Atmospheric Research最新文献

{"title":"Future projections of extreme precipitation over Indonesia's new capital under climate change scenario using CORDEX-SEA regional climate models","authors":"Marzuki Marzuki ,&nbsp;Ravidho Ramadhan ,&nbsp;Helmi Yusnaini ,&nbsp;Liew Juneng ,&nbsp;Fredolin Tangang ,&nbsp;Mutya Vonnisa ,&nbsp;Afdal Afdal ,&nbsp;Muhammad Rais Abdillah ,&nbsp;Rahmat Hidayat","doi":"10.1016/j.atmosres.2025.108389","DOIUrl":"10.1016/j.atmosres.2025.108389","url":null,"abstract":"<div><div>As Indonesia's new capital (hereafter called Nusantara City or NC) aspires to become a leading sustainable city, it must be developed with resilience to climate change. This study investigates the future seasonal extreme precipitation conditions in NC using a set of climate projections from the CORDEX-SEA Regional Climate Models (RCMs). The analysis integrates four Global Climate Models (GCMs) downscaled using two RCMs: RegCM4 and RCA4. The model results were analyzed for the periods 1970–2005 (historical), 2011–2040 (early century), 2041–2070 (mid-century), and 2071–2099 (late century) under both the low-emission (RCP 2.6) and high-emission (RCP 8.5) scenarios. Model evaluation using Integrated Multi-satellitE Retrievals for GPM (IMERG) Version 07B data shows that RegCM4-based downscaling more accurately captures mean rainfall, seasonal patterns, and extreme precipitation indices in NC than RCA4. The ensemble average of three RegCM4 runs (HadGEM2-ES, MPI-ESM-MR, and NorESM1) indicates significant increases in extreme precipitation indices under RCP 8.5 from the mid to late century. By the late century, indices such as Maximum 5-Day Precipitation (RX5days), Consecutive Dry Days (CDD), and Number of Very Heavy Precipitation Days (R50mm) are projected to increase by 5.88 %, 41.12 %, and 29.30 %, respectively, while Total Precipitation (PRPTOT), Consecutive Wet Days (CWD), and Number of Heavy Precipitation Days (R20mm) decrease by −15.69 %, −21.93 %, and − 13.78 %. Rainfall during the dry season (June–September) is projected to decline by approximately 17 % under RCP 2.6 and 25 % under RCP 8.5. Historically, El Niño has triggered droughts during the dry season in Kalimantan, and under future warming, severe droughts resembling those driven by El Niño may occur even in its absence. Furthermore, the divergent projections resulting from the various models employed here suggest the critical role of model selection in hydrological impact analysis, as different models can produce strongly divergent estimates of future extreme rainfall.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108389"},"PeriodicalIF":4.5,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-stationary temperature extremes in South Korea: An extreme value analysis of global warming impacts","authors":"Jung-Hee Ryu ,&nbsp;Jae-Heon Lee ,&nbsp;Song-Lak Kang","doi":"10.1016/j.atmosres.2025.108388","DOIUrl":"10.1016/j.atmosres.2025.108388","url":null,"abstract":"<div><div>Understanding the evolution of temperature extremes under global warming is crucial for effective regional climate adaptation. In South Korea—a region undergoing rapid urbanization and facing rising heat-related risks—there is a growing need to better understand these changes, particularly in relation to global climate drivers. To meet this need, this study employs a non-stationary Generalized Extreme Value (GEV) model that incorporates global mean surface temperature (GMST) as a covariate. Daily maximum and minimum temperatures from 60 nationwide weather stations were analyzed, focusing on summer and winter extremes over durations ranging from 1 to 15 days during the period 1974–2023.</div><div>The results reveal distinct regional and seasonal patterns of non-stationarity. Winter extremes have become milder, with broader temperature distributions and fewer cold events, indicating a weakening of cold spells. However, in terms of adverse societal and environmental impacts, summer extremes are more vulnerable. Tropical night events exhibit the greatest sensitivity to global warming, particularly along the west and south coasts, where their frequency and persistence have increased sharply. Heatwaves have also intensified, though less dramatically. These changes appear linked to large-scale climate dynamics, including intensification of the North Pacific Subtropical High and warming of surrounding seas, which enhance atmospheric moisture transport toward the Korean Peninsula. By integrating observational data with a dynamic statistical framework, this study provides new insights into the changing nature of temperature extremes and their drivers—offering a valuable basis for targeted adaptation strategies in South Korea.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108388"},"PeriodicalIF":4.