Characteristics of the Moscow Heat Island and Quality of Its Simulation with the COSMO-Ru1-MSK Model Based on the Mosecomonitoring Observations

The temporal and spatial variations in surface air temperature in Moscow are analyzed based on multiyear (2008–2022) observations from the Mosecomonitoring network for the megacity environment quality monitoring. The authors propose to represent the urban heat island (UHI) as zones encircling the warmest territory in the center, highlighting the urban periphery and outskirts, near suburbs, a background area, and an urban cold island in the Losiny Ostrov Park. Zonal temperature reflects the internal structure of the UHI and its dynamics, which allows focusing on individual areas of the megalopolis when developing measures to preserve air quality. The annual mean UHI magnitude in the center of Moscow has increased by 0.5°C over the past 10 years and reached 2.5°C. Significant interannual, seasonal, and interdaily variability in the daily mean and nighttime UHI magnitude is demonstrated. The relevance of estimating an anthropogenic component of the UHI based on the values of the nocturnal heat anomaly is emphasized. It has been found that the average long-term nocturnal UHI magnitude is approximately 1°C greater than the traditionally considered daily mean value. Hourly observations from more than 60 Mosecomonitoring network stations for August 2022, together with the Roshydromet weather station data, are used to verify numerical simulations of surface air temperature and the UHI using the updated COSMO-Ru1-MSK configuration of the COSMO atmospheric model with 1-km grid spacing. A new technique is proposed to compare modeling results with observations in the heterogeneous urban environment. The model satisfactorily reproduces the spatial structure of the UHI and the temperature differences between the proposed zones, although the modelled temperature diurnal turn in the city slightly lag behind observations. The Mosecomonitoring network data are promising for the verification of numerical weather prediction models on the city scale for Moscow in further research.