Atmospheric Research最新文献

{"title":"Enhancing 5-day particulate matter (PM10) forecasts in Morocco using U-net: A deep learning approach","authors":"Anass Houdou ,&nbsp;Kenza Khomsi ,&nbsp;Luca Delle Monache ,&nbsp;Weiming Hu ,&nbsp;Saber Boutayeb ,&nbsp;Lahcen Belyamani ,&nbsp;Fayez Abdulla ,&nbsp;Imad el Badisy ,&nbsp;Wael K. Al-Delaimy ,&nbsp;Mohamed Khalis","doi":"10.1016/j.atmosres.2025.108439","DOIUrl":"10.1016/j.atmosres.2025.108439","url":null,"abstract":"<div><div>Accurately predicting particulate matter is crucial for preventing health risks and protecting public health. This study improves the accuracy of particulate matter <span><math><mi>d</mi><mo>≤</mo><mn>10</mn><mspace></mspace><mi>μm</mi></math></span> (<span><math><msub><mi>PM</mi><mn>10</mn></msub></math></span> <!-->) forecasts over Morocco for the next five days using a U-Net-based deep learning model, marking the first work of its kind in the Middle East and North Africa (MENA) region. The U-Net model was used to post-process and improve <span><math><msub><mi>PM</mi><mn>10</mn></msub></math></span> forecasts from the Copernicus Atmosphere Monitoring Service (CAMS), with reanalysis data from CAMS serving as a reference to guide the model's learning. The U-Net architecture was modified to predict outputs at a resolution different from the inputs, eliminating the need for interpolation and preserving critical spatial details. The results demonstrated significant improvements over two baselines—CAMS forecasts and the Analog Ensemble model (AnEn)—by enhancing metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Coefficient of Determination (<span><math><msup><mi>R</mi><mn>2</mn></msup></math></span>), Index of Agreement (IOA), and biases, particularly in regions prone to dust storms, during the period prior to the CAMS forecast upgrade in mid-2023. In the second half of 2023, U-Net continued to improve predictions; however, the effect of the upgrade cycle became evident in its errors. This highlights the importance of retraining U-Net with updated data as it becomes available to maintain its reliability in operational forecasting systems. U-Net also proved effective in capturing particulate pollution, providing reliable predictions for values up to 500 <span><math><mi>μg</mi><mo>/</mo><mi>m</mi><mn>3</mn></math></span>. These findings underscore U-Net's potential for operational forecasting, supporting accurate early warnings to mitigate the health and environmental impacts of <span><math><msub><mi>PM</mi><mn>10</mn></msub></math></span> <!--> pollution.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108439"},"PeriodicalIF":4.4,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895875","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":"Evaluation of high-resolution WRF simulation in urban areas — Effect of different physics schemes on simulation performance in the Rhine-Main-Neckar area","authors":"Lukas Pilz ,&nbsp;Christopher Lüken-Winkels ,&nbsp;Michał Gałkowski ,&nbsp;David Ho ,&nbsp;Christoph Gerbig ,&nbsp;Fei Chen ,&nbsp;Sanam N. Vardag","doi":"10.1016/j.atmosres.2025.108435","DOIUrl":"10.1016/j.atmosres.2025.108435","url":null,"abstract":"<div><div>Quantifying and minimizing atmospheric transport errors is key to improve meteorological modeling and to better estimate urban greenhouse gas (GHG) and air pollution emissions from measurements. The Weather Research and Forecasting Model (WRF) model has been used to simulate urban atmospheric transport in many cities globally and there exist various possible configurations especially concerning choice of physics schemes, which influence the quality of the atmospheric simulation. Here, we conduct a comprehensive evaluation of WRF on 1<!--> <!-->km resolution for a polycentric European metropolitan area, namely the Rhine-Main-Neckar area by varying Land Surface Model (LSM), Surface Layer Model (SLM), Planetary Boundary Layer (PBL) and urban parametrization scheme configurations. We compare four month-long simulations to 2<!--> <!-->m temperature, 10<!--> <!-->m wind velocity and wind direction measured at 19 stations operated by the German Weather Service and to PBL height derived from radiosonde data at two locations. By showing kernel density functions in a Taylor diagram, we show the average performance of the schemes as well as the spread across different stations. We find that while the 2<!--> <!-->m temperature and PBL height performance are most sensitive to choice of urban parametrization scheme, 10<!--> <!-->m wind velocity and direction are most sensitive to choice of PBL scheme. Good overall performance was achieved using the Single-Layer Urban Canopy Model (SLUCM), Mellor-Yamada-Janjic (MYJ), Noah-Multiparametrization Land Surface Model (Noah-MP) and Monin-Obukhov (Janjic) (MO) schemes. While the ensemble spread is larger in winter than in summer, the choice of optimal scheme does not depend strongly on the season.