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This study presents the results of numerical modeling of the urban heat island (UHI) of Almaty using the Weather Research and Forecasting (WRF) model adapted to local climate zones (LCZ). The simulations were performed for a period characterized by pronounced anticyclonic conditions and, consequently, unfavorable atmospheric ventilation.To assess model performance, verification was carried out using data from ground-based meteorological stations and satellite observations. The results demonstrate that WRF adequately reproduces the diurnal temperature variation and weak wind regime within the urban agglomeration. The model successfully simulated the dynamics of inversion layers and local circulations, which play a key role in the development of stagnation conditions.The UHI was analyzed using the “virtual rural landscape” approach, in which the thermal field was calculated as the difference between scenarios with and without urban development. The modeling results show that the maximum UHI intensity occurs under nighttime conditions in the flat northwestern part of the city. Daytime UHI is characterized by lower intensity but a larger spatial extent compared to nighttime conditions. This pattern is explained by nocturnal katabatic flows of cold air from the mountains in the southern part of the city, which reduce the UHI intensity.A joint analysis of the UHI and wind fields at different times indicates that wind speeds exceeding 2 m/s lead to the transport of thermal pollution. The configuration of the heat island reveals that at night, katabatic flows displace warm air from the southern part of the city, while in the northern part it is captured by a zonal wind that bypasses the mountain range and blows in a northeasterly direction. During daytime, heat transport occurs toward the southeast, resulting in the advection of heat emitted by surrounding settlements into the urban area and toward the mountainous regions.The performed simulations demonstrate that the formation and evolution of the urban heat island in Almaty strongly depend on the time of day and the wind regime. The WRF model has proven to be an effective tool for analyzing urban microclimatic conditions and can be used in the development of adaptation strategies and air quality management, taking into account regional and local meteorological conditions.