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Py4CAtS—PYthon for Computational ATmospheric Spectroscopy

Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), 82234 Oberpfaffenhofen, Germany
Author to whom correspondence should be addressed.
Current address: EUMETSAT, 64283 Darmstadt, Germany.
Atmosphere 2019, 10(5), 262;
Received: 5 April 2019 / Revised: 3 May 2019 / Accepted: 6 May 2019 / Published: 10 May 2019
(This article belongs to the Special Issue Radiative Transfer Models of Atmospheric and Cloud Properties)
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Radiation is a key process in the atmosphere. Numerous radiative transfer codes have been developed spanning a large range of wavelengths, complexities, speeds, and accuracies. In the infrared and microwave, line-by-line codes are crucial esp. for modeling and analyzing high-resolution spectroscopic observations. Here we present Py4CAtS—PYthon scripts for Computational ATmospheric Spectroscopy, a Python re-implemen-tation of the Fortran Generic Atmospheric Radiation Line-by-line Code GARLIC, where computationally-intensive code sections use the Numeric/Scientific Python modules for highly optimized array processing. The individual steps of an infrared or microwave radiative transfer computation are implemented in separate scripts (and corresponding functions) to extract lines of relevant molecules in the spectral range of interest, to compute line-by-line cross sections for given pressure(s) and temperature(s), to combine cross sections to absorption coefficients and optical depths, and to integrate along the line-of-sight to transmission and radiance/intensity. Py4CAtS can be used in three ways: in the (Unix/Windows/Mac) console/terminal, inside the (I)Python interpreter, or Jupyter notebook. The basic design of the package, numerical and computational aspects relevant for optimization, and a sketch of the typical workflow are presented. In conclusion, Py4CAtS provides a versatile environment for “interactive” (and batch) line-by-line radiative transfer modeling. View Full-Text
Keywords: infrared; radiative transfer; molecular absorption; line-by-line infrared; radiative transfer; molecular absorption; line-by-line

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Schreier, F.; Gimeno García, S.; Hochstaffl, P.; Städt, S. Py4CAtS—PYthon for Computational ATmospheric Spectroscopy. Atmosphere 2019, 10, 262.

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