Metadata-Version: 1.1
Name: tartes
Version: 0.9.2
Summary: Two-stream radiative transfer in snow model
Home-page: http://lgge.osug.fr/~picard/tartes/
Author: Quentin Libois, Ghislain Picard
Author-email: quentin.libois@ujf-grenoble.fr, ghislain.picard@ujf-grenoble.fr
License: UNKNOWN
Description: Two-stream radiative transfer in snow model
        -------------------------------------------
        
        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.
        
Keywords: radiative transfer,model,snow,optics
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Other Environment
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
