This study considers experience in use of crowdsourced meteorological observations from the world’s biggest network of citizen weather stations (CWSs), Netatmo, for urban climate research and applied monitoring services on the example of Moscow megacity. Crowdsourcing paradigm is an emerging alternative to the development of expensive urban meteorological networks. We have experimentally evaluated the uncertainties of the Netatmo temperature observations and regard them as being acceptable when the stations are shadowed from the sun. In order to filter out the misrepresentative observations, a quality-control algorithm has been developed. Within more than 1500 CWSs in the Moscow region, only about 25% meet this quality control, which is still one order of magnitude higher than the number of official Roshydromet weather stations in the study area. Such amount of data opens new opportunities for spatially-resolving urban climate studies and for applied services. As an example of the latter, we present a prototype of a web-mapping application for a near-real-time temperature monitoring system in Moscow. The application’s backend includes automatic services for downloading of observations from Netatmo and official Roshydromet networks, as well as for database maintaining. The processed data are visualized interactively in a web browser. The application is available on the Internet at http://carto.geogr.msu.ru/mosclim/. It will be further developed to include a real-time thermal comfort assessment based on the contemporary PET and UTCI biometeorological indices, a visualization of the interpolated fields, and other improvements.
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