def test_bulk_shear_no_depth():
"""Test bulk shear with observed sounding and no depth given. Issue #568."""
data = get_upper_air_data(datetime(2016, 5, 22, 0), 'DDC')
u, v = bulk_shear(data['pressure'], data['u_wind'],
data['v_wind'], heights=data['height'])
truth = [20.225018939, 22.602359692] * units('knots')
assert_almost_equal(u.to('knots'), truth[0], 8)
assert_almost_equal(v.to('knots'), truth[1], 8)
def test_bulk_shear_no_depth():
"""Test bulk shear with observed sounding and no depth given. Issue #568."""
data = get_upper_air_data(datetime(2016, 5, 22, 0), 'DDC')
u, v = bulk_shear(data['pressure'], data['u_wind'],
data['v_wind'], height=data['height'])
truth = [20.225018939, 22.602359692] * units('knots')
assert_almost_equal(u.to('knots'), truth[0], 8)
assert_almost_equal(v.to('knots'), truth[1], 8)
def test_bulk_shear():
"""Test bulk shear with observed sounding."""
data = get_upper_air_data(datetime(2016, 5, 22, 0), 'DDC')
u, v = bulk_shear(data['pressure'], data['u_wind'],
data['v_wind'], heights=data['height'],
depth=6000 * units('meter'))
truth = [29.899581266946115, -14.389225800205509] * units('knots')
assert_almost_equal(u.to('knots'), truth[0], 8)
assert_almost_equal(v.to('knots'), truth[1], 8)
def test_bulk_shear():
"""Test bulk shear with observed sounding."""
data = get_upper_air_data(datetime(2016, 5, 22, 0), 'DDC')
u, v = bulk_shear(data['pressure'], data['u_wind'],
data['v_wind'], height=data['height'],
depth=6000 * units('meter'))
truth = [29.899581266946115, -14.389225800205509] * units('knots')
assert_almost_equal(u.to('knots'), truth[0], 8)
assert_almost_equal(v.to('knots'), truth[1], 8)
def test_bulk_shear_elevated():
"""Test bulk shear with observed sounding and a base above the surface."""
data = get_upper_air_data(datetime(2016, 5, 22, 0), 'DDC')
u, v = bulk_shear(data['pressure'], data['u_wind'],
data['v_wind'], heights=data['height'],
bottom=data['height'][0] + 3000 * units('meter'),
depth=3000 * units('meter'))
truth = [0.9655943923302139, -3.8405428777944466] * units('m/s')
assert_almost_equal(u, truth[0], 8)
assert_almost_equal(v, truth[1], 8)
def test_bulk_shear_elevated():
"""Test bulk shear with observed sounding and a base above the surface."""
data = get_upper_air_data(datetime(2016, 5, 22, 0), 'DDC')
u, v = bulk_shear(data['pressure'], data['u_wind'],
data['v_wind'], height=data['height'],
bottom=data['height'][0] + 3000 * units('meter'),
depth=3000 * units('meter'))
truth = [0.9655943923302139, -3.8405428777944466] * units('m/s')
assert_almost_equal(u, truth[0], 8)
assert_almost_equal(v, truth[1], 8)
gamma_water = -((T - water_temperature) / z).to('degC/km')
df[f'{int(p.magnitude)}_hPa_Γwater'] = [gamma_water.magnitude]
# Calculate RH
rh = mpcalc.relative_humidity_from_dewpoint(T, Td)
df[f'{int(p.magnitude)}_hPa_RH'] = [rh.magnitude * 100]
# Add u and v components
df[f'{int(p.magnitude)}_hPa_u'] = [u.magnitude]
df[f'{int(p.magnitude)}_hPa_v'] = [v.magnitude]
# Derive bulk shear (except at first level)
if p != p_data[0]:
u_shear, v_shear = mpcalc.bulk_shear(p_data,
