This study aims to measure carbon dioxide (CO₂) in Busan to enhance understanding of the urban atmospheric environment. Two sites with distinct environmental settings-Second College of Education Building (SEB; natural surroundings) and Mechanical Engineering Building (MEB; urban-adjacent)-were established at Pusan National University, and CO₂ measurements were carried out from March 2024 to February 2025 to analyze diurnal and seasonal variations. The SEB site, positioned lower than MEB, was more directly affected by local emission, resulting in an average summer CO₂ concentration of 458.2 ppm, being 12.6 ppm higher than MEB. It is noted that these differences reflect the combined effects of topography, instrument height, wind direction, and the planetary boundary layer height (PBLH). During summer, CO₂ concentrations at the SEB were higher than at MEB, with both sites showing increased levels during the night. SEB maintained elevated concentrations continuously from 6:00 p.m. to 8:00 a.m. the following day. Meteorological analysis revealed that humid air advected from the ocean in summer lowered PBLH and stabilized the near-surface atmosphere, creating favorable conditions for CO₂ accumulation. Furthermore, southwesterly wind-which accounted for about 30% of summer wind in two sites-suggests that nocturnal CO₂ emissions from vegetation respiration in nearby forests contribute to the observed summer CO₂ concentration increases. Overall, this study presents a comparative, observation-based analysis of CO₂ variability across two urban sites with contrasting environmental conditions, offering insights into the interplay between local emissions and meteorological factors. The results provide a basis for developing localized air quality management strategies.

The Arctic ozone depletion in 2020 spring drew significant scientific attention due to its rare occurrence in the Northern Hemisphere. Although relatively small in amplitude compared to the Antarctic ozone hole, the 2020 Arctic ozone depletion is the most extensive and markedly prolonged event in the Northern Hemisphere. This study investigates the 2020 Arctic ozone depletion within the context of the background conditions in the stratosphere by comparing it to the 2019 conditions when the stratospheric ozone concentration was high. In early spring 2020, the enhanced meridional temperature gradient strengthened the polar vortex and maintained a cold Arctic condition in the stratosphere, which is markedly different from the 2019 spring and climatological conditions. These background fields create favorable conditions for forming polar stratospheric clouds, which could efficiently cause chemical ozone destruction. Wave activity analysis reveals that the vertical Rossby wave propagation from the high-latitude troposphere and associated stratospheric drag were noticeably weaker than normal in the preceding winter. This contributed to the strong polar jet and weaker Brewer-Dobson circulation in the stratosphere. The strong positive Arctic Oscillation in early 2020 indicates a weaker Rossby wave drag in the high-latitude regions, and 3D stationary wave activity flux (Plum flux) manifests a clear decrease in vertical wave activity over the high-latitude Atlantic. However, its physical causes remain unclear.

This study quantitatively analyzed the regional characteristics of heavy precipitation and its associated damages in South Korea from May to October during the period 2016-2022. Additionally, spatial clustering based on the K-means method was performed using rainfall frequency, damage frequency, and topographic elevation. The analysis of cumulative rainfall and damage frequency showed that, in most regions, rainfall amounts associated with damage were comparable to or slightly higher than current heavy rain warning thresholds, generally within an operationally acceptable range. In the inland central regions (e.g., Chungcheongbuk-do, Chungcheongnam-do, and Gyeonggi-do), the proportion of damage relative to heavy rainfall occurrence was relatively high under intense rainfall conditions, whereas Jeju Island exhibited a high frequency of heavy rainfall but low damage occurrence. The clustering classified the country into four clusters, with consistent cluster configurations maintained under both the 3-hour and 12-hour cumulative rainfall criteria. Notably, the cluster encompassing the Seoul Metropolitan Area and southeastern coastal regions exhibited higher frequency of damage despite lower frequency of heavy rainfall, suggesting significant influences from socio-geographical factors. In contrast, the mountainous areas of Jeju, characterized by highest rainfall frequency and elevation, reported almost no damage, indicating that social exposure and physical vulnerability are critical determinants of damage rather than rainfall amount alone. These findings are expected to provide as foundational data for improving heavy rainfall warning systems and developing tailored response strategies.

