Atmospheric Research最新文献

{"title":"Added value of a multi-model ensemble of convection-permitting rainfall reanalyses over Italy","authors":"Antonio Giordani,&nbsp;Paolo Ruggieri,&nbsp;Silvana Di Sabatino","doi":"10.1016/j.atmosres.2025.108402","DOIUrl":"10.1016/j.atmosres.2025.108402","url":null,"abstract":"<div><div>Regional convection-permitting meteorological reanalyses substantially improve the atmospheric representation compared to convection-parameterized counterparts. This holds particularly for multi-scale driven variables such as precipitation in terms of spatial structures, intensity and frequency rates, or the timing and peak of its summer diurnal cycle. However, the simulation of convective-related phenomena is highly model-dependent, implying the inability to sample the full range of natural variability with single-model experiments. This challenge is exacerbated for km-scale simulations owing to the intrinsic chaotic nature underlying convection. Multi-model ensembles of high-resolution climate models demonstrate to reduce the simulation errors associated with individual model outputs over Europe. When applied to retrospective estimates, such ensemble approach could then offer a comprehensive, homogeneous, and optimized assessment of past atmospheric states.</div><div>This study presents the first multi-model ensemble of regional reanalyses over Italy considering four recently produced datasets to assess the added value of their joint use. These products are derived by dynamically downscaling the global reanalysis ERA5 with different numerical models: MERIDA_HRES, MOLOCH, SPHERA and VHR-REA_IT. The reference dataset for comparison is the pluviometer-based hourly analysis GRIPHO. The investigation over 2007–2016 includes the annual and seasonal variations in daily and hourly mean rainfall intensity and frequency, heavy precipitation occurrences, and their summer diurnal cycles. No single dataset systematically outperforms the others, and substantial inter-model variability is detected for summer precipitation. The ensemble improves rainfall statistical estimates compared to individual reanalyses by providing more realistic spatial patterns, enhanced skill, and reduced biases relative to observations. These findings have potential implications for downstream reanalysis applications.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108402"},"PeriodicalIF":4.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810259","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":"Characteristics of multi-layer clouds observed using ceilometer observations over Leh-Ladakh: A high-altitude cold desert region","authors":"Ruchita Shah ,&nbsp;Som Sharma ,&nbsp;Dharmendra Kamat ,&nbsp;Kondapalli Niranjan Kumar ,&nbsp;Prashant Kumar ,&nbsp;Shantikumar S. Ningombam ,&nbsp;Dorje Angchuk ,&nbsp;Rohit Srivastava","doi":"10.1016/j.atmosres.2025.108399","DOIUrl":"10.1016/j.atmosres.2025.108399","url":null,"abstract":"<div><div>The Leh-Ladakh region is a high-altitude cold desert (3255 m above mean sea level), located under the rain shadow of the Himalayas, display various cloud features crucial to understand the extreme weather conditions. Global Satellite Mapping of Precipitation (GSMaP) parameter helped to show that almost 37 % of rain falls over Leh-Ladakh region (7–38°N, 62–100°E) during last 23 years of monsoon season. Low rainfall though facing extreme rainfall events, need a continuous monitoring of cloud measurements. In the present study, cloud base height (CBH) variability is investigated using Ceilometer Lidar measurements, complemented by Moderate Resolution Imaging Spectroradiometer (MODIS), European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) during September 2022–August 2023. Our comparative findings suggested that Ceilometer's CBH measurements aligned with calculated MODIS CBH, whereas ERA5 CBH gets underestimate. Further, Ceilometer measurements of multi-layer clouds, consist of three distinct layers. These day-to-day seasonal variations in clouds show highest occurrence frequencies during the pre-monsoon (67.94 %) and monsoon (98 %), clearly reflects the onset and active phases of the Indian summer monsoon. Further, July recorded with the highest cloud occurrence frequency (84.03 %), consisting of single-layer (15.92 %), double-layer (25.98 %) and triple-layer (42.13 %) clouds. Our study inferred a high fraction of mid-level (∼3–6 km; 77.53 %) clouds during winter, pre-monsoon, monsoon, and post-monsoon seasons. Thus, altostratus, altocumulus, nimbostratus, or altogether were particularly prominent across all the seasons, with their variability linked to orographic and climatic factors.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108399"},"PeriodicalIF":4.