u_data,
v_data,
bottom=p_data[0],
depth=p_data[0] - p_data[i])
bulk_shear = mpcalc.wind_speed(u_shear, v_shear)
df[f'{int(p_data[0].magnitude)}-{int(p.magnitude)}_hPa_shear'] = [
bulk_shear.magnitude
]
# Append to main dataset
dataset = dataset.append(df)
# Load in model
ai_model = joblib.load('../models/LES_Band_Position_Model_KNN(n=2)_LO1_LatLon')
# Get predictions from machine learning model
predictions = pd.DataFrame()
def bulk_shear(self, depth=6 * units.kilometer):
return mpcalc.bulk_shear(self.p, self.u, self.v, self.z, depth=depth)
def process_skewt(self):
# Calculation
index_p100 = get_pressure_level_index(self.p_i, 100)
lcl_p, lcl_t = mpcalc.lcl(self.p_i[0], self.t_i[0], self.td_i[0])
lfc_p, lfc_t = mpcalc.lfc(self.p_i, self.t_i, self.td_i)
el_p, el_t = mpcalc.el(self.p_i, self.t_i, self.td_i)
prof = mpcalc.parcel_profile(self.p_i, self.t_i[0], self.td_i[0]).to('degC')
cape, cin = mpcalc.cape_cin(self.p_i, self.t_i, self.td_i, prof)
mucape, mucin = mpcalc.most_unstable_cape_cin(self.p_i, self.t_i, self.td_i)
pwat = mpcalc.precipitable_water(self.td_i, self.p_i)
i8 = get_pressure_level_index(self.p_i, 850)
i7 = get_pressure_level_index(self.p_i, 700)
i5 = get_pressure_level_index(self.p_i, 500)
theta850 = mpcalc.equivalent_potential_temperature(850 * units('hPa'), self.t_i[i8], self.td_i[i5])
theta500 = mpcalc.equivalent_potential_temperature(500 * units('hPa'), self.t_i[i5], self.td_i[i5])
thetadiff = theta850 - theta500
k = self.t_i[i8] - self.t_i[i5] + self.td_i[i8] - (self.t_i[i7] - self.td_i[i7])
a = ((self.t_i[i8] - self.t_i[i5]) - (self.t_i[i8] - self.td_i[i5]) -
(self.t_i[i7] - self.td_i[i7]) - (self.t_i[i5] - self.td_i[i5]))
sw = c_sweat(np.array(self.t_i[i8].magnitude), np.array(self.td_i[i8].magnitude),
np.array(self.t_i[i5].magnitude), np.array(self.u_i[i8].magnitude),
np.array(self.v_i[i8].magnitude), np.array(self.u_i[i5].magnitude),
np.array(self.v_i[i5].magnitude))
si = showalter_index(self.t_i[i8], self.td_i[i8], self.t_i[i5])
li = lifted_index(self.t_i[0], self.td_i[0], self.p_i[0], self.t_i[i5])
srh_pos, srh_neg, srh_tot = mpcalc.storm_relative_helicity(self.u_i, self.v_i, self.alt, 1000 * units('m'))
sbcape, sbcin = mpcalc.surface_based_cape_cin(self.p_i, self.t_i, self.td_i)
shr6km = mpcalc.bulk_shear(self.p_i, self.u_i, self.v_i, heights=self.alt, depth=6000 * units('m'))
wshr6km = mpcalc.wind_speed(*shr6km)
sigtor = mpcalc.significant_tornado(sbcape, delta_height(self.p_i[0], lcl_p), srh_tot, wshr6km)[0]
# Plotting
self.ax.set_ylim(1050, 100)
self.ax.set_xlim(-40, 50)
self.plot(self.p_i, self.t_i, 'r', linewidth=1)
self.plot(self.p_i[:self.dp_idx], self.td_i[:self.dp_idx], 'g', linewidth=1)
self.plot_barbs(self.p_i[:index_p100], self.u_i[:index_p100] * 1.94, self.v_i[:index_p100] * 1.94)
self.plot(lcl_p, lcl_t, 'ko', markerfacecolor='black')
self.plot(self.p_i, prof, 'k', linewidth=2)
if cin.magnitude < 0:
chi = -1 * cin.magnitude
self.shade_cin(self.p_i, self.t_i, prof)
elif cin.magnitude > 0:
chi = cin.magnitude
self.shade_cin(self.p_i, self.t_i, prof)
else:
chi = 0.
