In [1]:
import matplotlib.pyplot as plt
import numpy as np

from metpy.cbook import get_test_data
from metpy.calc import get_wind_components, lcl, dry_lapse, parcel_profile
from metpy.plots import SkewT
from metpy.units import units, concatenate

%matplotlib inline

In [2]:
# Parse the data
p, T, Td, direc, spd = np.loadtxt(get_test_data('may3_sounding.txt'),
        usecols=(0, 2, 3, 6, 7), skiprows=4, unpack=True)

In [3]:
# Add units to the data arrays
p = p * units.mbar
T = T * units.degC
Td = Td * units.degC
spd = spd * units.knot
direc = direc * units.deg

In [4]:
# Convert wind speed and direction to components
u, v = get_wind_components(spd, direc)

In [5]:
# Create a new figure. The dimensions here give a good aspect ratio
fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig, rotation=45)

# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
skew.plot(p, T, 'r')
skew.plot(p, Td, 'g')
skew.plot_barbs(p, u, v)
skew.ax.set_ylim(1000, 100)
skew.ax.set_xlim(-40, 60)

# Calculate LCL height and plot as black dot
l = lcl(p[0], T[0], Td[0])
lcl_temp = dry_lapse(concatenate((p[0], l)), T[0])[-1].to('degC')
skew.plot(l, lcl_temp, 'ko', markerfacecolor='black')

# Calculate full parcel profile and add to plot as black line
prof = parcel_profile(p, T[0], Td[0]).to('degC')
skew.plot(p, prof, 'k', linewidth=2)

# Example of coloring area between profiles
skew.ax.fill_betweenx(p, T, prof, where=T>=prof, facecolor='blue', alpha=0.4)
skew.ax.fill_betweenx(p, T, prof, where=T<prof, facecolor='red', alpha=0.4)

# An example of a slanted line at constant T -- in this case the 0
# isotherm
l = skew.ax.axvline(0, color='c', linestyle='--', linewidth=2)

# Add the relevant special lines
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()

# Show the plot
plt.show()