def HRRR_error_wind_speed(DATE):
"""
return the error between the forecast and the analysis
Use this for multiprocessing
"""
# HRRR Analysis
Hu = get_hrrr_variable(DATE, variable='UGRD:'+level, verbose=False)
Hv = get_hrrr_variable(DATE, variable='VGRD:'+level, verbose=False)
#
# HRRR Forecast
Hfu = get_hrrr_variable(DATE-timedelta(hours=fxx), variable='UGRD:'+level, fxx=fxx, verbose=False)
Hfv = get_hrrr_variable(DATE-timedelta(hours=fxx), variable='VGRD:'+level, fxx=fxx, verbose=False)
#
# proof that I grabbed the right data from the archive
#print Hu['msg'], Hu['valid']
#print Hfu['msg'], Hfu['valid']
#
# Calculate the difference between the HRRR analysis and HRRR forecast (fxx-anlys)
# so that the red shows where the forecast is fast and blue shows where forecast
# is slow.
aSPD = wind_uv_to_spd(Hu['value'], Hv['value'])
fSPD = wind_uv_to_spd(Hfu['value'], Hfv['value'])
diff = fSPD-aSPD
#
return diff
def plot_Gfile(f):
# File scan Start time
scanStart = datetime.strptime(f.split('_')[3], 's%Y%j%H%M%S%f')
# Build the URL and temporary file name, then download
URL = "https://pando-rgw01.chpc.utah.edu/GOES16/ABI-L2-MCMIPC/%s/%s" % (
DATE.strftime('%Y%m%d'), f)
NAME = "./temp_GOES16_%s.nc" % (scanStart.strftime('%Y%m%d_%H%M'))
urllib.urlretrieve(URL, NAME)
# Get GOES TrueColor
G = get_GOES16_truecolor(NAME)
# Get HRRR Variable
hDATE = datetime(scanStart.year, scanStart.month, scanStart.day,
scanStart.hour)
H = get_hrrr_variable(hDATE, variable='TMP:700 mb')
# Plot GOES-16 True Color
plt.figure(1, figsize=(8, 10))
plt.clf()
plt.cla()
newmap = m.pcolormesh(G['lon'],
G['lat'],
G['TrueColor'][:, :, 1],
color=G['rgb_tuple'],
linewidth=0,
latlon=True)
newmap.set_array(
None) # must have this line if using pcolormesh and linewidth=0
# Plot HRRR 700 mb temperatures on map
CS = m.contour(H['lon'],
H['lat'],
H['value'] - 273.15,
latlon=True,
levels=range(-30, 30, 2),
cmap='Spectral_r',
vmin=-10,
vmax=10)
plt.clabel(CS, inline=1, fmt='%2.f')
m.drawcoastlines()
m.drawstates()
plt.title('GOES-16 TrueColor/IR and HRRR 700 mb Temperature\nGOES Date:%s\nHRRR Date:%s' \
% (G['DATE'].strftime('%Y %b %d, %H:%M'), H['valid'].strftime('%Y %b %d, %H:%M')))
figname = 'GOES16TrueColor_HRRR700mbTemp_%s.png' % (
G['DATE'].strftime('%Y%m%d-%H%M'))
plt.savefig(figname, bbox_inches='tight', dpi=150)
print "Created:", figname
# Remove the temp file
os.remove(NAME)
print 'removed:', NAME
def HRRR_error(DATE):
"""
return the error between the forecast and the analysis
Use this for multiprocessing
"""
# HRRR Analysis
H = get_hrrr_variable(DATE, variable=var, verbose=False)
#
# HRRR Forecast
Hf = get_hrrr_variable(DATE-timedelta(hours=fxx), variable=var, fxx=fxx, verbose=False)
#
# proof that I grabbed the right data from the archive
#print H['msg'], H['valid']
#print Hf['msg'], Hf['valid']
#
# Calculate the difference between the HRRR analysis and HRRR forecast (fxx-anlys)
# so that the red shows where the forecast is fast and blue shows where forecast
# is slow.
diff = Hf['value']-H['value']
#
return diff
def make_plots(FILE):
# Get HRRR Temperature
scanStart = datetime.strptime(flist[0].split('/')[-1].split('_')[3],
's%Y%j%H%M%S%f')
DATE_hour = datetime(scanStart.year, scanStart.month, scanStart.day,
scanStart.hour)
H = get_hrrr_variable(DATE_hour, variable="HGT:500 mb")
# Get GOES data dictionary
G = get_GOES16_truecolor(FILE)
# Make and save images
map_HRRR_domain(G, H)
map_UTAH_domain(G)
def get_HRRR_value(getthisDATE):
"""
Getting HRRR data, just return the value (not the latitude and longitude)
"""
print getthisDATE
H = get_hrrr_variable(getthisDATE,
variable,
fxx=fxx,
model='hrrr',
field='sfc',
value_only=True,
verbose=False)
if H['value'] is None:
print "!! WARNING !! COULD NOT GET", getthisDATE
return H['value']
from BB_basemap.draw_maps import draw_CONUS_HRRR_map
from BB_downloads.HRRR_S3 import get_hrrr_variable
from BB_cmap.landuse_colormap import LU_MODIS21
#==============================================================================
DATE = datetime(2016, 9, 1)
model = 'hrrr'
# 1) Get Landuse from HRRR S3 archive
VAR = 'VGTYP:surface'
if model == 'hrrrX':
# The VGTYP variable is hidden here:
VAR = 'var discipline=2 center=59 local_table=1 parmcat=0 parm=198'
H = get_hrrr_variable(DATE, VAR, model=model)
# 2) Get the map object and draw map
m = draw_CONUS_HRRR_map()
m.drawcoastlines(linewidth=.3)
m.drawcountries(linewidth=.3)
m.drawstates(linewidth=.3)
x, y = m(H['lon'], H['lat'])
# 3) Plot the map
# Colormap and labels
cm, labels = LU_MODIS21()
m.pcolormesh(x, y, H['value'], cmap=cm, vmin=1, vmax=len(labels) + 1)
# Get Data
eDATE = DATE
prev30 = eDATE - timedelta(minutes=30)
prev60 = eDATE - timedelta(minutes=60)
prev90 = eDATE - timedelta(minutes=90)
print 'getting GLM'
GLM_prev_60_90 = accumulate_GLM(get_GLM_files_for_range(
prev90, prev60)) # 60-90 minutes ago
GLM_prev_30_60 = accumulate_GLM(get_GLM_files_for_range(
prev60, prev30)) # 30-60 minutes ago
GLM_prev_00_30 = accumulate_GLM(get_GLM_files_for_range(
prev30, eDATE)) # 0-30 minutes ago
print 'getting HRRR'
H = get_hrrr_variable(eDATE, 'UVGRD:500 mb', verbose=False)
# Set radius in miles
miles = 300
meters = 1609.344 * miles
# Set the earth elipse for pyproj.Geod
g = Geod(ellps='clrk66')
###############################################################################
for loc in location.keys():
l = location[loc]
# Perform distance calculation between fire and flashes
for data, name in [(GLM_prev_00_30, 'prev 00-30'),
(GLM_prev_30_60, 'prev 30-60'),
(GLM_prev_60_90, 'prev 60-90')]:
# proof that I grabbed the right data from the archive
#print H['msg'], H['valid']
#print Hf['msg'], Hf['valid']
#
# Calculate the difference between the HRRR analysis and HRRR forecast (fxx-anlys)
# so that the red shows where the forecast is fast and blue shows where forecast
# is slow.
diff = Hf['value']-H['value']
#
return diff
# Draw HRRR CONUS
m = draw_CONUS_HRRR_map()