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced onset of South Asian summer monsoon increases pre-monsoon precipitation over Tibetan Plateau","authors":"Dong Xuefeng ,&nbsp;Liu Yuzhi ,&nbsp;Yan Xiaoqiang ,&nbsp;Dong Wei","doi":"10.1016/j.atmosres.2025.108385","DOIUrl":"10.1016/j.atmosres.2025.108385","url":null,"abstract":"<div><div>The South Asian summer monsoon (SASM) exerts a profound influence on precipitation over Tibetan Plateau (TP), yet the impact of its recently advanced onset of the SASM (SASMO) on pre-monsoon TP precipitation remains unclear. Using observational, satellite, and reanalysis datasets, this study investigates how interannual variability in the SASMO affects May precipitation over the TP, based on moisture and dynamical budget analyses. Results show that the SASMO explains 45 % of interannual variability in May precipitation over the TP, with an advanced (delayed) onset corresponding to increased (decreased) precipitation. This relationship is linked to an anomalous Rossby wave train, characterized by an anticyclone over the western TP, a cyclone over the Indian subcontinent, and another cyclone over the eastern TP. These circulation patterns promote the northwestward expansion of the South Asian High and the intensification of the India-Burma trough in May. As a result, lower-level westerlies over the monsoon region during advanced SASMO years intensify to twice the climatological mean. Accordingly, net water vapor transport, moisture convergence, and ascending motion over the TP are enhanced by 123 %, 28 %, and 22 %, respectively, ultimately leading to a 14 % increase in May precipitation over the TP. Dynamic diagnostics indicate that vertical motion over the TP is primarily driven by vorticity advection processes. Moisture budget analysis suggests that the increase in May precipitation over the TP is dominated by dynamic processes induced by anomalous wind convergence associated with SASMO anomalies. These findings improve our understanding of the monsoon–precipitation relationship over the TP.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108385"},"PeriodicalIF":4.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modification of Air-Sea momentum flux parameterization considering non-local effects","authors":"Yuncong Jiang ,&nbsp;Yubin Li ,&nbsp;Xueyan Bi ,&nbsp;Nan Yang ,&nbsp;Yixiong Lu ,&nbsp;Tongwen Wu ,&nbsp;Zhiqiu Gao","doi":"10.1016/j.atmosres.2025.108382","DOIUrl":"10.1016/j.atmosres.2025.108382","url":null,"abstract":"<div><div>The air-sea momentum flux is an important component in air-sea interactions. In climate models, the estimation of air-sea momentum flux mainly relies on bulk flux parameterization based on the Monin-Obukhov Similarity Theory. However, the bulk flux parameterization has significant biases under light wind conditions. To reduce these inaccuracies, this study analyzed observational data from marine stations. The results showed that the non-local effects, which are overlooked by the traditional Monin-Obukhov Similarity Theory, are a significant factor contributing to inaccuracies in the air-sea momentum flux parameterization. Based on this finding, this study proposed a modification equation associated with non-local effects to improve the parameterization of air-sea momentum flux under near-neutral conditions. Furthermore, the modification equation was extended to non-neutral conditions, enabling its integration into air-sea momentum flux parameterization schemes and climate models. To evaluate the applicability and effectiveness of this modification, offline and online tests were conducted using two observational datasets and the Community Atmosphere Model version 6. Assessed by the comprehensive evaluation metric DISO, it was demonstrated that the non-local effects modification evidently enhanced the calculation accuracy of air-sea momentum flux and significantly improves the simulation performance in climate models.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108382"},"PeriodicalIF":4.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Key factors affecting atmospheric visibility during the 19th Asian Games in Hangzhou","authors":"Yang Wu ,&nbsp;Jing Wei ,&nbsp;Jiasi Shen ,&nbsp;Xiaoyuan Wang ,&nbsp;Zheng Xia ,&nbsp;Wenlong Zhao ,&nbsp;Da Xu ,&nbsp;Qian Tang ,&nbsp;Jinmei Ding ,&nbsp;Xudong Tian ,&nbsp;Yuwen Niu ,&nbsp;Zhibin Wang ,&nbsp;Bingye Xu","doi":"10.1016/j.atmosres.2025.108378","DOIUrl":"10.1016/j.atmosres.2025.108378","url":null,"abstract":"<div><div>Identifying the key factors that influence atmospheric visibility is critical for effective air pollution prevention and control. However, the complex nonlinear relationships between visibility and its influencing factors pose significant challenges. Most current studies rely on empirical models for statistical analysis, which can introduce significant inaccuracies.