Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 14
Articles | Volume 19, issue 14
https://doi.org/10.5194/amt-19-4943-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-4943-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 14
Research article
 | Highlight paper
 | 
30 Jul 2026
Research article | Highlight paper |  | 30 Jul 2026

disdrodb: an open-source Python package for standardized processing, sharing, and analysis of disdrometer data

Gionata Ghiggi, Kim Candolfi, Anne-Claire Billault-Roux, Régis Longchamp, Son Pham-Ba, Charlotte Weil, Remko Uijlenhoet, and Alexis Berne

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Editorial statement
I support the designation of this manuscript as a Highlighted Paper. The work presents a substantial community resource that goes beyond a software implementation by establishing a standardized, reproducible framework for disdrometer data sharing and analysis. Given its potential to facilitate future observational, microphysical, and remote sensing studies, I expect it will have broad and lasting impact within the atmospheric sciences.
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Short summary
disdrodb is a Python package for standardized sharing, processing, and analysis of disdrometer observations. It makes precipitation particle size distribution datasets easier to discover, access, and download, and converts heterogeneous raw measurements into global harmonized products for remote sensing precipitation retrievals and particle size distribution studies.
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