# need a set of lat/lon grid variables, so just grab with this...
H = get_hrrr_variable(datetime(2017, 10, 1), 'TMP:2 m')
options = {1:{'var' : 'TMP:2 m',
'name' : '2 m Temperature',
'mean label' : r'$\Delta$ Temperature (C)',
'rmse label' : 'RMSE Temperature (C)',
'save prefix': 'TMP2m',
'mean maxmin': [3, -3],
'rmse max' : 5,
'mean cmap' : 'bwr',
'WIND' : False},
2:{'var' : 'UGRD:10 m',
'name' : '10 m Wind Speed',
'mean label' : r'$\Delta$ Wind Speed (m s$\mathregular{^{-1}}$)',
'rmse label' : r'RMSE Wind Speed (m s$\mathregular{^{-1}}$)',
def make_plots(inputs):
VALIDDATE, fxx = inputs
print 'working on %s f%02d' % (VALIDDATE, fxx)
plt.clf()
plt.cla()
print fxx, VALIDDATE
# === Some housekeeping variables =============================================
# Convert Valid Date to Run Date, adjusted by the forecast
DATE = VALIDDATE - timedelta(hours=fxx)
# Parse Location lat/lon
if ',' in location:
# User put inputted a lat/lon point request
lat, lon = location.split(',')
lat = float(lat)
lon = float(lon)
else:
# User requested a MesoWest station
stninfo = get_station_info([location])
lat = stninfo['LAT']
lon = stninfo['LON']
# Preload the latitude and longitude grid
latlonpath = '/uufs/chpc.utah.edu/common/home/horel-group7/Pando/hrrr/HRRR_latlon.h5'
latlonh5 = h5py.File(latlonpath, 'r')
gridlat = latlonh5['latitude'][:]
gridlon = latlonh5['longitude'][:]
# === Create map of the domain ================================================
if dsize == 'conus' and model != 'hrrrAK':
barb_thin = 70
alpha = 1
t1 = datetime.now()
#m = draw_CONUS_HRRR_map(res=map_res)
m = np.load(
'/uufs/chpc.utah.edu/common/home/u0553130/public_html/Brian_Blaylock/cgi-bin/HRRR_CONUS_map_object_'
+ map_res + '.npy').item()
m.drawcountries(zorder=500)
m.drawstates(zorder=500)
m.drawcoastlines(zorder=500)
m.fillcontinents(color='tan', lake_color='lightblue', zorder=0)
m.drawmapboundary(fill_color='lightblue')
t2 = datetime.now()
else:
# configure some setting based on the requested domain size
if dsize == 'small':
plus_minus_latlon = .27 # +/- latlon box around center point
barb_thin = 1 # Thin out excessive wind barbs
arcgis_res = 1000 # ArcGIS image resolution
bfr = 15 # trim domain buffer
alpha = .75 # Alpha (pcolormesh transparency)
elif dsize == 'medium':
plus_minus_latlon = .75
barb_thin = 2
arcgis_res = 800
bfr = 35
alpha = .75
elif dsize == 'large':
plus_minus_latlon = 2.5
barb_thin = 6
arcgis_res = 800
bfr = 110
alpha = .75
elif dsize == 'xlarge':
plus_minus_latlon = 5
barb_thin = 12
arcgis_res = 700
bfr = 210
alpha = .75
elif dsize == 'xxlarge': # If domain runs into HRRR boundary, then it'll fail
plus_minus_latlon = 10
barb_thin = 25
arcgis_res = 700
bfr = 430
alpha = .75
elif dsize == 'xxxlarge':
plus_minus_latlon = 15
barb_thin = 35
arcgis_res = 1000
bfr = 700
alpha = .75
m = Basemap(resolution=map_res, projection='cyl',\
area_thresh=3000,\
llcrnrlon=lon-plus_minus_latlon, llcrnrlat=lat-plus_minus_latlon,\
urcrnrlon=lon+plus_minus_latlon, urcrnrlat=lat+plus_minus_latlon,)
m.drawstates(zorder=500)
m.drawcountries(zorder=500)
m.drawcoastlines(zorder=500)
#if dsize == 'small' or dsize == 'medium':
# m.drawcounties()
# === Add a Background image ==================================================
# Start the map image
plt.figure(1)
if background == 'arcgis' and dsize != 'conus':
m.arcgisimage(service='World_Shaded_Relief',
xpixels=arcgis_res,
verbose=False)
elif background == 'arcgisSat' and dsize != 'conus':
m.arcgisimage(service='ESRI_Imagery_World_2D',
xpixels=arcgis_res,
verbose=False)
elif background == 'arcgisRoad' and dsize != 'conus':
m.arcgisimage(service='NatGeo_World_Map',
xpixels=arcgis_res,
verbose=False)
elif background == 'terrain':
# Get data
H_ter = get_hrrr_variable(
DATE,
'HGT:surface',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
H_land = get_hrrr_variable(
DATE,
'LAND:surface',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Plot the terrain
m.contourf(gridlon,
gridlat,
H_ter['value'],
levels=range(0, 4000, 200),
cmap='Greys_r',
zorder=1,
latlon=True)
# Plot Water area
m.contour(gridlon,
gridlat,
H_land['value'],
levels=[0, 1],
colors='b',
zorder=1,
latlon=True)
elif background == 'landuse':
# Get data
from BB_cmap.landuse_colormap import LU_MODIS21
if model == 'hrrr':
VGTYP = 'VGTYP:surface'
else:
VGTYP = 'var discipline=2 center=59 local_table=1 parmcat=0 parm=198'
H_LU = get_hrrr_variable(
DATE,
VGTYP,
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Plot the terrain
cm, labels = LU_MODIS21()
m.pcolormesh(gridlon,
gridlat,
H_LU['value'],
cmap=cm,
vmin=1,
vmax=len(labels) + 1,
zorder=1,
latlon=True)
# Add SHAPEFILE
if is_FIRE:
plt.gca().add_collection(
PatchCollection(patches,
facecolor='indianred',
alpha=.65,
edgecolor='k',
linewidths=1,
zorder=1))
# === Figure Title ============================================================
if dsize != 'conus':
m.scatter(lon, lat, marker='+', c='r', s=100, zorder=1000, latlon=True)
plt.title('Center: %s\n%s' % (location, model.upper()),
fontweight='bold')
else:
plt.title('%s' % (model.upper()), fontweight='bold')
plt.title('Run: %s F%02d' % (DATE.strftime('%Y-%m-%d %H:%M UTC'), fxx),
loc='left')
plt.title('Valid: %s' %
(DATE + timedelta(hours=fxx)).strftime('%Y-%m-%d %H:%M UTC'),
loc='right')
# =============================================================================
if '10mWind_Fill' in plotcode or '10mWind_Shade' in plotcode or '10mWind_Barb' in plotcode or '10mWind_Quiver' in plotcode or '10mWind_p95_fill' in plotcode:
# Get data
H_u = get_hrrr_variable(
DATE,
'UGRD:10 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
H_v = get_hrrr_variable(
DATE,
'VGRD:10 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
spd = wind_uv_to_spd(H_u['value'], H_v['value'])
if '10mWind_Fill' in plotcode:
m.pcolormesh(gridlon,
gridlat,
spd,
latlon=True,
cmap=cm_wind(),
vmin=0,
vmax=60,
alpha=alpha)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'10 m Wind Speed (m s$\mathregular{^{-1}}$)')
if '10mWind_Shade' in plotcode:
m.contourf(gridlon,
gridlat,
spd,
levels=[10, 15, 20, 25],
colors=('yellow', 'orange', 'red'),
alpha=alpha,
extend='max',
zorder=1,
latlon=True)
cb = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cb.set_label(r'10 m Wind Speed (ms$\mathregular{^{-1}}$)')
if '10mWind_Barb' in plotcode or '10mWind_Quiver' in plotcode:
# For small domain plots, trimming the edges significantly reduces barb plotting time
if barb_thin < 20:
cut_v, cut_h = pluck_point_new(lat, lon, gridlat, gridlon)
Cgridlat = gridlat[cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
Cgridlon = gridlon[cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
H_u['value'] = H_u['value'][cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
H_v['value'] = H_v['value'][cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
else:
Cgridlat = gridlat
Cgridlon = gridlon
thin = barb_thin
# Add to plot
if '10mWind_Barb' in plotcode:
m.barbs(Cgridlon[::thin, ::thin],
Cgridlat[::thin, ::thin],
H_u['value'][::thin, ::thin],
H_v['value'][::thin, ::thin],
zorder=200,
length=5.5,
barb_increments={
'half': 2.5,
'full': 5,
'flag': 25
},
latlon=True)
if '10mWind_Quiver' in plotcode:
Q = m.quiver(Cgridlon[::thin, ::thin],
Cgridlat[::thin, ::thin],
H_u['value'][::thin, ::thin],
H_v['value'][::thin, ::thin],
zorder=350,
latlon=True)
qk = plt.quiverkey(Q,
.92,
0.07,
10,
r'10 m s$^{-1}$',
labelpos='S',
coordinates='axes',
color='darkgreen')
qk.text.set_backgroundcolor('w')
if '10mWind_p95_fill' in plotcode:
