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국제학술지

공지 (2026. 6. 1.)

현재까지 출판된 논문 목록입니다. 아직 준비 중인 논문은 포함하지 않은 점 참고 바랍니다.

Human-induced westerly jet shifts coordinate terrestrial productivity at the hemispheric scale

Accepted for publication.
- 작성자Yang et al.
- 작성일2026.05.26
- 조회수40
- 2026
Machine learning estimation of aerosol size distributions from meteorological data in the western Himalayas

Abstract Aerosol particle number size distribution (PNSD) measurements are fundamental for quantifying aerosol dynamics, as they govern processes such as new particle formation (NPF), coagulation, and the contribution of particles to cloud condensation nuclei (CCN), thereby influencing aerosol–cloud–climate interactions. However, in the Himalayan region of India, such measurements are particularly challenging due to complex terrain, strong vertical mixing, variable boundary layer dynamics, and limited observational coverage, further compounded by instrumental constraints and uncertainties in inversion techniques that can lead to incomplete or unrealistic datasets. Therefore, modeling approaches are essential for complementing observations and improving size-resolved aerosol characterization. In this study, observations were carried out at the high-altitude Himalayan Cloud Observatory (HCO; 30.34°N, 78.40°E, 1706 m AMSL) in Uttarakhand from 1 January to 31 December 2021. A feed-forward neural network (FFNN) model was developed using configurations with two hidden layers and 2–25 neurons, trained on 5-minute, hourly, and daily datasets to estimate particle number concentrations across different size bins using meteorological parameters. The optimal configuration (two layers with nine neurons) yielded moderate performance (R² = 0.22–0.45), with the highest accuracy at 27.4 nm and the lowest at 48.7 nm. The model demonstrates better performance for nucleation-mode particles, likely due to their relatively simple formation mechanisms associated with NPF, whereas Aitken- and accumulation-mode particles are influenced by multiple sources and complex growth processes. Diurnal analysis reveals a bimodal pattern in particle number concentrations, characterized by a short-lived morning peak and a more sustained evening peak. The model tends to overestimate concentrations from midnight to midday, while relatively improved performance is observed during the evening hours (16:00–21:00). This enhanced performance during the evening is likely associated with the prolonged increase in total particle concentrations, along with comparatively smoother variations in meteorological parameters, which together contribute to more stable and consistent model predictions. Seasonally, better model performance is observed during relatively stable winter and pre-monsoon periods, whereas increased fluctuations in meteorological parameters during the monsoon and post-monsoon periods introduce greater uncertainty. Stable wind speeds (1–2 m s⁻¹) from southeast to southwest directions further support improved predictions. Lower performance for finer particles is attributed to their dynamic behavior and higher removal rates in the atmosphere. Overall, further improvement in model performance requires incorporating longer-term and higher-resolution observational datasets, which would enhance training robustness and better capture the complex variability of aerosol processes in the region.
- 작성자Gautam et al.
- 작성일2026.05.26
- 조회수34
- 2026
Ontogeny of dwarf tropical cyclones in the western North Pacific

Abstract Destructive tropical cyclones (TCs) have recently been observed to develop despite strong vertical wind shear and cause catastrophic damages. This study investigates the properties of dwarf (or shallow) TCs which form under strong-shear conditions (≥ 13 m s−1) at the time of genesis, using 444 TCs over the western North Pacific for the period 2003–2022. The TCs are stratified by vertical wind shear magnitude to explore the climatology of TCs at genesis. The dwarf TCs generally have shorter life spans and weaker peak intensities compared to the normal TCs formed in weak-shear environments. The dynamics governing the dwarf and normal TC genesis are compared by analyzing the terms in the azimuthally-averaged tangential wind tendency equation. The difference between the dwarf and normal TCs occurs in the mean terms of the equation: the mid-tropospheric mean outflow of absolute vorticity and the vertical transport of the tangential wind gradient are stronger in the dwarf TCs than the normal TCs. Ultimately, the strong inward low-tropospheric winds in dwarf TCs enhance their tangential winds, causing the near-surface wind to reach 17 m s−1, the TC threshold.
- 작성자Yoo et al.
- 작성일2026.05.26
- 조회수40
- 2026
Disentangling key cloud properties for precipitation retrievals from geostationary satellite data using machine learning