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144865625","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":"Numerical simulations of a heavy rainfall event in the Sahelian region of Zinder in Niger","authors":"Abdoul Aziz Saidou Chaibou ,&nbsp;Kodjo Gboneh Gratien Edoh ,&nbsp;Soliou Kègnidé Adéchinan Gbadamassi ,&nbsp;Marisol Obono Ndong Abogo ,&nbsp;Inoussa Abdou Saley ,&nbsp;Isaac Kwesi Nooni ,&nbsp;Ibrah Seidou Sanda ,&nbsp;Moussa Mounkaila Saley ,&nbsp;Muhammad Ilyas Abro ,&nbsp;Boubacar Moumouni Kaougé ,&nbsp;Ousmane Baoua ,&nbsp;Gaptia Lawan Katiellou ,&nbsp;Adamou Ousmane Manga ,&nbsp;Dungall Laouali ,&nbsp;Maixent Olivier Claver Kambi","doi":"10.1016/j.atmosres.2025.108398","DOIUrl":"10.1016/j.atmosres.2025.108398","url":null,"abstract":"<div><div>Reliable modeling of heavy rainfall events is required for accurate flood prediction. This study evaluated the performance of the Weather Research and Forecasting (WRF) model in simulating heavy rainfall events that occurred on July 17, 2022 in the Sahelian region of Zinder in Niger. We performed a sensitivity study using various cumulus and microphysical schemes. We evaluated the reliability of the WRF model using different statistical approaches, including the probability of detection, false alarm ratio, success ratio, frequency bias, and critical success index. At the synoptic scale, atmospheric conditions were favorable for heavy precipitation in the Zinder region. Intense moisture transport from the southwest, high precipitable water values (≥ 50 kg/m²), strong wind shear (10–15 m/s) and convective instability indicators (high K index and low convective inhibition) contributed to the initiation and intensification of convection. Outgoing longwave radiation (OLR) analysis confirmed the presence of strong convective activity and an active easterly wave, which strengthened the organization of convective systems. The evaluation analysis showed that the model effectively captured the spatial pattern of heavy rainfall in all ensemble member simulations. When combined with the Purdue Lin (PL), Morrison-2 moment (M2), and New Thomson (TS) microphysical schemes, the Tiedkte (TK) cumulus scheme outperformed other convective schemes. The WRF model has the potential to improve the prediction of heavy rainfall events in Niger and to inform decision-making processes.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108398"},"PeriodicalIF":4.4,"publicationDate":"2025-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144763974","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 station, satellite, & combined data for XGBoost-based visibility forecast","authors":"Michaela Schütz,&nbsp;Adrian Schütz,&nbsp;Jörg Bendix,&nbsp;Jonas Müller und Boris Thies","doi":"10.1016/j.atmosres.2025.108395","DOIUrl":"10.1016/j.atmosres.2025.108395","url":null,"abstract":"<div><div>Radiation fog poses challenges for the very short-term weather forecasting due to its complex atmospheric dynamics. Accurate and spatially available visibility predictions are crucial for sectors where visibility conditions directly impact safety and operational efficiency. Traditional numerical weather prediction models lack real-time forecasting capabilities, so this study investigates a machine-learning-based visibility forecast with XGBoost for a station in Germany. Two data sources were used and compared: high-resolution station data and nationwide available Meteosat Second Generation (MSG) satellite data. The analysis investigates how the coarser spatial resolution of MSG data compares to finer station data in predicting fog formation and dissipation. Therefore, station-based predictors were substituted with MSG satellite data. Additionally, the study addresses data imbalances during training and evaluation by focusing on critical low-visibility conditions and specifically fog formation and dissipation. XGBoost significantly outperforms the three baseline models – pure visibility driven forecast, Persistence Model and Linear Regression. The mean absolute error (MAE) is less than 150 m in the low visibility range. For the predominantly MSG-variable-based model only 3 % of fog formations and 6 % of fog dissipations are completely missed. Furthermore, the MSG-model predicts 50 % of fog formations and 60 % of dissipations within the 30-min window of their actual occurrence. The model utilizing MSG data as substitutes for station-based predictors delivers comparable performance to the purely station-data-based forecast highlighting the potential of area-wide accessible MSG data. However, visibility measurements remain necessary for forecasting. Therefore, future research should develop satellite-derived products to replace visibility, enabling fully spatial forecasts.