Py4CAtS --- Python for Computational ATmospheric Spectroscopy

[Image: DLR]

Main Scripts/Functions: From Hitran/Geisa to cross sections to optical depths and radiance (intensity)

higstract: HItran-GeiSa extract (select) lines of a certain molecule (and isotope) and/or wavenumber range from line parameter database
lbl2xs: line-by-line (lbl) cross sections for some molecule(s) and some p, T
lbl2od: computation of line-by-line optical depth due to molecular absorption (combines lbl2xs, xs2ac, ac2od)
(d)od2ri: Given the (layer, delta) line-by-line optical depth solve Schwarzschild equation to radiation intensity

Installation: Getting started with Py4CAtS

Download a tarball of Python sources, some data files, and the documentation and unpack it at some convenient place:
tar xfvz py4CAtS.tgz

The top-level directory py4CAtS includes a 1.ReadMe file with basic instructions, and four subdirectories bin, data, doc, and src.

Prerequisites: Python (3) and numpy (sometimes scipy and matplotlib for plotting)

And you need some line data (HITRAN and/or GEISA). For the beginning, here is a thermal infrared excerpt of Hitran 86.

Usage

Py4CAtS can be used in two ways, from the Unix/Linux (or Windows/Mac?) console/terminal or (much better, more flexible, ..... See the demo !NEW!

or the poster for the ASA-HITRAN 2016 congress) inside the (I)Python interpreter or Jupyter Qt Console or notebook.

Documentation

For a detailed review of line-by-line modeling for infrared radiative transfer see the manual py4cats.pdf in the doc directory.
Sections 5 and 6 describe Py4CAtS' usage from the Unix/Linux shell and the (i)python shell, respectively.

How to cite Py4CAtS?

F. Schreier, S. Gimeno García, P. Hochstaffl and S. Städt. Py4CAtS --- Python for Computational ATmospheric Spectroscopy. Atmosphere 10(5), 262, 2019, doi: 10.3390/atmos10050262
F. Schreier and S. Gimeno Garcia. Py4CAtS – Python Tools for Line-by-Line Modelling of Atmospheric Radiative Transfer. In Robert F. Cahalan and Jürgen Fischer (editors), Radiation Processes in the Atmosphere and Ocean (IRS 2012): Proceedings of the International Radiation Symposium (IRC/IAMAS) Volume 1531 of AIP Conference Proceedings, pages 123 - 126. American Institute of Physics, 2013. doi: 10.1063/1.4804723
F. Schreier and P. Hochstaffl. Py4CAtS --- Python for Computational ATmospheric Spectroscopy. GSICS Quarterly 13(4), pp. 6 - 8, 2020 doi: 10.25923/ymt5-wz59
See also GARLIC (Generic Atmospheric Radiation Line-by-line Infrared Code, Py4CAtS' big brother): JQSRT 137, 29-50, 2014
and our related projects lbl4IR

(download BiBTeX entries)

What's new?

September 2019 -- January 2020: Module aeiou.py: function loadxyy with new optional argument xLimits; Module cgsUnits: lengthsUnits: ly, pc added; functions lambda2nu, nu2lambda: first argument (wavelengths or wavenumbers) are variable list arguments; Module lineshapes.py: function Rautian now calling hum2wei32 (old: hum1wei24); Module misc.py: function show_lambda with new arguments frmt, yShift, nanometer; Module py4cats.py: import show_lambda added;; Module oDepth.py: functions oDepth_altitudes, oDepth_pressures optionally return altitudes or pressures in km, mb, ....; Module xSection.py: function xsSave: third and fourth arguments swapped (interpolate <--> commentChar)
function xsRead: now can be called recursively
July 2020: Module convolution.py: functions convolveBox, convolveTriangle, convolveGauss: the number of grid points for the new wGrid is now evaluated as int(); Module myMatPlotLib.py: new module with some extra settings; Module py4cats.py: last section with matplotlib settings removed (now in new file myMatPlotLib.py)