DIR = '/uufs/chpc.utah.edu/common/home/horel-group8/blaylock/HRRR_OSG/hourly30/UVGRD_10_m/'
FILE = 'OSG_HRRR_%s_m%02d_d%02d_h%02d_f00.h5' % (
('UVGRD_10_m', VALIDDATE.month, VALIDDATE.day, VALIDDATE.hour))
with h5py.File(DIR + FILE, 'r') as f:
spd_p95 = f["p95"][:]
masked = spd - spd_p95
masked = np.ma.array(masked)
masked[masked < 0] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
masked,
vmax=10,
vmin=0,
latlon=True,
cmap='viridis',
alpha=alpha)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(
r'10 m Wind Speed exceeding 95th Percentile (m s$\mathregular{^{-1}}$)'
)
if '80mWind_Fill' in plotcode or '80mWind_Shade' in plotcode or '80mWind_Barb' in plotcode:
# Get data
H_u = get_hrrr_variable(
DATE,
'UGRD:80 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
H_v = get_hrrr_variable(
DATE,
'VGRD:80 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
spd = wind_uv_to_spd(H_u['value'], H_v['value'])
if '80mWind_Fill' in plotcode:
m.pcolormesh(gridlon,
gridlat,
spd,
latlon=True,
cmap=cm_wind(),
vmin=0,
vmax=60,
alpha=alpha)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'10 m Wind Speed (m s$\mathregular{^{-1}}$)')
if '80mWind_Shade' in plotcode:
m.contourf(gridlon,
gridlat,
spd,
levels=[10, 15, 20, 25],
colors=('yellow', 'orange', 'red'),
alpha=alpha,
extend='max',
zorder=10,
latlon=True)
cb = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cb.set_label(r'10 m Wind Speed (ms$\mathregular{^{-1}}$)')
if '80mWind_Barb' in plotcode:
# For small domain plots, trimming the edges significantly reduces barb plotting time
if barb_thin < 20:
cut_v, cut_h = pluck_point_new(lat, lon, gridlat, gridlon)
Cgridlat = gridlat[cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
Cgridlon = gridlon[cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
H_u['value'] = H_u['value'][cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
H_v['value'] = H_v['value'][cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
else:
Cgridlat = gridlat
Cgridlon = gridlon
# Add to plot
thin = barb_thin
m.barbs(Cgridlon[::thin, ::thin],
Cgridlat[::thin, ::thin],
H_u['value'][::thin, ::thin],
H_v['value'][::thin, ::thin],
zorder=200,
length=5.5,
color='darkred',
barb_increments={
'half': 2.5,
'full': 5,
'flag': 25
},
latlon=True)
if 'Fill80mWind' in plotcode:
m.pcolormesh(gridlon,
gridlat,
spd,
latlon=True,
cmap=cm_wind(),
vmin=0,
vmax=60,
alpha=alpha)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'80 m Wind Speed (m s$\mathregular{^{-1}}$)')
if 'Gust_Hatch' in plotcode:
H_gust = get_hrrr_variable(
DATE,
'GUST:surface',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Add to plot
m.contourf(gridlon,
gridlat,
H_gust['value'],
levels=[0, 10, 15, 20, 25],
hatches=[None, '.', '\\\\', '*'],
colors='none',
extend='max',
zorder=10,
latlon=True)
cb = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cb.set_label(r'Surface Wind Gust (ms$\mathregular{^{-1}}$)')
m.contour(gridlon,
gridlat,
H_gust['value'],
levels=[10, 15, 20, 25],
colors='k',
zorder=10,
latlon=True)
if 'dBZ_Fill' in plotcode or 'dBZ_Contour' in plotcode:
from BB_cmap.reflectivity_colormap import reflect_ncdc
# Get Data
if model == 'hrrr':
REFC = 'REFC:entire'
elif model == 'hrrrX' or model == 'hrrrAK':
REFC = 'var discipline=0 center=59 local_table=1 parmcat=16 parm=196'
H_ref = get_hrrr_variable(
DATE,
REFC,
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Mask values
dBZ = H_ref['value']
dBZ = np.ma.array(dBZ)
dBZ[dBZ == -10] = np.ma.masked
# Add Contour to plot
if 'dBZ_Contour' in plotcode:
cREF = m.contour(gridlon,
gridlat,
dBZ,
cmap=reflect_ncdc(),
levels=range(10, 80, 10),
latlon=True,
zorder=50)
plt.clabel(cREF,
cREF.levels[::2],
fmt='%2.0f',
colors='k',
fontsize=9)
#cb2 = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
#cb2.set_label('Simulated Composite Reflectivity (dBZ)')
# Add fill to plot
if 'dBZ_Fill' in plotcode:
m.pcolormesh(gridlon,
gridlat,
dBZ,
cmap=reflect_ncdc(),
vmax=80,
vmin=0,
alpha=alpha,
latlon=True)
cb2 = plt.colorbar(orientation='horizontal',
shrink=shrink,
pad=pad)
cb2.set_label('Simulated Composite Reflectivity (dBZ)')
if '2mDPT_p95p05_fill' in plotcode:
H_dpt = get_hrrr_variable(
DATE,
'DPT:2 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
DIR = '/uufs/chpc.utah.edu/common/home/horel-group8/blaylock/HRRR_OSG/hourly30/DPT_2_m/'
FILE = 'OSG_HRRR_%s_m%02d_d%02d_h%02d_f00.h5' % (
('DPT_2_m', VALIDDATE.month, VALIDDATE.day, VALIDDATE.hour))
### Plot Dew Point Depression
with h5py.File(DIR + FILE, 'r') as f:
dpt_p05 = f["p05"][:]
masked = H_dpt[
'value'] - dpt_p05 # both these datasets are in Kelvin, but when we take the difference it is in Celsius
masked = np.ma.array(masked)
masked[masked > 0] = np.ma.masked
mesh_depression = m.pcolormesh(gridlon,
gridlat,
masked,
vmax=10,
vmin=-10,
latlon=True,
cmap='BrBG')
### Plot Dew Point Exceedance
with h5py.File(DIR + FILE, 'r') as f:
dpt_p95 = f["p95"][:]
masked = H_dpt[
'value'] - dpt_p95 # both these datasets are in Kelvin, but when we take the difference it is in Celsius
masked = np.ma.array(masked)
masked[masked < 0] = np.ma.masked
mesh_exceedance = m.pcolormesh(gridlon,
gridlat,
masked,
vmax=10,
vmin=-10,
latlon=True,
cmap='BrBG')
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(
r'5$\mathregular{^{th}}$/95$\mathregular{^{th}}$ percentile 2 m Dew Point Depression/Exceedance (C)'
)
if '2mTemp_Fill' in plotcode or '2mTemp_Freeze' in plotcode or '2mTemp_p95p05_fill' in plotcode:
# Get Data
H_temp = get_hrrr_variable(
DATE,
'TMP:2 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
TMP = H_temp['value'] - 273.15
# Add fill to plot
if '2mTemp_Fill' in plotcode:
m.pcolormesh(gridlon,
gridlat,
TMP,
cmap=cm_temp(),
vmax=50,
vmin=-50,
alpha=alpha,
zorder=3,
latlon=True)
cbT = plt.colorbar(orientation='horizontal',
shrink=shrink,
pad=pad)
cbT.set_label('2 m Temperature (C)')
# Add freezing contour to plot
if '2mTemp_Freeze' in plotcode:
m.contour(gridlon,
gridlat,
TMP,
colors='b',
levels=[0],
zorder=400,
latlon=True)
if '2mTemp_p95p05_fill' in plotcode:
DIR = '/uufs/chpc.utah.edu/common/home/horel-group8/blaylock/HRRR_OSG/hourly30/TMP_2_m/'
FILE = 'OSG_HRRR_%s_m%02d_d%02d_h%02d_f00.h5' % (
('TMP_2_m', VALIDDATE.month, VALIDDATE.day, VALIDDATE.hour))
### Plot Temperature Depression
with h5py.File(DIR + FILE, 'r') as f:
tmp_p05 = f["p05"][:]
masked = H_temp[
'value'] - tmp_p05 # both these datasets are in Kelvin, but when we take the difference it is in Celsius
masked = np.ma.array(masked)
masked[masked > 0] = np.ma.masked
mesh_depression = m.pcolormesh(gridlon,
gridlat,
masked,
vmax=10,
vmin=-10,
latlon=True,
cmap='bwr')
### Plot Temperature Exceedance
with h5py.File(DIR + FILE, 'r') as f:
tmp_p95 = f["p95"][:]
masked = H_temp[
'value'] - tmp_p95 # both these datasets are in Kelvin, but when we take the difference it is in Celsius
masked = np.ma.array(masked)
masked[masked < 0] = np.ma.masked
mesh_exceedance = m.pcolormesh(gridlon,
gridlat,
masked,
vmax=10,
vmin=-10,
latlon=True,
cmap='bwr')
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(
r'5$\mathregular{^{th}}$/95$\mathregular{^{th}}$ percentile 2 m Temperature Depression/Exceedance (C)'
)
if '2mRH_Fill' in plotcode:
# Get Data
try:
H_RH = get_hrrr_variable(
DATE,
'RH:2 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Add fill to plot
m.pcolormesh(gridlon,
gridlat,
H_RH['value'],
cmap=cm_rh(),
vmin=5,
vmax=90,
zorder=3,
latlon=True)
cbT = plt.colorbar(orientation='horizontal',
pad=pad,
shrink=shrink)
cbT.set_label('2m Relative Humidity (%)')
except:
print "!! Some errors getting the RH value."