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108395"},"PeriodicalIF":4.4,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830378","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":"The impact of assimilating FY-3E MWHS-2 within 3DEnVar with surface humidity control variable on the forecast of Typhoon Doksuri","authors":"Feifei Shen ,&nbsp;Xiaolin Yuan ,&nbsp;Haiyan Fei ,&nbsp;Changliang Shao ,&nbsp;Dongmei Xu ,&nbsp;Qilong Sun","doi":"10.1016/j.atmosres.2025.108394","DOIUrl":"10.1016/j.atmosres.2025.108394","url":null,"abstract":"<div><div>In this study, FY-3E MWHS-2 radiance data are assimilated using the Hybrid Three-Dimensional Ensemble Variational (3DEnVar) data assimilation (DA) system with surface humidity (SH) coupled as an extended control variable to investigate the impact on the forecast and analysis of typhoon Doksuri. The efficiency of adjusting low level humidity is confirmed by a single temperature observation test. Nine experiments were conducted to assess the impact of coupled versus uncoupled SH configurations on the data assimilation system performance, and the effect of different weights assigned to the flow-dependent background error covariance on forecast accuracy. The results show that the assimilation of FY-3E MWHS-2 data within the 3DEnVar system coupled SH significantly improves the accuracy of typhoon forecasts. This improvement is particularly evident in the forecasted track, central pressure, and maximum wind speed. In this study, the optimal weight of the flow-dependent background error covariance was determined to be 50 %, which resulted in the lowest average errors in track (36.73 km), central pressure (17.37 hPa), and maximum wind speed (−11.56 m/s). Moreover, the DA system coupled SH demonstrated better performance in reducing the root mean square error (RMSE) and BIAS across the zonal component of wind (U-wind), meridional component of wind (V-wind), temperature, and specific humidity. Additionally, the introduction of SH has positively influenced the simulation of precipitation distribution and intensity, it specifically improves the simulation accuracy for precipitation events with a 24-h accumulated amount exceeding 25 mm.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108394"},"PeriodicalIF":4.4,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144763892","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":"Impact of preceding Arctic Oscillation anomaly on the zonal displacement of the South Asian High in July","authors":"Jiakang Duan ,&nbsp;Jilin Zhou ,&nbsp;Ruixiang Zhang ,&nbsp;Hao Wu ,&nbsp;Tao Wang ,&nbsp;Jiali Luo","doi":"10.1016/j.atmosres.2025.108393","DOIUrl":"10.1016/j.atmosres.2025.108393","url":null,"abstract":"<div><div>Using various observations and the linear baroclinic model (LBM), this study investigates the impact of out-of-phase variations in the Arctic Oscillation (AO) between March and April on the zonal shift of the South Asian High (SAH) in July. The results indicate that a negative AO in March followed by a positive AO in April can lead to an eastward shift of the SAH in July, and vice versa. This out-of-phase AO variation accounts for approximately 23 % of the interannual variation in the zonal shift of the SAH in July. Further analysis reveals that a negative AO in March induces positive sea surface temperature (SST) anomalies over the high-latitude North Atlantic by modulating surface heat fluxes and zonal SST advection. In April, the atmospheric circulation associated with the positive AO causes positive SST anomalies to develop to the west of Europe. Due to the ocean memory effect, these positive SST anomalies persist into July, leading to positive geopotential height anomalies in the troposphere and lower stratosphere over Northern Europe in July through eddy-mediated processes. The vorticity anomalies associated with the geopotential height anomalies trigger Rossby wave trains over Eurasia, characterized by negative geopotential height anomalies over the northwestern SAH and positive geopotential height anomalies over the eastern SAH, ultimately resulting in an eastward shift of the SAH.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108393"},"PeriodicalIF":4.4,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144756697","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":"Comparisons of gas-PM2.5 and gas-TSP partitioning of non-polar organic molecular makers in northern Nanjing, China","authors":"Wei Feng,&nbsp;Guihong Dong,&nbsp;Wanqing Qi,&nbsp;Mingjie Xie","doi":"10.1016/j.atmosres.2025.108392","DOIUrl":"10.1016/j.atmosres.2025.108392","url":null,"abstract":"<div><div>The gas-particle (G-P) partitioning of semi-volatile organic compounds has been commonly investigated by simultaneously measuring their concentrations in the gas and particle phases, but the effects of coarse particles were not well known. In