "#00A929", "#2AB8FF", "#1202FC", "#FF04F4", "#850C3E"]
cmap, norm = mpl.colors.from_levels_and_colors(clevs, colors, extend='max')
ax.pcolormesh(rain24['lon'],
rain24['lat'],
rain24['data'],
norm=norm,
cmap=cmap,
transform=datacrs,
zorder=2)
# add custom legend
legend_elements = [
Patch(facecolor=colors[0], label='0.1~10mm'),
Patch(facecolor=colors[1], label='10~25mm'),
Patch(facecolor=colors[2], label='25~50mm'),
Patch(facecolor=colors[3], label='50~100mm'),
Patch(facecolor=colors[4], label='100~250mm'),
Patch(facecolor=colors[5], label='>250mm')
]
ax.legend(handles=legend_elements, loc='lower right', fontsize=16)
# add logo
add_logo(fig, alpha=0.7)
# show figure
ax.set_adjustable('datalim')
plt.show()
def cref_uv850_compare(initial_time, fhour=0, map_center=(117, 39), map_width=12, draw_wind=False):
"""
Compare mesoscale model's composite reflectivity.
Arguments:
initial_time {string or datetime}} --
initial time, string or datetime ojbect.
like '18042008' or datetime(2018, 4, 20, 8).
Keyword Arguments:
fhour {int} -- forecast hour (default: {0})
map_center {tuple} -- map center (default: {(117, 39)})
map_width {int} -- map width (default: {12})
draw_wind {bool} -- draw 850hPa wind or not (default: {False})
"""
# micaps data directory
data_dirs = {'SHANGHAI': ['SHANGHAI_HR/COMPOSITE_REFLECTIVITY/ENTIRE_ATMOSPHERE',
'SHANGHAI_HR/UGRD/850', 'SHANGHAI_HR/VGRD/850'],
'BEIJING': ['BEIJING_MR/COMPOSITE_REFLECTIVITY/ENTIRE_ATMOSPHERE',
'BEIJING_MR/UGRD/850', 'BEIJING_MR/VGRD/850'],
'GRAPES_MESO': ['GRAPES_MESO_HR/RADAR_COMBINATION_REFLECTIVITY',
'GRAPES_MESO_HR/UGRD/850', 'GRAPES_MESO_HR/VGRD/850'],
'GRAPES_3KM': ['GRAPES_3KM/RADAR_COMBINATION_REFLECTIVITY',
'GRAPES_3KM/UGRD/850', 'GRAPES_3KM/VGRD/850']}
# get filename
filename = model_filename(initial_time, fhour)
# set up map projection
datacrs = ccrs.PlateCarree()
plotcrs = ccrs.AlbersEqualArea(
central_latitude=map_center[1], central_longitude=map_center[0],
standard_parallels=[30., 60.])
# set up figure
fig = plt.figure(figsize=(16, 12))
axes_class = (GeoAxes, dict(map_projection=plotcrs))
grid = AxesGrid(fig, 111, axes_class=axes_class, nrows_ncols=(2, 2),
axes_pad=0.05, cbar_location='right', cbar_mode='single',
cbar_pad=0.05, label_mode='')
# loop every data directory
for index, key in enumerate(data_dirs):
# get axis and data directory
ax = grid[index]
data_dir = data_dirs[key]
# retrieve data from micaps server
cref = get_model_grid(data_dir[0], filename=filename)
if cref is None:
return
init_time = cref.coords['init_time'].values[0]
if draw_wind:
u850 = get_model_grid(data_dir[1], filename=filename)
if u850 is None:
return
v850 = get_model_grid(data_dir[2], filename=filename)
if v850 is None:
return
# add title
if index == 0:
initial_str, fhour_str, valid_str = get_model_time_stamp(init_time, fhour)
fig.suptitle('CREF (dBz), 850-hPa Winds ' + initial_str + '; ' + fhour_str + '; ' + valid_str,
x=0.5, y=0.9, fontsize=16)
# prepare data
data = np.ma.masked_array(cref.values)
data[data == 9999] = np.ma.masked
data[data < 10] = np.ma.masked
cref_data = {'lon':cref.coords['lon'].values,
'lat':cref.coords['lat'].values,
'data':np.squeeze(data)}
if draw_wind:
uv850 = {'lon': u850.coords['lon'].values,
'lat': u850.coords['lat'].values,
'udata': np.squeeze(u850.values),
'vdata': np.squeeze(v850.values)}
# add map background
map_extent = (
map_center[0] - map_width/2.0, map_center[0] + map_width/2.0,
map_center[1] - map_width/3.0, map_center[1] + map_width/3.0)
ax.set_extent(map_extent, crs=datacrs)
add_china_map_2cartopy(
ax, name='province', edgecolor='black',
lw=2, zorder=100)
# draw composite reflectivity
x, y = np.meshgrid(cref_data['lon'], cref_data['lat'])
norm, cmap = colortables.get_with_steps('NWSReflectivity', 12, 4)
pm = ax.pcolormesh(x, y, cref_data['data'], norm=norm, cmap=cmap, transform=datacrs)
# draw wind vector
if draw_wind:
x, y = np.meshgrid(uv850['lon'], uv850['lat'])
ax.quiver(x, y, uv850['udata'], uv850['vdata'],
transform=datacrs, regrid_shape=25)
# add title
add_titlebox(ax, key)
# add color bar
cbar = grid.cbar_axes[0].colorbar(pm)
# show figure
plt.show()