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
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)
- 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)
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Wed Oct 14, 2020; 12:34
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