this study, collocated gas-PM_2.5 and gas-TSP samples were collected in the suburbs of Nanjing, a typical megacity in the Yangtze River Delta in China, and analyzed for non-polar organic molecular markers (NP-OMMs), including n-alkanes, polycyclic aromatic hydrocarbons (PAHs), oxygenated PAHs (oxy-PAHs), and steranes and hopanes. Except for low-volatility n-alkanes (vapor pressure &lt; 10⁻¹⁰ atm), all other groups of NP-OMMs in paired PM_2.5 and TSP samples had comparable median concentrations, and the concentration time series of PAHs, oxy-PAHs, and steranes and hopanes were strongly correlated (<em>r</em> &gt; 0.80, <em>p</em> &lt; 0.01). Based on the collocated measurements of gaseous samples, the relative uncertainties for the concentrations of grouped n-alkanes and oxy-PAHs (17.3 %–27.7 %) are greater than for the PAHs (12.4 %–21.3 %). The mean particulate fractions of the grouped NP-OMMs were almost identical between gas-PM_2.5 and gas-TSP samples, indicating a weak influence of coarse particles on the distribution of NP-OMMs in the gas and particle phases in Nanjing. Whenever the gas-PM_2.5 or gas-TSP data were used to validate the prediction of G-P partitioning coefficients, the partitioning of gaseous n-alkanes and PAHs into the particle phase was majorly driven by absorption and adsorption mechanisms, respectively. When coarse particles were considered for the prediction of the G-P partitioning of PAHs, less liquid-like sorption had to be assumed.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108392"},"PeriodicalIF":4.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750251","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":"An evaluation of sub-daily precipitation simulations from a new high-resolution regional atmospheric reanalysis ALADIN","authors":"Vojtěch Bližňák ,&nbsp;Petr Zacharov ,&nbsp;Robert Kvak ,&nbsp;Aart Overeem","doi":"10.1016/j.atmosres.2025.108391","DOIUrl":"10.1016/j.atmosres.2025.108391","url":null,"abstract":"<div><div>This transboundary study evaluates the ability of the new high-resolution atmospheric reanalysis ALADIN to simulate sub-daily precipitation totals in the Czech Republic, Germany and, the Netherlands during 18 warm seasons (April–October) from 2002 to 2019. Specifically, the evaluation is performed separately for two numerical weather prediction (NWP) model runs. The first, ALADIN/Reanalysis, includes the full assimilation of the observed data every 6 h using a digital upper-air filter, which combines the high-resolution ALADIN guess with ERA5, the result of a global 4D variational analysis. The second, ALADIN/Evaluation Run, is also driven by ERA5 but uses no surface data assimilation. The evaluation is performed on an hourly basis with a horizontal grid spacing of 2.3 km (total = 215,169 km²) compared with observational data represented by gauge-adjusted radar precipitation measurements. The results show that simulated seasonal precipitation sums are overestimated by an average of 20 % (ALADIN/Reanalysis) and 23 % (ALADIN/Evaluation Run) compared to observations. The overestimation is usually greater in higher-elevation areas such as the Alps and the Black Forest in southern Germany or the Ore Mountains and the Giant Mountains in the Czech Republic. On the other hand, precipitation sums for the Netherlands appear to be the most accurate, with overestimations of less than 20 % for both NWP model runs. The main reason for higher seasonal precipitation sums is the large number of very low hourly precipitation totals (i.e., &lt; 0.1 mm) in the reanalysis. Once filtered out, the mean precipitation totals are typically underestimated throughout the diurnal cycle, especially in higher-elevation areas. In addition, maximum values of convective precipitation in mountainous regions are simulated in the morning, while their actual occurrence prevails in the afternoon when the warming of the Earth's surface culminates. In contrast, the frequency of high hourly precipitation totals is underestimated in both model runs, as evident from the frequency of 24 mm precipitation totals in the ALADIN/Reanalysis and 29 mm in the ALADIN/Evaluation Run. The underestimation is less evident in the ALADIN/Evaluation run, which can produce higher hourly precipitation totals than the ALADIN/Reanalysis run. Additionally, the results show that reanalysis can more plausibly simulate long-term stratiform precipitation events than purely convective events or stratiform events with embedded convection.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108391"},"PeriodicalIF":4.