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This article addresses modeling of the atmospheric boundary layer of the city of Almaty (Kazakhstan) in stagnant, environmentally unfavorable conditions using WRF Model. The city is located on the northern slope of Trans-Ili Alatau, where the rate of recurrence of calm and low-wind (1–2 m/sec) days reaches about 80%. All simulations were made for a period from 28.11.2016 to 05.12.2016, covering main synoptic situations of the stagnant atmosphere: the extent of Asian anticyclone, higher and lower pressure gradient fields. The model integrated three nested domains with grid sizes 9, 3 and 1 km, respectively. The initial boundary conditions were formed based on ERA5-reanalysis. Subject to the WRF model requirements, the land-use map with a standard USGS set (24 categories) was developed, to which 3 categories of the urban areas were added. The most relevant configuration of parameterization methods was selected: short-wave and long-wave radiation (Mlawer), surface layer (Monin-Obukhov similarity theory), urban area (BEP), boundary layer (Bougeault-Lacarrere), turbulence (Smagorinsky). The article demonstrates that the WRF model adequately reflects fundamental urban atmosphere patterns in the most unfavorable anticyclone periods of the autumn-winter season. It was established that the accuracy of estimates decreases with the transition to weak cyclonic activity. Based on the simulation results and remote sensing data, the territory in question is divided into four climatic zones to which a comparative method was applied; however for a detailed correlative analysis a denser network of meteorological stations is required. Calculations showed that the wind along the Ili river valley prevails in the northern part, regularly changing its western direction to eastern. Near the mountain area mountain-valley wind circulation prevails. The blocking inversion layer has a strong impact. The urban heat islands strongly depend on wind conditions. For example, a nocturnal heat island is cooled by the cold wind flow from the mountains.

Recently, NOAA developed the AVHRR-based Vegetation Condition Index (VCI) for drought monitoring. This index was used for estimating pasture and crop productivity in Kazakhstan. The results of VCI-derived vegetation conditions were compared with vegetation density, biomass and reflectance measured in different climatic and ecological zones with elevation from 2001 to 700 m and a large range of the NDVI variation (over space and season) from 0.05 to 0.47. An estimation error of AVHRR-derived vegetation density was less than 16 per cent. First time it was shown that the VCI-derived vegetation condition data can be effectively used for quantitative assessments of both vegetation state and productivity (density and biomass:) over large areas.

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