pressure = wrfOutputFile.variables["P"][:] + wrfOutputFile.variables["PB"][:]
qvapor = wrfOutputFile.variables["QVAPOR"][:]
qvapor = numpy.ma.masked_where(qvapor < 0.00002, qvapor)
T0 = 273.15
referencePressure = 100000.0 # [Pa]
epsilon = 0.622 # Rd / Rv
# Temperatures in Celsius
temperature = theta * numpy.power((pressure / referencePressure), 0.2854) - T0
vaporPressure = pressure * qvapor / (epsilon + qvapor)
dewPointTemperature = 243.5 / (
(17.67 / numpy.log(vaporPressure * 0.01 / 6.112)) - 1.0) # In celsius
dewPointTemperature = numpy.ma.masked_invalid(dewPointTemperature)
# Now we have the pressure, temperature and dew point temperature in the whole domain
# Select one vertical column , t =0 , x=30, y=30
inputData = dict(
pressure=pressure[0, :, 30, 30] / 100,
temperature=temperature[0, :, 30, 30],
dewPointTemperature=dewPointTemperature[0, :, 30, 30],
)
mySounding = sounding(inputData)
mySounding.quickPlot()
def calculate_radar_hid(radar, sounding_names, radar_band="S"):
"""
Use radar and sounding data to calculate:
- Temperature and height profiles
- Hydrometeor classification with CSU_RadarTools
- Liquid and ice water masses, ice fraction
Parameters
----------
radar: Py-ART radar data
sounding_names: list of sounding data filenames
radar_band: radar band
Returns
-------
file: radar data with HID and water masses
"""
# Getting date for sounding - optional
# radar_date = pd.to_datetime(radar.time['units'][14:])
# Interpolating with sounding
soundings = sounding(sounding_names)
# - optional: sounding_names.loc[str(radar_date.date())].item()
radar_T, radar_z = interpolate_sounding_to_radar(soundings, radar)
# Extracting necessary variables
z_corrected = radar.fields["corrected_reflectivity"]["data"]
zdr = radar.fields["differential_reflectivity"]["data"]
kdp = radar.fields["specific_differential_phase"]["data"]
rho_hv = radar.fields["cross_correlation_ratio"]["data"]
# Classifying
scores = csu_fhc.csu_fhc_summer(
weights={
"DZ": 1,
"DR": 1,
"KD": 1,
"RH": 1,
"LD": 1,
"T": 1
},
dz=z_corrected,
zdr=zdr,
kdp=kdp,
rho=rho_hv,
use_temp=True,
T=radar_T,
band=radar_band,
verbose=True,
method="hybrid",
)
fh = np.argmax(scores, axis=0) + 1
# - Adding to radar file
radar = add_field_to_radar_object(fh,
radar,
standard_name="Hydrometeor ID")
# - Calculating liquid and ice mass
mw, mi = csu_liquid_ice_mass.calc_liquid_ice_mass(z_corrected,
zdr,
radar_z / 1000.0,
T=radar_T)
# - Adding to radar file
file = add_field_to_radar_object(
mw,
radar,
field_name="MW",
units=r"$g\ m^{-3}$",
long_name="Liquid Water Mass",
standard_name="Liquid Water Mass",
)
file = add_field_to_radar_object(
mi,
file,
field_name="MI",
units=r"$g\ m^{-3}$",
long_name="Ice Water Mass",
standard_name="Ice Water Mass",
)
return file
"""
Simple SkewT Figure example from Sounding
"""
# For python2.7 compatibility
from __future__ import print_function, division
# Load the sounding class from the package
from SkewTplus.sounding import sounding
# Load the sounding datas
mySounding = sounding("./exampleSounding.txt")
# Show the SkewT diagram of the Sounding
mySounding.quickPlot()
"""
Simple SkewT Figure example from Sounding
"""
from __future__ import print_function, division
from SkewTplus.skewT import figure
from SkewTplus.sounding import sounding
# Load the sounding data
mySounding = sounding("./armSoundingExample.cdf")
# Create a Figure Manager
mySkewT_Figure = figure()
# Add an Skew-T axes to the Figure
mySkewT_Axes = mySkewT_Figure.add_subplot(111, projection="skewx")
