Urban trees play a crucial role in mitigating heat stress. Accurately representing the physical processes associated with trees in mesoscale models is essential for reliable simulations of urban environments across city to regional scales. We implement an urban canopy model incorporating trees into the Weather Research and Forecasting model to develop a fully coupled modeling system. The model is evaluated against pedestrian-level temperature, flux tower, and soil moisture measurements from the Seoul metropolitan area. Two heatwave episodes are simulated, and the model demonstrates reasonable performance in reproducing intra-city temperature differences, canyon air temperatures, and sensible and latent heat fluxes. A stronger cooling effect of trees is observed in commercial/industrial areas, with a daily mean temperature reduction of 1.1°C compared to 0.64°C in residential areas. The cooling effect is pronounced at night in narrower and deeper canyons, attributed to the greater longwave cooling of leaves. As soil moisture decreases, the cooling effects of trees diminish; however, significant cooling persists under very dry conditions due to tree shading, which is more prominent in commercial/industrial areas than in residential areas. Our findings indicate that comprehensive studies encompassing various tree and urban configurations are necessary to optimize the role of trees in sustainable cities.

How to cite: Ryu, Y.-H. and Park, M.-S.: Online coupling of an urban canopy model with trees and a mesoscale atmospheric model to assess the cooling effects of trees, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-983, https://doi.org/10.5194/icuc12-983, 2025.

The Urban Heat Island (UHI) effect, characterized by elevated urban temperatures compared to rural areas, is a critical challenge in urban climatology, exacerbated by global warming and rapid urbanization. This study investigates the fundamental mechanisms of the UHI effect by integrating theoretical modeling with observational data from Korea, focusing on the interplay between urban heat storage, anthropogenic heat, and climatic factors. Using a simplified day-night model based on the Surface Energy Flux Balance (SEFB) framework, we demonstrate that the UHI effect arises primarily from two mechanisms: (1) a decrease in the diurnal temperature range (DTR) due to the increased heat capacity of urban materials, and (2) an increase in mean temperature driven by additional energy fluxes, such as anthropogenic heat. Comparative analysis between Seoul, a major city, and Boeun, a rural area, reveals qualitative agreement between model predictions and observed data. Despite its higher latitude, Seoul exhibits significantly higher nighttime temperatures than Boeun, underscoring the role of urban heat storage in sustaining nighttime warming. Additionally, a temporary daytime temperature inversion in Boeun, driven by greater solar radiation, highlights the contrasting thermal dynamics between urban and rural environments. Long-term analyses reveal distinct evolutionary patterns of UHI effects in major cities and new towns. In major cities, rapid urbanization from the 1970s to the 1990s led to a steady decrease in DTR and a peak in nighttime temperature differences, followed by stabilization. In contrast, new towns consistently increased nighttime temperature differences, closely tied to urban development and population growth. Both cases demonstrate the critical role of heat storage and anthropogenic heat in shaping the UHI effect, with observed trends closely mirroring theoretical predictions. This study emphasizes the vulnerability of urban areas to climate change, as UHI effects amplify global warming's impact, heightening urban heat stress. 

How to cite: Jeon, M., Moon, W., Kim, J.-J., and Baik, J.-J.: Exploring Urban Heat Islands with a simple thermodynamic model, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-57, https://doi.org/10.5194/icuc12-57, 2025.

In Large Eddy Simulation (LES), inflow turbulence boundary conditions are crucial in accuracy of predicting atmospheric turbulent flows in urban environments. The cell perturbation method (CPM; Muñoz-Esparza and Kosovic, 2018) assigns thermal perturbations near inflow boundary regions to enhance rapid turbulence development. In this study, we implement the CPM module for use in the PALM v6.0 (Parallelized Large-Eddy Simulation Model, version 6.0) LES model, expanding the model’s capability to simulate time-varying inflow turbulence boundary conditions. The module was coded using the Message Passing Interface (MPI) parallel programming standard based on the Synthetic Turbulent Generator (STG) method in the PALM model. The performance of the CPM module was evaluated against a series of idealized simulations under neutral, unstable, and stable stability conditions. The developed CPM method showed clear development into turbulent flow compared to simulations with no inflow turbulence and the STG turbulence method. The two turbulence inflow methods performed differently in turbulence patch distance and energy spectrum under different atmospheric stability conditions. The CPM developed turbulent fields in a shorter distance under unstable and neutral conditions, while the STG showed earlier development of turbulent fields in stable condition. This study demonstrated that the CPM can be used in time-varying inflow turbulent simulations in urban environments.

