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Can the crowdsourcing data paradigm take atmospheric science to a new level? A case study of the urban heat island of London quantified using Netatmo weather stations
Author(s) -
Chapman Lee,
Bell Cassandra,
Bell Simon
Publication year - 2017
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.4940
Subject(s) - crowdsourcing , environmental science , range (aeronautics) , citizen science , meteorology , atmospheric research , point (geometry) , climatology , computer science , data science , geography , engineering , world wide web , geology , botany , biology , aerospace engineering , geometry , mathematics
Crowdsourcing techniques are frequently used across science to supplement traditional means of data collection. Although atmospheric science has so far been slow to harness the technology, developments have now reached the point where the benefits of the approaches simply cannot be ignored: crowdsourcing has potentially far‐reaching consequences for the way in which measurements are collected and used in the discipline. To illustrate this point, this paper uses air temperature data from the prolific, low‐cost, Netatmo weather station to quantify the urban heat island of London over the summer of 2015. The results are broadly comparable with previous studies, and indeed standard observations (albeit with a warm bias, a likely consequence of non‐standard site exposure), showing a range of magnitudes of between 1 and 6 °C across the city depending on atmospheric stability. However, not all the results can be easily explained by physical processes and therefore highlight quality issues with crowdsourced data that need to be resolved. This paper aims to kickstart a step‐change in the use of crowdsourcing in urban meteorology by encouraging atmospheric scientists to more positively engage with the new generation of manufacturers producing mass market sensors.