Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 8
Articles | Volume 19, issue 8
https://doi.org/10.5194/gmd-19-3213-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-3213-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 8
Model description paper
 | 
23 Apr 2026
Model description paper |  | 23 Apr 2026

MeteoSaver v1.0: a machine-learning based software for the transcription of historical weather data

Derrick Muheki, Bas Vercruysse, Krishna Kumar Thirukokaranam Chandrasekar, Christophe Verbruggen, Julie M. Birkholz, Koen Hufkens, Hans Verbeeck, Pascal Boeckx, Seppe Lampe, Ed Hawkins, Peter Thorne, Dominique Kankonde Ntumba, Olivier Kapalay Moulasa, and Wim Thiery

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Latest update: 23 Apr 2026
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Short summary
Archives worldwide host vast records of observed weather data crucial for understanding climate variability. However, most of these records are still in paper form, limiting their use. To address this, we developed MeteoSaver, an open-source tool, to transcribe these records to machine-readable format. Applied to ten handwritten temperature sheets, it achieved a median accuracy of 74 %. This tool offers a promising solution to preserve records from archives and unlock historical weather insights.
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