Leveraging crowdsourced data for extreme heat monitoring

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dc.contributor.authorAzargoshasbi, Forood
dc.contributor.authorVahmani, Pouya
dc.contributor.authorMinet, Laura
dc.date.accessioned2026-03-05T17:18:54Z
dc.date.available2026-03-05T17:18:54Z
dc.date.copyright2025
dc.description.abstractThe combined effects of urban microclimate heterogeneity and climate change exacerbate the disproportionate impact of heatwaves on urban areas, a trend expected to intensify. Crowdsourcing is a promising tool to monitor temperatures at a high spatiotemporal scale, which is now deemed critical. However, quality control is essential before the use of such data. Traditional quality control methods often fail to capture short extreme weather events like heatwaves, as they frequently eliminate crucial observations from these intense, brief episodes. Here, a quality control methodology, tailored to short-term heatwaves built on existing quality control methods, is introduced and tested on crowdsourced monitoring networks for five North American cities and three heatwave episodes. This framework is centred around a systematic comparison with traditional weather stations. The results show that the designed procedure can effectively filter out false data points and corrupt stations whilst preserving observational data points capturing heatwaves. In the worst case, 24.7% of a heatwave episode's records are eliminated, compared to 75% using an existing detailed quality control method. We further show that crowdsourced monitoring could bring more insight into the spatiotemporal variability of temperature and living experiences during heatwaves compared to the sparse traditional weather station networks.
dc.description.reviewstatusReviewed
dc.description.scholarlevelFaculty
dc.description.sponsorshipThis work was supported by the Natural Sciences and Engineering Research Council of Canada, RGPIN-2023-04107.
dc.identifier.citationAzargoshasbi, F., Vahmani, P., & Minet, L. (2025). Leveraging crowdsourced data for extreme heat monitoring. International Journal of Climatology. https://doi.org/10.1002/joc.70050
dc.identifier.urihttps://doi.org/10.1002/joc.70050
dc.identifier.urihttps://hdl.handle.net/1828/23412
dc.language.isoen
dc.publisherInternational Journal of Climatology
dc.rightsCC BY-NC-ND 4.0en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectclustering
dc.subjectheat exposure
dc.subjectheatwaves
dc.subjectNorth America
dc.subjectquality control
dc.subjectInstitute for Integrated Energy Systems (IESVic)
dc.subject.departmentDepartment of Civil Engineering
dc.titleLeveraging crowdsourced data for extreme heat monitoring
dc.typeArticle

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