Editorial for the Special Issue on Climate Change and Climate Variability, and Their Impact on Extreme Events (1st Edition)

In recent decades, the effects of climate change and climate variability have attracted significant global attention due to their growing impact on extreme weather and climate events [1,2,3,4,5]. These changes influence crucial sectors such as agriculture, water resources, health, infrastructure, and the economy, with implications that demand adaptive strategies [6,7,8,9]. Thus, studies on improving and enhancing the methods of modeling and analyzing climatic phenomena are growing, with a specific focus on precipitation patterns, monsoon dynamics, temperature variability, and the impacts of climate indices on local and regional weather and climate [10,11,12]. In light of these pressing concerns, this Special Issue of Atmosphere attempted to bring together diverse research that explores the complex relationship between climate dynamics and extreme weather events through both observational and numerical modeling studies. Our aim was to enhance the understanding of climate variability at all scales, including local, regional, and global, and to contribute to a more precise understanding of these challenges. Thus, the contributions of this collection largely focus on the global urgency of understanding and addressing complex climate dynamics across diverse environments. Some studies investigate temperature trends, climate variability, and the impacts of drought on agriculture, revealing important regional and seasonal differences [13,14,15,16,17]. Research on cyclone activity highlights the influence of sea surface temperatures and wind shear [18,19], while work on cloud cover, CO₂ forcing, and cyclonic storm prediction advances our understanding of atmospheric responses and modeling techniques [20,21]. Other contributions explore phenomena like the Arctic Oscillation, winter cold spells, and jet stream responses to Arctic warming [22,23]. Papers also focus on local and regional climate impacts, such as moisture variability, seasonal climate trends, and the effects of anthropogenic heat in industrial areas [24,25,26,27]. Further studies address monsoon variability, the influence of El Niño and La Niña on pre-monsoon convection, and projected changes in extreme precipitation [28,29].

Hong et al. [Contribution 1] utilized a multi-model ensemble to project future precipitation extremes in Iran under three climate scenarios [13]. Their results indicated a significant increase in the frequency and intensity of extreme precipitation events by 2100, particularly over Iran’s western and southwestern regions. This study highlighted the need for adaptive strategies in response to intensified rainfall patterns. Maity et al. [Contribution 2] assessed how soil moisture initialization affects monsoon simulation accuracy using the RegCM4 model [24]. They highlighted that initializing with high-resolution soil moisture data enhances the model’s ability to predict surface temperatures and rainfall, particularly in normal monsoon years, though challenges remain in accurately capturing monsoon variability in extreme years. Seasonal differences in tropical cloud cluster formation were explored by Peng et al. [Contribution 3] over the Western North Pacific to identify opposing trends in May (increasing) and October (decreasing) [14]. They attributed these trends to varying sea surface temperature patterns and atmospheric circulation changes, highlighting the seasonal impact on cyclone formation potential.

The trends in extreme temperatures across China from 1966 to 2015 were analyzed by Chen et al. [Contribution 4] to show the increased maximum and minimum temperatures and greater instability in extreme events [25]. They noted that the El Niño phenomenon and rising average temperatures contribute to these shifts, with particular instability observed over China’s central and southern regions. Mishra et al. [Contribution 5] used numerical modeling to assess the impact of industrial heat and moisture emissions on local weather in Odisha, India [26]. Their findings indicated that industrial heat intensifies rainfall locally, with rainfall increases being most sensitive to the combined effects of heat and moisture. This indicated the local climate implications of industrial emissions. Tasnim et al. [Contribution 6] investigated 41 years of seasonal climate changes affecting Maine’s wild blueberry production to provide valuable insights for agricultural planning in response to climate shifts [15]. They noted a significant warming trend in fall and winter temperatures, with less change in spring and summer. They also found that longer, warmer growing seasons impact blueberry growth differently across different regions.

