Atmospheric Research最新文献

{"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":"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":"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":"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}

{"title":"Convective cold pools and attendant turbulence at the Amazon Tall Tower Observatory (ATTO)","authors":"Maurício I. Oliveira ,&nbsp;Luca Mortarini ,&nbsp;Otávio C. Acevedo ,&nbsp;Iván Mauricio Cely-Toro ,&nbsp;Martina Grosso ,&nbsp;Luciane I. Reis ,&nbsp;Cléo Q. Dias-Júnior ,&nbsp;Carlos A. Quesada ,&nbsp;Bruno Z. Ribeiro ,&nbsp;Daiane V. Brondani","doi":"10.1016/j.atmosres.2025.108351","DOIUrl":"10.1016/j.atmosres.2025.108351","url":null,"abstract":"<div><div>Deep moist convection significantly disturbs the evolution of the planetary boundary layer (PBL) through its convective cold pools (CCPs). This study investigates the statistics of CCPs and their impact on PBL turbulence as observed at the Amazon Tall Tower Observatory (ATTO) site. To obtain a large dataset of CCPs, we adapted an existing CCP-detection algorithm for use in multilevel, micrometeorological data. Application of the algorithm to ATTO observations collected from August 2021 through December 2023 resulted in a dataset consisting of 410 CCPs. CCPs occur nearly every other day at the ATTO site, although they are most common from April through September and are least common from December through March. The occurrence of CCPs is linked to the diurnal cycle of the PBL, with more events around 1800 UTC and the less events around 1100 UTC. The strength of CCP perturbations varies strongly as a function of the distance from the canopy. Above the canopy (approximately 37 m), CCPs exhibit well-defined gust fronts, marked by sharp drops in temperature and humidity, gusting winds, overturning circulations, and pressure rises. During gust front passages, sensible (latent) heat fluxes are briefly enhanced and subsequently invert sign (weaken) in the CCPs, as previously unstable (moister) PBLs become stable (drier). Turbulence is stronger and more anisotropic during gust fronts and just above the canopy due to mechanical drag. Anisotropic turbulence may be transported upward to 200 m by the gust fronts. Below the canopy, CCPs and attendant perturbations are drastically damped, except in high-end cases.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108351"},"PeriodicalIF":4.5,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702888","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":"A preliminary study of FY-4B AGRI all-sky assimilation by WRFDA for tropical cyclones","authors":"Chun Yang ,&nbsp;Tingting Zhong ,&nbsp;Jinzhong Min","doi":"10.1016/j.atmosres.2025.108377","DOIUrl":"10.1016/j.atmosres.2025.108377","url":null,"abstract":"<div><div>A new assimilation module for AGRI (Advanced Geostationary Radiation Imager) carried on Fengyun-4B (FY-4B) is developed within the WRFDA (Weather Research and Forecasting model's Data Assimilation) system. The impacts of assimilating FY-4B AGRI clear-sky and all-sky data are evaluated with cycling assimilation experiments for the typhoon Doksuri (2023) and Talim (2023) forecast. For typhoon Doksuri, compared with the benchmark experiment, AGRI assimilation brings a better analysis and forecast for atmospheric variables (wind, temperature and humidity). Meanwhile, clear error reductions for typhoon track and intensity forecasts are achieved with clear-sky and all-sky AGRI assimilation. The positive impact on landing precipitation prediction is also obtained by verifying with GPM (Global Precipitation Measurement) precipitation data. Moreover, AGRI all-sky assimilation yields better typhoon forecasts than clear-sky assimilation. In addition, the channel selection sensitivity for AGRI assimilation is also assessed with group experiments. It is suggested that with the assimilation of a new water vapor channel at 7.42 <span><math><mi>μm</mi></math></span>, which is newly added in FY-4B, multiple-channel assimilation shows greater benefit for forecast than single-channel assimilation. The same positive impact of AGRI assimilation is also present in typhoon Talim (2023) forecast. Overall, the all-sky assimilation of FY-4B AGRI water vapor channels data is beneficial for the typhoon forecast.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108377"},"PeriodicalIF":4.