Assessing the potential and application of crowdsourced urban wind data

Arjan M Droste,Daniel Fenner,Bert G Heusinkveld,Gert‐Jan Steeneveld

doi:10.1002/qj.3811

Abstract

AbstractThe use of crowdsourcing – obtaining large quantities of data through the Internet – has been of great value in urban meteorology. Crowdsourcing has been used to obtain urban air temperature, air pressure, and precipitation data from sources such as mobile phones or personal weather stations (PWSs), but so far wind data have not been researched. Urban wind behaviour is highly variable and challenging to measure, since observations strongly depend on the location and instrumental set‐up. Crowdsourcing can provide a dense network of wind observations and may give insight into the spatial pattern of urban wind. In this study, we evaluate the skill of the popular “Netatmo” PWS anemometer against a reference for a rural and an urban site. Subsequently, we use crowdsourced wind speed observations from 60 PWSs in Amsterdam, the Netherlands, to analyse wind speed distributions of different Local Climate Zones (LCZs). The Netatmo PWS anemometer appears to systematically underestimate the wind speed, and episodes with rain or high relative humidity degrade the measurement quality. Therefore, we developed a quality assurance (QA) protocol to correct PWS measurements for these errors. The applied QA protocol strongly improves PWS data to a point where they can be used to infer the probability density distribution of wind speed of a city or neighbourhood. This density distribution consists of a combination of two Weibull distributions, rather than the typical single Weibull distribution used for rural wind speed observations. The limited capability of the Netatmo PWS anemometer to measure near‐zero wind speed causes the QA protocol to perform poorly for periods with very low wind speeds. However, results for a year‐long wind speed climatology of the wind speed are satisfactory, as well as for a shorter period with higher wind speeds.

Highlights

IntroductionWith ongoing climate change and urbanisation, the need for accurate urban weather information has never been more urgent
The urban climate is a subject of increasing interest in science and society
Data were filtered for rain and humidity (QA step C), but not for low wind speeds (QA step B), since the Amsterdam Atmospheric Meteorological Supersite (AAMS) sonic anemometer is well capable of measuring very low wind speeds

Summary

Introduction

With ongoing climate change and urbanisation, the need for accurate urban weather information has never been more urgent. The urban climate is of particular importance to human thermal comfort and air quality, and their associated health risks (Moonen et al, 2012). The lack of urban weather observations is a major challenge in characterising the urban climate. Several cities have dedicated observational networks, for example, Birmingham (England, Warren et al, 2016), Berlin (Germany; Fenner et al, 2014), Novi Sad (Serbia; Savicet al., 2019), Ghent (Belgium; Caluwaerts et al, 2020) or Amsterdam (the Netherlands; Ronda et al, 2017), but the majority of cities across the world lack such a detailed network. Though obstructions characterise the urban climate, their heterogeneity complicates taking representative measurements of the city as a whole. Vast differences can occur, especially in wind speed, and in temperature and, to a lesser extent, humidity (Heusinkveld et al, 2014)

Objectives

Results

Discussion

Conclusion