Quickstart Guide¶

Performing a calculation with sasktran can be broken up into three steps:

Defining the geometry of the problem. Typically this boils down to calculating an observer location, a look vector, and a timestamp for the measurements. sasktran contains several tools to aid with this computation.
Creating a representation of the atmospheric state for the calculation.
Choosing a radiative transfer model and setting it up for the calculation.

Defining the Geometry¶

The raw input to sasktran for each measurement is the observer location, a unit look vector, and a timestamp represented with a Modified Julian Date. If you already have these things, excellent, we can directly create a sasktran.Geometry object,

import sasktran as sk

geometry = sk.Geometry()

los_1 = sk.LineOfSight(observer=[3.676013154788849600e+005, 1.009976313640051500e+006, -6.871601202127538600e+006],
                       look_vector=[2.884568631765662100e-001, 7.925287180643269000e-001,  5.372996083468238900e-001],
                       mjd=54832.5)
los_2 = sk.LineOfSight(observer=[3.692808540679614500e+005, 1.014590807988641800e+006, -6.870844156040793300e+006],
                       look_vector=[2.884568631765662100e-001, 7.925287180643269000e-001,  5.372996083468238900e-001],
                       mjd=54832.5)

geometry.lines_of_sight = [los_1, los_2]

If you want to define the geometry based on solar angles, there are several convenience methods that can help:

from sasktran.geometry import VerticalImage

geometry = VerticalImage()
geometry.from_sza_saa(sza=60, saa=60, lat=0, lon=0, tanalts_km=[10, 20, 30, 40], mjd=54372, locallook=0,
                      satalt_km=600, refalt_km=20)

Nadir viewing geometries can also be configured in a similar way:

from sasktran.geometry import NadirGeometry

geometry = NadirGeometry()
geometry.from_zeniths_and_azimuths(solar_zenith=60, solar_azimuth=30, observer_mjds=[54372], observer_zeniths=[90], observer_azimuths=[60])

Representing the Atmosphere¶

Each atmospheric constituent is represented by two things:

A climatology which specifies the amount and distribution of the constituent, the class sasktran.Climatology helps here. All climatologies are specified with respect to particle number density in units of /cm3
An optical property of type sasktran.OpticalProperty which defines the species cross sections.

The sasktran.Atmosphere combines these things together for multiple species to make up the full atmospheric state. Many precomputed climatologies and optical properties are avaialable, or you can define your own. But for now let’s create an atmosphere consisting of Rayleigh scattering and ozone absorption with precomputed climatologies:

import sasktran as sk

atmosphere = sk.Atmosphere()

atmosphere['ozone'] = sk.Species(sk.O3OSIRISRes(), sk.Labow())
atmosphere['air'] = sk.Species(sk.Rayleigh(), sk.MSIS90())

Setting up the Engine¶

The final step is creating the sasktran.Engine object which actually performs the radiative transfer calculation. sasktran contains multiple radiative transfer models, but for most standard applications it is recommended to use the hr engine which is suitable for all viewing geometries in the UV-VIS-NIR spectral regime:

import sasktran as sk
from sasktran.geometry import VerticalImage

# First recreate our geometry and atmosphere classes
geometry = VerticalImage()
geometry.from_sza_saa(sza=60, saa=60, lat=0, lon=0, tanalts_km=[10, 20, 30, 40], mjd=54372, locallook=0,
                      satalt_km=600, refalt_km=20)

atmosphere = sk.Atmosphere()

atmosphere['ozone'] = sk.Species(sk.O3OSIRISRes(), sk.Labow())
atmosphere['air'] = sk.Species(sk.Rayleigh(), sk.MSIS90())

# And now make the engine
engine = sk.EngineHR(geometry=geometry, atmosphere=atmosphere)

# Choose some wavelengths to do the calculation at
engine.wavelengths = [340, 600]

# And do the calculation
radiance = engine.calculate_radiance()