Preprints
https://doi.org/10.5194/amt-2023-254
https://doi.org/10.5194/amt-2023-254
22 Jan 2024
 | 22 Jan 2024
Status: a revised version of this preprint is currently under review for the journal AMT.

ampycloud: an algorithm to characterize cloud layers above aerodromes using ceilometer measurements

Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, and Pieter du Preez

Abstract. Ceilometers are used routinely at aerodromes world-wide to measure the height and sky coverage fraction of cloud layers. This information, possibly combined with direct observations by human observers, contributes to the production of Meteorological Aerodrome Reports (METARs). Here, we present ampycloud, a new algorithm and associated Python package for automatic processing of ceilometer measurements, with the aim to characterize cloud layers above aerodromes. The ampycloud algorithm has been developed at the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss) as part of the AMAROC (AutoMETAR/AutoReport rOund the Clock) program, to fully automate the creation of METARs at Swiss civil aerodromes. ampycloud is designed to work with no (direct) human supervision. The algorithm consists of three distinct, sequential steps that rely on agglomerative clustering methods and Gaussian mixture models to identify distinct cloud layers. The robustness of the ampycloud algorithm stems from the first processing step, simple and reliable. It constrains the two subsequent processing steps that are more sensitive, but also better suited to handle complex cloud distributions. The software implementation of the ampycloud algorithm takes the form of an eponym, pip-installable Python package developed on Github. The code is made accessible to the general community as an open-source software under the terms of the 3-Clause BSD license.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, and Pieter du Preez

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-254', Anonymous Referee #1, 08 Mar 2024
    • AC1: 'Reply on RC1', Frédéric Vogt, 16 May 2024
  • RC2: 'Comment on amt-2023-254', Anonymous Referee #2, 17 Apr 2024
    • AC2: 'Reply on RC2', Frédéric Vogt, 16 May 2024
Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, and Pieter du Preez

Data sets

ampycloud: example datasets Frédéric P. A. Vogt https://zenodo.org/doi/10.5281/zenodo.10171151

Model code and software

ampycloud Frédéric P. A. Vogt and Daniel Regenass https://zenodo.org/doi/10.5281/zenodo.8399683

Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, and Pieter du Preez

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Short summary
ampycloud is new algorithm developed at MeteoSwiss to characterize the height and sky coverage fraction of cloud layers above aerodromes via ceilometer measurements. This algorithm was devised as part of a larger effort to fully automate the creation of Meteorological Aerodrome Reports (METARs) at Swiss civil airports. The ampycloud algorithm was implemented as a Python package, that is made publicly available to the community under the 3-Clause BSD license.