This study classified tropical cyclones (TCs) passing near Daegu as compound, rain-dominant, wind-dominant, or weak based on observed daily precipitation and maximum wind speed at the Daegu Automated Surface Observing System (ASOS). TCs of the compound type had the closest tracks to the Daegu ASOS and exhibited the highest maximum sustained wind speed (MSWS). These TCs maintained their intensity due to weak vertical wind shear and strong vertical velocity (VV) around the Korean Peninsula during their influence period. Rain-dominant TCs exhibited greater intensity in terms of mean sea level pressure (MSLP) while passing east of the Daegu ASOS. During the period influenced by rain-dominant TCs, high VV was observed because the Korean Peninsula was located south of the jet stream entrance. Wind-dominant TCs exhibited higher MSWS intensity while passing west of the Daegu ASOS, placing Daegu within the dangerous semicircle of TCs. Weak TCs had the farthest tracks from the Daegu ASOS and exhibited the lowest intensity in terms of MSWS and MSLP. The multiple linear regression model developed in this study performed poorly in predicting rainfall and maximum wind speed at Daegu, as well as determining the type of influence although it performed moderately well in predicting whether Daegu is influenced by a TC. This is because simple linear regression cannot capture nonlinear relationships, and the meteorological variables are at a synoptic scale much larger than that of Daegu. Addressing these limitations in future work could improve TC impact warnings for Daegu.

Urban heat islands (UHIs) can intensify during high-temperature weather events such as tropical nights, leading to even greater thermal stress in cities. This study investigates the interactions between UHIs and tropical nights in Busan, South Korea, using 52 years (1973~2024) of observational data. In Busan, the frequency and intensity of tropical nights are 48.8% and 0.19℃ higher than in rural areas, respectively, and these differences have become more pronounced as urbanization has progressed. On average, the UHI intensity is higher on tropical nights than on non-tropical nights, as warmer, drier, and less cloudy nighttime conditions on Busan's tropical nights lead to a positive interaction between UHIs and tropical nights. However, the UHI-tropical night interaction shows considerable variability, being either strongly positive or strongly negative. This is caused by contrasting characteristics of tropical nights in Busan, which result from their different mechanisms and synoptic patterns. Specifically, tropical nights that exhibit strong positive interactions with UHI are relatively calm, dry, and hot with clear skies, driven by strong insolation and subsidence under the dominance of a persistent anticyclone. In contrast, tropical nights that exhibit strong negative interactions with UHI are much more windy, cloudy, and moist. They are driven by reduced nighttime radiative cooling and warm advection when warm moist air is transported by southwesterlies at the periphery of the western North Pacific subtropical high.

A wind shear detection system using WISSDOM (WInd Synthesis System using DOppler Measurements) a 1 km resolution analysis field incorporating radar radial velocities through 3D-VAR was developed and evaluated to detect wind shear along aircraft glide paths at domestic airports. This system addresses limitations of existing LLWAS, which detects low-level wind shear only within a narrow area near runways at altitudes below 30 m. Vertical and horizontal wind shear detection techniques were applied in parallel, with performance verified using LLWAS alarm data and IATA aircraft observations from Incheon, Jeju, and Yangyang airports. Wind shear values from the system were generally lower than the ICAO standard (5 kt/100 ft). Optimal thresholds maximizing TSS were derived: vertical 1.0~1.5 kt/100 ft and horizontal 1.6~2.4 kt/km. Performance was highest at Incheon (horizontal wind shear PODY 0.82, AUC 0.71), followed by Jeju, and lower at Yangyang. Case analyses using AMDAR data showed spatial similarity between observed and detected wind shear events, supporting the system's operational capability. Despite resolution limits for sub-kilometer phenomena, the system effectively detects mesoscale wind shear and offers a practical means to enhance aviation safety and operational efficiency.