How to cite: Woo, J.-W. and Lee, S.-H.: Integration of the Cell Perturbation Method (CPM) for inflow turbulence boundary condition in PALM v6.0, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-759, https://doi.org/10.5194/icuc12-759, 2025.

Understanding the characteristics of wind at pedestrian level is important to ensure pedestrian safety and comfort in urban environments. Pedestrian-level wind characteristics are mainly affected by the average characteristics of surrounding buildings such as plan and frontal area densities and mean building height, and the shape of each building also has a big impact on the wind characteristics. In particular, the various shapes of buildings, including curved surfaces, complicate the wind environment in urban areas. Currently, various computational fluid dynamics (CFD) models are being utilized to study the complex flows in urban areas. Many CFD models use cartesian grids to simulate flows in urban space by converting the urban space made up of buildings into a set of cuboids. The OpenFOAM (Open Field Operation And Manipulation) model, an open source CFD model, has the advantage of being able to represent the curved shape of building to the greatest extent possible by generating unstructured meshes using the mesh generation utility called snappyHexMesh.

In this study, we simulate the campus space of University of Seoul located in Seoul, South Korea using structured (cartesian grid) and unstructured meshes for OpenFOAM simulations, and compare the results over the two meshes. To implement realistic flow conditions, a mesoscale weather model (WRF) are used as the initial and lateral boundary conditions. In this study, we analyze the differences in the generation of turbulent eddies specially around the curved building surfaces according to the two types of meshes and compare the simulation results with observations. We expect that using the unstructured mesh will allow us to more accurately simulate flow separation, wakes around buildings, and turbulence statistics at pedestrian level. This study can be used to identify detailed features of pedestrian-level wind (e.g., gustiness), thereby providing a basis for pedestrian environmental impact assessment.

How to cite: Park, S.-B., An, H.-B., and Yeon, B.-D.: Comparative simulations of the pedestrian-level wind environment using structured and unstructured meshes, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-529, https://doi.org/10.5194/icuc12-529, 2025.

Urban Air Mobility (UAM) is an innovative aviation system designed for efficient operation in urban areas, providing solutions for rapid transportation of passengers and cargo. The safe operation of UAM depends on accurate predictions of weather phenomena such as turbulence, gusts, and icing conditions. However, the lack of observational data in the atmospheric boundary layer, which is UAM's primary operational area, has limited research on real-time weather prediction (nowcasting). To address this issue, this study utilizes high-resolution meteorological data from the Boseong Weather Observation Tower, which provides detailed insights into atmospheric boundary layer conditions. This study improves prediction accuracy by combining Long Short-Term Memory (LSTM) networks, specialized in time series data analysis, with Fully Connected Layers. Additionally, through power spectrum analysis, we investigate the impact of meteorological variable characteristics on prediction performance and identify the optimal amount of data required for deep learning-based real-time weather prediction models. The results of this study are expected to contribute to the development of real-time weather prediction models that can enhance the safety and efficiency of UAM operations. By addressing observational data gaps and utilizing deep learning technology, this study aims to contribute to establishing UAM as a reliable urban transportation solution. Furthermore, the methodology proposed in this study can be applied to building weather prediction systems for UAM operations in various urban environments, which is expected to play a crucial role in the development of sustainable transportation infrastructure for smart cities.

How to cite: Kim, H., Jeon, M., Lee, J., and Moon, W.: Deep Learning-Based Short-Term Weather Forecasting and Optimal Data Quantity Analysis for Urban Air Mobility, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-67, https://doi.org/10.5194/icuc12-67, 2025.