print "!! If you requested an old date, from HRRR version 1, there isn't a RH variable,"
print "!! and this code doesn't get the dwpt and convert it to RH yet."
if '700Temp_Fill' in plotcode or '700Temp_-12c' in plotcode:
# Get Data
H_temp = get_hrrr_variable(
DATE,
'TMP:700 mb',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
TMP = H_temp['value'] - 273.15
# Add fill to plot
if '700Temp_Fill' in plotcode:
m.pcolormesh(gridlon,
gridlat,
TMP,
cmap=cm_temp(),
vmax=50,
vmin=-50,
alpha=alpha,
zorder=3,
latlon=True)
cbT = plt.colorbar(orientation='horizontal',
shrink=shrink,
pad=pad)
cbT.set_label('700 mb Temperature (C)')
# Add -12 C contour to plot
if '700Temp_-12c' in plotcode:
m.contour(gridlon,
gridlat,
TMP,
colors='b',
levels=[-12],
latlon=True,
zorder=400)
if '500HGT_Contour' in plotcode:
H_500 = get_hrrr_variable(
DATE,
'HGT:500 mb',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
CS = m.contour(gridlon,
gridlat,
H_500['value'],
levels=range(5040, 6181, 60),
linewidths=1.7,
colors='k',
latlon=True,
zorder=400)
plt.clabel(CS, inline=1, fmt='%2.f')
if '500Wind_Fill' in plotcode or '500Wind_Barb' in plotcode or '500Vort_Fill' in plotcode or '500Conv_Fill' in plotcode:
H_u = get_hrrr_variable(
DATE,
'UGRD:500 mb',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
H_v = get_hrrr_variable(
DATE,
'VGRD:500 mb',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
if '500Wind_Fill' in plotcode:
spd = wind_uv_to_spd(H_u['value'], H_v['value'])
m.pcolormesh(gridlon,
gridlat,
spd,
latlon=True,
cmap=cm_wind(),
vmin=0,
vmax=60)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'500 mb Wind Speed (m s$\mathregular{^{-1}}$)')
if '500Conv_Fill' in plotcode or '500Vort_Fill' in plotcode:
dudx, dudy = np.gradient(H_u['value'], 3, 3)
dvdx, dvdy = np.gradient(H_v['value'], 3, 3)
if '500Vort_Fill' in plotcode:
vorticity = dvdx - dudy
# Mask values
vort = vorticity
vort = np.ma.array(vort)
vort[np.logical_and(vort < .05, vort > -.05)] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
vort,
latlon=True,
cmap='bwr',
vmax=np.max(vort),
vmin=-np.max(vort))
cb = plt.colorbar(orientation='horizontal',
pad=pad,
shrink=shrink)
cb.set_label(r'500 mb Vorticity (s$\mathregular{^{-1}}$)')
if '500Conv_Fill' in plotcode:
convergence = dudx + dvdy
# Mask values
conv = convergence
conv = np.ma.array(conv)
conv[np.logical_and(conv < .05, conv > -.05)] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
conv,
latlon=True,
cmap='bwr',
vmax=np.max(conv),
vmin=-np.max(conv))
cb = plt.colorbar(orientation='horizontal',
pad=pad,
shrink=shrink)
cb.set_label(r'500 mb Convergence (s$\mathregular{^{-1}}$)')
if '500Wind_Barb' in plotcode:
# For small domain plots, trimming the edges significantly reduces barb plotting time
if barb_thin < 20:
cut_v, cut_h = pluck_point_new(lat, lon, gridlat, gridlon)
Cgridlat = gridlat[cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
Cgridlon = gridlon[cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
H_u['value'] = H_u['value'][cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
H_v['value'] = H_v['value'][cut_v - bfr:cut_v + bfr,
cut_h - bfr:cut_h + bfr]
else:
Cgridlat = gridlat
Cgridlon = gridlon
thin = barb_thin
m.barbs(Cgridlon[::thin, ::thin],
Cgridlat[::thin, ::thin],
H_u['value'][::thin, ::thin],
H_v['value'][::thin, ::thin],
zorder=200,
length=6,
color='navy',
barb_increments={
'half': 2.5,
'full': 5,
'flag': 25
},
latlon=True)
#plt.ylabel(r'Barbs: half=2.5, full=5, flag=25 (ms$\mathregular{^{-1}}$)')
if 'MSLP_Contour' in plotcode or 'MSLP_Fill' in plotcode:
H = get_hrrr_variable(
DATE,
'MSLMA:mean sea level',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
if 'MSLP_Contour' in plotcode:
CS = m.contour(gridlon,
gridlat,
H['value'] / 100.,
latlon=True,
levels=range(952, 1200, 4),
colors='k',
zorder=400)
CS.clabel(inline=1, fmt='%2.f', zorder=400)
if 'MSLP_Fill' in plotcode:
m.pcolormesh(gridlon,
gridlat,
H['value'] / 100.,
latlon=True,
cmap='viridis')
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label('Mean Sea Level Pressure (hPa)')
if '2mPOT_Fill' in plotcode:
# Get Data
H_temp = get_hrrr_variable(
DATE,
'POT:2 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
TMP = H_temp['value'] - 273.15
m.pcolormesh(gridlon,
gridlat,
TMP,
cmap="Oranges",
alpha=alpha,
zorder=3,
latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label('2 m Potential Temperature (C)')
if 'SkinTemp_Fill' in plotcode:
# Get Data
H_temp = get_hrrr_variable(
DATE,
'TMP:surface',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
TMP = H_temp['value'] - 273.15
m.pcolormesh(gridlon,
gridlat,
TMP,
cmap="Spectral_r",
alpha=alpha,
zorder=3,
latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label('Skin Temperature (C)')
if 'AccumPrecip_Fill' in plotcode or '1hrPrecip_Fill' in plotcode:
if 'AccumPrecip_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(
DATE,
'APCP:surface:0',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Mask values
prec = H['value']
prec = np.ma.array(prec)
prec[prec == 0] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
prec,
cmap=cm_precip(),
alpha=alpha,
vmin=0,
vmax=762,
zorder=3,
latlon=True)
cbS = plt.colorbar(orientation='horizontal',
shrink=shrink,
pad=pad)
cbS.set_label('Accumulated Precipitation since F00 (mm)')
if '1hrPrecip_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(
DATE,
'APCP:surface',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Mask values
prec = H['value']
prec = np.ma.array(prec)
prec[prec == 0] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
prec,
cmap=cm_precip(),
alpha=alpha,
vmin=0,
vmax=762,
zorder=3,
latlon=True)
cbS = plt.colorbar(
orientation='horizontal',
shrink=shrink,
pad=pad,
extend="max",
)
cbS.set_label('1 hour Accumulated Precipitation (mm)')
if 'SnowCover_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(
DATE,
'SNOWC',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Mask values
snow = H['value']
snow = np.ma.array(snow)
snow[snow == 0] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
snow,
cmap="Blues",
alpha=alpha,
zorder=3,
latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label('Snow Cover (%)')
if 'PWAT_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(
DATE,
'PWAT:entire',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
m.pcolormesh(gridlon,
gridlat,
H['value'],
cmap="RdYlGn",
alpha=alpha,
vmin=0,
zorder=3,
latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label(
r'Vertically Integrated Liquid Water (kg m$\mathregular{^{-2}}$)')
if 'CAPE_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(
DATE,
'CAPE:surface',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Mask values
cape = H['value']
cape = np.ma.array(cape)
cape[cape == 0] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
cape,
cmap="Oranges",
alpha=alpha,
zorder=3,
latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label(r'Surface CAPE (J kg$\mathregular{^{-1}}$)')
if 'CIN_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(
DATE,
'CIN:surface',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Mask values
cin = H['value']
cin = np.ma.array(cin)
cin[cin == 0] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
cin,
cmap="BuPu",
alpha=alpha,
zorder=3,
latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label(r'Surface CIN (J kg$\mathregular{^{-1}}$)')
if 'RedFlag_Fill' in plotcode or 'RedFlag_Contour' in plotcode or 'RedFlagPot_Fill' in plotcode:
