SMART-G, a Monte Carlo GPU Radiative Transfer code
- Coupled Ocean/Atmosphere Monte Carlo Radiative Transfer solver
- GPU accelerated using the CUDA framework (massively parallel processing)
- Coded in Python and PyCUDA
- Physical processes
- scattering (molecules, water, aerosols, clouds)
- absorption (molecules, water, aerosols) and with extended band models (K distribution, …)
- reflection/refraction (Fresnel, atmospheric refraction)
- polarization
- Plane-parallel or spherical-shell atmosphere
- Surface
- wind roughned sea surface
- bidirectional reflectance distribution function
- horizontal variation of surface albedo
- Fast spectral computation
- 3-Dimensional characteristics
- 3D optical properties of atmosphere
- 3D objects
Applications
Simulation of radiance in limb geometry with atmospheric refraction
![Web_Limb_profils Vertical profiles of limb diffuse radiance as a function of the tangent height for different Relative Azimuth to the Sun, wavelengths and Solar Zenith Angles.](https://hygeos.com/wp-content/uploads/Web_Limb_profils.webp)
![Web_Limb_RGB RGB composite of the limb radiance for a low Sun in the forward directions](https://hygeos.com/wp-content/uploads/Web_Limb_RGB.webp)
Limb diffuse radiance for an observer at 120km altitude as a function of the tangent height for different relative azimuths to the Sun (ΔΦ = 0, 30, 60, 90°), 3 wavelengths (430, 660 and 840 nm) and 4 solar zenith angles (SZA = 60, 80, 91 and 94°).
The computation time with 105 photons/height/azimuth is about 1s with a GeForce RTX3090 graphics card.
RGB composite (430nm, 660nm, 840nm) of the limb radiance for a low Sun (SZA=94°) in the forward directions up to ΔΦ = 20°.
Simulation of topographic and 3D objects influence on radiance
Radiometric calibration of in situ spectro-radiometer at the top of a mountain. The radiometer is viewing a horizontal plate of known bidirectional reflectance with the Sun disk unobscured and masked, allowing a determination of the direct component of downwelling planar irradiance.
The SMART-G simulation is done with a proper k-distribution at the same spectral resolution as the instrument.
![Web_object_spectrum Radiance by a radiometer and simulated by SMART-G](https://hygeos.com/wp-content/uploads/Web_object_spectrum-scaled.webp)
Simulation of 2D adjacency effects
![Web_adjacency_schema Scheme of the adjacency effects](https://hygeos.com/wp-content/uploads/Web_adjacency_schema.webp)
![Web_adjacency_snow Simulation of TOA spectra of S3/OLCI sensor for a black ocean pixel as a function of the distance to the coastline](https://hygeos.com/wp-content/uploads/Web_adjacency_snow.webp)
Simulation of TOA spectra of the Sentinel-3/OLCI sensor for a black ocean pixel as a function of the distance d to the linear coastline separating ocean and land covered by snow and ice. The principal plane is parallel to the coastline.
Simulation of 3D clouds
![Web_3D_BOA Surface reflectances simulated by SMART-G at 710 nm](https://hygeos.com/wp-content/uploads/Web_3D_BOA.webp)
![Web_3D_TOA TOA reflectances simulated by SMART-G at 710 nm for a cloudy scene.](https://hygeos.com/wp-content/uploads/Web_3D_TOA.webp)
Maps of surface (left) and TOA (right) reflectances at 710 nm for a cloudy scene, simulated using Large Eddy Simulation microphysical outputs and for a continental aerosol polluted atmosphere. The horizontal resolution is 66 m and there are 53 vertical layers for a total of atmospheric cell of 100x100x53. The surface is a lambertian reflector whose spectral albedo is obtained from Sentinel-2 Land Cover map.