Atmospheric Research最新文献

{"title":"Research on the characteristics and mechanisms of convective cloud precipitation in the Mount Everest region","authors":"Lei Wang ,&nbsp;Yueqing Li ,&nbsp;Ge Wang ,&nbsp;Xiangde Xu ,&nbsp;Shunjiu Wang ,&nbsp;ZhiboGao ,&nbsp;Hao Wang ,&nbsp;Zhiwei Heng ,&nbsp;Chenghong Zhang ,&nbsp;Xiaoli Zhao ,&nbsp;QiangyuZeng ,&nbsp;CanweiWang ,&nbsp;KuiZhang","doi":"10.1016/j.atmosres.2025.108064","DOIUrl":"10.1016/j.atmosres.2025.108064","url":null,"abstract":"<div><div>Fundamental research on refined observations and structural characteristics of the spatial and temporal evolution of precipitation-producing weather in the Mount Everest region (MER) is lacking. Via the second comprehensive scientific investigation and research plan of the Qinghai–Tibet Plateau, in this paper, we report the first observation experiment with multisource remote sensing detection equipment for studying convective cloud precipitation on the northern slope in the MER from 2019 to 2023, revealing the unique mechanism triggering summer convective cloud precipitation and the spatial and temporal evolution of its macro- and microscale physical structural characteristics. Multisource detection equipment, including X-band dual-polarization Doppler weather radar, ground automatic stations, 2D video disdrometers, microwave radiometers and radio sounding, were employed to construct an observation network. Secondary inversion data were derived from these multisource observation data. Compared with observation data from other regions, such as Chengdu, summer convective cloud precipitation data in the MER revealed two unique macro- and microstructural characteristics. The internal physical mechanism underlying the influence of the northern slope on summer convective cloud precipitation in the MER is that the extremely high elevation, complex topography, summer South Asian monsoon and intense solar radiation jointly promote the formation of intense thermal vertical motion throughout the troposphere and weak dynamic uplift and poor water vapor conditions in the boundary layer. This study may bridge the gap in detailed observations of the weather structure of the convective cloud precipitation for the northern slope of the MER in summer and provide a significant reference for further studies of Tibetan Plateau weather changes and their potential impacts on the global climate.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108064"},"PeriodicalIF":4.5,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672860","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":"Hourly calibration algorithm for Fengyun-2G quantitative precipitation estimates using spatial random forest and improved temporal disaggregation scheme","authors":"Hao Wu ,&nbsp;Bin Yong ,&nbsp;Zhehui Shen","doi":"10.1016/j.atmosres.2025.108061","DOIUrl":"10.1016/j.atmosres.2025.108061","url":null,"abstract":"<div><div>Fengyun satellite series offers Quantitative Precipitation Estimates (QPEs) with high spatiotemporal resolution, providing coverage at both regional and global scales. However, as indirect estimates of precipitation based on infrared data, Fengyun-2G (FY-2G) QPEs inherently contain considerable regional and seasonal uncertainties. In this study, to mitigate these errors, we propose a novel calibration algorithm that enhances the spatial and temporal performance of FY-2G QPE at both daily and hourly scales. This method consists of two components: first, a daily-scale spatial calibration using a multi-variable-assisted Random Forest (RF) technique, and second, an hourly-scale temporal calibration based on an Improved Proportional Factor (IPF) method, which refines traditional PF approaches by integrating Geographic Difference Analysis (GDA) and Inverse Distance Weighting (IDW) for error correction. The proposed approach was applied to generate a high-quality FY-2G precipitation dataset for the Chinese mainland (0.1°/hr, 2018–2019). Validation against the China Merged Precipitation Analysis (CMPA) dataset demonstrates significant improvements: Daily-scale spatial calibration using RF increases the correlation coefficient (CC) from 0.74 to 0.92 (+24.3 %), reduces BIAS from 15.69 % to 8.04 % (−48.8 %), and decreases RMSE from 5.97 mm to 2.93 mm (−50.9 %). Hourly-scale temporal calibration using RF-IPF improves CC from 0.47 (FY-2G) to 0.77, reduces BIAS from −36.73 % to 8.25 %, and lowers RMSE from 2.98 mm to 2.11 mm during extreme precipitation events. These results highlight the effectiveness of the proposed calibration framework in enhancing both spatial and temporal accuracy of infrared-based QPEs. Unlike existing methods that primarily focus on daily-scale corrections, our approach extends calibration to the hourly level, improving precipitation estimates crucial for short-duration extreme weather events. While this methodology is demonstrated in China, its framework can be adapted to other satellite-based precipitation datasets and applied across diverse climatic and topographic regions, providing valuable insights for hydrological and climatic research worldwide.