Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networks

<p>Rain gauge measurements are one of the primary techniques used to estimate a precipitation field, but they require careful quality control. This paper describes a modified RainGaugeQC system, which is applied to real-time quality control of rain gauge measurements made every 10 min. This sy...

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Main Authors: K. Ośródka, J. Szturc, A. Jurczyk, A. Kurcz
Format: Article
Language:English
Published: Copernicus Publications 2025-07-01
Series:Atmospheric Measurement Techniques
Online Access:https://amt.copernicus.org/articles/18/3229/2025/amt-18-3229-2025.pdf
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author K. Ośródka
J. Szturc
A. Jurczyk
A. Kurcz
author_facet K. Ośródka
J. Szturc
A. Jurczyk
A. Kurcz
author_sort K. Ośródka
collection DOAJ
description <p>Rain gauge measurements are one of the primary techniques used to estimate a precipitation field, but they require careful quality control. This paper describes a modified RainGaugeQC system, which is applied to real-time quality control of rain gauge measurements made every 10 min. This system works operationally at the national meteorological and hydrological service in Poland. The RainGaugeQC algorithms, which have been significantly modified, are described in detail. The modifications were made primarily to control data from non-professional measurement networks, which may be of lower quality than professional data, especially in the case of personal stations. Accordingly, the modifications went in the direction of performing more sophisticated data control, applying weather radar data, and taking into account various aspects of data quality, such as consistency analysis of data time series and bias detection. The effectiveness of the modified system was verified based on independent measurement data from manual rain gauges, which are considered one of the most accurate measurement instruments, although they mostly provide daily totals. In addition, an analysis of two case studies is presented. This highlights various issues involved in using non-professional data to generate multi-source estimates of the precipitation field.</p>
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issn 1867-1381
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publishDate 2025-07-01
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series Atmospheric Measurement Techniques
spelling doaj-art-224f11edf00e4edc971e9351c8129c082025-08-20T02:40:27ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482025-07-01183229324510.5194/amt-18-3229-2025Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networksK. Ośródka0J. Szturc1A. Jurczyk2A. Kurcz3Centre of the Weather Forecasting Service, Institute of Meteorology and Water Management – National Research Institute, ul. Podleśna 61, 01-673 Warsaw, PolandCentre of the Weather Forecasting Service, Institute of Meteorology and Water Management – National Research Institute, ul. Podleśna 61, 01-673 Warsaw, PolandCentre of the Weather Forecasting Service, Institute of Meteorology and Water Management – National Research Institute, ul. Podleśna 61, 01-673 Warsaw, PolandCentre of the Weather Forecasting Service, Institute of Meteorology and Water Management – National Research Institute, ul. Podleśna 61, 01-673 Warsaw, Poland<p>Rain gauge measurements are one of the primary techniques used to estimate a precipitation field, but they require careful quality control. This paper describes a modified RainGaugeQC system, which is applied to real-time quality control of rain gauge measurements made every 10 min. This system works operationally at the national meteorological and hydrological service in Poland. The RainGaugeQC algorithms, which have been significantly modified, are described in detail. The modifications were made primarily to control data from non-professional measurement networks, which may be of lower quality than professional data, especially in the case of personal stations. Accordingly, the modifications went in the direction of performing more sophisticated data control, applying weather radar data, and taking into account various aspects of data quality, such as consistency analysis of data time series and bias detection. The effectiveness of the modified system was verified based on independent measurement data from manual rain gauges, which are considered one of the most accurate measurement instruments, although they mostly provide daily totals. In addition, an analysis of two case studies is presented. This highlights various issues involved in using non-professional data to generate multi-source estimates of the precipitation field.</p>https://amt.copernicus.org/articles/18/3229/2025/amt-18-3229-2025.pdf
spellingShingle K. Ośródka
J. Szturc
A. Jurczyk
A. Kurcz
Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networks
Atmospheric Measurement Techniques
title Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networks
title_full Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networks
title_fullStr Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networks
title_full_unstemmed Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networks
title_short Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networks
title_sort adaptation of raingaugeqc algorithms for quality control of rain gauge data from professional and non professional measurement networks
url https://amt.copernicus.org/articles/18/3229/2025/amt-18-3229-2025.pdf
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AT jszturc adaptationofraingaugeqcalgorithmsforqualitycontrolofraingaugedatafromprofessionalandnonprofessionalmeasurementnetworks
AT ajurczyk adaptationofraingaugeqcalgorithmsforqualitycontrolofraingaugedatafromprofessionalandnonprofessionalmeasurementnetworks
AT akurcz adaptationofraingaugeqcalgorithmsforqualitycontrolofraingaugedatafromprofessionalandnonprofessionalmeasurementnetworks