Abstract Cloud properties governing precipitation formation remain poorly understood due to their intrinsic complexity and the difficulty of identifying physically consistent predictors. This study identifies the key variables in precipitation retrievals over the East Asian mid-latitude and tropical warm pool regions using the geostationary satellite data collected in the year 2023, in conjunction with machine learning and Shapley additive explanations. In the East Asian mid-latitudes, light-to-moderate precipitation is associated with the ice water path and the cloud particle growth characteristics, as indicated by the spectral reflectance (R) difference between 1.61 µm and 0.47 µm (R0.47 − R1.61) and between 1.61 µm and 0.64 µm (R0.64 − R1.61), respectively. Heavy precipitation events are linked to the presence of high-altitude cirrus clouds indicated by R1.37 and the upper-tropospheric moisture content characterized by the brightness temperature (BT) difference between 6.2 µm and 9.6 µm (BT6.2 − BT9.6). Over the tropical warm pool region, light-to-moderate precipitation is related to ice water path and cloud optical thickness, while heavy precipitation is predominantly related to the surface reflectance contrast, represented by R0.47 − R0.86 and R0.64 − R0.86, which modulates the initiation and intensity of convection. These results demonstrate that the optimal cloud properties and environmental predictors for satellite-based precipitation retrievals vary by regions and intensities.
- 작성자Choi et al.
- 작성일2026.05.26
- 조회수33
- 2026
Forecasting land-use and land-cover change for groundwater sustainability in the Muvattupuzha basin using CA-Markov ...

Abstract Rapid urbanization and land use and land cover (LULC) change have affected groundwater dynamics and its quality in many river basins. The present study uses an integrated framework combining multi-temporal Landsat imagery, geospatial analysis, multivariate statistics, and Machine Learning (ML) approaches to understand LULC changes and groundwater dynamics and its quality degradation. The supervised classification was used in the present study, which shows that built-up land increased significantly from 12.3% (329.13 km2) in 2003 to 44.4% (1,187.11 km2) in 2023, mainly due to the conversion of agricultural and forested land. Furthermore, future LULC dynamics by the CA-Markov model indicate continuous landscape transformation, with net conversions into built-up and forested areas during the periods 2023–2033 and 2033–2043, respectively, while there is a decline in water bodies and agricultural land use, and their rates of change stabilize over the periods approaching 2043–2050. Multivariate statistical analyses, such as correlation analysis, Principal Component Analysis (PCA), and Cluster Analysis, identify both geogenic processes and human activities as dominant determinants of groundwater hydrochemistry. To investigate the relationships between physicochemical parameters and nitrate variability, 3 ML models were employed: Random Forest (RF), Support Vector Regression (SVR), and XGBoost. Model interpretation using SHapley Additive exPlanations (SHAP) showed that Mg2+, Ca2+, and alkalinity are the significant factors influencing nitrate distribution, reflecting buffering reactions and redox-controlled processes. An integrated framework combining LULC, hydrogeochemical, and ML techniques provides a strong foundation for assessing groundwater. It offers insights into sustainable land-use planning and groundwater management in rapidly urbanizing tropical basins. Full title: Forecasting land-use and land-cover change for groundwater sustainability in the Muvattupuzha basin using CA-Markov (2033−2050)
- 작성자Alagulakshmi et al.
- 작성일2026.05.26
- 조회수27
- 2026
Comparative evaluation of ML models for spatio-temporal groundwater quality prediction and classification in MRB, India

