Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 13, issue 6
Articles | Volume 13, issue 6
https://doi.org/10.5194/amt-13-2979-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-2979-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 6
Research article
 | 
05 Jun 2020
Research article |  | 05 Jun 2020

An improved post-processing technique for automatic precipitation gauge time series

Amber Ross, Craig D. Smith, and Alan Barr

Viewed

Total article views: 2,427 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,566 765 96 2,427 89 110
  • HTML: 1,566
  • PDF: 765
  • XML: 96
  • Total: 2,427
  • BibTeX: 89
  • EndNote: 110
Views and downloads (calculated since 20 Dec 2019)
Cumulative views and downloads (calculated since 20 Dec 2019)

Viewed (geographical distribution)

Total article views: 2,427 (including HTML, PDF, and XML) Thereof 2,323 with geography defined and 104 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 26 Jul 2025
Download
Short summary
The raw data derived from most automated accumulating precipitation gauges often suffer from non-precipitation-related fluctuations in the measurement of the gauge bucket weights from which the precipitation amount is determined. This noise can be caused by electrical interference, mechanical noise, and evaporation. This paper presents an automated filtering technique that builds on the principle of iteratively balancing noise to produce a clean precipitation time series.
Read more
Share