Modeling of the Calm Situations in the Atmosphere of Almaty

Abstract

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.

Investigating Stagnant Air Conditions in Almaty: A WRF Modeling Approach

“…This study is a continuation of previous work [23][24][25] on modeling complex atmospheric processes occurring in the air basin of the city of Almaty, Kazakhstan (43°15′ N 76°54′ E). Almaty is a major urban center with a population exceeding 2 million people.…”

“…Based on previous work [23,25], in this study, the WRF model of version 4.3 was used, for which three nested domains, D1, D2 and D3, were established in the Lambert conformal conic projection. The domains have grid resolutions of 9 km, 3 km, and 1 km, respectively.…”

“…The following microphysical process parameterization methods adopted from previous works [25] were maintained: WSM6 (WRF-Single-Moment-6-Class Microphysics Scheme) for cloud microphysics parameterization [42]; RRTMG (Rapid Radiative Transfer Model for General Circulation Models) for parameterizing shortwave and longwave radiation [43]; MOST for parameterization of the surface layer of agricultural areas according to the Monin-Obukhov similarity theory [44]; BEP (Building Environment Parameterization) for urban areas [39]; BouLac for parameterization of the Bougeault-Lacarrère planetary boundary layer [45]; KF for Kain-Fritsch convective parameterization scheme [46]; 2D Smagorinsky for parameterization of turbulence (horizontal turbulent diffusion) [35].…”

“…Almaty's unique location in the foothills presents a fascinating case study, potentially influencing UHI development patterns. Building on previous research [25], this study aims to compare results obtained from space-based sensing data with a focus on analyzing the dynamic processes that govern UHI formation in Almaty.…”

The Issue of Using Ordinal Quantities to Estimate the Vulnerability of Seabirds to Oil Spills

“…To correctly assess seabirds' vulnerability to oil, it is necessary to develop models based on metric values on a ratio scale. This could include different approaches, for example, (1) the use of species biodiversity [3,53], while taking into account their abundance (more detail see in [30]); (2) parameters assessment based on expert assessments which provides results on ratio scale [38]; (3) the use of several anthropogenic factors strictly on a ratio scale with calculation of vulnerability coefficients based on them [32].…”