Sahu et al. [Contribution 7] examined how El Niño and La Niña events influence pre-monsoon convective systems in eastern India, focusing on lightning activity, precipitation, and thermodynamic indices [28]. Their study revealed that El Niño years see increased lightning and thermodynamic activity, while La Niña phases show increased precipitation and convective instability, suggesting critical shifts in severe weather risks. Regional variations in the onset dates of the Indian summer monsoon from 1951 to 2017 are examined by Saini et al. [Contribution 8], aiming to enhance and improve the insights into monsoon predictability across India [29]. They found that climate factors like El Niño and La Niña significantly affect time of onset, particularly in northern and northeastern regions. Their analysis highlighted how flood and drought years impact the time of onset. Li et al. [Contribution 9] applied end-member modeling to analyze grain-size distributions from lake core sediments over Anguli-Nuur, northern China, to reconstruct the historical moisture variability [27]. Their findings identified four key sediment end-members that are linked to distinct transport processes. This study revealed fluctuations in East Asian monsoon strength since the last deglaciation, aligning with broader monsoonal and North Atlantic climate patterns.

A comprehensive analysis of winter cold spells across the Balkan Peninsula was conducted by Tringa et al. [Contribution 10] to provide insight into atmospheric dynamics linked to extreme cold conditions [20]. Their investigation of the circulation types associated with cold events revealed a decreasing trend in cold spell frequency. Yang et al. [Contribution 11] explored the mid-latitude jet stream’s response to Arctic warming using an idealized General Circulation Model (GCM) [22]. They showed how Arctic amplification leads to a wavier jet stream pattern, affecting mid-latitude weather patterns and potentially exacerbating extreme weather events in these regions. Liang et al. [Contribution 12] examined the complex interactions between wave-mean flows and Arctic Oscillations (AO) in winter seasons [23]. By analyzing AO variability across multiple time scales, they revealed the influence of wave breaking and El Niño–Southern Oscillation (ENSO) phases on AO indices, contributing to a deeper understanding of winter climate patterns. Singh et al. [Contribution 13] attempted the challenging task of predicting cyclonic storms, using the Weather Research and Forecasting (WRF) model to predict the track and intensity of Cyclone Fani [18]. Their study demonstrated the utility of high-resolution modeling in accurately forecasting the trajectory and impacts of severe cyclones, which is crucial for disaster preparedness.

Zhou et al. [Contribution 14] presented an analysis of cloud cover responses to a quadrupled CO₂ forcing using data from CMIP6 models [21]. By decomposing fast and slow responses, they provided a nuanced view of cloud behavior under anthropogenic climate change, with implications for understanding cloud-driven feedback mechanisms in warming scenarios. Badji et al. [Contribution 15] investigated the Standardized Precipitation Evapotranspiration Index (SPEI) over Huaibei Plain of China, where agricultural drought events have intensified due to climate change [16]. They predicted increasingly severe drought events, potentially affecting food security and regional agriculture. Hibbert et al. [Contribution 16] analyzed changes in sea surface temperatures (SSTs) and vertical wind shear (VWS) over the Caribbean and the Atlantic hurricane development region [19]. Their study highlighted a significant rise in SSTs alongside a decline in VWS. These changes, which have intensified storm activity, highlighted how regional warming influences cyclone dynamics—a key concern for regions susceptible to tropical cyclones. Safari and Sebaziga [Contribution 17] examined the trends and variability in temperature over four decades to explore the impact of rising temperatures on agriculture and water resources [17]. Their findings of an increasing number of warm days and nights highlighted a statistically significant rise in minimum temperatures during both the long dry season and short rain season.

The 17 contributions in this Special Issue cover a diverse array of topics that emphasize the multifaceted nature of climate-related challenges. We hope these studies illustrate the latest advancements and findings in this domain, each focusing on various aspects of climate variability and its impacts. We believe these studies will provide critical insights into temperature trends, drought, tropical cyclone activity, sea surface changes, and other essential topics that are related the broader goals of climate science and policy.