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144738261","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":"Hierarchical clustering for diurnal cycles of lightning using LIS satellite data","authors":"Huangjie Kong,&nbsp;Li Cai,&nbsp;Wenchao Fan,&nbsp;Jianguo Wang,&nbsp;Jinxin Cao,&nbsp;Mi Zhou,&nbsp;Yadong Fan","doi":"10.1016/j.atmosres.2025.108390","DOIUrl":"10.1016/j.atmosres.2025.108390","url":null,"abstract":"<div><div>This article harnesses data from the Lightning Imaging Sensor (LIS) to explore global diurnal cycles of lightning (DCL) spanning the period from 1998 to 2015. Lightning parameters—frequency, radiance, and footprint—were standardized to a 0.5° × 0.5° resolution grid and segmented into distinct diurnal patterns using the Bisecting K-Means algorithm. Across these patterns, significant differences emerge between ocean and land lightning activity. Globally, lightning frequency demonstrates a unimodal variation, reaching a peak at 16:00 and a valley at 10:00, driven by solar heating of the landmass and contributed to predominantly by lightning over land. The land/ocean frequency ratio shifts dynamically throughout the day, ranging from 0.70 to 11.36. Ocean lightning consistently shows higher radiance and footprint than land. The ocean/land radiance and footprint ratio follow a similar diurnal trend as frequency, ranging from 1.33 to 2.22 and from 1.16 to 1.39, respectively. Clustering analysis underscores the contrasting dynamics of land and ocean, with ocean lightning concentrated during nighttime hours, while land lightning peaks in the afternoon and evening. Transitional zones with distinct clusters are observed along the coastline. Furthermore, DCLs reveal differences across the three lightning parameters: frequency trends are more temporal concentrations, whereas radiance and footprint clusters span broader time periods. DCLs exhibit pronounced spatial heterogeneity across latitude, distance from coastline, and elevation. The clustering patterns shift at different critical latitudes for each parameter, with hemispheric asymmetry in distribution patterns. Clusters exhibit distinct distance-variation patterns over land and ocean, with nocturnal activity patterns becoming dominant with increasing elevation. This study fills a pivotal gap in global DCL research and provides important clues for studying lightning mechanisms, thereby contributing to the development of effective global lightning protection strategies.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108390"},"PeriodicalIF":4.4,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144738262","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":"Variability of submicron ice-nucleating particles at urban and rural sites in Japan related to aerosol chemical components","authors":"Ayumi Iwata ,&nbsp;Samuel Gray Murray Horwitz ,&nbsp;Kazuki Kurihara ,&nbsp;Atsushi Matsuki ,&nbsp;Tomoaki Okuda","doi":"10.1016/j.atmosres.2025.108386","DOIUrl":"10.1016/j.atmosres.2025.108386","url":null,"abstract":"<div><div>Ice-nucleating particles (INPs) play a pivotal role in cloud formation and precipitation, yet predicting their concentrations remains difficult due to limited understanding of their spatiotemporal variability and characteristics. Therefore, it is important to provide insights into how aerosol properties and meteorological parameters are related to INP concentrations. This study investigated INP concentrations, their heat sensitivity, particle chemical components, and meteorological parameters at urban (Yokohama) and rural (Noto) sites in Japan during Dust and Non-Dust periods. While no single key factor consistently explained INP concentrations, relatively strong associations were observed with factors implying particles such as mineral dust, heat-sensitive biological particles, and Pb-containing particles from coal and waste combustion, with variations depending on site and season. During the Dust period, INP concentrations at both sites were correlated with the mineral indicators (<em>R</em> &gt; 0.57), though INPs above −15 °C remained low at Noto site (<em>R</em> = 0.49). In the Non-Dust period, mineral indicators cannot account for INP levels at either site (<em>R</em> &lt; −0.31). Heat treatment-induced deactivation of INPs above −15 °C in the urban area suggested a close association between biological INPs and mineral particles. Although submicron INPs account for only a small fraction of total INPs at the surface (e.g., &lt; 6.5 % at −12.5 °C), the particle types that contributed to the variability in INP concentrations were nevertheless supported previous qualitative findings. Our findings also highlight the complexity of quantitatively linking environmental factors that vary by region and time to INP concentration variations to characterize aerosol–cloud interactions.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108386"},"PeriodicalIF":4.4,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750179","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}