Abstract Groundwater contamination has increased significantly due to population growth, land-use change, and unsustainable resource exploitation, necessitating advanced predictive tools for effective water governance. This study presents a multi-temporal, comparative machine learning (ML) to evaluate groundwater quality in the Muvattupuzha River Basin, Kerala, India, using datasets from 2003, 2013, and 2023. A total of five supervised ML models (i.e., decision tree [DT], logistic regression, support vector machine, random forest, and k-nearest neighbor) are systematically assessed to distinguish groundwater as safe or unsafe. Model performance is evaluated using accuracy, recall, F1-score, coefficient of determination, and root-mean-square error. Among the five models, the DT consistently outperforms others, achieving a maximum classification accuracy (96%). It also demonstrates strong interpretability under data-limited conditions. The novelty of the presented work lies in integrating model-specific feature importance with hydrochemical reasoning, revealing that salinity-related parameters serve as effective surrogate indicators for large-scale groundwater quality screening, while nutrients and hardness reflect localized anthropogenic and geogenic controls. The temporal analysis captures the evolving dynamics of groundwater quality over two decades. It is highlighting emerging risks despite partial improvements. Overall, the proposed model advances interpretable, data-driven groundwater assessment and provides actionable insights for early warning, sustainable monitoring, and policy-oriented water resource management in rapidly transforming river basins. Full title: Comparative evaluation of machine learning models for spatio-temporal groundwater quality prediction and classification in the Muvattupuzha river basin, India
- 작성자Alagulakshmi et al.
- 작성일2026.05.26
- 조회수26
- 2026
City-scale calibration of a low-cost PM2.5 network for regulatory-compliant air-quality assessment

Abstract This study presents the calibration and performance analysis of a low-cost sensor (LCS) network for monitoring particulate matter with diameters ≤ 2.5 µm (PM2.5) in Bucharest, Romania. The InfoAer network comprised 44 Clarity Node-S sensors deployed across the city. The performance of sensors was evaluated against reference measurements from the National Environmental Protection Agency (NEPA) regulatory monitoring stations. The manufacturer’s pre-calibration significantly underestimated PM2.5 concentrations, particularly during the summer months, when meteorological conditions favor the formation of secondary aerosols. Nine spatial clusters with collocated InfoAer-NEPA measurements were identified, with one designated for calibration model development and the remaining eight for independent validation. Multiple seasonal calibration models were developed using temperature, relative humidity, and nitrogen dioxide as predictor variables in a multiple linear regression formulation. Calibration performance was compromised during hot, dry conditions, when PM2.5 concentrations were typically low, likely due to reduced aerosol scattering efficiency and increased measurement uncertainty. Using only temperature and relative humidity as predictors, the optimal model, selected via a two-step calibration process, substantially improved measurement accuracy. Pearson correlation coefficients improved from 0.06 to 0.65 and from −0.28 to 0.89 for the dry and humid seasons, respectively. However, considerable inter-sensor variability in calibration performance was observed, indicating the need for additional meteorological or chemical parameters in future calibration algorithms. Application of the calibration model to the entire InfoAer network revealed significant air quality violations across Bucharest. On average, calibrated sensors recorded more than 60 days of exceedances of the European Union’s daily PM2.5 limit value (25 μg m−3) per year, which far exceeded the permitted frequency of 35 exceedances per year. Prior to calibration, only 8 of 44 sensors (18%) exceeded this threshold; post-calibration analysis revealed violations at all monitoring locations. These results demonstrated the critical importance of proper LCS calibration for accurately assessing regulatory compliance and protecting public health.
- 작성자Blaga et al.
- 작성일2026.05.26
- 조회수33
- 2026
Feasibility of cow-dung groundnut-shell composite as a decentralized renewable fuel for clean cooking