self.shade_cape(self.p_i, self.t_i, prof)
self.plot_dry_adiabats(linewidth=0.5)
self.plot_moist_adiabats(linewidth=0.5)
self.plot_mixing_lines(linewidth=0.5)
plt.title('Skew-T Plot \nStation: {} Time: {}'.format(self.st, self.time.strftime('%Y.%m.%d %H:%M')), fontsize=14, loc='left')
# Add hodograph
ax = self._fig.add_axes([0.95, 0.71, 0.17, 0.17])
h = Hodograph(ax, component_range=50)
h.add_grid(increment=20)
h.plot_colormapped(self.u_i[:index_p100], self.v_i[:index_p100], self.alt[:index_p100], linewidth=1.2)
# Annotate parameters
# Annotate names
namelist = ['CAPE', 'CIN', 'MUCAPE', 'PWAT', 'K', 'A', 'SWEAT', 'LCL', 'LFC', 'EL', 'SI', 'LI', 'T850-500',
'θse850-500', 'SRH', 'STP']
xcor = -50
ycor = -90
spacing = -9
for nm in namelist:
ax.text(xcor, ycor, '{}: '.format(nm), fontsize=10)
ycor += spacing
# Annotate values
varlist = [cape, chi, mucape, pwat, k, a, sw, lcl_p, lfc_p, el_p, si, li, self.t_i[i8] - self.t_i[i5], thetadiff,
srh_tot, sigtor]
xcor = 10
ycor = -90
for v in varlist:
if hasattr(v, 'magnitude'):
v = v.magnitude
ax.text(xcor, ycor, str(np.round_(v, 2)), fontsize=10)
ycor += spacing
# Annotate units
unitlist = ['J/kg', 'J/kg', 'J/kg', 'mm', '°C', '°C', '', 'hPa', 'hPa', 'hPa', '°C', '°C', '°C', '°C']
xcor = 45
ycor = -90
for u in unitlist:
ax.text(xcor, ycor, ' {}'.format(u), fontsize=10)
ycor += spacing
skew.plot_barbs(p[ix], u[ix], v[ix])
skew.ax.set_ylim(1075, 100)
skew.ax.set_ylabel('Pressure (hPa)')
lcl_pressure, lcl_temperature = mpcalc.lcl(p[0], T[0], Td[0]) #LCL
pwat = mpcalc.precipitable_water(Td, p, 500 * units.hectopascal).to('in') #PWAT
cape, cin = mpcalc.most_unstable_cape_cin(p[:], T[:], Td[:]) #MUCAPE
cape_sfc, cin_sfc = mpcalc.surface_based_cape_cin(p, T, Td) #SBCAPE
prof = mpcalc.parcel_profile(p, T[0], Td[0]).to('degC') #parcel profile
equiv_pot_temp = mpcalc.equivalent_potential_temperature(p, T, Td) #equivalent potential temperature
el_pressure, el_temperature = mpcalc.el(p, T, Td) #elevated level
lfc_pressure, lfc_temperature = mpcalc.lfc(p, T, Td) #LFC
#calculates shear
u_threekm_bulk_shear, v_threekm_bulk_shear = mpcalc.bulk_shear(p, u, v, hgt, bottom = min(hgt), depth = 3000 * units.meter)
threekm_bulk_shear = mpcalc.get_wind_speed(u_threekm_bulk_shear, v_threekm_bulk_shear)
u_onekm_bulk_shear, v_onekm_bulk_shear = mpcalc.bulk_shear(p, u, v, hgt, bottom = min(hgt), depth = 1000 * units.meter)
onekm_bulk_shear = mpcalc.get_wind_speed(u_onekm_bulk_shear, v_onekm_bulk_shear)
#shows the level of the LCL, LFC, and EL.
skew.ax.text(T[0].magnitude, p[0].magnitude + 5, str(int(np.round(T[0].to('degF').magnitude))), fontsize = 'medium', horizontalalignment = 'left', verticalalignment = 'top', color = 'red')
skew.ax.text(Td[0].magnitude, p[0].magnitude + 5, str(int(np.round(Td[0].to('degF').magnitude))), fontsize = 'medium', horizontalalignment = 'right', verticalalignment = 'top', color = 'green')
skew.ax.text(lcl_temperature.magnitude + 5, lcl_pressure.magnitude, "---- LCL", fontsize = 'medium', verticalalignment = 'center')
skew.ax.text(Td[0].magnitude - 10, p[0].magnitude, 'SFC: {}hPa ----'.format(p[0].magnitude), fontsize = 'medium', horizontalalignment = 'right', verticalalignment = 'center', color = 'black')
if str(lfc_temperature.magnitude) != 'nan': #checks to see if LFC/EL exists. If not, skip.
skew.ax.text(lfc_temperature.magnitude + 5, lfc_pressure.magnitude, "---- LFC", fontsize = 'medium', verticalalignment = 'center')
skew.ax.text(el_temperature.magnitude + 5, el_pressure.magnitude, "---- EL", fontsize = 'medium', verticalalignment = 'center')
skew.plot(p, prof, 'k-', linewidth=1) #plots parcel profile