This study investigates the physical mechanisms of a downslope windstorm that occurred in the Gangneung region on April 11, 2023, using numerical simulation and the shallow water theory. In shallow water theory, the mechanism of a downslope windstorm involves the flow transition from subcritical to supercritical due to changes in the fluid thickness and velocity, which is identified by the Froude number ($Fr=U/{\sqrt{gH}}$). While previous studies calculated the Fr using a fixed characteristic depth, this study applied the spatially varying flow thickness for the Fr calculation, assuming that the lower tropospheric inversion layer with the maximum Brunt-Väisälä frequency could be considered as the free surface in shallow water theory. Numerical simulation conducted using the Weather Research and Forecasting (WRF) model revealed that the new Fr calculated with the varying flow thickness aligns better with shallow water theory and effectively explains the physical mechanisms of the downslope windstorm. On the upwind side, the westerly flow is well identified as subcritical until it reaches the crest, several kilometers west of Daegwallyeong, where its Fr transitions to supercritical by decreased flow thickness and increased wind speed. The flow further accelerated while descending the lee side under supercritical conditions. The subcritical-to-supercritical transition made the westerly flow keep accelerating, causing the downslope windstorm at Gangneung Airport. The new spatially varying Fr revealed clear distinctions between the downslope windstorm and turbulent regions closely matching observations at Gangneung Airport.

Methane, despite having a relatively shorter atmospheric lifespan than carbon dioxide, is a potent greenhouse gas with a global warming potential over 80 times higher on a 20-year basis. Therefore, reducing methane emissions can significantly contribute to effective climate change mitigation. In the energy sector, methane emissions primarily originate from leaks during fossil fuel production, processing, transport, and usage. This study highlights the need for and the potential benefits of expanding Leak Detection and Repair (LDAR) programs based on strengthened Measurement, Monitoring, Reporting, and Verification (MMRV) systems. If LDAR is expanded to power generation facilities in Korea, it's possible to prevent methane leakage equivalent to about 2.57% of the nation's annual power generation. This could result in a saving of over 620,000 tons of LNG, achieving a cost reduction of approximately 530 billion KRW. This is further estimated to save social value costs equivalent to 5 trillion KRW and is expected to reduce greenhouse gases by about 80,000 tons of CO₂eq from the fuel combustion process. Mitigating methane emissions not only contributes to climate change mitigation but also reduces tropospheric ozone formation, thereby improving air quality and public health. Furthermore, preventing unintended energy loss yields mid- and long-term economic savings. Given that South Korea is one of the largest importers of natural gas, enhancing methane management in industrial complexes and metropolitan areas is essential for achieving national carbon neutrality goals. Moreover, Expanding LDAR programs can practically contribute to the country's Nationally Determined Contributions (NDCs).

Climate change has a pronounced impact on plant phenology, which is closely linked to ecosystem productivity, carbon cycling, and biodiversity. Analyzing phenological shifts using long-term monitoring data is therefore essential for understanding ecosystem responses to climate change. In this study, we quantitatively assessed four key phenophases (budburst, flowering onset, leaf unfolding onset, and 90~100% fall foliage) based on observations of 20 deciduous broadleaf species collected at 10 arboreta across South Korea from 2009 to 2024. Phenological records were further combined with climatic variables from the Automated Synoptic Observing System (ASOS) to evaluate correlations between phenological events and climate factors. The results showed that budburst (-0.94 d yr^-1), flowering (-0.83 d yr^-1), and leaf unfolding (-0.79 d yr^-1) advanced consistently, while peak (90~100%) fall foliage was delayed (+0.33 d yr^-1), leading to an extension of the average growing season by more than 17 days. A distinct seasonal transition point was also identified between fruit set and fruit maturity, where DOY (Day of year) values increased sharply. Regional analysis indicated consistent advancement of spring events across most regions, whereas fall foliage tended to be delayed. Correlation analysis revealed that spring phenophases advanced in response to winter-early spring air and surface temperatures, while fall foliage showed strong positive correlations with late-summer air temperature, surface temperature, and dew point temperature. Stepwise multiple-regression models further showed that leaf unfolding and flowering showed very high explanatory power from climatic predictors (Adjusted R²: 0.96 and 0.95, respectively), confirming them as the phases most sensitive to interannual climatic variability. This study integrated nationwide long-term phenological observations updated through 2024 to present species- and region-level recent changes, and applied rolling 2- to 3-month analysis windows to systematically identify, for each phenophase, the sensitive periods and the direction of climatic influences. Moving beyond a simple confirmation of growingseason extension, we quantified stage-specific meteorological influence and sensitivity windows, thereby enhancing the comparability and reproducibility of the results. Our findings can serve as a scientific basis for predicting ecosystem responses to climate change and informing the development of climate crisis adaptation strategies.