Abstract Conventional biomass fuels (e.g., untreated firewood and raw cow dung cakes) continue to be the predominant household energy source in rural areas, but this can lead to serious indoor air pollution and associated health consequences. This study presents a cost effective, scalable, and environmentally friendly energy source derived from a mixture of locally available cow dung and groundnut shell powder. Fuel cakes are made in the form of a disc so that they could be used in current rural cookstoves, making them user-friendly and requiring minimal change in cooking habits. Four different composition ratios C1 (100% cow dung), C2 (75% cow dung + 25% groundnut shell), C3 (50% cow dung + 50% groundnut shell), and C4 (25% cow dung + 75% groundnut shell) are experimented. The C4 ratio results in a 29.6% higher calorific value (19,700 ± 370 kJ kg− 1) compared to pure cow dung with significant emission reduction up to 43% of particulate matter ≤ 2.5 μm in diameter, 29% of carbon dioxide, and 53% formaldehyde. The present study contributes directly to Sustainable Development Goal (SDG) 7 (affordable and clean energy) and SDG 13 (climate action), providing a realistic solution to reduce pollution, improve indoor air quality, and promote energy equity in disadvantaged populations.
- 작성자Gautam et al.
- 작성일2026.05.26
- 조회수21
- 2026
AI-based analysis of climatic and air pollution determinants of dog bite incidence

Abstract Dog bite incidents are an emerging public health concern that may be influenced by changing environmental conditions. This study investigated the relationship between meteorological variables (maximum temperature and relative humidity) and dog bite incidence across five Indian states: Bihar, Karnataka, Punjab, Telangana, and Uttar Pradesh. The role of key air pollutants, including formaldehyde, nitrogen dioxide, sulfur dioxide, and ozone, was also examined. Statistical analyses showed that maximum temperature (p = 0.0014) and relative humidity (p = 0.0252) were significantly associated with dog bite incidence, with higher temperatures associated with increased incidence and higher humidity with reduced incidence. Principal component analysis (PCA) revealed no apparent clustering or dominant trend in environmental factors, indicating that temperature and humidity alone do not sufficiently explain dog bite variability across regions. Correlation analysis across monthly data demonstrated a strong overall positive association with maximum temperature (r = 0.84), although short-term annual trends show nonlinear fluctuations influenced by additional contextual factors. To predict dog bite risk, an artificial intelligence model (H2O XGBoost) was developed, achieving 87% accuracy and a mean absolute percentage error of 9.6%. This study highlights the importance of localized environmental interpretation and region-specific variability, contributing to understanding the ecological determinants of animal-related injuries and supports Sustainable Development Goals 3 (good health and well-being), 11 (sustainable cities and communities), and 13 (climate action) by informing strategies for safer and more resilient urban environments.
- 작성자Gautam et al.
- 작성일2026.05.26
- 조회수42
- 2026
Spatio-temporal analysis of land use transformations and their environmental implications in the Thamirabarani River...

Abstract Rapid population growth and associated land-use/land-cover (LULC) transformations exacerbate environmental stress on natural resources, underscoring the importance of continuous monitoring to support sustainable land and water management. This study examines the spatio-temporal dynamics of LULC changes and the interrelationships among LULC, the normalized difference vegetation index (NDVI), land surface temperature (LST), and soil temperature (ST) in the Thamirabarani River Basin in Tamil Nadu, India. Multi-temporal satellite datasets from Landsat-8 (30 m resolution) and Sentinel-2 (10 m resolution) were processed in Google Earth Engine for the period from 2015 to 2024. The change detection analysis presented significant increases in built-up areas (11.6%) and barren land (11.9%), indicating rapid urbanization and progressive land degradation. NDVI analysis showed a significant positive long-term trend across the basin (slope = 0.00055, p = 0.0369), reflecting seasonal and interannual vegetation variability. Although, spatial analysis revealed a stable vegetation condition across the basin, minor reduction in vegetation was observed in urban and degraded areas, where the expansion of built-up and barren land has led to localized vegetation loss. Analyses of LST and ST showed substantial seasonal variations, indicating the critical role of vegetation cover in regulating land-atmosphere energy exchanges. NDVI exhibited a negative correlation with LST (R2 = 0.15-0.55), reflecting the cooling effect of vegetation which reduces surface heating through canopy shading and enhanced evapotranspiration. This suggests that vegetation activity partially controls LST and ST. The present results demonstrate the urgent need to implement integrated, sustainable land and water management strategies, including promoting climate-resilient agricultural practices, regulating urban expansion, and implementing systematic vegetation restoration programs, to maintain ecosystem stability and resilience in the basin under intensifying climatic and anthropogenic pressures. Full title: Spatio-temporal analysis of land use transformations and their environmental implications in the Thamirabarani River Basin, India using Landsat-8 and Sentinel-2 satellite imageries
- 작성자Harani et al.
- 작성일2026.05.26
- 조회수22
- 2026
Emergence of autumn rainy season in Korea due to tropical cyclone influence

