To improve our knowledge of urban meteorology, including those processes applicable to high-resolution meteorological models in the Seoul Metropolitan Area (SMA), the Weather Information Service Engine (WISE) Urban Meteorological Observation System (UMS-Seoul) has been designed and installed. The UMS-Seoul incorporates 14 surface energy balance (EB) systems, 7 surface-based three-dimensional (3-D) meteorological observation systems and applied meteorological (AP) observation systems, and the existing surface-based meteorological observation network. The EB system consists of a radiation balance system, sonic anemometers, infrared CO₂/H₂O gas analyzers, and many sensors measuring the wind speed and direction, temperature and humidity, precipitation, and air pressure. The EB-produced radiation, meteorological, and turbulence data will be used to quantify the surface EB according to land use and to improve the boundary-layer and surface processes in meteorological models. The 3-D system, composed of a wind lidar, microwave radiometer, aerosol lidar, or ceilometer, produces the cloud height, vertical profiles of backscatter by aerosols, wind speed and direction, temperature, humidity, and liquid water content. It will be used for high-resolution reanalysis data based on observations and for the improvement of the boundary-layer, radiation, and microphysics processes in meteorological models. The AP system includes road weather information, mosquito activity, water quality, and agrometeorological observation instruments. The standardized metadata for networks and stations are documented and renewed periodically to provide a detailed observation environment. The UMS-Seoul data are designed to support real-time acquisition and display and automatically quality check within 10 min from observation. After the quality check, data can be distributed to relevant potential users such as researchers and policy makers. Finally, two case studies demonstrate that the observed data have a great potential to help to understand the boundary-layer structures more deeply, improve the performance of high-resolution meteorological models, and provide useful information customized based on the user demands in the SMA.

Accurate boundary layer structure and height are critical in the analysis of the features of air pollutants and local circulation. Although surface-based remote sensing instruments provide a high temporal resolution of the boundary layer structure, there are numerous uncertainties in terms of the accurate determination of the atmospheric boundary layer heights (ABLHs). In this study, an algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained using a ceilometer and a microwave radiometer in Seoul city, Korea. A maximum of 19 ABLHs were estimated via the conventional time-variance, gradient, wavelet, and clustering methods using the backscatter coefficient from the ceilometer. Meanwhile, several stable boundary layer heights were extracted through near-surface inversion and environmental lapse rate methods using the potential temperature from the microwave radiometer. The ISABLE algorithm can find an optimal ABLH from post-processing, such as k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. It was found that the ABLH determined using ISABLE exhibited more significant correlation coefficients and smaller mean bias and root mean square error between the radiosonde-derived ABLHs than those obtained using the most conventional methods. Clear skies exhibited higher daytime ABLH than cloudy skies, and the daily maximum ABLH was recorded in summer because of the more intense radiation. The ABLHs estimated by ISABLE are expected to contribute to the parameterization of vertical diffusion in the atmospheric boundary layer.

Local circulation plays an important role in producing high-resolution meteorological and air quality information. In this study, detailed surface meteorological and vertical profile features about sea and land breezes in the Seoul Metropolitan Area (SMA) were investigated using the data from urban meteorological observation system in SMA (UMS-Seoul). These data were obtained from high-resolution surface meteorological stations and three wind lidar stations for 6 consecutive days (17–22 May 2016) with very weak synoptic winds and low cloud covers. The 6-day average diurnal variations of surface meteorological variables revealed temperature differences between land and sea, driving the pressure differences between the two. This induced sea–land-breeze circulation. The resulting sea breeze began at the shoreline at 1200 local standard time (LST), moved landward at a rate of about 10 km h⁻¹, and reached 60 km from the shoreline at 1800 LST. The land breeze occurred within 50 km of the shoreline until noon. The sea-breeze front was identified by a steep horizontal temperature gradient, and its passage was accompanied by an abrupt temperature drop as well as vapor pressure and wind increases. The time–height cross section of wind indicated that the top of sea (land) breeze reached a maximum height of 1.5 km (0.8 km) with maximum winds 0.4 km (0.3–0.4 km) high in the late afternoon (early morning). The returning (easterly) flow at 1.5–1.6 km was clearly observed over the sea-breeze cells.

Vertical mixing in the planetary boundary layer (PBL) is an important factor in the prediction of particulate matter (PM) concentrations; however, PBL height (PBLH) in the stable atmosphere remains poorly understood. In particular, the assessment of uncertainties related to nocturnal PBLH (nPBLH) is challenging due to the absence of stable atmosphere observations. In this study, we explored nPBLH–PM_2.5 interactions by comparing model results and observations during the Korea–United States Air Quality Study (KORUS-AQ) campaign (1–31 May 2016). Remote sensing measurements (e.g., aerosol and wind Doppler lidar) and on-line WRF-Chem modeling results were used by applying three different PBL parameterizations: Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ), and Asymmetrical Convective Model v2 (ACM2). Our results indicated that the uncertainties of PBLH–PM interactions were not large in daytime, whereas the uncertainties of nPBLH–PM_2.5 interactions were significant. All WRF-Chem experiments showed a clear tendency to underestimate nighttime nPBLH by a factor of ~3 compared with observations, and shallow nPBLH clearly led to extremely high PM_2.5 peaks during the night. These uncertainties associated with nPBLH and nPBLH–PM_2.5 simulations suggest that PM_2.5 peaks predicted from nighttime or next-morning nPBLH simulations should be interpreted with caution. Additionally, we discuss uncertainties among PBL parameterization schemes in relation to PM_2.5 simulations.