# generalized criteria for red flag warning
# Winds (gusts) greater than 6.7 m/s and RH < 25%
rf_RH = 25
rf_WIND = 6.7
# Get Data
H_gust = get_hrrr_variable(
DATE,
'GUST:surface',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
H_rh = get_hrrr_variable(
DATE,
'RH:2 m',
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
RedFlag = np.logical_and(H_gust['value'] > rf_WIND,
H_rh['value'] < rf_RH)
if 'RedFlag_Contour' in plotcode:
try:
CS = m.contour(gridlon,
gridlat,
RedFlag,
latlon=True,
colors='maroon',
zorder=400)
except:
# maybe there isn't any contours in this domain
pass
if 'RedFlag_Fill' in plotcode:
RedFlag = np.ma.array(RedFlag)
RedFlag[RedFlag == 0] = np.ma.masked
m.pcolormesh(gridlon,
gridlat,
RedFlag,
cmap="YlOrRd_r",
alpha=alpha,
zorder=4,
latlon=True)
if 'RedFlagPot_Fill' in plotcode:
cdict3 = {
'red': ((0.0, 1.0, 1.0), (0.5, 0.5, 0.5), (0.5, 1.0, 1.0),
(1.0, 0.4, 0.4)),
'green': ((0.0, 1.0, 1.0), (0.5, 0.5, 0.5), (0.5, 0.4, 0.4),
(1.0, 0.0, 0.0)),
'blue': ((0.0, 1.0, 1.0), (0.5, 0.5, 0.5), (0.5, 0.0, 0.0),
(1.0, 0.0, 0.0))
}
plt.register_cmap(name='FirePot', data=cdict3)
# Definate Red Flag Area:
RED_FLAG = np.logical_and(H_rh['value'] < rf_RH,
H_gust['value'] > rf_WIND)
# Linear Equation
b = (rf_RH - rf_WIND) * (rf_RH / rf_WIND)
z = -(rf_RH / rf_WIND) * (H_rh['value'] - H_gust['value']) + b
m.pcolormesh(gridlon,
gridlat,
z,
cmap="FirePot",
alpha=alpha,
vmax=200,
vmin=-200,
zorder=3,
latlon=True)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'Red Flag Potential')
m.contour(gridlon,
gridlat,
z,
colors='k',
levels=[0],
zorder=3,
latlon=True)
m.contour(gridlon,
gridlat,
RED_FLAG,
colors='darkred',
levels=[0],
zorder=3,
latlon=True)
plt.xlabel(
r'Red Flag Criteria: Winds > 6.7 m s$\mathregular{^{-1}}$ and RH < 25%'
)
# =============================================================================
# Hack! Plot an extra HRRR variable not listed on the webpage hrrr_custom.html
# This extra argument will let you attempt to plot a different variable for
# a quicklook.
try:
# Must be a variable from a line in the .idx file
hrrrVAR = form['extraVAR'].value
extraHRRR = get_hrrr_variable(
DATE,
hrrrVAR,
model=model,
fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
m.pcolormesh(gridlon,
gridlat,
extraHRRR['value'],
cmap='viridis',
alpha=alpha,
zorder=3,
latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label(hrrrVAR + ' (units)')
except:
pass
# =============================================================================
#plt.ylabel('Section Timer:%s\nFull Timer:%s' % (t2-t1, datetime.now()-firsttimer))
SAVEDIR = '/uufs/chpc.utah.edu/common/home/u0553130/public_html/oper/HRRR_yesterday/%s/%s/' % (
MAP_DIR, DOMAIN)
if not os.path.exists(SAVEDIR):
os.makedirs(SAVEDIR)
SAVEFIG = SAVEDIR + '%s_f%02d' % (VALIDDATE.strftime('h%H'), fxx)
plt.savefig(SAVEFIG) # Plot standard output.
print 'SAVED:', SAVEFIG
verbose=True)
x, y = m(a['LON'], a['LAT'])
points = plt.scatter(x, y,
c=a['solar_radiation'],
cmap='magma',
vmin=0, vmax=1070,
linewidths=0)
if attime == sDATE:
cb = plt.colorbar(orientation='horizontal', pad=.01, shrink=.8)
cb.set_label(r'Solar Radiation (W m$\mathregular{^{-2}}$)')
plt.title('MesoWest Stations: %s' % attime.strftime('%Y-%m-%d %H%M UTC'))
plt.savefig('solar_nation/%s.png' % attime.strftime('%Y-%m-%d_%H%M'), bbox_inches='tight')
points.remove()
plt.clf(); plt.cla()
m.drawcoastlines()
m.drawstates()
m.drawcountries()
for attime in DATES:
print attime
H = get_hrrr_variable(attime, variable="DSWRF:surface")
x, y = m(H['lon'], H['lat'])
mesh = plt.pcolormesh(x, y, H['value'], vmin=0, vmax=1070, cmap='magma')
if attime == sDATE:
cb = plt.colorbar(orientation='horizontal', pad=.01, shrink=.8)
cb.set_label(r'Solar Radiation (W m$\mathregular{^{-2}}$)')
plt.title('HRRR anlys: %s' % attime.strftime('%Y-%m-%d %H%M UTC'))
plt.savefig('solar_nation/HRRR_%s.png' % attime.strftime('%Y-%m-%d_%H%M'), bbox_inches='tight')
mesh.remove()
def make_plots(inputs):
VALID_DATE, fxx = inputs
print 'working on %s f%02d' % (VALID_DATE, fxx)
plt.clf(); plt.cla()
print fxx, VALID_DATE
# === Some housekeeping variables =============================================
# Convert Valid Date to Run Date, adjusted by the forecast
DATE = VALID_DATE - timedelta(hours=fxx)
# Parse Location lat/lon
if ',' in location:
# User put inputted a lat/lon point request
lat, lon = location.split(',')
lat = float(lat)
lon = float(lon)
else:
# User requested a MesoWest station
stninfo = get_station_info([location])
lat = stninfo['LAT']
lon = stninfo['LON']
# Preload the latitude and longitude grid
latlonpath = '/uufs/chpc.utah.edu/common/home/horel-group/archive/HRRR/oper_HRRR_latlon.h5'
latlonh5 = h5py.File(latlonpath, 'r')
gridlat = latlonh5['latitude'][:]
gridlon = latlonh5['longitude'][:]
# === Create map of the domain ================================================
if dsize == 'conus' and model != 'hrrrAK':
barb_thin = 70
alpha = 1
t1= datetime.now()
#m = draw_CONUS_HRRR_map(res=map_res)
m = np.load('/uufs/chpc.utah.edu/common/home/u0553130/public_html/Brian_Blaylock/cgi-bin/HRRR_CONUS_map_object_'+map_res+'.npy').item()
m.drawcountries(zorder=500)
m.drawstates(zorder=500)
m.drawcoastlines(zorder=500)
m.fillcontinents(color='tan',lake_color='lightblue', zorder=0)
m.drawmapboundary(fill_color='lightblue')
t2 = datetime.now()
else:
# configure some setting based on the requested domain size
if dsize == 'small':
plus_minus_latlon = .27 # +/- latlon box around center point
barb_thin = 1 # Thin out excessive wind barbs
arcgis_res = 1000 # ArcGIS image resolution
bfr = 15 # trim domain buffer
alpha = .75 # Alpha (pcolormesh transparency)
elif dsize == 'medium':
plus_minus_latlon = .75
barb_thin = 2
arcgis_res = 800
bfr = 35
alpha = .75
elif dsize == 'large':
plus_minus_latlon = 2.5
barb_thin = 6
arcgis_res = 800
bfr = 110
alpha = .75
elif dsize == 'xlarge':
plus_minus_latlon = 5
barb_thin = 12
arcgis_res = 700
bfr = 210
alpha = .75
elif dsize == 'xxlarge': # If domain runs into HRRR boundary, then it'll fail
plus_minus_latlon = 10
barb_thin = 25
arcgis_res = 700
bfr = 430
alpha = .75
elif dsize == 'xxxlarge':
plus_minus_latlon = 15
barb_thin = 35
arcgis_res = 1000
bfr = 700
alpha = .75
m = Basemap(resolution=map_res, projection='cyl',\
area_thresh=3000,\
llcrnrlon=lon-plus_minus_latlon, llcrnrlat=lat-plus_minus_latlon,\
urcrnrlon=lon+plus_minus_latlon, urcrnrlat=lat+plus_minus_latlon,)
m.drawstates(zorder=500)
m.drawcountries(zorder=500)
m.drawcoastlines(zorder=500)
#if dsize == 'small' or dsize == 'medium':
# m.drawcounties()
# === Add a Background image ==================================================
# Start the map image
plt.figure(1)
if background == 'arcgis' and dsize != 'conus':
m.arcgisimage(service='World_Shaded_Relief', xpixels=arcgis_res, verbose=False)
elif background == 'arcgisSat' and dsize != 'conus':
m.arcgisimage(service='ESRI_Imagery_World_2D', xpixels=arcgis_res, verbose=False)
elif background == 'arcgisRoad' and dsize != 'conus':
m.arcgisimage(service='NatGeo_World_Map', xpixels=arcgis_res, verbose=False)
elif background == 'terrain':
# Get data
H_ter = get_hrrr_variable(DATE, 'HGT:surface',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
H_land = get_hrrr_variable(DATE, 'LAND:surface',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
# Plot the terrain
m.contourf(gridlon, gridlat, H_ter['value'],
levels=range(0, 4000, 200),
cmap='Greys_r',
zorder=1,
latlon=True)
