Agrometeorological events that are dangerous for crops include droughts, dry winds, frosts, heavy rains, hail, strong winds, and dust storms. The most common and dangerous are droughts and dry winds.Drought is a natural phenomenon that is one of the most complex and least studied natural hazards, capable of causing irreparable damage to ecosystems with a wide impact on water resources, agricultural production, ecosystem functions, the environment, local and global economies. The article is a review that presents some of the most frequently and widely used drought indices and indicators in the last two decades, summarizes the results of atmospheric drought research using these indices, demonstrates the relationship between the occurrence of atmospheric drought in various regions of Central Asia and the characteristics of its severity depending on the types of large-scale atmospheric circulation. We compared meteorological and remote sensing indices and identified favorable indices for parameterization and monitoring of droughts. The papers presented in the review provide valuable scientific information and possible directions for further research on drought in Central Asia.

Drought is one of the main climate-induced risks threatening agricultural sustainability in semi-arid regions. Northern Kazakhstan, a key grain-producing region in Central Asia, exhibits increasing vulnerability to droughts due to climatic variability and reliance on rainfed agriculture. This study evaluates the informativeness of drought indices based on the response of agricultural vegetation to dry conditions using remote sensing-based vegetation indices across Northern Kazakhstan from 1990 to 2024. Ground-based meteorological indices—the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Hydrothermal Coefficient (HTC), and the Modified China-Z Index (MCZI)—and vegetation indices—the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), and the Vegetation Health Index (VHI)—were analyzed using data from 11 representative meteorological stations. For the first time in Kazakhstan, the MCZI was calculated, demonstrating high sensitivity to local climate variability and strong agreement with the VHI. The SPI, MCZI, and HTC showed strong seasonal correlations with vegetation indices, whereas the SPEI had a weak correlation, limiting its applicability. The highest correlations (r ≥ 0.82) between meteorological and vegetation indices were recorded in summer, while spring and autumn were influenced by phenological and temperature factors. Persistent drying trends in the southern and southwestern areas contrasted with moderate wetting in the north. The combined use of the SPI, MCZI, HTC, and VHI proved effective for monitoring droughts. The results provide a reproducible foundation for local drought assessment and early warning systems, supporting climate-resilient agricultural planning and sustainable land and water resource management. The results also offer actionable insights to enhance adaptation strategies and support long-term agricultural and environmental sustainability in Central Asia and similar continental agroecosystems.

Solar activity manifests itself in the form of sunspots on the solar surface and solar flares, which can influence Earth's climatic conditions, including drought in mid-latitude regions. This study examines the impact of solar flares on drought conditions in Northern Kazakhstan and analyzes the relationship between solar activity parameters and drought indices. Twelve solar flares of classes X and M recorded in 2014 were analyzed using multi-wavelength data from SDO/AIA, GOES, and HMI/SOLIS magnetograms. Key physical parameters of the flares were determined, including duration, spatial scale, and magnetic reconnection rate. The reconnection rates ranged from 10⁻⁴ to 10⁻³ and showed an inverse dependence on the GOES classification, consistent with the Petschek reconnection theory. Additionally, correlation links were investigated between solar activity indices (WSN, SSN), atmospheric oscillations (NAO, AO), and drought indices (SPI3, HTC). Significant strong correlations were established: between WSN and NAO (r = 0.63), NAO and SPI3 (r = 0.70), as well as a strong negative correlation between SSN and HTC (r = –0.66), indicating a potential connection between solar activity and drought formation in temperate regions. Key words: solar flares, magnetic reconnection, sunspot activity, drought indices, atmospheric oscillations.