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108435"},"PeriodicalIF":4.4,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144897999","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":"Convection initiation over central–eastern China: Statistics show higher frequencies over mountains with less stringent atmospheric conditions and more heterogeneous surface characteristics","authors":"Qian Wei ,&nbsp;Jianhua Sun ,&nbsp;Xianhong Meng ,&nbsp;Yuanchun Zhang ,&nbsp;Linlin Zheng ,&nbsp;Zheng Ma","doi":"10.1016/j.atmosres.2025.108438","DOIUrl":"10.1016/j.atmosres.2025.108438","url":null,"abstract":"<div><div>A total of 11,646 convection initiation (CI) events (CIEs) were identified during the warm seasons (May to September) from 2016 to 2020 in the middle reaches of the Yangtze River Basin (MR-YRB), using a CI identification method and composite reflectivity (CR) data. CI occurs more frequently in July and August, accounting for 62.7 % of the total CIEs, and predominantly between 11:00 to 16:00 Beijing Time (BJT), representing 62.2 % of the total CIEs. These events are distributed across different terrains, including mountains (elevations exceeding 400 m), foothills (elevations ranging from 100 to 400 m), and plains (elevations ranging from 0 to 100 m). The spatial distribution of high-frequency CIE regions is closely associated with mountains within the MR-YRB. Mountains experience twice as many CIEs as plains, even under conditions of weaker instability and vertical wind shear, although these events tend to be smaller and short-lived. In contrast, foothill CIEs exhibit the largest convective areas. A single peak in CI frequency occurs at noon (12:00–13:00 BJT) across all terrain types, coincides with the highest initiation elevations (400–600 m) and largest convective areas under conditions of maximum thermal instability. Heterogeneity in soil moisture (SM, 0–5 cm) and surface heat fluxes (SHF) has potential to play a crucial role in the triggering of noontime CIEs. Mountain CIEs exhibit the highest degree of heterogeneity. They typically occur in regions with higher SM than surrounding areas and proximity to areas with enhanced SHF. Higher SM may provide favorable conditions for CI by increasing low-level moisture and moist static energy at mountain CI sites. Pronounced SM heterogeneity may further promote CI by facilitating either latent or sensible heating processes, which can generate mesoscale thermal circulations in the vicinity of pronounced SM gradients.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108438"},"PeriodicalIF":4.4,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144897973","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":"Future changes of precipitation recycling over Northwest China by CMIP6 models","authors":"Ping Wu ,&nbsp;Xiucang Li ,&nbsp;Yanju Liu ,&nbsp;Ying Xu ,&nbsp;Yihui Ding","doi":"10.1016/j.atmosres.2025.108437","DOIUrl":"10.1016/j.atmosres.2025.108437","url":null,"abstract":"<div><div>This study evaluates the simulation capabilities of 11 CMIP6 global climate models for hydrological cycle components in Northwest China (NWC) during 1995–2014, utilizing ERA5 reanalysis data for validation. Results demonstrate that the CMIP6 ensemble effectively captures spatiotemporal patterns of precipitation, precipitation recycling ratio (ρ), and internal/external cycling precipitation. Subsequent analysis compares projected hydrological changes under SSP1–2.6 (low-emission) and SSP5–8.5 (high-emission) scenarios (2021−2100) against the historical baseline. The findings suggest that NWC is projected to experience a wetter climate in the future, with precipitation increase rates of 0.52 % per decade under the SSP1–2.6 and 3.12 % per decade under the SSP5–8.5. The most rapid intensification occurs in the early 21st century (2021–2040), followed by mid-21st century (2041–2060) deceleration in the growth rate. By the end of the century (2081–2100), precipitation declines under SSP1–2.6 but resurges under SSPP5–8.5, with maximum moistening concentrated in central NWC. Regarding the precipitation recycling rate (ρ), the overall rate in NWC is projected to fluctuate within ±5 % under the SSP1–2.6. In contrast, it is expected to exhibit a fluctuating downward trend under the SSP5–8.5, decreasing by 1.04 % per decade and reaching nearly 5.1 % lower than the baseline period by the end of the 21st century. This indicates progressive weakening of internal cycling under high emissions. Spatially, the distribution of ρ is highly uneven. The internal cycle is expected to increase significantly in the central region of NWC due to the abnormal enhancement of evaporation, while it will gradually weaken over time in other regions. Future precipitation increases primarily derive from the combined effects of internal and external cycling, but is primarily driven by changes in external cycling precipitation (P_o) through enhanced moisture transport. Moreover, under the high emission scenario, the contribution from external cycling demonstrates progressive increase, while internal cycling exhibits gradually weaken. This suggests that as climate warming accelerates in NWC, the rapid ablation of glaciers and snowmelt may lead to a transition from strengthening to weakening of the internal cycle because of the increasing ineffective evaporation. Even if the absolute precipitation increases in the future, the additional moisture may be offset by ineffective evaporation, making it difficult to convert into usable water resources. This poses a severe challenge for future water resource management in NWC.