# Plot Water area
m.contour(gridlon, gridlat, H_land['value'],
levels=[0, 1],
colors='b',
zorder=1,
latlon=True)
elif background == 'landuse':
# Get data
from BB_cmap.landuse_colormap import LU_MODIS21
if model=='hrrr':
VGTYP = 'VGTYP:surface'
else:
VGTYP = 'var discipline=2 center=59 local_table=1 parmcat=0 parm=198'
H_LU = get_hrrr_variable(DATE, VGTYP,
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False,
value_only=True)
# Plot the terrain
cm, labels = LU_MODIS21()
m.pcolormesh(gridlon, gridlat, H_LU['value'],
cmap=cm, vmin=1, vmax=len(labels) + 1,
zorder=1,
latlon=True)
# Add SHAPEFILE
if is_FIRE:
plt.gca().add_collection(PatchCollection(patches,
facecolor='indianred',
alpha=.65,
edgecolor='k',
linewidths=1,
zorder=1))
# === Figure Title ============================================================
if dsize != 'conus':
m.scatter(lon, lat, marker='+', c='r', s=100, zorder=1000, latlon=True)
plt.title('Center: %s\n%s' % (location, model.upper()), fontweight='bold')
else:
plt.title('%s' % (model.upper()), fontweight='bold')
plt.title('Run: %s F%02d' % (DATE.strftime('%Y-%m-%d %H:%M UTC'), fxx), loc='left')
plt.title('Valid: %s' % (DATE+timedelta(hours=fxx)).strftime('%Y-%m-%d %H:%M UTC') , loc='right')
# =============================================================================
if '10mWind_Fill' in plotcode or '10mWind_Shade' in plotcode or '10mWind_Barb' in plotcode:
# Get data
H_u = get_hrrr_variable(DATE, 'UGRD:10 m',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
H_v = get_hrrr_variable(DATE, 'VGRD:10 m',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
spd = wind_uv_to_spd(H_u['value'], H_v['value'])
if '10mWind_Fill' in plotcode:
m.pcolormesh(gridlon, gridlat, spd,
latlon=True,
cmap='magma_r',
vmin=0, alpha=alpha)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'10 m Wind Speed (m s$\mathregular{^{-1}}$)')
if '10mWind_Shade' in plotcode:
m.contourf(gridlon, gridlat, spd,
levels=[10, 15, 20, 25],
colors=('yellow', 'orange', 'red'),
alpha=alpha,
extend='max',
zorder=1,
latlon=True)
cb = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cb.set_label(r'10 m Wind Speed (ms$\mathregular{^{-1}}$)')
if '10mWind_Barb' in plotcode:
# For small domain plots, trimming the edges significantly reduces barb plotting time
if barb_thin < 20:
cut_v, cut_h = pluck_point_new(lat, lon, gridlat, gridlon)
Cgridlat = gridlat[cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
Cgridlon = gridlon[cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
H_u['value'] = H_u['value'][cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
H_v['value'] = H_v['value'][cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
else:
Cgridlat = gridlat
Cgridlon = gridlon
# Add to plot
thin = barb_thin
m.barbs(Cgridlon[::thin,::thin], Cgridlat[::thin,::thin],
H_u['value'][::thin,::thin], H_v['value'][::thin,::thin],
zorder=200, length=5.5,
barb_increments={'half':2.5, 'full':5,'flag':25},
latlon=True)
if '80mWind_Fill' in plotcode or '80mWind_Shade' in plotcode or '80mWind_Barb' in plotcode:
# Get data
H_u = get_hrrr_variable(DATE, 'UGRD:80 m',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
H_v = get_hrrr_variable(DATE, 'VGRD:80 m',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
spd = wind_uv_to_spd(H_u['value'], H_v['value'])
if '80mWind_Fill' in plotcode:
m.pcolormesh(gridlon, gridlat, spd,
latlon=True,
cmap='magma_r',
vmin=0, alpha=alpha)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'10 m Wind Speed (m s$\mathregular{^{-1}}$)')
if '80mWind_Shade' in plotcode:
m.contourf(gridlon, gridlat, spd,
levels=[10, 15, 20, 25],
colors=('yellow', 'orange', 'red'),
alpha=alpha,
extend='max',
zorder=10,
latlon=True)
cb = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cb.set_label(r'10 m Wind Speed (ms$\mathregular{^{-1}}$)')
if '80mWind_Barb' in plotcode:
# For small domain plots, trimming the edges significantly reduces barb plotting time
if barb_thin < 20:
cut_v, cut_h = pluck_point_new(lat, lon, gridlat, gridlon)
Cgridlat = gridlat[cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
Cgridlon = gridlon[cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
H_u['value'] = H_u['value'][cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
H_v['value'] = H_v['value'][cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
else:
Cgridlat = gridlat
Cgridlon = gridlon
# Add to plot
thin = barb_thin
m.barbs(Cgridlon[::thin,::thin], Cgridlat[::thin,::thin],
H_u['value'][::thin,::thin], H_v['value'][::thin,::thin],
zorder=200, length=5.5, color='darkred',
barb_increments={'half':2.5, 'full':5,'flag':25},
latlon=True)
if 'Fill80mWind' in plotcode:
m.pcolormesh(gridlon, gridlat, spd,
latlon=True,
cmap='plasma_r',
vmin=0,
alpha=alpha)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'80 m Wind Speed (m s$\mathregular{^{-1}}$)')
if 'Gust_Hatch' in plotcode:
H_gust = get_hrrr_variable(DATE, 'GUST:surface',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
# Add to plot
m.contourf(gridlon, gridlat, H_gust['value'],
levels=[0, 10, 15, 20, 25],
hatches=[None, '.', '\\\\', '*'],
colors='none',
extend='max',
zorder=10,
latlon=True)
cb = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cb.set_label(r'Surface Wind Gust (ms$\mathregular{^{-1}}$)')
m.contour(gridlon, gridlat, H_gust['value'],
levels=[10, 15, 20, 25],
colors='k',
zorder=10,
latlon=True)
if 'dBZ_Fill' in plotcode or 'dBZ_Contour' in plotcode:
from BB_cmap.reflectivity_colormap import reflect_ncdc
# Get Data
if model == 'hrrr':
REFC = 'REFC:entire'
elif model == 'hrrrX' or model == 'hrrrAK':
REFC = 'var discipline=0 center=59 local_table=1 parmcat=16 parm=196'
H_ref = get_hrrr_variable(DATE, REFC,
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
# Mask values
dBZ = H_ref['value']
dBZ = np.ma.array(dBZ)
dBZ[dBZ == -10] = np.ma.masked
# Add Contour to plot
if 'dBZ_Contour' in plotcode:
cREF = m.contour(gridlon, gridlat, dBZ,
cmap=reflect_ncdc(),
levels=range(10, 80, 10),
latlon=True,
zorder=50)
plt.clabel(cREF, cREF.levels[::2], fmt='%2.0f', colors='k', fontsize=9)
#cb2 = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
#cb2.set_label('Simulated Composite Reflectivity (dBZ)')
# Add fill to plot
if 'dBZ_Fill' in plotcode:
m.pcolormesh(gridlon, gridlat, dBZ,
cmap=reflect_ncdc(),
vmax=80, vmin=0,
alpha=alpha,
latlon=True)
cb2 = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cb2.set_label('Simulated Composite Reflectivity (dBZ)')
if '2mTemp_Fill' in plotcode or '2mTemp_Freeze' in plotcode:
# Get Data
H_temp = get_hrrr_variable(DATE, 'TMP:2 m',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
TMP = H_temp['value']-273.15
# Add fill to plot
if '2mTemp_Fill' in plotcode:
m.pcolormesh(gridlon, gridlat, TMP,
cmap="Spectral_r",
alpha=alpha,
zorder=3, latlon=True)
cbT = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbT.set_label('2m Temperature (C)')
# Add freezing contour to plot
if '2mTemp_Freeze' in plotcode:
m.contour(gridlon, gridlat, TMP,
colors='b',
levels=[0],
zorder=400,
latlon=True)
if '2mRH_Fill' in plotcode:
# Get Data
try:
H_RH = get_hrrr_variable(DATE, 'RH:2 m',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
# Add fill to plot
m.pcolormesh(gridlon, gridlat, H_RH['value'], cmap="BrBG",
vmin=0, vmax=100,
zorder=3,
latlon=True)
cbT = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cbT.set_label('2m Relative Humidity (%)')
except:
print "!! Some errors getting the RH value."