</div><div>This study integrates the traditional IMPROVE analysis method with machine learning models to investigate the driving factors of atmospheric visibility and the causes of low visibility events during the 19th Asian Games in Hangzhou. The results indicate that SO₄²⁻, NO₃⁻, organic aerosols (OA), and black carbon (BC) are the primary light extinction contributors among PM_2.5 chemical components. Secondary formation processes were the dominant factor that accounted for 57 % of extinction coefficient, relative humidity and vehicles together contributed 30 % of extinction coefficient. During periods of low visibility (&lt;10 km), the contributions of secondary nitrates and relative humidity content to extinction coefficient increased significantly, suggesting that hygroscopic growth of secondary nitrates was the primary driver of such events.</div><div>The results of the study show that machine learning models closely match the IMPROVE approach during periods of low visibility. In addition, machine learning models outperform the IMPROVE method in their ability to capture the complex non-linear relationships between forcing factors and visibility. To effectively manage secondary nitrate pollution, it is critical to reduce emissions of nitrogen oxides (NOx) and ammonia (NH₃) while improving overall air quality. This comprehensive analytical approach provides scientific evidence for improving urban atmospheric visibility.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108378"},"PeriodicalIF":4.5,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving aerosol forecasting through visibility data assimilation in WRF-chem: Methodology and evaluation","authors":"Shuang Mei ,&nbsp;Wei You ,&nbsp;Wei Zhong ,&nbsp;Zengliang Zang ,&nbsp;Jianping Guo ,&nbsp;Xiaoping Cheng ,&nbsp;Lina Gao","doi":"10.1016/j.atmosres.2025.108383","DOIUrl":"10.1016/j.atmosres.2025.108383","url":null,"abstract":"<div><div>Chinese high-density visibility observation stations provide more uniform coverage than traditional air quality monitors, spanning urban, rural, and remote areas, which improves spatial representativeness. The visibility data from these stations has the potential to optimize aerosol initial conditions in air quality models, thereby improving the accuracy of pollution forecasting. This study details the development of a visibility observation assimilation module integrated with the WRF-Chem model. We aim to assimilate visibility data and evaluate the improvement in model performance achieved through assimilation compared to a direct WRF-Chem simulation. The assimilation system utilizes an advanced multi-scale three-dimensional variational assimilation (MS-3DVAR) technique and employs WRF-Chem MOSAIC aerosol species concentrations as control variables. To extensively evaluate the developed visibility assimilation algorithm, we conducted three numerical experiments focused on the forecasting accuracy of dust events that occurred in Northern China in March 2021. The first experiment (DA_PM&amp;AOD) assimilated particulate matter (PM_2.5 and PM₁₀) and satellite-derived aerosol optical depth (AOD) data. The second experiment (DA_EXT) assimilated visibility data, while the third experiment (DA_ALL) integrated particulate matter, AOD, and visibility data. The evaluation demonstrates that, the control experiment group consistently underestimated the values during dust events. The DA_EXT assimilation group significantly improved the forecast accuracy of PM₁₀ concentration and EXT (extinction coefficient). In the DA_PM&amp;AOD experiment, the agreement index between PM₁₀ simulation and observation increased to above 0.9. In the DA_ALL experiment, the agreement index for EXT simulation reached 0.677. The evaluation reveals that assimilating visibility data significantly improves both the initial aerosol fields and dust process forecasting in the model. This enhancement compensates for spatial and temporal discontinuities in satellite observations of visible light channels.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108383"},"PeriodicalIF":4.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Polarimetric insights into pre-monsoon convective clouds and hail storm microphysics over central India using polarimetric radar observation","authors":"Kumar Abhijeet ,&nbsp;Sachin M. Deshpande ,&nbsp;G. Pandithurai","doi":"10.1016/j.atmosres.2025.108381","DOIUrl":"10.1016/j.atmosres.2025.108381","url":null,"abstract":"<div><div>The present study characterizes the pre-monsoon convective clouds (PMCC) observed in the monsoon core zone and a hail-producing storm during the pre-monsoon month observed using C-band dual-polarization (CDPR) radar at the IITM's Atmospheric Research Testbed (ART) facility in Silkheda, 60 km north of Bhopal. The composite analysis of PMCC has shown that the maximum height of 35- and 50-dBZ echo tops (ETHs) is around 13 km and 11 km, respectively, indicating intense and deep convection. The mean value of Convective Available Potential Energy (CAPE) is also high for the pre-monsoon season. The composite contoured-frequency-by-altitude diagrams (CFADs) of PMCC show a high frequency of smaller values of differential reflectivity (<em>Z</em>_DR ∼ 0 dB) and specific differential phase (<em>K</em>_DP) above the melting layer, indicating that intense convective updrafts dominate the PMCC, causing hail/graupel particles to be rimmed heavily above the melting layer and reach greater heights. The wider distribution or higher values of <em>Z</em>_H, <em>Z</em>_DR, <em>K</em>_DP, and small values of correlation coefficient <em>ρ</em>_HV (&lt;0.95) near the surface indicate the presence of a rain-hail mixture during the pre-monsoon month.