Abstract: Autumn in Korea, following the peak rainy season in summer, is of a great importance as it coincides with the intensive harvesting of crops and fruits. Hence, autumn rainfall critically affects agricultural production in Korea. This study shows the emergence of new rainfall peaks in autumn, leading to potentially significant agricultural damages. In the monthly period from September 10 to October 10, the total rainfall in the recent period (150 mm for 1998–2023) has increased by 44 mm compared to the previous period (106 mm for 1979–1997), averaged over 61 stations. Heavy rainfall days (≥ 100 mm day−1) have also occurred more frequently. The most plausible mechanism for these changes is the delayed retreat of the western North Pacific subtropical high in autumn which results in westward shift of tropical cyclone (TC) tracks and increased number of days on which Korea is affected by TCs. In addition, rising sea surface temperatures (0.5–1.0°C) in the western North Pacific and the South China Sea appear to be related to increased TC-induced heavy rainfall in Korea. Enhanced low-level moisture transports from these warm oceanic areas toward Korea, combined with upper-level wind divergence, are likely to have intensified the conditions for the TC-induced heavy rainfall. This study highlights the need for further research and public awareness of the changing autumn rainfall patterns and their impacts on agriculture and infrastructure. Available online 4 July 2025
- 작성자Kim et al.
- 작성일2025.10.28
- 조회수201
- 2026
Limitations of ENSO-based prediction of Korean winter temperature

Abstract: This study investigates the statistical and dynamical relationship between the El Niño-Southern Oscillation (ENSO) and winter surface air temperature (SAT) in Korea, using station observations and reanalysis data from 1920 to 2023. Historical SAT records are compiled from 7, 14, and 60 stations for 1920–1959, 1960–1972, and 1973–2023, respectively. Despite the statistically significant correlation (r = 0.28) between the Niño 3.4 index and winter SAT in Korea, ENSO alone explains only a limited amount of interannual variability. Classifying the SAT anomalies according to the ENSO phase (i.e., warm for El Niño and cold for La Niña), the Niño 3.4 index yields binary-classification accuracy of 0.68; however, about half of the correctly classified anomalies fall within ±0.5 standard deviations from the climatological mean. Also, composite circulation patterns based on ENSO phases differ structurally from those associated with actual SAT anomalies. A multiple linear regression analysis reveals that mid- to high-latitude climate variables, such as the East Asian winter monsoon, western North Pacific (WNP) sea surface temperatures (SSTs), and the Arctic Oscillation, exhibit stronger and more stable associations with Korean winter SAT than ENSO. Especially WNP SSTs show the largest standardized regression coefficients (> 5.0) to indicate their dominant role. This study suggests the need for integrated forecasting approaches that consider both the tropical and extratropical influences, rather than relying solely on ENSO signals for improving the accuracy of seasonal climate predictions and supporting adaptive risk management strategies for wintertime extremes in the Korean Peninsula.
- 작성자Yoo et al.
- 작성일2025.10.28
- 조회수307
- 2025
Microplastic transfer pathways in rural household environments through integrated compartmental analysis