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108437"},"PeriodicalIF":4.4,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144890831","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":"Interdecadal change in the relationship between the NAO and summer rainfall in Northern Central Asia","authors":"Yichen Yang ,&nbsp;Yong Zhao ,&nbsp;Lixia Meng ,&nbsp;Ruibo Zhang","doi":"10.1016/j.atmosres.2025.108430","DOIUrl":"10.1016/j.atmosres.2025.108430","url":null,"abstract":"<div><div>Based on the Climate Research Unit (CRU) monthly rainfall data and the NationalCenters for Environment Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis atmospheric circulation data during 1961–2020, we examine the interdecadal change in the relationship between the North Atlantic Oscillation (NAO) and summer rainfall in northern Central Asia (CA). Results show that the NAO negatively (positively) correlates with summer rainfall in northern CA during 1969–1989 (1990–2010), but it becomes obviously closer in the second period, indicating their relationship has experienced a significant interdecadal change over the past 60 years. The varying relationship between the NAO and summer rainfall in northern CA is caused by the interdecadal change in the NAO-related large-scale circulation anomalies. The positive NAOI is well related to the strengthening subtropical westerly jet over CA, an anomalous cyclone over west of CA and southerly wind prevailing over northern CA and convergences of water vapor occupying the whole northern CA, so the relationship between the NAO and summer rainfall in northern CA has become stronger during 1990–2010. Furthermore analysis suggests that the intensity of subtropical westerly jet over CA plays an important role in linking the NAO and summer rainfall in northern CA. In the first period, the atmospheric teleconnection pattern triggered by the NAO only has weak effects on the subtropical westerly jet over CA, but in the second period it can strongly modulate the change in the intensity of subtropical westerly jet over CA.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108430"},"PeriodicalIF":4.4,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144885716","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":"Assessment of the performance of ground-based and SARAH-3 solar radiation data over Eastern Africa","authors":"Donath Uwanyirigira ,&nbsp;Béatrice Morel ,&nbsp;Chao Tang ,&nbsp;Jörg Trentmann ,&nbsp;Jean Uwamahoro ,&nbsp;Innocent Nkurikiyimfura ,&nbsp;Fabien Habyarimana","doi":"10.1016/j.atmosres.2025.108413","DOIUrl":"10.1016/j.atmosres.2025.108413","url":null,"abstract":"<div><div>Solar radiation can be a potential source of cost-effective and sustainable energy, offering the promise of a clean and safe environment in the East African region. However, reliable solar radiation data remain limited, hindering accurate assessment of the available solar potential and characterisation of the local and regional climate. To address this issue, this study used in situ measurements from 11 ground-based meteorological stations to comprehensively evaluate the performance of the satellite-derived solar radiation product, SARAH-3, across Kenya, Tanzania, Uganda, and Rwanda. Statistical distribution, degree of linear association, explanatory strength, infra-daily, daily, and seasonal cycles were used to assess the degree of similarity. Our findings revealed a significant agreement between surface reference data and SARAH-3 Global Horizontal Irradiance (GHI) data and a significant linear association between bias and the Orographic Complexity Index (OCI) of the neighbour area of the observation points with Pearson’s correlation coefficients (R) of −0.53. At half-hour resolution, in situ measurements and satellite-based solar radiation data revealed high R values, ranging from 0.70 to 0.92, with significant explanatory capacity between 54% and 86%. Percentage bias (PB) was markedly lower than 5% for most stations, except in Rwanda, where PB reached 25%. The distributions of the data sets were generally skewed in the same direction, with a slight difference. Linear association and explanatory capacity improved significantly on the daily time scale, with R exceeding 0.90 and coefficients of determination greater than 78% at all stations. Furthermore, PB and Mean Absolute Error (MAE) were generally low on the monthly scale, except in Rwanda, particularly in Mukarange, where they reached 24.61% and 42.92, respectively. SARAH-3 successfully reproduces infra-daily, daily, and cycles, although its spatial performance is strongly influenced by terrain complexity. These findings confirm the potential of SARAH-3 for solar energy production and climate-related studies in the East African region.