def plot_sounding_data_csv(filename, output):
"""Plot SkewT from a CSV sounding data file
:param filename: The name of the file to open.
:type filename: str
:param output: The name of the file to output plot
:type output: str
The datafile format is CSV with the following columns:
- pressure (mb)
- height (m)
- temperature (C)
- dew point (C)
- wind direction (degrees)
- wind speed (m/s)
Missing values should be filled with the value -9999.00
"""
p,z,T,Td,wdir,wspd = np.loadtxt(filename, delimiter=',', unpack=True)
# Pressure to Pa
p = p * 100.
# z to km
#z = z / 1000.
# interpolate missing wind
nk = len(z)
u = np.empty(nk, np.float32)
v = np.empty(nk, np.float32)
for k in range(nk):
if wdir[k] == -9999. and wspd[k] == -9999.:
u[k] = v[k] = -9999.
else:
u[k], v[k] = dyn.wind_deg_to_uv(wdir[k], wspd[k])
#print('{0:5.2f} {1:5.2f} = {2:5.2f} {3:5.2f}'.format(wdir[k], wspd[k], u[k], v[k]))
_z = np.empty(2,np.float32)
_u = np.empty(2,np.float32)
_v = np.empty(2,np.float32)
print('INTERPOLATING')
for k in range(nk):
if wdir[k] == -9999. and wspd[k] == -9999.:
kb = ke = k
while kb >= 0 and wdir[kb] == -9999. and wspd[kb] == -9999.:
kb -= 1
while ke <= nk-1 and wdir[ke] == -9999. and wspd[ke] == -9999.:
ke += 1
# everything in bounds
if kb >= 0 and ke <= nk-1:
_z[0] = z[kb]
_z[1] = z[ke]
_u[0] = u[kb]
_u[1] = u[ke]
_v[0] = v[kb]
_v[1] = v[ke]
u[k] = pymeteo.interp.linear(_z, _u, z[k])
v[k] = pymeteo.interp.linear(_z, _v, z[k])
elif kb < 0:
u[k] = u[ke]
v[k] = v[ke]
elif ke > nk-1:
u[k] = u[kb]
v[k] = v[kb]
for k in range(nk):
# kt to m/s
u[k] = u[k] * 0.5144444
v[k] = v[k] * 0.5144444
# print('{0:5.2f} {1:5.2f} = {2:5.2f} {3:5.2f}'.format(wdir[k], wspd[k], u[k], v[k]))
# calc theta
th = np.empty(nk, np.float32)
# calc qv
qv = np.empty(nk, np.float32)
for k in range(nk):
th[k] = met.theta(T[k]+met.T00, p[k])
w = met.es(Td[k]+met.T00) / met.es(T[k]+met.T00)
pp = met.es(T[k]+met.T00) / p[k]
qv[k] = 0.622 * pp * w
#qv[k] = met.es(Td[k]+met.T00) / (met.Rv * (T[k]+met.T00))
#print(z, th, p, qv, u, v)
plot(None, z, th, p, qv, u, v, output, title='Sounding Data')
def plot_sounding_data_csv(filename, output):
"""Plot SkewT from a CSV sounding data file
:param filename: The name of the file to open.
:type filename: str
:param output: The name of the file to output plot
:type output: str
The datafile format is CSV with the following columns:
- pressure (mb)
- height (m)
- temperature (C)
- dew point (C)
- wind direction (degrees)
- wind speed (m/s)
Missing values should be filled with the value -9999.00
"""
p, z, T, Td, wdir, wspd = np.loadtxt(filename, delimiter=',', unpack=True)
# Pressure to Pa
p = p * 100.
# z to km
#z = z / 1000.
# interpolate missing wind
nk = len(z)
u = np.empty(nk, np.float32)
v = np.empty(nk, np.float32)
for k in range(nk):
if wdir[k] == -9999. and wspd[k] == -9999.:
u[k] = v[k] = -9999.
else:
u[k], v[k] = dyn.wind_deg_to_uv(wdir[k], wspd[k])
#print('{0:5.2f} {1:5.2f} = {2:5.2f} {3:5.2f}'.format(wdir[k], wspd[k], u[k], v[k]))
_z = np.empty(2, np.float32)
_u = np.empty(2, np.float32)
_v = np.empty(2, np.float32)
print('INTERPOLATING')
for k in range(nk):
if wdir[k] == -9999. and wspd[k] == -9999.:
kb = ke = k
while kb >= 0 and wdir[kb] == -9999. and wspd[kb] == -9999.:
kb -= 1
while ke <= nk - 1 and wdir[ke] == -9999. and wspd[ke] == -9999.:
ke += 1
# everything in bounds
if kb >= 0 and ke <= nk - 1:
_z[0] = z[kb]
_z[1] = z[ke]
_u[0] = u[kb]
_u[1] = u[ke]
_v[0] = v[kb]
_v[1] = v[ke]
u[k] = pymeteo.interp.linear(_z, _u, z[k])
v[k] = pymeteo.interp.linear(_z, _v, z[k])
elif kb < 0:
u[k] = u[ke]
v[k] = v[ke]
elif ke > nk - 1:
u[k] = u[kb]
v[k] = v[kb]
for k in range(nk):
# kt to m/s
u[k] = u[k] * 0.5144444
v[k] = v[k] * 0.5144444
# print('{0:5.2f} {1:5.2f} = {2:5.2f} {3:5.2f}'.format(wdir[k], wspd[k], u[k], v[k]))
# calc theta
th = np.empty(nk, np.float32)
# calc qv
qv = np.empty(nk, np.float32)
for k in range(nk):
th[k] = met.theta(T[k] + met.T00, p[k])
w = met.es(Td[k] + met.T00) / met.es(T[k] + met.T00)
pp = met.es(T[k] + met.T00) / p[k]
qv[k] = 0.622 * pp * w
#qv[k] = met.es(Td[k]+met.T00) / (met.Rv * (T[k]+met.T00))
#print(z, th, p, qv, u, v)
plot(None, z, th, p, qv, u, v, output, title='Sounding Data')
# Read data
ds = xr.open_dataset(file)
p = ds['pressure'].isel({'sounding': 0}).values * units.hPa
z = ds['altitude'].isel({'sounding': 0}).values * units.meters
T = ds['temperature'].isel({'sounding': 0}).values * units.degC
Td = ds['dewPoint'].isel({'sounding': 0}).values * units.degC
wind_speed = ds['windSpeed'].isel({
'sounding': 0
}).values * (units.meter / units.second)
wind_dir = ds['windDirection'].isel({'sounding': 0}).values * units.degrees
# Calculate input for skewt
u, v = mpcalc.wind_components(wind_speed, wind_dir)
th = met.theta(np.array(T) + met.T00, np.array(p) * 100)
w = met.es(np.array(Td) + met.T00) / met.es(np.array(T) + met.T00)
pp = met.es(np.array(T) + met.T00) / (np.array(p) * 100)
qv = 0.622 * pp * w
# Create skewt
skewt.plot(None,
np.array(z),
th,
np.array(p) * 100,
qv,
np.array(u),
np.array(v),
'sounding.pdf',
title=os.path.basename(file))