Abstract: Microplastic (MP) pollution is a serious environmental and public health concern. However, the mechanisms governing MP distribution and transport in rural household environments remain poorly understood. This study presents the first integrated compartmental analysis of MP transfer between outdoor and indoor matrices, including soil, indoor air (inlet and outlet), and reused cooking oil in households located in Karunya Nagar (10.938523°N, 76.743782°E), a rural area in India. Samples were selected based on waste mismanagement profiles and analyzed using Fourier transform infrared spectroscopy. High plastic loads detected in the soil samples consisted of polypropylene (PP, 38.21%), polyethylene terephthalate (PET, 32.85%), polyethylene (22.78%), and polystyrene (PS, 6.16%), likely originating from agricultural films, packaging, and burned household waste. Samples from the air inlet predominantly contained PP (41.72%) and PET (33.94%), suggesting resuspension from contaminated soil due to wind action. Substantial concentrations of PET (42.4%) and PS (25.4%) were detected in reused indoor cooking oil, representing increases of 29.1% and 14.2%, respectively, relative to the air inlet samples. This suggested sorption and thermal transfer during cooking processes in open containers. Increases of 9.4% PP and 0.27% PET in air outlet profiles provided evidence of re-aerosolization during heating and inefficient ventilation. Polymer aging and oxidative degradation were confirmed by spectral intensities at 1783.1 cm−1, 1161.15 cm−1, and 509.21 cm−1. These results reveal a continuous, cyclic pathway of MP entry, accumulation, and secondary emission within rural households, demonstrating an overlooked but critical exposure route that necessitates targeted waste management and health interventions.
- 작성자Rakshith et al.
- 작성일2025.10.28
- 조회수120
- 2025
FTIR based assessment of MP contamination in soil water and insect ecosystems reveals environmental and ecological risks

Abstract: Microplastic (MP) pollution has emerged as a critical global environmental concern, impacting soil, water, and insect ecosystems. This study quantified MP prevalence in soil, water, and insect samples collected from specified rural and semi-urban study areas in the southern India, using Fourier-transform infrared (FTIR) spectroscopy for contamination assessment. The results revealed a predominance of polypropylene/polystyrene (PP/PS; 91.3%), followed by polyethylene (PE; 15.1%), polyethylene terephthalate (PET; 9.2%), and polyamide (PA; 6.2%). Insect samples showed high MP adherence, particularly in blister beetles, click beetles, and carpenter bees, suggesting their role as vectors for MP dissemination, mainly through adherence pathways. FTIR analysis confirmed characteristic MP absorption peaks at 1637.6 cm−1 (PP/PS), 1031.9 cm−1 (PE), 582.5 cm−1 (PET), and 3448.7 cm−1 (-OH groups), indicating interactions between MP and organic matter. FTIR analysis of soil samples showed PE as the dominant MP, with higher quantities in garbage sites (36.0%) and residential areas (34.9%) compared to agricultural farms (18.9%). Soil samples varied significantly, with bulk density (1.1–1.4 g cc−1), porosity (36.1–58.0%), and organic carbon content (0.7–1.9%), indicating potential impacts on fertility and microbial activity. Water samples from irrigation sources showed detectable PET (1.2%) and PA (0.7%) concentrations, with a distinct peak at 2316.5 cm−1, raising concerns about agricultural sustainability and food safety. These findings highlight the urgent need for stricter waste management regulations and further studies into the long-term environmental and human health risks of MP pollution. Full title: FTIR based assessment of microplastic contamination in soil water and insect ecosystems reveals environmental and ecological risks
- 작성자Rathikannu et al.
- 작성일2025.10.28
- 조회수122
- 2025
Arctic wildfire carbon emissions strongly influenced by midsummer Tibetan Plateau precipitation