print "!! If you requested an old date, from HRRR version 1, there isn't a RH variable,"
print "!! and this code doesn't get the dwpt and convert it to RH yet."
if '700Temp_Fill' in plotcode or '700Temp_-12c' in plotcode:
# Get Data
H_temp = get_hrrr_variable(DATE, 'TMP:700 mb',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
TMP = H_temp['value']-273.15
# Add fill to plot
if '700Temp_Fill' in plotcode:
m.pcolormesh(gridlon, gridlat, TMP,
cmap="Spectral_r",
alpha=alpha,
zorder=3, latlon=True)
cbT = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbT.set_label('700 mb Temperature (C)')
# Add -12 C contour to plot
if '700Temp_-12c' in plotcode:
m.contour(gridlon, gridlat, TMP,
colors='b',
levels=[-12],
latlon=True,
zorder=400)
if '500HGT_Contour' in plotcode:
H_500 = get_hrrr_variable(DATE, 'HGT:500 mb',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
CS = m.contour(gridlon, gridlat, H_500['value'],
levels=range(5040, 6181, 60),
linewidths=1.7,
colors='k',
latlon=True,
zorder=400)
plt.clabel(CS, inline=1, fmt='%2.f')
if '500Wind_Fill' in plotcode or '500Wind_Barb' in plotcode or '500Vort_Fill' in plotcode or '500Conv_Fill' in plotcode:
H_u = get_hrrr_variable(DATE, 'UGRD:500 mb',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
H_v = get_hrrr_variable(DATE, 'VGRD:500 mb',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
if '500Wind_Fill' in plotcode:
spd = wind_uv_to_spd(H_u['value'], H_v['value'])
m.pcolormesh(gridlon, gridlat, spd,
latlon=True, cmap='BuPu', vmin=0)
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'500 mb Wind Speed (m s$\mathregular{^{-1}}$)')
if '500Conv_Fill' in plotcode or '500Vort_Fill' in plotcode:
dudx, dudy = np.gradient(H_u['value'], 3, 3)
dvdx, dvdy = np.gradient(H_v['value'], 3, 3)
if '500Vort_Fill' in plotcode:
vorticity = dvdx - dudy
# Mask values
vort = vorticity
vort = np.ma.array(vort)
vort[np.logical_and(vort < .05, vort > -.05) ] = np.ma.masked
m.pcolormesh(gridlon, gridlat, vort,
latlon=True, cmap='bwr',
vmax=np.max(vort),
vmin=-np.max(vort))
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'500 mb Vorticity (s$\mathregular{^{-1}}$)')
if '500Conv_Fill' in plotcode:
convergence = dudx + dvdy
# Mask values
conv = convergence
conv = np.ma.array(conv)
conv[np.logical_and(conv < .05, conv > -.05) ] = np.ma.masked
m.pcolormesh(gridlon, gridlat, conv,
latlon=True, cmap='bwr',
vmax=np.max(conv),
vmin=-np.max(conv))
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label(r'500 mb Convergence (s$\mathregular{^{-1}}$)')
if '500Wind_Barb' in plotcode:
# For small domain plots, trimming the edges significantly reduces barb plotting time
if barb_thin < 20:
cut_v, cut_h = pluck_point_new(lat, lon, gridlat, gridlon)
Cgridlat = gridlat[cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
Cgridlon = gridlon[cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
H_u['value'] = H_u['value'][cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
H_v['value'] = H_v['value'][cut_v-bfr:cut_v+bfr, cut_h-bfr:cut_h+bfr]
else:
Cgridlat = gridlat
Cgridlon = gridlon
thin = barb_thin
m.barbs(Cgridlon[::thin, ::thin], Cgridlat[::thin, ::thin], H_u['value'][::thin, ::thin], H_v['value'][::thin, ::thin],
zorder=200, length=6, color='navy',
barb_increments={'half':2.5, 'full':5,'flag':25},
latlon=True)
#plt.ylabel(r'Barbs: half=2.5, full=5, flag=25 (ms$\mathregular{^{-1}}$)')
if 'MSLP_Contour' in plotcode or 'MSLP_Fill' in plotcode:
H = get_hrrr_variable(DATE, 'MSLMA:mean sea level',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
if 'MSLP_Contour' in plotcode:
CS = m.contour(gridlon, gridlat, H['value']/100.,
latlon=True,
levels=range(952, 1200, 4),
colors='k',
zorder=400)
CS.clabel(inline=1, fmt='%2.f',
zorder=400)
if 'MSLP_Fill' in plotcode:
m.pcolormesh(gridlon, gridlat, H['value']/100.,
latlon=True,
cmap='viridis')
cb = plt.colorbar(orientation='horizontal', pad=pad, shrink=shrink)
cb.set_label('Mean Sea Level Pressure (hPa)')
if '2mPOT_Fill' in plotcode:
# Get Data
H_temp = get_hrrr_variable(DATE, 'POT:2 m',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
TMP = H_temp['value']-273.15
m.pcolormesh(gridlon, gridlat, TMP,
cmap="Oranges",
alpha=alpha,
zorder=3, latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label('2 m Potential Temperature (C)')
if 'SkinTemp_Fill' in plotcode:
# Get Data
H_temp = get_hrrr_variable(DATE, 'TMP:surface',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
TMP = H_temp['value']-273.15
m.pcolormesh(gridlon, gridlat, TMP,
cmap="Spectral_r",
alpha=alpha,
zorder=3, latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label('Skin Temperature (C)')
if 'AccumPrecip_Fill' in plotcode or '1hrPrecip_Fill' in plotcode:
#import matplotlib.colors
#cmap = matplotlib.colors.LinearSegmentedColormap.from_list("Precip", ["#00db16", "blue", "#d10000", 'black'])
cdict3 = {'red': ((0.0, 0.0, 0.0),
(0.25, 1.0, 1.0),
(0.5, 0.0, 0.0),
(1.0, 1.0, 1.0)),
'green': ((0.0, 0.7, 0.7),
(0.25, 1.0, 1.0),
(0.5, 0.0, 0.0),
(1.0, 0.0, 0.0)),
'blue': ((0.0, 0.18, 0.18),
(0.25, 1.0, 1.0),
(0.5, 1.0, 1.0),
(1.0, 0.0, 0.0))
}
plt.register_cmap(name='BlueRed3', data=cdict3)
cmap = 'BlueRed3'
if 'AccumPrecip_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(DATE, 'APCP:surface:0',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
# Mask values
prec = H['value']
prec = np.ma.array(prec)
prec[prec == 0] = np.ma.masked
m.pcolormesh(gridlon, gridlat, prec,
cmap='BlueRed3',
alpha=alpha,
vmin=.25,
zorder=3, latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label('Accumulated Precipitation since F00 (mm)')
if '1hrPrecip_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(DATE, 'APCP:surface',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
# Mask values
prec = H['value']
prec = np.ma.array(prec)
prec[prec == 0] = np.ma.masked
m.pcolormesh(gridlon, gridlat, prec,
cmap='BlueRed3',
alpha=alpha,
vmin=.25, vmax=20,
zorder=3, latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad, extend="max",)
cbS.set_label('1 hour Accumulated Precipitation (mm)')
if 'SnowCover_Fill' in plotcode:
# Get Data
H = get_hrrr_variable(DATE, 'SNOWC',
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
# Mask values
snow = H['value']
snow = np.ma.array(snow)
snow[snow == 0] = np.ma.masked
m.pcolormesh(gridlon, gridlat, snow,
cmap="Blues",
alpha=alpha,
zorder=3, latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label('Snow Cover (%)')
