Exploratory analysis of citizen observations of hourly precipitation over Scandinavia
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Published:2023-05-31
Issue:
Volume:20
Page:35-48
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ISSN:1992-0636
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Container-title:Advances in Science and Research
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language:en
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Short-container-title:Adv. Sci. Res.
Author:
Lussana CristianORCID, Baietti Emma, Båserud LineORCID, Nipen Thomas Nils, Seierstad Ivar Ambjørn
Abstract
Abstract. We present a comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national meteorological services, the latter used as reference values. The empirical distributions of the crowdsourced observations in the surroundings of reference stations are used to assess accuracy and precision of crowdsourced data. We found that reference values are typically within the distribution of the crowdsourced data. However, as the amount of precipitation increases, the spread of the crowdsourced distribution increases and the reference values are more and more frequently found towards the right tail of the distribution. These results indicate that accuracy and precision of crowdsourced data change as precipitation increases. We have studied the sensitivity of our results to the size of the neighbourhood chosen around the reference stations and we show that by aggregating the values over those neighbourhoods, crowdsourced data can be trusted in determining precipitation occurrence. We have assessed the variability of precipitation within small neighbourhoods (of radius 1, 3 and 5 km) and we provide estimates on the basis of the precipitation amounts. Our study quantifies the variability of hourly precipitation over small regions, of the size of the so-called “unresolved spatial scales” in limited area models, based on three years of data collected at several places in Scandinavia.
Publisher
Copernicus GmbH
Subject
Atmospheric Science,Pollution,Geophysics,Ecological Modeling
Reference35 articles.
1. Alerskans, E., Lussana, C., Nipen, T. N., and Seierstad, I. A.: Optimizing
Spatial Quality Control for a Dense Network of Meteorological Stations, J. Atmos. Oceanic Tech., 39, 973–984, https://doi.org/10.1175/JTECH-D-21-0184.1, 2022. a 2. Bárdossy, A., Seidel, J., and El Hachem, A.: The use of personal weather
station observations to improve precipitation estimation and interpolation,
Hydrol. Earth Syst. Sci., 25, 583–601, https://doi.org/10.5194/hess-25-583-2021, 2021. a 3. Båserud, L., Lussana, C., Nipen, T. N., Seierstad, I. A., Oram, L., and
Aspelien, T.: TITAN automatic spatial quality control of meteorological
in-situ observations, Adv. Sci. Res., 17, 153–163, https://doi.org/10.5194/asr-17-153-2020, 2020. a 4. Colli, M., Lanza, L., and Chan, P.: Co-located tipping-bucket and optical drop counter RI measurements and a simulated correction algorithm, Atmos. Res., 119, 3–12, https://doi.org/10.1016/j.atmosres.2011.07.018, 2013. a 5. de Vos, L., Leijnse, H., Overeem, A., and Uijlenhoet, R.: The potential of
urban rainfall monitoring with crowdsourced automatic weather stations in
Amsterdam, Hydrol. Earth Syst. Sci., 21, 765–777, https://doi.org/10.5194/hess-21-765-2017, 2017. a
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