Abstract: Wildfires in the Arctic are accelerating ecosystem damage and increasing global carbon emissions. Siberia, a major Arctic wildfire hotspot, is shaped by both local weather and distant climate influences. Here we use climate reanalysis data and numerical model experiments to show that summer wildfires in Siberia are strongly influenced by rainfall patterns over the Tibetan Plateau, one of the Northern Hemisphere’s largest summer heat sources. A dipole in Tibetan Plateau rainfall—wetter in the west, drier in the east—coincides with more fires in central Siberia and fewer in the east. This pattern alters high-altitude winds, shifting the jet stream northward and generating air flow changes that create favorable fire conditions across Siberia. Model experiments support a causal link. The resulting carbon dioxide emissions can match annual emissions from all Nordic countries. These findings highlight an overlooked driver of Arctic wildfires and improve our understanding of their role in the global carbon cycle.
- 작성자Yang et al.
- 작성일2025.10.28
- 조회수1107
- 2025
Extratropical transition pathways of tropical cyclones and their role in storm intensity and destructiveness

Abstract: Tropical cyclones (TCs) undergoing extratropical transition (ET) can have widespread impacts; however, the differences in their evolutionary pathways remain incompletely understood. In this study, the cyclone phase space is applied to classify TCs in the western North Pacific from 1979 to 2022 into three distinct types. Type 1 exhibits the most pronounced asymmetry changes and retains the strongest surface winds, whereas Type 2 undergoes more modest asymmetry changes and maintains a weaker wind field. Type 3, in contrast, preserves a relatively symmetric wind field throughout the transition and occurs in a more baroclinic environment. Among the pathways, Type 1 demonstrates the highest post-transition destructiveness. Sensitivity analysis indicates that while most findings are robust across classification thresholds, Type 3 is particularly sensitive to threshold selection and requires careful interpretation. The present results enhance our understanding of ET variability and its implications for mid-latitude storm impacts.
- 작성자Cheung et al.
- 작성일2025.10.28
- 조회수125
- 2025
High PM2.5 episodes in Seoul, Korea, associated with Siberian High intensity

Abstract: The Siberian High (SH) dominates the wintertime atmospheric circulation over East Asia which strongly modulates the concentration of particulate matter ≤ 2.5 μm in diameter (PM2.5) in the region. While the SH exhibits considerable day-to-day variations, previous studies have focused on its seasonal and interannual effects rather than its short-term influence on PM2.5 concentrations. This study investigates the link between the evolution of atmospheric circulation associated with the changes in the SH intensity and the occurrence of high PM2.5 concentrations (≥ 35 µg m−3) in Seoul, Korea. Using a hierarchical clustering method, the synoptic patterns associated with 94 high-PM2.5 episodes in Seoul during the winters of 2008–2022 are classified into two groups based on the intensity of SH: 49 episodes with strong SH and 45 episodes with weak SH. Each SH pattern can induce high-PM2.5 episodes over distinct daily timescales through different dynamical and thermodynamical processes in the upper and lower troposphere. The strong SH is transformed into a migratory anticyclone over Korea, reducing wind speeds in the lower troposphere. These conditions suppress atmospheric ventilation and enhance dynamic stability, providing a favorable environment for rapid accumulation of PM2.5 near the surface within two days. During the weak SH events, the anticyclonic flow in the upper troposphere increases air temperatures in the mid-to-lower troposphere, resulting in increased low-tropospheric thermal stability. Air pollutants cannot disperse into the upper atmosphere and gradually accumulate to high PM2.5 levels over a period of four days. This study highlights that the development of atmospheric circulation in both strong and weak SH patterns plays an important role in the air quality degradation in Seoul through different temporal characteristics. These SH-driven atmospheric circulations provide valuable insights for improving forecast accuracy and enabling targeted emission control strategies based on the expected timing of pollution episodes.
- 작성자Kim et al.
- 작성일2025.10.28
- 조회수182
- 2025
Observational study of a quasi-stationary mesoscale convective system during extreme rainfall on 8 August 2022 in Korea