Urban Air Mobility (UAM) operates at altitudes of 1,000–2,000 feet within urban environments, where dynamic airflows require precise and real-time meteorological forecasts. Traditional large-scale forecasting systems often fail to capture intra-urban phenomena such as turbulence, while high-resolution Computational Fluid Dynamics (CFD) simulations are prohibitively computationally expensive for real-time applications. To address these challenges, this study introduces a deep learning-based emulator that rapidly generates CFD-like results using data from the Local Data Assimilation and Prediction System (LDAPS). The proposed model integrates Residual Dense Blocks (RDBs) with a wind direction classification system, significantly enhancing both predictive accuracy and computational efficiency. RDBs enable the effective learning of complex data patterns, while the wind direction classification system accurately predicts real-time wind direction changes, crucial for safe route planning and flight management in UAM operations. Experimental results demonstrate that the emulator reduces Mean Square Error (RMSE) compared to traditional forecasting models and achieves high accuracy in wind direction classification. Additionally, the emulator exhibits markedly lower computational costs and faster processing times than conventional CFD simulations, confirming its suitability for real-time applications. This deep learning-based emulator facilitates high-resolution urban-scale weather forecasting essential for the safe and efficient integration of UAM into urban airspaces. Furthermore, the approach holds significant potential for broader applications in urban meteorology and real-time computational tasks, establishing a new standard for meteorological forecasting tools in complex urban environments

Key Words: Urban Air Mobility (UAM), Urban meteorology, Deep Learning, Emulator, Computational Fluid Dynamics (CFD).

How to cite: Bae, J., Lee, Y., Rho, J.-H., Kang, G., Kim, J.-J., and Son, R.: Near-Real Time Weather Forecasting for Urban Air Mobility Using Deep Learning Emulators, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-40, https://doi.org/10.5194/icuc12-40, 2025.

Atmospheric turbulence is highly dynamic in both temporal and spatial aspects, so to detect it, equipment that can rapidly scan with high resolution within seconds is necessary. The Wind Lidar can complement the shortcomings of various remote sensing equipment and enable high-resolution rapid scanning, making it an optimal device for turbulence detection. With various scan modes, it can capture the three-dimensional spatial distribution of winds within seconds, making it particularly advantageous for detecting low-level winds within 600 meters over the urban area. Data were collected from the WIND3D6000 model by LEICE, which is installed near Incheon airport, and seven quality management techniques were applied and evaluated for their performance to enhance the quality. Subsequently, using the radial velocity derived from VAD scans, the eddy dissipation rate (EDR) was calculated based on Kolmogorov theory. The atmospheric boundary layer height was estimated using radiosonde. Typhoon cases provide a good choice for explaining the development and variation of the atmospheric boundary layer as meteorological variables such as temperature, humidity, wind direction, and speed change rapidly along their path. This study revealed that during clear days between 09:00 and 16:00, the EDR generally increased as the atmospheric boundary layer developed, and following boundary layer destruction, the EDR values also decreased accordingly. After typhoons made landfall, precipitation increased, hindering the development of the atmospheric boundary layer, with high EDR values primarily observed during precipitation periods. These results validate the potential of utilizing wind lidars for high-resolution wind and turbulence detection in the lower atmosphere, and through EDR calculations, they also indicate the ability to estimate the development of the atmospheric boundary layer.

How to cite: Kwon, B. H., Kim, S., Lee, K., Bae, H., Seo, Z., and Koo, Y.: Eddy dissipation rate in the atmospheric boundary layer based on radial velocity of wind lidar , 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-154, https://doi.org/10.5194/icuc12-154, 2025.

Recently, the industry using unmanned aerial vehicle (UAV) is rapidly growing. Accordingly, researches on the relevant issues including urban meteorology are being actively conducted. However, concerns about the reliability of observation sensors used in meteorological monitoring equipped with drones highlight the need for further research. The Boseong Standard Meteorological Observatory’s comprehensive observation tower, situated in flat and homogeneous terrain without tall buildings nearby, is an ideal site to verify the reliability of UAV observation data.

In this study, the reliability of UAV meteorological observations is quantitatively verified by comparing the UAV-observed meteorological factors with measurements from the Boseong observation tower. Observations were conducted from January 20 to 22, 2025, using a UAV with an iMET-X4 temperature and humidity sensor and an FT742-SM wind speed and direction sensor. A total of 39 flights were performed, including stationary flights at altitudes of 300, 80, 60, 40, 20, and 10m for 150 seconds each. To analyze turbulence characteristics, additional stationary flights at 300 and 80m for 930 seconds each were performed.

The reliability of UAV meteorological observations was evaluated by comparing vertical meteorological data between UAV and towers and statistically analyzing the accuracy of UAV observation data. In addition to standard variables such as wind and temperature, we expect that production of post-processed observation data such as turbulent intensity can also be obtained using the UAV meteorological observation.

