CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications

In recent years, the collection and utilisation of crowdsourced data has gained attention in atmospheric sciences and citizen weather stations (CWS), i.e., privately-owned weather stations whose owners share their data publicly via the internet, have become increasingly popular. This is particularly...

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Autores principales:	Daniel Fenner, Benjamin Bechtel, Matthias Demuzere, Jonas Kittner, Fred Meier
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	crowdsourcing quality control citizen weather station private weather station urban climate Netatmo Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/fdc4e7cdd8d24223afc4246126835cf1
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spelling	oai:doaj.org-article:fdc4e7cdd8d24223afc4246126835cf12021-12-03T15:36:12ZCrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications2296-665X10.3389/fenvs.2021.720747https://doaj.org/article/fdc4e7cdd8d24223afc4246126835cf12021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fenvs.2021.720747/fullhttps://doaj.org/toc/2296-665XIn recent years, the collection and utilisation of crowdsourced data has gained attention in atmospheric sciences and citizen weather stations (CWS), i.e., privately-owned weather stations whose owners share their data publicly via the internet, have become increasingly popular. This is particularly the case for cities, where traditional measurement networks are sparse. Rigorous quality control (QC) of CWS data is essential prior to any application. In this study, we present the QC package “CrowdQC+,” which identifies and removes faulty air-temperature (ta) data from crowdsourced CWS data sets, i.e., data from several tens to thousands of CWS. The package is a further development of the existing package “CrowdQC.” While QC levels and functionalities of the predecessor are kept, CrowdQC+ extends it to increase QC performance, enhance applicability, and increase user-friendliness. Firstly, two new QC levels are introduced. The first implements a spatial QC that mainly addresses radiation errors, the second a temporal correction of the data regarding sensor-response time. Secondly, new functionalities aim at making the package more flexible to apply to data sets of different lengths and sizes, enabling also near-real time application. Thirdly, additional helper functions increase user-friendliness of the package. As its predecessor, CrowdQC+ does not require reference meteorological data. The performance of the new package is tested with two 1-year data sets of CWS data from hundreds of “Netatmo” CWS in the cities of Amsterdam, Netherlands, and Toulouse, France. Quality-controlled data are compared with data from networks of professionally-operated weather stations (PRWS). Results show that the new package effectively removes faulty data from both data sets, leading to lower deviations between CWS and PRWS compared to its predecessor. It is further shown that CrowdQC+ leads to robust results for CWS networks of different sizes/densities. Further development of the package could include testing the suitability of CrowdQC+ for other variables than ta, such as air pressure or specific humidity, testing it on data sets from other background climates such as tropical or desert cities, and to incorporate added filter functionalities for further improvement. Overall, CrowdQC+ could lead the way to utilise CWS data in world-wide urban climate applications.Daniel FennerDaniel FennerBenjamin BechtelMatthias DemuzereJonas KittnerFred MeierFrontiers Media S.A.articlecrowdsourcingquality controlcitizen weather stationprivate weather stationurban climateNetatmoEnvironmental sciencesGE1-350ENFrontiers in Environmental Science, Vol 9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	crowdsourcing quality control citizen weather station private weather station urban climate Netatmo Environmental sciences GE1-350
spellingShingle	crowdsourcing quality control citizen weather station private weather station urban climate Netatmo Environmental sciences GE1-350 Daniel Fenner Daniel Fenner Benjamin Bechtel Matthias Demuzere Jonas Kittner Fred Meier CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications
description	In recent years, the collection and utilisation of crowdsourced data has gained attention in atmospheric sciences and citizen weather stations (CWS), i.e., privately-owned weather stations whose owners share their data publicly via the internet, have become increasingly popular. This is particularly the case for cities, where traditional measurement networks are sparse. Rigorous quality control (QC) of CWS data is essential prior to any application. In this study, we present the QC package “CrowdQC+,” which identifies and removes faulty air-temperature (ta) data from crowdsourced CWS data sets, i.e., data from several tens to thousands of CWS. The package is a further development of the existing package “CrowdQC.” While QC levels and functionalities of the predecessor are kept, CrowdQC+ extends it to increase QC performance, enhance applicability, and increase user-friendliness. Firstly, two new QC levels are introduced. The first implements a spatial QC that mainly addresses radiation errors, the second a temporal correction of the data regarding sensor-response time. Secondly, new functionalities aim at making the package more flexible to apply to data sets of different lengths and sizes, enabling also near-real time application. Thirdly, additional helper functions increase user-friendliness of the package. As its predecessor, CrowdQC+ does not require reference meteorological data. The performance of the new package is tested with two 1-year data sets of CWS data from hundreds of “Netatmo” CWS in the cities of Amsterdam, Netherlands, and Toulouse, France. Quality-controlled data are compared with data from networks of professionally-operated weather stations (PRWS). Results show that the new package effectively removes faulty data from both data sets, leading to lower deviations between CWS and PRWS compared to its predecessor. It is further shown that CrowdQC+ leads to robust results for CWS networks of different sizes/densities. Further development of the package could include testing the suitability of CrowdQC+ for other variables than ta, such as air pressure or specific humidity, testing it on data sets from other background climates such as tropical or desert cities, and to incorporate added filter functionalities for further improvement. Overall, CrowdQC+ could lead the way to utilise CWS data in world-wide urban climate applications.
format	article
author	Daniel Fenner Daniel Fenner Benjamin Bechtel Matthias Demuzere Jonas Kittner Fred Meier
author_facet	Daniel Fenner Daniel Fenner Benjamin Bechtel Matthias Demuzere Jonas Kittner Fred Meier
author_sort	Daniel Fenner
title	CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications
title_short	CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications
title_full	CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications
title_fullStr	CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications
title_full_unstemmed	CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications
title_sort	crowdqc+—a quality-control for crowdsourced air-temperature observations enabling world-wide urban climate applications
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/fdc4e7cdd8d24223afc4246126835cf1
work_keys_str_mv	AT danielfenner crowdqcaqualitycontrolforcrowdsourcedairtemperatureobservationsenablingworldwideurbanclimateapplications AT danielfenner crowdqcaqualitycontrolforcrowdsourcedairtemperatureobservationsenablingworldwideurbanclimateapplications AT benjaminbechtel crowdqcaqualitycontrolforcrowdsourcedairtemperatureobservationsenablingworldwideurbanclimateapplications AT matthiasdemuzere crowdqcaqualitycontrolforcrowdsourcedairtemperatureobservationsenablingworldwideurbanclimateapplications AT jonaskittner crowdqcaqualitycontrolforcrowdsourcedairtemperatureobservationsenablingworldwideurbanclimateapplications AT fredmeier crowdqcaqualitycontrolforcrowdsourcedairtemperatureobservationsenablingworldwideurbanclimateapplications
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CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications

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