# Extract the data from the Sounding
# The getCleanSounding method remove levels where invalid temperatura or pressure
# values are present
pressure, temperature, dewPointTemperature = mySounding.getCleanSounding()
# Add a profile to the Skew-T diagram
mySkewT_Axes.addProfile(
pressure,
temperature,
dewPointTemperature,
hPa=True,
'''
Plot two soundings in the same Skew-T diagram with out any parcel analysis
'''
from __future__ import print_function, division
from SkewTplus.skewT import figure
from SkewTplus.sounding import sounding
#Load the sounding data
mySounding1 = sounding("./bna_day1.txt")
mySounding2 = sounding("./bna_day2.txt")
# Create a Figure Manager with a suitable size for both plots
mySkewT_Figure = figure(figsize=(5, 6))
# Add the Skew-T axes to the Figure
mySkewT_Axes1 = mySkewT_Figure.add_subplot(111, projection='skewx', tmin=-40)
# Add one profile to the Skew-T diagram
# The line style is set to be a solid line and a label is added
# to the plot. Since the label is not None, a legend will be added
# automatically to the plot
mySkewT_Axes1.addProfile(*mySounding1.getCleanSounding(),
hPa=True,
celsius=True,
parcel=False,
label='Day 1',
linestyle='-')
# Add a second profile to the Skew-T diagram
from netCDF4 import Dataset
import numpy
from SkewTplus.skewT import figure
from SkewTplus.sounding import sounding
from SkewTplus.thermodynamics import parcelAnalysis, liftParcel
import matplotlib.pyplot as plt
# Read the examples soundings
# Load the sounding class from the package
#Load the sounding data
print("Testing TXT reader")
assert(sounding("./exampleSounding.txt")['pressure'][-1]==34.0)
assert(sounding("./94610.2010032200.txt")['pressure'][-1]==8.8)
assert(sounding("./94866.2010030600.txt")['pressure'][-1]==37.6)
assert(sounding("./94975.2013070900.txt")['pressure'][-1]==57.0)
assert(sounding("./94975.2013070900.txt")['pressure'][-1]==57.0)
assert(sounding("./bna_day1.txt")['pressure'][-1]==100.0)
assert(sounding("./bna_day2.txt")['pressure'][-1]==100.0)
assert(sounding("./sounding_high_tropo.txt")['pressure'][-1]==14.7)
# Show the SkewT diagram of the Sounding
mySounding = sounding("./exampleSounding.txt")
mySounding.quickPlot()
'''
Simple SkewT Figure example from Sounding
qvapor = wrfOutputFile.variables['QVAPOR'][:]
qvapor = numpy.ma.masked_where(qvapor < 0.00002, qvapor)
T0 = 273.15
referencePressure = 100000.0 # [Pa]
epsilon = 0.622 # Rd / Rv
# Temperatures in Celsius
temperature = theta * numpy.power((pressure / referencePressure), 0.2854) - T0
vaporPressure = pressure * qvapor / (epsilon + qvapor)
dewPointTemperature = 243.5 / (
(17.67 / numpy.log(vaporPressure * 0.01 / 6.112)) - 1.) #In celsius
dewPointTemperature = numpy.ma.masked_invalid(dewPointTemperature)
# Now we have the pressure, temperature and dew point temperature in the whole domain
# Select one vertical column , t =0 , x=30, y=30
mySounding = sounding() # Create an empty sounding
#Add fields
mySounding.addField('pressure', pressure[0, :, 30, 30], "Pressure", "Pa")
mySounding.addField('temperature', temperature[0, :, 30, 30], "Temperature",
"C")
mySounding.addField('dewPointTemperature', dewPointTemperature[0, :, 30, 30],
"Dew Point Temperature", "C")
mySounding.quickPlot()
"""
Created on Apr 22, 2017
@author: aperez
"""
from SkewTplus.sounding import sounding
mySounding = sounding()
mySounding.fetchFromWeb("20170410:00", "OAX")
mySounding.quickPlot()
mySounding = sounding("20170410:00", fileFormat="web", stationId="OAX")
mySounding.quickPlot()