Submitted as: development and technical paper
28 Sep 2023
Submitted as: development and technical paper |  | 28 Sep 2023
Status: this preprint is currently under review for the journal GMD.

PyRTlib: an educational Python-based library for non-scattering atmospheric microwave Radiative Transfer computations

Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano

Abstract. This article introduces PyRTlib, a new standalone Python package for non-scattering line-by-line microwave Radiative Transfer simulations. PyRTlib is a flexible and user-friendly tool for computing down and up-welling brightness temperatures and related quantities (e.g., atmospheric absorption, optical depth, opacity, mean radiating temperature) written in Python, a language commonly used nowadays for scientific software development especially by students and early career scientists. PyRTlib allows simulating observations from ground-based, airborne, and satellite microwave sensors in clear sky and in cloudy conditions (under non-scattering Rayleigh approximation). The intention for PyRTlib is not to be a competitor for state-of-the-art atmospheric radiative transfer codes that excel for speed and/or versatility (e.g., ARTS, RTTOV). The intention is to provide an educational tool, completely written in Python, to readily simulate atmospheric microwave radiative transfer from a variety of input profiles, including predefined climatologies, global radiosonde archives, and model reanalysis. The paper presents quick examples for the built in modules to access popular open data archives. The paper also presents examples for computing simulated brightness temperature for different platforms (ground-based, airborne, and satellite), using various input profiles, showing how to easily modify other relevant parameters, such as observing angle (zenith, nadir, slant), surface emissivity, and gas absorption model. PyRTlib can be easily embedded in other Python codes needing atmospheric microwave radiative transfer (e.g., surface emissivity models and retrievals). Despite its simplicity, PyRTlib can be readily used to produce present-day scientific results, as demonstrated by two examples showing (i) absorption model comparison and validation with ground-based radiometric observations and (ii) uncertainty propagation of spectroscopic parameters through the radiative transfer calculations following a rigorous approach. To our knowledge, the uncertainty estimate is not provided by any other currently available microwave radiative transfer code, making PyRTlib unique for this aspect in the atmospheric microwave radiative transfer code scenario.

Salvatore Larosa et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2023-171', Anonymous Referee #1, 04 Oct 2023
  • RC2: 'Comment on gmd-2023-171', Anonymous Referee #2, 15 Oct 2023
  • CC1: 'Comment on gmd-2023-171', Philipp Hochstaffl, 25 Oct 2023
  • RC3: 'Comment on gmd-2023-171', Anonymous Referee #3, 27 Oct 2023
  • CC2: 'Comment on gmd-2023-171', Mario Mech, 19 Nov 2023

Salvatore Larosa et al.

Model code and software

A python package for non-scattering line-by-line microwave Radiative Transfer simulations. Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano

Salvatore Larosa et al.


Total article views: 573 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
490 70 13 573 3 2
  • HTML: 490
  • PDF: 70
  • XML: 13
  • Total: 573
  • BibTeX: 3
  • EndNote: 2
Views and downloads (calculated since 28 Sep 2023)
Cumulative views and downloads (calculated since 28 Sep 2023)

Viewed (geographical distribution)

Total article views: 558 (including HTML, PDF, and XML) Thereof 558 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 06 Dec 2023
Short summary
PyRTlib is an attractive educational software because it provides a flexible and user friendly tool to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols and hydrometeors). PyRTlib is a so called Radiative Transfer model which are commonly used to simulate and understand remote sensing observations from ground-based, airborne or satellite instruments.