Simultaneous assessment of the summer urban heat island in Moscow megacity based on in situ observations, thermal satellite images and mesoscale modeling

This study compares three popular approaches to quantify the urban heat island (UHI) effect in Moscow megacity in a summer season (June-August 2015). The first approach uses the measurements of the near-surface air temperature obtained from weather stations, the second is based on remote sensing fro...

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Bibliographic Details
Published in:GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY
Main Authors: Mikhail Varentsov I., Mikhail Grishchenko Y., Hendrik Wouters
Other Authors: The major research (supercomputer modeling, processing of the satellite images, data management and analysis) performed by M.I. Varentsov and M.Yu. Grishchenko was funded by the grant program of Russian Science Foundation (project No. 17-77-20070 “An initial assessment and projection of the bioclimatic comfort in Russian cities in XXI century against the context of climate change”). The work of Hendrik Wouters (discussing and interpreting the results, participation in writing the paper) was funded by the European Research Council (ERC) under Grant Agreement No. 715254 (DRY–2–DRY). The research was carried out using the equipment of the shared research facilities of HPC computing resources at Lomonosov Moscow State University. The authors are grateful to the administration and stuff of the Federal State Budgetary Institution “Central Administration of Hydrological and Environmental Monitoring” and to the administration and stuff of the Вudgetary Environmental Protection Institution “Mosecomonitoring” for providing the data of meteorological observations used in the study.
Format: Article in Journal/Newspaper
Language:English
Published: Russian Geographical Society 2019
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Online Access:https://ges.rgo.ru/jour/article/view/903
https://doi.org/10.24057/2071-9388-2019-10
Description
Summary:This study compares three popular approaches to quantify the urban heat island (UHI) effect in Moscow megacity in a summer season (June-August 2015). The first approach uses the measurements of the near-surface air temperature obtained from weather stations, the second is based on remote sensing from thermal imagery of MODIS satellites, and the third is based on the numerical simulations with the mesoscale atmospheric model COSMO-CLM coupled with the urban canopy scheme TERRA_URB. The first approach allows studying the canopy-layer UHI (CLUHI, or anomaly of a near- surface air temperature), while the second allows studying the surface UHI (SUHI, or anomaly of a land surface temperature), and both types of the UHI could be simulated by the atmospheric model. These approaches were compared in the daytime, evening and nighttime conditions. The results of the study highlight a substantial difference between the SUHI and CLUHI in terms of the diurnal variation and spatial structure. The strongest differences are found at the daytime, at which the SUHI reaches the maximal intensity (up to 10°С) whereas the CLUHI reaches the minimum intensity (1.5°С). However, there is a stronger consistency between CLUHU and SUHI at night, when their intensities converge to 5–6°С. In addition, the nighttime CLUHI and SUHI have similar monocentric spatial structure with a temperature maximum in the city center. The presented findings should be taken into account when interpreting and comparing the results of UHI studies, based on the different approaches. The mesoscale model reproduces the CLUHI-SUHI relationships and provides good agreement with in situ observations on the CLUHI spatiotemporal variations (with near-zero biases for daytime and nighttime CLUHI intensity and correlation coefficients more than 0.8 for CLUHI spatial patterns). However, the agreement of the simulated SUHI with the remote sensing data is lower than agreement of the simulated CLUHI with in situ measurements. Specifically, the model tends to overestimate the daytime SUHI intensity. These results indicate a need for further in-depth investigation of the model behavior and SUHI–CLUHI relationships in general.