Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 20
Articles | Volume 28, issue 20
https://doi.org/10.5194/hess-28-4715-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-4715-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 20
Technical note
 | 
29 Oct 2024
Technical note |  | 29 Oct 2024

Technical note: A guide to using three open-source quality control algorithms for rainfall data from personal weather stations

Abbas El Hachem, Jochen Seidel, Tess O'Hara, Roberto Villalobos Herrera, Aart Overeem, Remko Uijlenhoet, András Bárdossy, and Lotte de Vos

Viewed

Total article views: 1,646 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,238 349 59 1,646 54 45
  • HTML: 1,238
  • PDF: 349
  • XML: 59
  • Total: 1,646
  • BibTeX: 54
  • EndNote: 45
Views and downloads (calculated since 31 Aug 2023)
Cumulative views and downloads (calculated since 31 Aug 2023)

Viewed (geographical distribution)

Total article views: 1,646 (including HTML, PDF, and XML) Thereof 1,526 with geography defined and 120 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Dec 2024
Download
Short summary
This study presents an overview of open-source quality control (QC) algorithms for rainfall data from personal weather stations (PWSs). The methodology and usability along technical and operational guidelines for using every QC algorithm are presented. All three QC algorithms are available for users to explore in the OpenSense sandbox. They were applied in a case study using PWS data from the Amsterdam region in the Netherlands.  The results highlight the necessity for data quality control.
Read more