This research utilized data from the "Standardization of National Meteorological Equipment and Observation Data" project by the Korea Meteorological Administration's National Institute of Meteorological Sciences and was supported by the "Development of Core Technologies for Safe Operation of Korean Urban Air Mobility (K-UAM)" (RS-2024-00404042) project funded by the Korea Meteorological Administration. And this work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (RS-2024-00356913).

How to cite: Park, C., Lee, H., Kim, S., Ko, W., Choi, D., Kim, Y.-U., Jeon, Y., Kim, Y., Choi, M., Kwak, K.-H., and Lee, J.: Verification of UAV Meteorological Observation Against a Tall Meteorological Tower, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-672, https://doi.org/10.5194/icuc12-672, 2025.

Urban Air Mobility(UAM) is gaining attention as an innovative solution in transportation systems and is expected to alleviate urban traffic congestion. However, UAM aircraft are smaller and lighter compared to conventional airplanes, making them more vulnerable to various weather conditions. Specifically, UAM operates at altitudes ranging from 1,000 ft to 2,000 ft, which fall within the Planetary Boundary Layer(PBL). This layer is highly active with weather phenomena such as turbulence, potentially posing significant challenges to safe UAM operations. Furthermore, the absence of commercialized UAM aircraft limits direct analysis of turbulence and other weather factors. To address this challenge, this study proposes an alternative research method using light aircraft (defined as having a Maximum Take-Off Weight(MTOW) of 5,670 kg or less), specifically a Cessna, which shares similar size and operational altitude characteristics with UAM.

In this study, a Cessna aircraft was equipped with portable 3-axis accelerometers (x, y, z) to analyze the impacts of turbulence and weather effects at UAM operational altitudes over the Taean Peninsula on Korea’s western coast. The accelerometers recorded turbulence-induced vibrations(aircraft bumpiness) at a high sampling frequency of 100 Hz. These data were then compared and validated against Pilot Reports(PIREPs), which document unusual weather conditions during flights, to assess the sensor data's reliability and accuracy.

The analysis of the accelerometer data revealed stronger fluctuations over mountainous regions and land-sea boundaries, such as coastal areas. This finding was supported by PIREPs, which confirmed turbulence in similar regions. These results indirectly confirmed the impact of terrain features on turbulence at UAM operational altitudes. Consequently, this study demonstrated an alternative research method using light aircraft and portable accelerometers to measure and analyze turbulence at UAM operational altitudes. This research is expected to lay the groundwork for the future development of UAM aircraft and the establishment of weather support systems.

How to cite: Kwon, D., Choi, Y., and Won, W.-S.: Experimental Measurement of Turbulence at UAM Operational Altitudes Using an Aircraft-Mounted Accelerometer, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-574, https://doi.org/10.5194/icuc12-574, 2025.

While South Korea has undergone rapid urbanization concentrated in its metropolitan area, this development has likely affected meteorological conditions and nearby airports. Gimpo International Airport, located in Seoul, has experienced the effects of increasing urbanization in its surrounding areas. Gimpo International Airport is a core transportation hub for the metropolitan area, with an annual passenger volume of 34.73 million passengers. Its importance is expected to grow further with the planned installation of Urban Air Mobility (UAM) vertiports by 2030.

This study examines the correlation between the expansion of urbanization and low-altitude wind conditions around Gimpo International Airport.

Pilots have reported an increased frequency of turbulence during approach procedures at Gimpo International Airport. This study analyzes the impact of the expansion of high-rise buildings around the airport on wind conditions resulting from urbanization.

To conduct this analysis, ERA5 reanalysis data was utilized to collect wind data at 3,000ft altitude (approximately 925hPa), while Automated Weather Station (AWS) observational data was employed to obtain surface wind information. Subsequently, wind direction and speed were compared between these two altitudes.

The impact of urbanization on wind conditions was evaluated considering the changes in building distribution along approach routes. Comparing the meteorological conditions over the past 30 years between downtown and the airport area has revealed a significant difference in wind speed.

Due to the difference in this wind speed, the effect of turbulence or shear is considered to be increased. This study quantitatively examines the influence of urbanization on aircraft approach procedures and UAM operational altitude, providing foundational data for ensuring UAM safety and serving as a key reference for analyzing the safety of aircraft operations.

How to cite: Choi, Y., Kwon, D., and Won, W.-S.: Effects of Urbanization on Low-Altitude Wind Conditions Around Airport Approach Paths, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-575, https://doi.org/10.5194/icuc12-575, 2025.