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"321 ","pages":"Article 108061"},"PeriodicalIF":4.5,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687670","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":"Spatial characteristics and prediction of tropical cyclone-induced storm surge along the Guangdong and Hong Kong Coast","authors":"Qinglan Li ,&nbsp;Riaz Ali ,&nbsp;Jiali Zhang ,&nbsp;Lunkai He ,&nbsp;Zhijian Wu ,&nbsp;Yongchang Ye ,&nbsp;Li Zhang ,&nbsp;Pak-Wai Chan","doi":"10.1016/j.atmosres.2025.108052","DOIUrl":"10.1016/j.atmosres.2025.108052","url":null,"abstract":"<div><div>This study investigates the spatial characteristics and prediction of Tropical Cyclone (TC)-induced storm surges at 18 coastal sites along the Guangdong and Hong Kong coasts when TCs are within 800 km of the sites, using the TC best-track datasets and European Centre for Medium-Range Weather Forecasts datasets from 2009 to 2023. Innovatively, we developed a figure-based statistical model utilizing polar coordinates to determine TC positions relative to specific sites, with shadings denoting historical storm surge values at the site associated with TC intensity, position and size. The model for storm surges at the 18 sites induced by TCs was calibrated with data from 2009 to 2018 and validated with data from 2019 to 2022. Data from 2023 was used to test the model's predictive accuracy. Results show that TC intensity is a significant driver of storm surge, with higher-intensity TCs causing larger surges. Storm surges are influenced by TC azimuth and distance relative to the sites. TCs in the southeast and southwest quadrants, particularly within 600 km, generate more severe surges. Notably, TCs within 0–200 km of the sites, regardless of quadrant, pose the highest risk due to their high intensity around landfall. TC size and SLR also play crucial roles, with larger TCs and higher SLR values (computed using a 60-km radius) leading to larger surges. The figure-based statistical model effectively predicts TC-induced storm surges with minimal computational resources and provides a valuable tool for forecasting future storm surges, supporting disaster preparedness and mitigation efforts along the coast.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108052"},"PeriodicalIF":4.5,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672862","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":"Evaluating thunderstorm characteristics and air quality during the COVID-19 lockdown in Northeastern and Eastern India","authors":"Rupraj Biswasharma ,&nbsp;Gour Prasad Pramanik ,&nbsp;N. Umakanth ,&nbsp;Imolemba Longkumer ,&nbsp;Imlisunup Pongener ,&nbsp;Mahen Konwar ,&nbsp;Debajyoti Samanta ,&nbsp;D.M. Lal ,&nbsp;V. Gopalakrishnan ,&nbsp;Sunil D. Pawar ,&nbsp;A.K. Kamra ,&nbsp;Sanjay Sharma","doi":"10.1016/j.atmosres.2025.108053","DOIUrl":"10.1016/j.atmosres.2025.108053","url":null,"abstract":"<div><div>The impacts of the COVID-19 lockdown on thunderstorm properties, influenced by changes in air quality, were investigated in Northeastern (Kohima, 25.66° N, 94.08° E) and Eastern (Rampurhat, 24.17° N, 87.78° E) India using seven years of ground-based observations. During the lockdown period (LP), Cloud-to-ground (CG) flashes decreased by 67 % and 51 % over Kohima and Rampurhat respectively. Reductions were noted in the number of thunderstorms and various intensity parameters such as duration, flashes per thunderstorm, Peak Flash Rate (PFR), IC: CG ratio, and lightning peak currents. Significant changes in anthropogenic aerosols were observed, with notable reductions in SO₂, NO₂, and PM₁₀ levels. Regardless of the specific raindrop formation mechanism in the two regions, higher concentrations of moderate to larger raindrops were observed during LP. Also, the mixed-phase region of thunderstorms shows a reduction in water content (both liquid and ice) in the mixed phase and the total column. Daily-scale analysis reveals non-linear associations between pollutant concentrations and CG flashes in both regions, with relative humidity (RH) potentially influencing these relationships. Overall, thunderstorm intensity parameters, mixed-phase processes, and rain DSDs were associated with reduced pollutant concentrations during LP. The similarity of trends in multiple parameters during PLP-LP-ALP aligns with established facts, affirming that reduced pollutants lead to noticeable changes in thunderstorm characteristics. The partial rebound of pollutants and other parameters during ALP remained below pre-lockdown levels, which might suggest the lasting impacts of reduced human activities on atmospheric conditions. Further research is necessary to confirm if these measures could mitigate climatic changes and potentially guide policymakers in addressing such changes.