Future climate change and its impact on drought is critical for Uzbekistan, located in Central Asia, the world’s largest arid zone. This study examines the evolving intensity of climate change and drought events using multi-model ensembles (MMEs) derived from the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5 and CMIP6) simulated under the Representative Concentration Pathway and Shared Socioeconomic Pathway (RCP and SSP) scenarios. The projections show different rates of increase in temperature and precipitation under the RCPs and SSPs. Projected temperature increases are expected to reach up to 2–2.5 °C under SSP1-2.6, SSP2-4.5, and SSP3-7.0, by mid-century. By 2080–2099, an increase is projected of 2–3 °C in monthly mean temperatures throughout the year (SSP1-2.6), and a more pronounced increase in summer up to 3–4 °C (SSP2-4.5) and 4–6 °C (SSP3-7.0), with a marked contrast in conditions between the mountainous and desert regions of Uzbekistan. Regional changes in precipitation over the study periods show relatively little variability, except for FD, where notable trends are found. Under SSP1-2.6 and SSP2-4.5, the increase in precipitation is relatively modest, whereas the changes in SSP3-7.0 are more substantial, with some regions experiencing variations of up to 10–20 mm per period. The Standardized Precipitation Evapotranspiration Index (SPEI), calculated based on the projected temperature and precipitation, provides an estimate of future drought trends. Our results show increasing aridity under all scenarios by mid-century, with longer-term projections indicating stabilization around different SPEI values by 2100: RCP2.6 and SSP1-1.9 stabilize around −1.0; RCP4.5, RCP6.0, SSP2-4.5, and SSP3-7.0 stabilize around −1.5; while RCP8.5 and SSP5-8.5 scenarios project values of −2 or less by 2100. Notable differences in the SPEI index are found between lowland and foothill regions. In view of Uzbekistan’s heavy reliance on agriculture and irrigation, which are the sectors that are expected to be mostly affected by climate change, our study provides a scientific basis for informed policy decision-making. This includes various aspects such as planning and management water resources, as well as the broader socioeconomic development of the country.

Climate change and shrinking of the Aral Sea have significantly affected the region’s temperature variations. Observed interannual changes in Uzbekistan’s air temperature compared to the duration of synoptic weather types (SWT) in Middle Asia were analyzed. Nonparametric Mann–Kendall statistical test and climate trends coefficients were used to identify trend characteristics of observed temperature from 1961–2016 to the baseline period of 1961–1990. The results showed increasing temperature trends average to 1 °C in warm and cold half years over Uzbekistan. The 1991–2016 decadal temperature trend ranged from 0.25 °C/decade in the northwest to 0.52 °C/decade in the center, especially pronounced in the oasis and Aral Sea zones. There were also significant changes in the structure of regional SWT. The main difference in the structure of SWT in Middle Asia relative to the baseline period was expressed in a decrease of cold mass invasion duration from 113.4 to 76.1 days and an increase in low-gradient baric field duration from 65.8 to 134.6 days. The process of anthropogenic warming, which began in Uzbekistan in the 1960s of the twentieth century, has accelerated from the mid-1970s with a higher mean annual air temperature than the baseline period’s climate normals (1961–1990) and is associated with changes in the regional SWT over Middle Asia.

The results of investigations of the foehn influence on the air pollution level are given as the Colchian Lowland (the southwestern Caucasus) and the Akhangaran valley (Western Tien Shan) case study. The calculations of distribution fields of the NOx concentrations in the Akhangaran valley are considered. It is shown that foehn processes influence substantially the atmosphere pollution level in the mountain countries. Their due regard, when studying the atmosphere pollution, will allow significant increasing of the accuracy of ecological estimates of the natural environmental state. A conclusion is made that this meteorological event ought to be referred to regional dangerous meteorological conditions that promote intensification of the local atmosphere pollution.

Taking into account bioclimatic conditions of a territory is one of the necessary elements for the tourism industry. In order to assess the bioclimatic conditions of selected settlements of Uzbekistan, such as Samarkand, Dagbit, Tashkent and the Chimgan mountain recreation zone, a thermohygrometric coefficient of air aridity is used. It is shown that the coefficient has a good response to changes in temperature and humidity and a clearly defined tendency in its annual and daily course. Based on the statistical processing of the data series of standard observations of air temperature and dew point at Samarkand, Dagbit, Tashkent Observatory and Chimgan meteorological stations for the period of 2009-2018 the spatial-temporal features of distribution of thermal comfort conditions are revealed.

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Reliable projections of temperature and precipitation underpin water and agricultural planning in arid Central Asia, yet most Coupled Model Intercomparison Project Phase 6 (CMIP6) assessments for the region are domain-averaged and do not resolve the contrasting physical-geographical zones of Uzbekistan. This study assesses projected changes in both variables over the national territory using observation-constrained CMIP6 ensembles under three Shared Socioeconomic Pathway (SSP) scenarios. Historical simulations from 51 models were interpolated to 34 meteorological stations spanning 64 to 2,127 m above sea level (a.s.l.) and ranked against observations for 1991–2014 on a composite score built from absolute bias, error and anomaly correlation. Models ranking in the top ten and offering complete scenario coverage were retained, giving a four-model temperature ensemble and a three-model precipitation ensemble. Bias correction specific to each model, station and month was derived over the baseline and held fixed to 2100. Both ensembles outperform every individual member, with the annual anomaly root mean square error (RMSE) falling to 0.54 °C for temperature and to 24.2% for precipitation. Warming is large, spatially near-uniform and strongly scenario-dependent, reaching +1.34, +2.53 and +4.91 °C for 2071–2100 under the three pathways, with a range across stations of only 0.31 °C under the highest. Precipitation increases by +2.7, +7.2 and +9.5%, but lies well below the 24.2% validation error and the scenario distributions overlap in every decade, so they constrain the direction of the change rather than its magnitude. The increase falls almost entirely in winter and spring and accrues mainly in the mountain zone, and is no relief of water stress in the irrigated lowlands.CMIP6; SSP Scenarios; Multi-Model Ensemble; Bias Correction; Precipitation Anomaly; Temperature Anomaly; Central Asia; Uzbekistan