Skip to main content

Two-stream radiative transfer in snow model

Project description

TARTES is a fast and easy-to-use optical radiative transfer model used to compute snow albedo (spectral and broadband) and energy absorption profile. TARTES represents the snowpack as a stack of horizontal homogeneous layers. Each layer is characterized by the snow specific surface area (SSA), snow density, impurities amount and type, and two parameters for the geometric grain shape: the asymetry factor g and the absorption enhancement parameter B. The albedo of the bottom interface can be prescribed. The model is fast and easy to use compared to more elaborated models like DISORT - MIE (Stamnes et al. 1988). It is based on the Kokhanovsky and Zege (2004) formalism for weakly absorbing media to describe the single scattering properties of each layers and the delta-eddington approximation to solve the radiative transfer equation. Despite its simplicity, it is accurate in the visible and near-infrared range for pristine snow as well as snow containing impurities represented as Rayleigh scatterers (their size is assumed much smaller than the wavelength) whose refractive indices and concentrations can be prescribed.

TARTES is compatible with Python 2.7x and 3.4+.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tartes-1.2.0.tar.gz (564.7 kB view details)

Uploaded Source

File details

Details for the file tartes-1.2.0.tar.gz.

File metadata

  • Download URL: tartes-1.2.0.tar.gz
  • Upload date:
  • Size: 564.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for tartes-1.2.0.tar.gz
Algorithm Hash digest
SHA256 579f5cb9fc6fee48f9c2cef20ebf55a5a3994272b2ce40ae2b9fbee007bae247
MD5 d609c8a69c12c85816ca89dee8a55c56
BLAKE2b-256 159b5dbb10bfc5b2686e310d68fed19239653375abb9bafe46353be7cc220587

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page