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108053"},"PeriodicalIF":4.5,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672861","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":"Control of combustion related ammonia emissions can be effective in mitigating PM2.5 pollution in two megacities in Sichuan Basin, Southwest China","authors":"Hao Xiao ,&nbsp;Hong-Wei Xiao ,&nbsp;Yu Xu ,&nbsp;Neng-Jian Zheng ,&nbsp;Hua-Yun Xiao","doi":"10.1016/j.atmosres.2025.108059","DOIUrl":"10.1016/j.atmosres.2025.108059","url":null,"abstract":"<div><div>The elevated concentration of ammonium (NH₄⁺) in PM_2.5 is a significant contributor to haze formation. However, the reduction potential and sources of its precursor ammonia (NH₃) remain unclear, particularly in the Sichuan Basin, where limited attention has been given to these issues. Here, daily PM_2.5 samples were simultaneously collected from the cities of Chengdu and Chongqing between 1 September to 30 November 2017. The concentration of major water-soluble inorganic ions and the δ¹⁵N-NH₄⁺ value in PM_2.5 were measured. As a result, no significant difference in NH₄⁺ concentration was observed between Chengdu (4.8 ± 3.4 μg m⁻³) and Chongqing (4.5 ± 2.7 μg m⁻³). Although clear differences in the major chemical forms of NH₄⁺ in PM_2.5 were identified, the rapid increase in ammonium nitrate (NH₄NO₃) was a key factor in triggering haze formation in both cities. The reduction of NOx emission proved more effective than NH₃ in mitigation aerosol pollution in the short term. However, the decrease in NH₄NO₃ concentrations was more pronounced, particularly on haze days, when both NH₃ and NOx reductions were considered concurrently. The Bayesian Mixing Model (MixSIAR) revealed significant differences in the source-resolved structure of NH₄⁺ between Chengdu and Chongqing. Specifically, combustion and volatile sources accounted for 47.7 % and 52.3 % in Chengdu, while they accounted for 65.1 % and 34.9 % in Chongqing. However, combustion emissions remain a major source of NH₄⁺ in PM_2.5 during haze days in both cities, contributing over 65 % of NH₄⁺ concentrations. Based on these results, reducing combustion emissions is an effective strategy for mitigating haze pollution in Chengdu and Chongqing.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108059"},"PeriodicalIF":4.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629221","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":"Comparison of model-derived carbon dioxide datasets with the Orbiting Carbon Observatory 3 (OCO-3) observations","authors":"Farhan Mustafa ,&nbsp;Ming Xu","doi":"10.1016/j.atmosres.2025.108057","DOIUrl":"10.1016/j.atmosres.2025.108057","url":null,"abstract":"<div><div>Multiple satellites are currently in orbit around the Earth, providing reliable and consistent estimates of the column-averaged dry-air mole fraction of CO₂, i.e., XCO₂. However, the satellite datasets suffer spatiotemporal gaps due to the narrow swath widths and the influence of clouds and aerosols. Model-derived CO₂ datasets can fill these gaps; however, these model datasets lack the consistency of the satellite observations. Scientists are continually refining their methods to improve the accuracy of the model datasets. Therefore, regular evaluation of the model estimates against precise datasets is imperative to confirm their reliability. In our study, we extensively evaluated the performance of two widely used models, the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker and the Copernicus Atmosphere Monitoring Service (CAMS), by comparing their CO₂ datasets with the Orbiting Carbon Observatory 3 (OCO-3) XCO₂ retrievals utilizing three years of data from 2020 to 2022. The results showed that overall, the CarbonTracker dataset was underestimated by -0.08 ± 0.38 ppm with an RMSE of 0.98 ppm, and the CAMS estimates were overestimated by 0.34 ± 0.43 ppm with an RMSE of 1.05 ppm. For a more detailed assessment, we compared the model and the satellite datasets separately over 10 regions of the world in terms of spatial distribution, monthly changes, seasonal variations, latitudinal distribution, and annual XCO₂ growth rates. The model datasets exhibited good consistency with the satellite observations in most regions. However, significant discrepancies were observed in areas such as the Tibetan Plateau, the Himalayan Mountain ranges, equatorial Africa, and the Amazon.