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.

Urban climate comfort is an indicator of a set of parameters, such as temperature, humidity, and solar radiation for a person’s sensation of being favorable to being outdoors or indoors. In this study, an attempt to develop a technology of real-time prediction of thermal comfort conditions in urban landscape is described (based on the example of Moscow State University campus). For this, the authors used a RayMan model-based algorithm for calculating three most popular worldwide comfort indexes. In the scripting method, predictive data of the Canadian global model meteorological parameters are automatically transferred to the RayMan-model (with an implementation of the unique thermal and radiation properties of the Moscow State University campus landscape) by using an autoclicker software. For the convenience of perception of the information, the results of calculations are visualized on the basis of a free web mapping service. Thus, the main idea of the work is that any user with minimum expenditure of his time resource and without knowledge of the model’s work can launch the program and receive an individual forecast of comfort conditions for the next few hours in a visually understandable format. It is suggested that the developed methodology will be used for calculations on projected areas to identify the safest construction option. Such realtime forecasting will continue to be of particular importance for urban infrastructure.

<p>Wind speed modeling on microscale can be important not only for local authorities but also for citizens.  Due to the heterogeneity of urban development in the Moscow region, wind gusts geography and thermal comfort conditions at different points in the same territory will differ noticeably with the same meteorological parameters. Thus, it is necessary to study such parameters  at the microscale. Therefore, within the framework of this study, in order to inform the public about the negative impact of the weather, and further to minimize the consequences on the human body, an attempt was made to develop an operational system for predicting dangerous conditions  of wind gusts and  thermal comfort.</p><p>In order to collect climate statistics, climate data were calculated for comfort conditions for the MSU campus using the RayMan model. Wind gusts modeling was performed using ENVI-MET model.   Therefore, it is possible to analyze the changes in biometric conditions and wind speed in recent years and track trends in various locations.</p><p>Since the input parameters for the RayMan diagnostic model, which processes only text documents, serve as predictive data for the Canadian GEM global meteorological parameters in grib2 format, a program for converting files using Command.exe and Fortran-90 language allowed us to create an online module for predicting biometric indices (UTCI, PET and mPET).</p><p>For the convenience of perception of information, the results of calculations are visualized on the basis of Yandex maps.</p><p>Research was supported by the grant program of Russian Foundation of Basic Research (project no. 19-35-70009 mol_a_mos ). The work of Pavel Konstantinov, Elizaveta Nikolaeva and Sergey Bukin was supported by Russian Science Foundation (project no. 19-77-30012)</p>

Comfort indices are used to assess the harm to human health caused by unfavorable thermal conditions. All calculated indices are based on both meteorological and physiological parameters. An algorithm is used which is based on a model RayMan for calculating two of the most common thermal indexes: PET and UTCI, which are based on a balance of human energy or models of human heat fluxes. The purpose of this research is to develop a real-time system of calculating comfort indices based on data of a web service for monitoring weather conditions in Moscow and the Moscow region. The technology is based on the use of specialized libraries of the Python language (pyautogui, pywinauto) to interact with the keys of a keyboard and a mouse, because it is necessary to write paths to files and make keystrokes in the model. The result is presented in a visually understandable form with a spatial distribution of the thermal stress in the form of points with signed index values at the locations of weather stations throughout Moscow and the surrounding areas. A test of sensitivity of the RayMan model to changes in a sky view factor (SVF) is also carried out. It is shown that the PET index is more sensitive to changes in SVF than UTCI. An assessment is made of the summer frequency of occurrence of cases with unfavorable levels of the thermal stress (taking into account SVF) at stations of the Roshydromet network in Moscow and the Moscow region. It is shown that during the controversial summer of 2019, the points where strong and extreme heat stresses most often occurred are located within the territories of Domodedovo and Sheremetyevo airports.