Articles | Volume 19, issue 14
https://doi.org/10.5194/amt-19-4943-2026
https://doi.org/10.5194/amt-19-4943-2026
Research article
 | Highlight paper
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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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Cited articles

Abel, S. J. and Boutle, I. A.: An improved representation of the raindrop size distribution for single‐moment microphysics schemes, Q. J. R. Meteorol. Soc., 138, 2151–2162, https://doi.org/10.1002/qj.1949, 2012. a
Adirosi, E., Volpi, E., Lombardo, F., and Baldini, L.: Raindrop size distribution: Fitting performance of common theoretical models, Adv. Water Resour., 96, 290–305, https://doi.org/10.1016/j.advwatres.2016.07.010, 2016. a
Adirosi, E., Porcù, F., Montopoli, M., Baldini, L., Bracci, A., Capozzi, V., Annella, C., Budillon, G., Bucchignani, E., Zollo, A. L., Cazzuli, O., Camisani, G., Bechini, R., Cremonini, R., Antonini, A., Ortolani, A., Melani, S., Valisa, P., and Scapin, S.: Database of the Italian disdrometer network, Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, 2023. a
Andsager, K., Beard, K. V., and Laird, N. F.: Laboratory Measurements of Axis Ratios for Large Raindrops, J. Atmos. Sci., 56, 2673–2683, https://doi.org/10.1175/1520-0469(1999)056<2673:LMOARF>2.0.CO;2, 1999. a
Angulo-Martínez, M., Beguería, S., and Kyselý, J.: Use of disdrometer data to evaluate the relationship of rainfall kinetic energy and intensity (KE-I), Sci. Tot. Environ., 568, 83–94, https://doi.org/10.1016/j.scitotenv.2016.05.223, 2016. a
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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.
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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