Hydrometeorological monitoring using opportunistic sensing networks in the Amsterdam metropolitan area

Journal Article (2020)
Author(s)

L. W. de Vos (Wageningen University & Research)

A. M. Droste (Wageningen University & Research)

M. J. Zander (Wageningen University & Research)

Aart Overeem (Wageningen University & Research)

H. Leijnse (Royal Netherlands Meteorological Institute (KNMI))

Bert G. Heusinkveld (Wageningen University & Research)

Gert Jan Steeneveld (Wageningen University & Research)

R. Uijlenhoet (Wageningen University & Research)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1175/BAMS-D-19-0091.1
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Publication Year
2020
Language
English
Affiliation
External organisation
Issue number
2
Volume number
101
Pages (from-to)
E167-E185

Abstract

The ongoing urbanization and climate change urges further understanding and monitoring of weather in cities. Two case studies during a 17-day period over the Amsterdam metropolitan area, the Netherlands, are used to illustrate the potential and limitations of hydrometeorological monitoring using nontraditional and opportunistic sensors. We employ three types of opportunistic sensing networks to monitor six important environmental variables: 1) air temperature estimates from smartphone batteries and personal weather stations, 2) rainfall from commercial microwave links and personal weather stations, 3) solar radiation from smartphones, 4) wind speed from personal weather stations, 5) air pressure from smartphones and personal weather stations, and 6) humidity from personal weather stations. These observations are compared to dedicated, traditional observations where possible, although such networks are typically sparse in urban areas. First, we show that the passage of a front can be successfully monitored using data from several types of nontraditional sensors in a complementary fashion. Also, we demonstrate the added value of opportunistic measurements in quantifying the urban heat island (UHI) effect during a hot episode. The UHI can be clearly determined from personal weather stations, though UHI values tend to be high compared to records from a traditional network. Overall, this study illustrates the enormous potential for hydrometeorological monitoring in urban areas using nontraditional and opportunistic sensing networks.

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