Abstract: On 8 August 2022, a quasi-stationary mesoscale convective system (MCS) produced prolonged extreme rainfall (> 100 mm h−1) over the Seoul metropolitan area, Republic of Korea. These organized convective systems, primarily composed of convective components with interspersed stratiform elements, are characterized by the successive local generations of convective cells. This study analyzes data from multiple observational platforms to understand the formation of the MCS and its microphysical evolution. The convective cells were initiated just off the west coast near Seoul, along the boundary between warm and cold air masses. Low-level convergence and favorable environmental conditions, including low lifting condensation level, level of free convection, and large convective available potential energy, facilitated the triggering of these cells. As the cells moved inland, they intensified rapidly due to the land-sea surface-friction contrast. Radar data show that as the MCS matured, reflectivity increased and the differential reflectivity decreased downward above the melting level, indicating the growth of ice crystals and graupels. The evolution of microphysical structure led to increases in both the mean diameter (Dm) and the number concentration (NT) of raindrops. This observation also suggests that the rainfall intensity was more closely related to the increase in NT than Dm during the period of heavy downpours. This study improves our understanding of the mesoscale processes related to extreme rainfall in Korea, critical for forecasting local heavy rainfall.
- 작성자Kim et al.
- 작성일2025.10.28
- 조회수171
- 2025
Recent changes in summer rainfall characteristics in Korea

Abstract: This study investigates the long-term variation in the summer rainfall characteristics in Korea by analysing the amount and intensity of rainfall and the number of rainy days at 57 stations for the June–September period from 1976 to 2023. For the primary rainy season, from 22 June to 1 August, the amount of rainfall in the post-2000 period is greater than that in the pre-2000 period, whereas the number of rainy days remains similar throughout the entire period. Rainfall intensity increases until 2000, then remains nearly unchanged after 2000. For the secondary rainy season, from 2 August to 10 September, both the rainfall amount and number of rainy days in the post-2000 period are larger than those in the pre-2000 period; however, the increase in rain intensity is less pronounced than that in the primary rainy season. These rainfall changes for the two rainy intra-seasons are found to be closely related to the increase in the frequency of heavy rainfall events (≥80 mm day−1), especially in the Seoul metropolitan area and the southern coastal regions. Previous studies have attributed the changes in the primary rainy season to the decrease (increase) in stationary fronts (convective rainfall), whereas the changes in all fronts (stationary and occluded) and the reduced influence of tropical cyclones in August have been identified as the main contributor in the secondary rainy season. This study improves our understanding of the recent changes in summer rainfall characteristics in Korea.
- 작성자Ho et al.
- 작성일2025.10.28
- 조회수262
- 2025
Interactions of the background state and eddies in shaping Aleutian Low variations

Abstract: The Aleutian Low (AL) is a dominant feature of the mean circulation in the North Pacific during the winter season. The background stationary wave, air-sea interaction, and transient eddies over the North Pacific exert distinct impacts on the interannual variations of the AL intensity and position. In this study, we adopt the quasi-geostrophic geopotential tendency equation to investigate the roles of various physical processes in the maintenance and interannual variations of this system. The results show that absolute vorticity advection plays the most important role in the formation and maintenance of AL intensity, while high-frequency transient eddies contribute most to the meridional and zonal shifts of the AL. The high-frequency transient eddy vorticity forcing affects the AL through the barotropic energy conversion process, and, in turn, the AL enhances the high-frequency transient eddies through the baroclinic energy conversion process, forming a positive feedback. The associated high-frequency eddy kinetic energy anomalies exhibit an eastward movement toward the east coast of North America in the years of an intensified AL, which explains why a strengthened AL is often accompanied by an eastward movement. Furthermore, the energy conversion terms of high-frequency transient eddies are mostly located over the extratropical eastern North Pacific, leading to asymmetric features in the zonal movement of the AL.
- 작성자Lin et al.
- 작성일2025.10.28
- 조회수126
- 2025