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108057"},"PeriodicalIF":4.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672866","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":"Analysis of profuse winter rainfall over Northern Taiwan and weather-type association","authors":"Jen-Ping Chen ,&nbsp;Pei-Chun Tsai ,&nbsp;Li-Ru Chen ,&nbsp;Chung-Kai Wu ,&nbsp;Emmanuel Fontaine","doi":"10.1016/j.atmosres.2025.108055","DOIUrl":"10.1016/j.atmosres.2025.108055","url":null,"abstract":"<div><div>The profuse winter rainfall over Taiwan's northern coastal mountain area (NCMA) was investigated and quantified, focusing on the associated daily weather types, for ten winters from November 2010 to February 2021. The dominant rainfall-producing system we identified is the boundary-layer-top clouds associated with the northeasterly monsoon (N-type weather), contributing 43 % to the rainfall and 55.6 % to rainy days. Rainfall from the N-type weather correlated highly with the surface winds, total column water (<em>TCW</em>), and the Oceanic Niño Index. While the rainfall depends linearly on <em>TCW</em>, a cubic dependence is found on the northerly wind speed. The N-type rainfall can be drastically enhanced when an overlaying cloud layer emerges in the lower free troposphere. The Oceanic Niño Index represents a large-scale influence on the East Asian winter monsoon, regulating winds and water vapor of the region. Regional-scale composite analysis substantiated such regional influences, with heavier NCMA rainfall associated with stronger Mongolian/Siberian High and enhanced moisture transport at the lower free troposphere over Taiwan. The NCMA winter rainfall shows significant decadal variation, but no apparent long-term trend can be observed from 1940 to 2023.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108055"},"PeriodicalIF":4.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636830","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":"Analysis of anomalous cloud-to-ground lightning in a Wuhan tornadic supercell on 14 May 2021","authors":"Rong Yu ,&nbsp;Muyun Du ,&nbsp;Dong Zheng ,&nbsp;Jue Wang","doi":"10.1016/j.atmosres.2025.108056","DOIUrl":"10.1016/j.atmosres.2025.108056","url":null,"abstract":"<div><div>Data primarily from the China Lightning Detection Network and dual-polarization radars were analyzed to investigate the cloud-to-ground lightning activity and its relationship with the thunderstorm structure in a supercell in Wuhan, Hubei, China, on May 14, 2021. This storm produced an EF3-scale (Enhanced Fujita Scale) tornado and exhibited complex variations in cloud-to-ground lightning activity. The dominant polarity of cloud-to-ground lightning transitioned from negative to positive and back to negative, with each polarity reversal accompanied by a decrease in cloud-to-ground lightning frequency. During a period when positive cloud-to-ground flashes accounted for 92.7 % of all cloud-to-ground flashes, the mean peak current reached an extraordinary 96.1 kA, significantly higher than during other periods or for negative cloud-to-ground lightning throughout the thunderstorm's lifetime. The tornado occurred near the peak of positive cloud-to-ground lightning activity. Based on an analysis of the relationship between cloud-to-ground lightning activity and the dynamic and microphysical parameters derived from radar data, it is deduced that the storm's charge structure likely evolved through the following sequence: an initial normal tripolar structure with predominant negative cloud-to-ground lightning, transitioning to an inverted tripolar structure during the dominance of positive cloud-to-ground lightning, followed by an inverted dipolar structure with a temporary increase and predominance of negative cloud-to-ground frequency, and finally returning to a normal tripolar structure characterized by high-frequency, predominantly negative cloud-to-ground lightning. The high peak current of positive cloud-to-ground lightning may be attributed to increased charge density from intense convection and a strong environmental electric field, particularly at lower lightning initiation altitudes.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108056"},"PeriodicalIF":4.