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144664683","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":"Raindrop size distribution of monsoon and tropical cyclone events over South China","authors":"Ruize Lai,&nbsp;Sheng Hu,&nbsp;Xiantong Liu,&nbsp;Hui Xiao,&nbsp;Huiqi Li","doi":"10.1016/j.atmosres.2025.108376","DOIUrl":"10.1016/j.atmosres.2025.108376","url":null,"abstract":"<div><div>The rainy season in South China is predominantly influenced by monsoon and tropical cyclone (TC) weather systems. However, due to the lack of long-term observational data, the microphysical characteristics of raindrop size distributions (DSDs) associated with these systems remain insufficiently understood. This study utilizes five years (2016–2020) of 2DVD observations to analyze the differences in DSD characteristics of monsoon and TC rainfall. The results indicate that monsoon rainfall exhibits higher concentrations of medium to large raindrops (diameter <span><math><mo>&gt;</mo></math></span> 2.1 mm), along with larger mean rainfall rates (<em>R</em>) and mass-weighted mean diameters (<em>D</em>_<em>m</em>), but lower normalized intercept parameters (<em>N</em>_<em>w</em>) compared to TC rainfall. Distinct differences in the mean normalized DSDs are observed between monsoon and TC rainfall. Convective rain under both systems shows the characteristics of maritime convective rain. Additionally, the relationships between kinetic energy (KE) and <em>R</em>, KE and <em>D</em>_<em>m</em>, as well as radar reflectivity (<em>Z</em>) and <em>R</em>, differ between monsoon and TC rainfall. TC events have relatively humid atmospheric conditions and higher wind speeds, resulting in the presence of a large number of small raindrops. These findings enhance understanding of the DSD characteristics under different synoptic regimes and provide valuable implications for improving rainfall KE estimation, DSD retrieval, and quantitative precipitation estimation over South China.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108376"},"PeriodicalIF":4.5,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144664715","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":"Long-term validation and error analysis of MODIS and VIIRS dark target aerosol products in Africa","authors":"Xiaoxia Xue ,&nbsp;Leiku Yang ,&nbsp;Ping Zhang ,&nbsp;Muhammad Bilal ,&nbsp;Weiqian Ji ,&nbsp;Xin Pei ,&nbsp;Yizhe Fan ,&nbsp;Xiaofeng Lu ,&nbsp;Xiaoqian Cheng","doi":"10.1016/j.atmosres.2025.108372","DOIUrl":"10.1016/j.atmosres.2025.108372","url":null,"abstract":"<div><div>This study reports the accuracy and uncertainty of aerosol optical depth (AOD) retrievals for the dark target (DT) algorithm over Africa. Three AOD products from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), the NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS), and the Suomi-NPP (SNPP) VIIRS were evaluated against ground-based Aerosol Robotic Network (AERONET) observations during the period from 2018 to 2023. The validation results indicate that all three products show good validation accuracy in northern Africa, with a slight underestimation in southern Africa. However, it is worth noting that a severe systematic underestimation was observed for all three products in western Africa. Although the correlation coefficients (R) between these three products and the AERONET observations in western Africa are all greater than 0.9, they exhibit significant negative mean biases (MB) of less than −0.18 and root mean square errors (RMSE) exceeding 0.25. Subsequently, an in-depth analysis of error dependence was conducted to explore the underlying causes of this underestimation in this region. The analysis reveals that the aerosol model assumptions and surface reflectance estimation in the DT algorithm jointly lead to this underestimation. Specifically, the underestimation is more pronounced under conditions of strongly absorbing aerosols and sparse vegetation surfaces with high reflectance. Additionally, it was found that as the scattering angle (SCA) increases, the degree of AOD underestimation also intensifies. These results provide critical insights to guide the ongoing refinement of the DT algorithm in western Africa.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"327 ","pages":"Article 108372"},"PeriodicalIF":4.5,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144664953","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}