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

Abstract

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.

Impact of Urban Canopy Parameters on a Megacity’s Modelled Thermal Environment

“…The city has experienced an increasing UHI intensity trend over the last decades [40], with a present-day annual-mean UHI intensity of 2 • peaking to more than 10 • C during calm and clear nights [41,42]. Its relevance as a test-bed for model testing and verification is shown by previous studies using COSMO model with the TERRA_URB scheme [6,39,43].…”

“…TERRA_URB was originally implemented in the COSMO-CLM version 5.0_clm9 as a separate branch of the model development. This version was successfully used for urban climate simulations in global cities [20,21,24,39,43,[46][47][48][49]. Recently, the TERRA_URB scheme was implemented to a newer version of COSMO (5.05urb, used in the current study) as part of the AEVUS (Analysis and evaluation of the TERRA_URB scheme) priority task of the COSMO consortium [6,50].…”

“…The annual-mean AHF is defined based on a Stewart and Kennedy (2017) [69], who suggest an annual mean value of 52 W/m 2 within the administrative borders of Moscow (excluding the "New Moscow" area). To obtain a detailed spatial pattern on a 1 km grid, this value was "weighted" by the product of H and R. Despite the evident simplicity, this approach proved itself in the previous modelling studies for Moscow [6,39,43].…”

Re-introduction of vivax malaria in a temperate area (Moscow region, Russia): a geographic investigation

“…On average, the centre of Moscow megacity is 2 ℃ warmer than surrounding rural areas [27], however, the urban-rural temperature difference could reach up to 14 ℃ [28]. According to the recent observational and modelling studies, the urban-induced temperature anomaly covers the whole city and its nearest suburbs, beyond its administrative limits [29,30]. Moreover, there has been an intensification of the UHI of Moscow, which is caused by urban growth and development and is especially pronounced in summer [27,31].…”

Spatiotemporal analysis of the land surface temperature distribution over the territory of Novosibirsk city based on Landsat data

“…Land surface temperature retrieved from Landsat data is used extensively for many applications including observation of urban heat islands, locating persistent anomalies, and monitoring urban sprawl. Examples include studies of urban heat islands of cities located in moderate climate zones such as Moscow and Nizhny Novgorod, as well as largest cities located above the Polar Circle, the cities of Murmansk, Norilsk, Vorkuta, Apatity, Salekhard, Noviy Urengoy, Nadym [3][4][5][6][7]. Detection of changes of the urban landscape of Krasnoyarsk was performed using the land surface temperature data retrieved from thermal infrared satellite imagery [8].…”