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SASKTRAN2

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SASKTRAN2#

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The SASKTRAN Radiative Transfer Framework (Version 2)

SASKTRAN2 is an atmospheric radiative transfer model developed at the University of Saskatchewan. It is a full rewrite of the original SASKTRAN Model providing

  • A simpler, more powerful, user interface

  • Full capability to calculate weighting functions, i.e. derivatives of output radiative quantities with respect to input atmospheric properties

  • Greatly improved efficiency for hyperspectral calculations

SASKTRAN2 is still in active development, and things are subject to change quickly, however it is already usable for many applications. After Installing the model, we recommend starting with the Quick Start Guide to get a feel for the core concepts of the interface.

Installation

SASKTRAN2 is available both as a conda and pip package on most platforms.

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Quick Start Guide

The quick start guide will help you set up your first radiative transfer calculation.

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User’s Guide

The user’s guide demonstrates SASKTRAN2’s features through example, including powerful features such as calculating derivatives of output values with respect to input values.

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API Reference

A full reference to SASKTRAN2’s API. This section assumes you are already familiar with the core concepts of the model.

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License#

SASKTRAN2 is made available under the MIT license (see License)

We request that users of the model contact the authors before publishing results using SASKTRAN2, and that the following publications are acknowledged:

Zawada, D. J., Dueck, S. R., Rieger, L. A., Bourassa, A. E., Lloyd, N. D., and Degenstein, D. A.: High-resolution and Monte Carlo additions to the SASKTRAN radiative transfer model, Atmos. Meas. Tech., 8, 2609-2623, https://doi.org/10.5194/amt-8-2609-2015, 2015.

Bourassa, A. E., Degenstein, D. A., and Llewellyn, E. J.: SASKTRAN: A Spherical Geometry Radiative Transfer Code for Efficient Estimation of Limb Scattered Sunlight, J Quant Spectrosc Radiat Trans, Volume 109, Issue 1, 52-73, https://doi.org/10.1016/j.jqsrt.2007.07.007, 2008.

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