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629222","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":"How the unparalleled dust storm over the Arabian Peninsula in May 2022 exacerbated the record-breaking heatwave in China in the ensuing summer","authors":"Dapeng Zhang ,&nbsp;Yanyan Huang ,&nbsp;Jin Dai ,&nbsp;Botao Zhou ,&nbsp;Zhicong Yin ,&nbsp;Huijun Wang","doi":"10.1016/j.atmosres.2025.108054","DOIUrl":"10.1016/j.atmosres.2025.108054","url":null,"abstract":"<div><div>Against the background of global warming, the increasing frequency of extreme high-temperature events (EHTF) in East China poses a huge threat to societal development and public health, and this was starkly demonstrated by the record-breaking EHTF observed in China in summer 2022. In this study, it was found that the record-breaking dust storm in May 2022 over the Arabian Peninsula accounted for approximately 65.2 % of the abnormal amplitude of July–August EHTF in China in the ensuing summer. Mechanistically, the dust aerosols of this heavy dust storm over the Arabian Peninsula were transferred downstream by the trade winds, whereupon they cooled the Indian Ocean via radiative processes and warmed the Tibetan Plateau through the so-called “snow-darkening effect”. These dust effects persisted until late summer and consequently strengthened the Indian summer monsoon and wetted the Indochina Peninsula. Subsequently, the associated enhanced and eastward-shifted South Asian high and westward-shifted western Pacific subtropical high contributed to the record-breaking EHTF in 2022. A physical–empirical forecast model was developed based on the preceding May dust signals over the Arabian Peninsula, and results showed that it skillfully predicts the interannual variability of July–August EHTF in East China during 2009–2022, and especially the record-breaking amplitude in 2022.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108054"},"PeriodicalIF":4.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672863","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":"Coupling effects of moisture sources and meteorological factors on stable isotopes in precipitation over the Hunshandake Sandy Land, northern China","authors":"Yusheng Hao ,&nbsp;Debin Jia ,&nbsp;Wenxu Su ,&nbsp;Weiying Feng","doi":"10.1016/j.atmosres.2025.108058","DOIUrl":"10.1016/j.atmosres.2025.108058","url":null,"abstract":"<div><div>Effective management of water resources and the development of climate adaptation strategies in arid and semi-arid regions increasingly rely on a comprehensive understanding of water cycle processes in the context of global climate change. This study focuses on the Hunshandake Sandy Land, a key ecological barrier in northern China. It analyzes the influence of climate conditions and moisture sources on precipitation isotope composition using 394 precipitation samples collected between 2014 and 2021. Precipitation δ¹⁸O and d-excess show significant variability and distinct seasonal patterns, with δ¹⁸O values ranging from 1.78 ‰ to −24.51 ‰ and d-excess values from −26.28 ‰ to 39.08 ‰. Temperature is identified as the primary factor influencing precipitation δ¹⁸O and d-excess, accounting for 42 % of the monthly δ¹⁸O variation and 16 % of the monthly d-excess variation. The Local Meteoric Water Line, δ²H = 6.66δ¹⁸O – 3.48, highlights the dry, low-rainfall, and high-evaporation characteristics of the Hunshandake Sandy Land. The backward trajectory calculations reveal that northern China, central China, and Mongolia are the primary sources of moisture absorption, contributing 38.25 %, 26.20 %, and 14.21 % of the moisture to Hunshandake Sandy Land precipitation, respectively. The influence of monsoon climates varies over time, leading to significant variability in the contribution of different moisture source regions to Hunshandake Sandy Land precipitation. Specifically, northern China contributes 36.09 % of the moisture in the wet season and 40.42 % in the dry season, whereas central China contributes 29.39 % in the wet season and 23.02 % in the dry season. The Hunshandake Sandy Land precipitation sample index (I_HSL) was defined, and a multiple linear model for monthly precipitation δ¹⁸O values was developed using temperature, relative humidity, and I_HSL: (δ¹⁸O = 0.320 T - 0.068RH + 0.022 I_HSL - 11.615). This model can explain 49 % of the monthly precipitation δ¹⁸O variability.These findings enhance the understanding of the water cycle in arid and semi-arid regions.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"320 ","pages":"Article 108058"},"PeriodicalIF":4.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672865","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}