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108413"},"PeriodicalIF":4.4,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852071","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":"Detection and attribution of heat waves with the Multivariate Autoencoder Flow-Analogue Method (MvAE-AM)","authors":"Cosmin M. Marina ,&nbsp;Jorge Pérez-Aracil ,&nbsp;Ronan McAdam ,&nbsp;Eugenio Lorente-Ramos ,&nbsp;Niklas Luther ,&nbsp;Eduardo Zorita ,&nbsp;Enrico Scoccimarro ,&nbsp;Jürg Luterbacher ,&nbsp;Elena Xoplaki ,&nbsp;Sancho Salcedo-Sanz","doi":"10.1016/j.atmosres.2025.108409","DOIUrl":"10.1016/j.atmosres.2025.108409","url":null,"abstract":"<div><div>Heat waves (HWs) are complex, multivariate, extreme weather events that cause significant harm to human health, ecosystems, and economies. Correct detection and attribution of HWs to anthropogenic climate change is important to better understand the underlying mechanisms and to improve predictions. In this work, we address this issue and propose a multivariate version of a hybrid approach to reconstruct heat waves, consisting of the AM and deep Autoencoders (MvEA-AM algorithm), improving existing less effective methods used until now, such as the multivariate Analogue Method (MvAM). The proposed hybrid approach produces a more reliable representation of the event than the classical MvAM for reconstructing and attributing HWs in Europe. The explainable and interpretable analysis of the obtained results is based on leveraging the SHapley Additive exPlanations (SHAP) method to explain deep learning algorithms, a capability that is not achievable with the MvAM. This explainability analysis shows that our model learns useful features during the training of the algorithm, which are aligned with the Physics of the problem, and employs the correct features during reconstruction and attribution analysis of the HWs considered.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108409"},"PeriodicalIF":4.4,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144865626","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":"Global 20-year time series of XCO2 concentrations derived from satellite observations and interpolations to analyze XCO2 anomalies caused by wildfires","authors":"Wolfgang M. Wefers ,&nbsp;Dominik Schmidt ,&nbsp;Lukas W. Lehnert ,&nbsp;Maximilian Reuter ,&nbsp;Michael Buchwitz ,&nbsp;Claudia Kammann ,&nbsp;Kai Velten","doi":"10.1016/j.atmosres.2025.108408","DOIUrl":"10.1016/j.atmosres.2025.108408","url":null,"abstract":"<div><div>Accurate, long-term records of atmospheric CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> concentrations are crucial for understanding carbon cycle dynamics and evaluating the impacts of natural and anthropogenic emissions. In this study, we present a global dataset of column-averaged CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> concentrations (XCO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>) covering the period 2003–2022, generated using an enhanced version of the XCO2SAT+ method. This approach integrates satellite observations from four missions (ENVISAT, GOSAT, GOSAT, GOSAT-2 and OCO-2) harmonized through the EMMA v4.5 product, and applies a novel spatio-temporal interpolation algorithm to estimate monthly mean XCO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> values at 23<!--> <!-->958 locations worldwide (<span><math><mo>≈</mo></math></span>95 km grid spacing). The dataset provides XCO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> estimates over global land surfaces and adjacent coastal regions. Validation against 28 TCCON sites yielded a mean absolute error (MAE) of <span><math><mrow><mn>0</mn><mo>.</mo><mn>76</mn><mspace></mspace><mstyle><mi>p</mi><mi>p</mi><mi>m</mi></mstyle></mrow></math></span>, comparable to NOAA’s CarbonTracker model (<span><math><mrow><mi>MAE</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>71</mn><mspace></mspace><mstyle><mi>p</mi><mi>p</mi><mi>m</mi></mstyle></mrow></math></span>). The method reliably reconstructs XCO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> time series even in regions with sparse satellite coverage, while preserving spatial and seasonal variability. As a demonstration, we identify XCO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> anomalies linked to major wildfire events, including North American mega-fires in 2018 and recurring fire activity in tropical northern Africa, with localized monthly anomalies exceeding 2<!--> <!-->ppm–4<!--> <!