</div><div>The microphysical characteristic of a hailstorm event that produced hailstones over Bhopal on 30th April 2023 is explored. It is found that the CAPE value was building up before the hailstorm event, and it was high just before the hailstone was observed over Bhopal. Time evolution of storms indicates the dominant presence of graupel/hail at 5-11 km. Graupel/hail will form due to the riming or accretion processes of cloud droplets, supercooled water, or ice particles. It has been observed that the riming process is dominant during the storm's evolution, which produces very low values of <em>Z</em>_DR and <em>K</em>_DP. The high value of <em>ρ</em>_HV (&gt;0.99) at these altitudes suggests that the graupel/hail is dry. The updraft associated with a convectively unstable atmosphere exaggerates the growth of ice crystals by a rapid collection of supercooled water droplets. That ultimately led to forming graupel/hailstones through the riming process. The wet hailstones and large raindrops signatures close to the surface are also observed and are characterized by higher values of <em>Z</em>_H (&gt; 50 dBZ), enhanced <em>Z</em>_DR (∼ 3–4 dB), and a depleted <em>ρ</em>_HV (&lt; 0.95). Additionally, a <em>K</em>_DP exceeding 1.8°/km near the surface indicates the process of hail melting/hail coated with water.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108381"},"PeriodicalIF":4.5,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstruction of high-precision gridded precipitation dataset in the alpine cold regions of the Qilian Mountains: An intelligent technological framework from downscaling to calibration","authors":"Renjun Wang ,&nbsp;Xiang Qin ,&nbsp;Yushuo Liu ,&nbsp;Jianyu Zhao ,&nbsp;Rui Zhang ,&nbsp;Zizhen Jin ,&nbsp;Yanzhao Li ,&nbsp;Wentao Du ,&nbsp;Jizu Chen ,&nbsp;Weijun Sun","doi":"10.1016/j.atmosres.2025.108387","DOIUrl":"10.1016/j.atmosres.2025.108387","url":null,"abstract":"<div><div>Accurate precipitation data play a vital role in hydrological and climate studies, with their significance being especially pronounced in alpine cold regions where in-situ observational data are limited. However, existing gridded precipitation datasets often suffer from low resolution and significant biases, making them inadequate for addressing the strong spatiotemporal heterogeneity of alpine areas. To address these challenges, this study developed a novel Three-Layer Intelligent Downscaling and Calibration (TLIDC) framework, integrating Geographically Weighted Regression (GWR) and Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN-BiLSTM) model, to generate high-precision gridded precipitation data tailored for alpine regions.</div><div>The TLIDC framework was quantitatively evaluated using data from 100 rain gauge stations in the Qilian Mountains and applied to reconstruct daily precipitation data at a 0.01° × 0.01° spatial resolution for the Qilian Mountains from 1950 to 2024. The results demonstrate that: (1) The TLIDC framework effectively downscales the coarse spatial resolution ERA5-Land precipitation data, producing high spatial resolution outputs that preserve the temporal periodicity and overall spatial distribution, while markedly enhancing spatial detail and visual clarity. (2) The calibration module of the TLIDC framework effectively corrected the bias in the raw precipitation data, significantly improving data performance, particularly in areas with scarce ground observation data. Compared to CHM_PRE, CN05.1, and TRMM, the generated data showed a 15.95 % ∼ 25.20 % improvement in precipitation event identification accuracy. Furthermore, the Pearson correlation coefficient (CC) for precipitation simulation accuracy increased by 0.30–0.55, while the root mean square error (RMSE) and mean absolute error (MAE) decreased by 3.33–4.58 mm/day and 1.42–2.27 mm/day, respectively. (3) The high-precision precipitation dataset for the Qilian Mountains, reconstructed using the TLIDC framework, has a multi-year average of 296.84 mm/year for the period 1999–2019. This value is close to the multi-year averages of three other precipitation products, which range from 296.43 to 352.47 mm/year. Additionally, the spatial distribution pattern of this dataset aligns with those of the other products. (4) From 1950 to 2024, precipitation in the Qilian Mountains has increased at a linear rate of 2.49 mm per decade (<em>p</em> &lt; 0.05), exhibiting a spatial pattern of decreasing precipitation from southeast to northwest. Our findings offer a viable solution for generating high-precision precipitation data in alpine cold regions with complex topography and sparse observational networks, addressing a critical gap in current climate and hydrological research.