Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-9131
Main Title: Development and Application of a Statistically-Based Quality Control for Crowdsourced Air Temperature Data
Author(s): Napoly, Adrien
Grassmann, Tom
Meier, Fred
Fenner, Daniel
Type: Article
Is Supplemented By: 10.14279/depositonce-6740.3
Language Code: en
Abstract: In urban areas, dense atmospheric observational networks with high-quality data are still a challenge due to high costs for installation and maintenance over time. Citizen weather stations (CWS) could be one answer to that issue. Since more and more owners of CWS share their measurement data publicly, crowdsourcing, i.e., the automated collection of large amounts of data from an undefined crowd of citizens, opens new pathways for atmospheric research. However, the most critical issue is found to be the quality of data from such networks. In this study, a statistically-based quality control (QC) is developed to identify suspicious air temperature (T) measurements from crowdsourced data sets. The newly developed QC exploits the combined knowledge of the dense network of CWS to statistically identify implausible measurements, independent of external reference data. The evaluation of the QC is performed using data from Netatmo CWS in Toulouse, France, and Berlin, Germany, over a 1-year period (July 2016 to June 2017), comparing the quality-controlled data with data from two networks of reference stations. The new QC efficiently identifies erroneous data due to solar exposition and siting issues, which are common error sources of CWS. Estimation of T is improved when averaging data from a group of stations within a restricted area rather than relying on data of individual CWS. However, a positive deviation in CWS data compared to reference data is identified, particularly for daily minimum T. To illustrate the transferability of the newly developed QC and the applicability of CWS data, a mapping of T is performed over the city of Paris, France, where spatial density of CWS is especially high.
URI: https://depositonce.tu-berlin.de/handle/11303/10142
http://dx.doi.org/10.14279/depositonce-9131
Issue Date: 29-Aug-2018
Date Available: 18-Oct-2019
DDC Class: 550 Geowissenschaften
Subject(s): urban climate
crowdsourcing
citizen weather stations
air temperature
data quality
quality control
Sponsor/Funder: DFG, 322579844, Hitzewellen in Berlin, Deutschland - Stadtklimamodifkationen
BMBF, 01LP1602A, Verbundprojekt Stadtklima: Evaluierung von Stadtklimamodellen (Modul B), 3DO Teilprojekt 1: Dreidimensionales Monitoring atmosphärischer Prozesse in Berlin
License: https://creativecommons.org/licenses/by/4.0/
Journal Title: Frontiers in Earth Science
Publisher: Frontiers Media S.A.
Publisher Place: Lausanne
Volume: 6
Article Number: 118
Publisher DOI: 10.3389/feart.2018.00118
EISSN: 2296-6463
Appears in Collections:FG Polymertechnik und Polymerphysik » Publications



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