# =============================================================================
# Hack! Plot an extra HRRR variable not listed on the webpage hrrr_custom.html
# This extra argument will let you attempt to plot a different variable for
# a quicklook.
try:
# Must be a variable from a line in the .idx file
hrrrVAR = form['extraVAR'].value
extraHRRR = get_hrrr_variable(DATE, hrrrVAR,
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
m.pcolormesh(gridlon, gridlat, extraHRRR['value'],
cmap='viridis',
alpha=alpha,
zorder=3, latlon=True)
cbS = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cbS.set_label(hrrrVAR+' (units)')
except:
pass
# =============================================================================
#plt.ylabel('Section Timer:%s\nFull Timer:%s' % (t2-t1, datetime.now()-firsttimer))
SAVEDIR = '/uufs/chpc.utah.edu/common/home/u0553130/public_html/PhD/HRRR/Events_Day/%s/' % EVENT
if not os.path.exists(SAVEDIR):
os.makedirs(SAVEDIR)
SAVEFIG = SAVEDIR + '%s_f%02d' % (VALID_DATE.strftime('%Y-%m-%d_h%H'), fxx)
plt.savefig(SAVEFIG) # Plot standard output.
print 'SAVED:', SAVEFIG
# Convert Valid Date to Run Date, adjusted by the forecast
DATE = DATE - timedelta(hours=fxx)
plt.title('%s' % (model.upper()), fontweight='bold')
plt.title('Run: %s F%02d' % (DATE.strftime('%Y-%m-%d %H:%M UTC'), fxx), loc='left')
plt.title('Valid: %s' % (DATE+timedelta(hours=fxx)).strftime('%Y-%m-%d %H:%M UTC') , loc='right')
# =============================================================================
from BB_cmap.reflectivity_colormap import reflect_ncdc
# Get Data
if model == 'hrrr':
REFC = 'REFC:entire'
elif model == 'hrrrX' or model == 'hrrrAK':
REFC = 'var discipline=0 center=59 local_table=1 parmcat=16 parm=196'
H_ref = get_hrrr_variable(DATE, REFC,
model=model, fxx=fxx,
outDIR='/uufs/chpc.utah.edu/common/home/u0553130/temp/',
verbose=False, value_only=True)
# Mask values
dBZ = H_ref['value']
dBZ = np.ma.array(dBZ)
dBZ[dBZ == -10] = np.ma.masked
# Add Contour to plot
PM = m.pcolormesh(gridlon, gridlat, dBZ,
cmap=reflect_ncdc(),
vmax=80, vmin=0,
latlon=True)
if DATE == DATES[0]:
cb2 = plt.colorbar(orientation='horizontal', shrink=shrink, pad=pad)
cb2.set_label('Simulated Composite Reflectivity (dBZ)')
print "\n--------------------------------------------------------"
print " Working on the HRRR 3D surface (%s)" % sys.argv[0]
print "--------------------------------------------------------\n"
#==============================================================================
# Directory to save figures (subdirectory will be created for each stnID)
SAVE_dir = '/uufs/chpc.utah.edu/common/home/u0553130/public_html/PhD/HRRR/'
#==============================================================================
# Get Terrain Data from HRRR
DATE = datetime(2017, 6, 25)
variable = 'HGT:surface'
topo = get_hrrr_variable(DATE, variable)
topo = hrrr_subset(topo, half_box=40)
# Make 3D projection plot
fig = plt.figure()
ax = fig.gca(projection='3d')
# Plot the surface.
surf = ax.plot_surface(topo['lon'][50:100, 50:100],
topo['lat'][50:100, 50:100],
topo['value'][50:100, 50:100],
cmap='terrain',
linewidth=0,
antialiased=False)
import sys
sys.path.append('/uufs/chpc.utah.edu/common/home/u0553130/pyBKB_v2')
sys.path.append('B:\pyBKB_v2')
from BB_basemap.draw_maps import draw_CONUS_HRRR_map
from BB_downloads.HRRR_S3 import get_hrrr_variable
from BB_cmap.terrain_colormap import terrain_cmap_256
DATE = datetime(2017, 1, 1)
# 1) Get Topography and Land-Sea mask from HRRR S3 archive
VAR = 'HGT:surface'
LAND = 'LAND:surface'
H = get_hrrr_variable(DATE, VAR)
L = get_hrrr_variable(DATE, LAND, value_only=True)
# 2) Set water value in Topography
water = -99
topo = H['value']
topo[L['value'] == 0] = water
# 2) Get the map object and draw map
m = draw_CONUS_HRRR_map()
m.drawcoastlines(linewidth=.5, color=(0, 0, 0, .75))
m.drawcountries(linewidth=.5, color=(0, 0, 0, .75))
m.drawstates(linewidth=.3, color=(0, 0, 0, .75))
x, y = m(H['lon'], H['lat'])
vmaxD = 4
ticks = range(vminD, vmaxD + 1)
cmap = 'plasma'
for i in range(num):
if DATES[i].minute != 0:
# HRRR is only available at the top of the hour
print 'skipping', DATES[i]
continue
else:
# Plot the HRRR Data
attime = DATES[i]
print DATES[i]
print '!', attime
if variable == 'UVSpeed:10 m':
uH = get_hrrr_variable(attime, variable='UGRD:10 m')
vH = get_hrrr_variable(attime, variable='VGRD:10 m')
uHX = get_hrrr_variable(attime,
variable='UGRD:10 m',
model='hrrrX',
removeFile=True,
value_only=True)
vHX = get_hrrr_variable(attime,
variable='VGRD:10 m',
model='hrrrX',
removeFile=True,
value_only=True)
H = {
'lat': uH['lat'],
'lon': uH['lon'],
'value': wind_uv_to_spd(uH['value'], vH['value'])
U = p.map(get_HRRR_value, requestDATES) U = np.array([x for x in U if x is not None]) p.close() # variable = 'VGRD:10 m' p = multiprocessing.Pool(cpu_count) V = p.map(get_HRRR_value, requestDATES) V = np.array([x for x in V if x is not None]) p.close() # Convert U and V to Speed and Direction WSPD = wind_uv_to_spd(U, V) WDIR = wind_uv_to_dir(U, V) # get a single H dictionary (need the lat/lon arrays) H = get_hrrr_variable(requestDATES[0], 'UGRD:10 m') # Histogram bins num_dir_sectors = 8 # Number of directional sectors (sectors calculated in histogram function) speed_bins = np.arange(0, 10, 2) # Speed bins num_spd_bins = len(speed_bins) # Number of speed bins rose_dim = num_spd_bins * num_dir_sectors x_dim, y_dim = H['value'].shape # make rose table for each point in HRRR indexes = [[i, j] for i in range(x_dim) for j in range(y_dim)] p = multiprocessing.Pool(cpu_count) result = np.array(p.map(get_hist_table, indexes)) p.close()
within = 15
is_colorbar_on = False
SAVEDIR = '/uufs/chpc.utah.edu/common/home/u0553130/public_html/PhD/Eclipse20170821/'
for i in range(num):
if DATES[i].minute != 0:
# HRRR is only available at the top of the hour
print 'skipping', DATES[i]
continue
else:
# Plot the HRRR Data
attime = DATES[i]
print DATES[i]
print '!', attime
H = get_hrrr_variable(attime, variable="DSWRF:surface")
HX = get_hrrr_variable(attime,
variable="DSWRF:surface",
model='hrrrX',
removeFile=False,
value_only=True)
Hx, Hy = m(H['lon'], H['lat'])
HRRR_plot = ax2.pcolormesh(Hx,
Hy,
H['value'],
vmin=100,
vmax=1000,
cmap='magma')
HRRRx_plot = ax3.pcolormesh(Hx,
Hy,
HX['value'],