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108387"},"PeriodicalIF":4.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urbanization intensified predecessor rainfall redistribution associated with Typhoon Khanun (2017) in the lower Yangtze River region","authors":"Jiaxi Wu ,&nbsp;Huiyan Xu ,&nbsp;Yu Song ,&nbsp;Yebing Liu ,&nbsp;Xiayi Lang","doi":"10.1016/j.atmosres.2025.108384","DOIUrl":"10.1016/j.atmosres.2025.108384","url":null,"abstract":"<div><div>The Yangtze River Delta region (YRD) is one of the most important regions with rapid urbanization in China. The research employs the Weather Research and Forecasting Model (WRF) to investigate the influences of urbanization on precipitation patterns and intensities of predecessor rain events (PREs) induced by Typhoon Khanun (2017) in the YRD. The results indicate that using land use data during the precipitation event can improve the model simulation performance. Although the total regional precipitation remains relatively unchanged, urbanization significantly alters the spatiotemporal distribution of rainfall, resulting in enhanced precipitation in the coastal urban regions near the heavy precipitation center regions, with a maximum increase up to 52 %. In contrast, rainfall near the inland outer region of the heavy precipitation center is reduced, with a maximum decrease up to 50 %, exhibiting a prominently uneven distribution pattern, which requires adaptive zoning in flood management. Mechanistically, around the coastal urban regions near heavy precipitation centers, urbanization enhances water vapor convergence and atmospheric instability, necessitating revised stormwater infrastructure design standards for these high-risk zones; while it suppresses water vapor transport, enhancing atmospheric stability in the inland outer region. Further analysis of the cloud microphysics reveals that urbanization significantly strengthens the processes of raindrop accretion of cloud water and water vapor condensing into raindrops, thereby promoting increased rainfall in the coastal urban region; in contrast, it may weaken the processes of snow melting and water vapor condensing into raindrops, leading to reduced precipitation in the peripheral inland outer region. These findings offer scientific support for climate-resilient urban planning, demonstrating how urbanization shifts precipitation patterns, necessitating coordinated regional adaptation for flood resilience.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108384"},"PeriodicalIF":4.5,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extremes of diurnal temperature range in karst regions: Definition, trends and interaction with wind speed","authors":"Ruizhi Sun,&nbsp;Xushu Wu","doi":"10.1016/j.atmosres.2025.108379","DOIUrl":"10.1016/j.atmosres.2025.108379","url":null,"abstract":"<div><div>Diurnal temperature range (DTR) is an important climate indicator that exerts substantial effects on society as well as the environment, particularly on karst landforms where the ecosystem is vulnerable and sensitive to DTR. However, the space-time pattern of extremes of DTR and their relationship with wind speed over global karst regions remain poorly understood. In this study, we defined DTR extremes and investigated the spatiotemporal patterns of warm-season extremes and their relationships with wind speeds across global karst regions during 1980–2022. Our results reveal that arid zones such as the Middle East and northwestern China exhibit large long-term mean DTR and DTR extremes. There is an increase in the frequency of DTR extremes for most regions, though pronounced regional divergence of DTR trends exists. The intensity of DTR extremes show apparent increasing trends in North America and Europe, but in other regions decreased trends are prevailing. For most regions worldwide, declining wind speed trends are discerned, though slight increases are observed in the western United States. Moreover, wind speed is generally strengthened along with larger DTR. Daytime DTR extremes dominate North America, Europe and south China, while nighttime extremes are likely to occur in the Middle East and Asia. These findings advance the understanding of DTR extremes in fragile karst ecosystems, which could help for region-specific climate adaptation strategies.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108379"},"PeriodicalIF":4.5,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}