-->ppm. Comparison with recent machine learning (ML) products confirms that the XCO2SAT+ method achieves higher accuracy across multiple TCCON sites and time frames. This semi-empirical dataset provides a valuable alternative to assimilation-based models, supporting climate research, emission monitoring, and the detection of CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> perturbations from extreme events at high spatial and temporal resolution.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108408"},"PeriodicalIF":4.4,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896022","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":"Microphysical mechanisms of stratiform precipitation with different radar reflectivity profiles in South China: Insights from dual-frequency radar observations","authors":"Qinghui Li ,&nbsp;Zhian Yuan ,&nbsp;Xuejin Sun","doi":"10.1016/j.atmosres.2025.108403","DOIUrl":"10.1016/j.atmosres.2025.108403","url":null,"abstract":"<div><div>Investigating radar reflectivity profiles below the freezing level helps improve surface rainfall estimation. In South China, stratiform rain is common, but the microphysical processes and key factors behind its vertical structure variations are still unclear. Based on ground-based dual-frequency radar observations from Longmen in South China, this study categorizes stratiform precipitation into three types: growth, stable, and evaporative, and examines their formation mechanisms. The results indicate that growth-type precipitation is primarily driven by weak updrafts (0 <span><math><mo>∼</mo></math></span> 0.5 m/s), which prolong the residence time of raindrops in the warm cloud layer (temperature above 0 °C), enhancing coalescence growth and leading to increased reflectivity to ground. Stable-type precipitation occurs in a high-humidity environment (<span><math><mrow><mo>&gt;</mo><mn>90</mn><mtext>%</mtext></mrow></math></span>), which suppresses raindrop evaporation, resulting in minimal vertical variation in the reflectivity profile. In contrast, evaporative-type precipitation is closely associated with lower relative humidity (<span><math><mrow><mn>70</mn><mtext>%</mtext><mo>∼</mo><mn>90</mn><mtext>%</mtext></mrow></math></span>), with a pronounced decrease in reflectivity. Although both stable and evaporative precipitation are accompanied by downdraft (0 <span><math><mo>∼</mo></math></span> 0.5 m/s), the difference in relative humidity (maximum difference exceeds 20%) is the key factor driving the distinct reflectivity profile between the two types, while the influence of air motion is relatively secondary.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108403"},"PeriodicalIF":4.4,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922835","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":"Effect of the southeastern Tibetan Plateau heat forcing on the tropical easterly jet in boreal summer","authors":"Xuejiao He ,&nbsp;Yuanyuan Guo ,&nbsp;Sihua Huang ,&nbsp;Xiaodan Chen ,&nbsp;Zhiping Wen","doi":"10.1016/j.atmosres.2025.108429","DOIUrl":"10.1016/j.atmosres.2025.108429","url":null,"abstract":"<div><div>As a strong upper-tropospheric easterly jet stream over the Afro-Australian monsoon region, the tropical easterly jet (TEJ) originates from the meridional thermal contrast between the Asian landmass, the Tibetan Plateau (TP) in particular, and the tropical Indian Ocean in boreal summer. Here, we find that the atmospheric heat source anomaly over the southeastern TP can induce an opposite response of the upper-tropospheric zonal wind over the western Pacific, where the TEJ usually inflows and manifests as the double easterly jets. Positive TP heating anomaly could accelerate the northern branch of double easterly jets and decelerate the southern one, and vice versa. Two pathways linking the TP heating and the TEJ are proposed. First, positive heat forcing over the southeastern TP can directly induce the easterly responses over the South Asia by the thermal wind which is mainly determined by the changed meridional temperature gradient. The associated easterly response significantly accelerates the northern part of the TEJ. The other pathway suggests that the TP heating will indirectly modulate the southern branch of double easterly jets by changing the thermal condition over the western North Pacific (WNP). The negative WNP heat anomaly exerts a pair of upper-level cyclones straddling the equator with anomalous westerly in between, primarily decelerating the south branch of the double easterly jets over the Maritime Continent. Our findings suggest the TP heating anomaly significantly influences the upper-tropospheric TEJ, especially the double jets in its inflow region, advancing understanding of the TEJ variability and the Asian summer monsoon dynamics.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"328 ","pages":"Article 108429"},"PeriodicalIF":4.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842460","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}