The general circulation in mid-latitudes is characterized by planetary geostrophic motion, where heat and momentum fluxes from synoptic eddies play a crucial role. The poleward heat flux, produced by baroclinic eddy growth, reduces the meridional temperature gradient and is parameterized as eddy diffusion. Similarly, eddy momentum flux, driven by barotropic wave breaking, is assumed proportional to the horizontal shear of the zonal mean zonal wind, intensifying upper-level westerlies. Incorporating turbulent eddy parameterizations into the planetary-scale heat equation, a balance is achieved between the two fluxes, resulting in eddy-driven circulations in mid-latitudes akin to the Farrell cell. The meridional domain is governed by a fourth-order characteristic equation, exhibiting two primary features related to anomalous potential temperature. The first feature is a linear decline in anomalous potential temperature, inducing westerly winds in midlatitudes. The second feature, represented by a trigonometric function, corresponds to jet streams generated by eddy momentum flux. The meridional structure of the circulation is influenced by three factors. The first factor is a structural number D/SM, where D represents eddy diffusivity, S signifies dry static stability, and M is the proportionality constant for momentum flux, summarizing the life cycle of synoptic eddies. The second factor relates to planetary size relative to the external Rossby deformation radius. Finally, a vertical structure of the atmosphere, associated with eigenvalues of the vertical mode in the main heat equation, constitutes the third factor. The combination of these three factors within the characteristic equation determines the location and number of eddy-driven circulations in mid-latitudes.

Understanding the observational characteristics of precipitation detectors and selecting appropriate sensors for specific purposes are essential for securing meteorological data and ensuring reliable observations. This study compares the detection characteristics and response times of four types of precipitation detectors through field experiments. The objective is to provide foundational data for establishing sensor selection criteria suitable for meteorological observation. The tested sensors employ capacitive, impedance, radar, and optical detection methods. The impedance and domestic capacitive sensors showed stable detection performance, albeit with occasional missed rainfall events. The foreign capacitive sensor responded later and ceased detection earlier than other sensors, yet demonstrated high accuracy. The optical sensor rapidly detected rainfall onset but continued to report rainfall even after cessation and failed to detect snowfall. The radar-based sensor was effective for snow detection due to its detection principle but occasionally produced false positives under non-precipitating conditions due to atmospheric particles. Based on statistical and characteristic analyses, it is concluded that impedance, capacitive, and radar sensors are generally suitable for meteorological applications, with radar sensors being optimal for snow detection.

Recent advances in artificial intelligence (AI) technologies are broadly integrated across all stages of climate prediction systems, driving significant innovations. Deep learning-based weather prediction models are rapidly progressing worldwide, demonstrating performance surpassing that of traditional numerical model-based integrated forecasting systems. In ocean modeling, deep learning simultaneously learns local detailed structures and global ocean configurations, precisely simulating complex ocean dynamics from mesoscale eddies to extensive current patterns, thereby substantially enhancing prediction ability. For land surface modeling, deep learning adopts hybrid forms combined with physics-based approaches to more accurately reproduce intricate land responses, with the integration of vegetation water stress modules enabling realistic depictions of land-atmosphere interactions. In data assimilation, AI contributions are prominent, where deep learning methods utilizing automatic differentiation, diffusion models, and image restoration techniques offer superior computational efficiency and expressiveness compared to conventional data assimilation approaches. Recent technologies like Variational AutoEncoders and Score-based Diffusion effectively incorporate high-dimensional nonlinear characteristics, continuously improving ocean and atmospheric initial field performance. Various deep learning methods exhibit potential for high-resolution enhancement of climate prediction outputs, while deep learning-based generative models are primarily employed for post-processing techniques to correct model biases. Beyond technical advances, AI-based technologies provide a strategic pathway toward operational implementation and climate services, enhancing both forecast accuracy and computational efficiency. Collectively, these developments point toward an integrated, next-generation climate prediction framework that bridges physical modeling, data-driven methods, and practical applications.