Discrete Ordinates Solver for the (1D) Radiative Transfer Equation in a single or multi-layer atmosphere.
Project description
Introduction
The PythonicDISORT package is a Discrete Ordinates Solver for the (1D) Radiative Transfer Equation in a single or multi-layer atmosphere.
It is coded entirely in Python 3 and in as "Pythonic" a manner as possible: we vectorize as well as use list comprehension and map
as much as possible.
It is based on Stamnes' FORTRAN DISORT (see References, in particular [2, 3, 8]) and has its main features: delta-M scaling, Nakajima-Tanaka (NT) corrections, only flux option, isotropic internal sources (thermal source), Bi-Directional Reflectance Function (BDRF) and more.
This repository also includes our F2PY-wrapped Stamnes DISORT (version 4.0.99) in the disort4.0.99_f2py
directory.
The original was downloaded from http://www.rtatmocn.com/disort/. The wrapper was inspired by https://github.com/kconnour/pyRT_DISORT.
Documentation
https://pythonic-disort.readthedocs.io/en/latest/
Also see the accompanying Jupyter Notebook: Pythonic-DISORT.ipynb
in the docs
directory.
The Jupyter Notebook provides comprehensive documentation, suggested inputs, explanations,
mathematical derivations and verification tests.
We highly recommend reading the non-optional parts of sections 1 and 2 before use.
PyTest
Separate from the verification tests in the notebook, we used PyTest to recreate most of the test problems from Stamnes et. al.'s disotest.f90
.
With PyTest installed, execute the console command pytest
in the pydisotest
directory to run these tests.
Installation
- From PyPI:
pip install PythonicDISORT
- From Conda-forge: (TODO: need to first publish on Conda-forge)
- By cloning repository:
pip install .
in thePythonic-DISORT
directory;pip install -r all_optional_dependencies.txt
to install all optional dependencies
Requirements to run PythonicDISORT
- Python 3.8+
numpy >= 1.17.3
scipy >= 1.8.0
- (OPTIONAL)
pytest >= 6.2.5
Additional requirements to run the Jupyter Notebook
autograd >= 1.5
jupyter > 1.0.0
notebook > 6.5.2
- (OPTIONAL)
ipympl >= 0.8.8
Our F2PY-wrapped Stamnes' DISORT (in the disort4.0.99_f2py
directory) must also be set up to run the last section (section 6).
Compatibility
The PythonicDISORT package should be system agnostic given its minimal dependencies and pure Python code. We are not sure if the Jupyter Notebook or our F2PY-wrapped Stamnes' DISORT will run without issues on non-Windows systems. Everything was built and tested on Windows 11 and not yet tested on other systems.
References
-
S. Chandrasekhar. 1960. Radiative Transfer.
-
Knut Stamnes and S-Chee Tsay and Warren Wiscombe and Kolf Jayaweera. 1988. Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. http://opg.optica.org/ao/abstract.cfm?URI=ao-27-12-2502.
-
Stamnes, S.. 1999. LLLab disort website. http://www.rtatmocn.com/disort/.
-
Knut Stamnes and Paul Conklin. 1984. A new multi-layer discrete ordinate approach to radiative transfer in vertically inhomogeneous atmospheres. https://www.sciencedirect.com/science/article/pii/0022407384900311.
-
W. J. Wiscombe. 1977. The Delta–M Method: Rapid Yet Accurate Radiative Flux Calculations for Strongly Asymmetric Phase Functions. https://journals.ametsoc.org/view/journals/atsc/34/9/1520-0469_1977_034_1408_tdmrya_2_0_co_2.xml.
-
J. H. Joseph and W. J. Wiscombe and J. A. Weinman. 1976. The Delta-Eddington Approximation for Radiative Flux Transfer. https://journals.ametsoc.org/view/journals/atsc/33/12/1520-0469_1976_033_2452_tdeafr_2_0_co_2.xml.
-
Sykes, J. B.. 1951. Approximate Integration of the Equation of Transfer. https://doi.org/10.1093/mnras/111.4.377.
-
Stamnes, Knut and Tsay, Si-Chee and Wiscombe, Warren and Laszlo, Istvan and Einaudi, Franco. 2000. General Purpose Fortran Program for Discrete-Ordinate-Method Radiative Transfer in Scattering and Emitting Layered Media: An Update of DISORT.
-
Z. Lin and S. Stamnes and Z. Jin and I. Laszlo and S.-C. Tsay and W.J. Wiscombe and K. Stamnes. 2015. Improved discrete ordinate solutions in the presence of an anisotropically reflecting lower boundary: Upgrades of the DISORT computational tool. https://www.sciencedirect.com/science/article/pii/S0022407315000679.
-
Trefethen, L. N.. 1996. Finite difference and spectral methods for ordinary and partial differential equations. https://people.maths.ox.ac.uk/trefethen/pdetext.html.
-
T. Nakajima and M. Tanaka. 1988. Algorithms for radiative intensity calculations in moderately thick atmospheres using a truncation approximation. https://www.sciencedirect.com/science/article/pii/0022407388900313.
-
K. Connour and A. Stcherbinine. 2022. pyRT_DISORT. https://github.com/kconnour/pyRT_DISORT.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for PythonicDISORT-0.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b34f02053d682c70f86910e8c9c380f321a9034f9cf49a967e84418d7e7b3c3d |
|
MD5 | 6025f25c3d45335ba3c037962951daec |
|
BLAKE2b-256 | 496c605c8104e1b11d5d2f66c96c3da3b65e7945b2f15fccc6ff548b632400ef |