A Band Emission Model¶
SASKTRAN includes a model to include effects from photochemical emission in the oxygen A band.
This is included as
ABandEmission, and can be created through
import sasktran as sk import numpy as np emissions_alts_km = np.arange(0, 200) aband_emission = sk.ABandEmission(emissions_alts_km)
Running the Model¶
To run the model we need three things
A representation of the atmospheric state, containing pressure, temperature, ozone, and O2.
A location to run the model at.
The solar geometry
The representation of the atmospheric state is an instance of the
Atmosphere object, for example,
atmosphere = sk.Atmosphere() # Set the background pressure/temperature atmosphere.atmospheric_state = sk.MSIS90() # Set the constituent species atmosphere['ozone'] = sk.Species(sk.O3OSIRISRes(), sk.Labow()) atmosphere['air'] = sk.Species(sk.Rayleigh(), sk.MSIS90()) atmosphere['O2'] = sk.Species(sk.HITRANChemical('O2'), sk.MSIS90(include_o2=True), species='SKCLIMATOLOGY_O2_CM3')
Note that some of the climatologies used here are focused on the stratosphere, and may not be suitable for the mesosphere.
For more accurate calculations using the A band emission model it is recommended to create
ClimatologyUserDefined objects with realistic mesospheric profiles.
Having created the atmosphere we can then run the model, usually running the model takes around 40 seconds depending how many altitudes are requested.
ref = [40, 0, 0, 54372] # Lat/lon/altitude/mjd sun = np.array([0, 0, 1]) emission_source, emission_wavel = aband_emission.run_model(atmosphere, ref, sun)
Including the Model in a Radiative Transfer Calculation¶
There are two ways we can use the emission model and include them in a radiative transfer calculation.
The first is to take the values we have already calculated and create a
# Convert emission altitudes to m, and source function from /cm to /m emission_table = sk.EmissionTable(emissions_alts_km * 1000, emission_wavel, emission_source * 100)
EmissionTable can then be added to the
Atmosphere object that goes into the radiative transfer model.
We also have to tell the radiative transfer model to specifically include emissions in the calculation.
atmosphere.emissions['aband'] = emission_table geo = sk.VerticalImage() geo.from_sza_saa(70, 60, 0, 0, np.array([30, 40, 50, 60, 70]), 54372, 0) engine = sk.EngineHR(geometry=geo, atmosphere=atmosphere, wavelengths=np.arange(760, 780, 1e-2)) engine.include_emissions = True radiance = engine.calculate_radiance()
This method of including emissions in the model is a bit clunky since we have to first run the model at a specific location and solar geometry.
atmosphere.emissions['aband'] = sk.ABandEmission(emissions_alts_km) geo = sk.VerticalImage() geo.from_sza_saa(70, 60, 0, 0, np.array([30, 40, 50, 60, 70]), 54372, 0) engine = sk.EngineHR(geometry=geo, atmosphere=atmosphere, wavelengths=np.arange(760, 780, 1e-2)) engine.include_emissions = True radiance = engine.calculate_radiance()
The main advantage to this method is that the location and solar geometry used to run the A band emission model are taken directly from SASKTRAN to match the radiative calculation. The downside is that the A band emission model is executed every time the radiative transfer calculation is performed.