Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a ceilometer and microwave radiometer
Abstract. Accurate boundary-layer structure and height are critical in analyzing the features of air pollutants as well as the local circulation. Although surface-based remote sensing instruments give high temporal resolution of the boundary-layer structure, there were many uncertainties in determining the accurate 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 by a ceilometer and microwave radiometer in Seoul City, Korea. A maximum of 19 ABLHs were calculated by the conventional time-variance, gradient, wavelet, and clustering methods using the backscatter coefficient data. Meanwhile, several stable boundary layer heights were extracted by the near-surface inversion and environmental lapse rate methods using potential temperature data. The ISABLE algorithm could find an optimal ABLH from post-processing including k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. It is found that the ABLH determined by ISABLE exhibited larger correlation coefficients and smaller absolute bias and root mean square errors between the radiosonde-derived ABLHs than those obtained by most conventional methods. Clear skies showed higher daytime ABLH than cloudy skies, and the daily maximum ABLH was recorded in spring due to the stronger radiation. The ABLHs estimated by ISABLE are expected to contribute to the parameterization of vertical diffusion in the atmospheric boundary layer and in understanding the severe smog/haze events that arise from by fumigation during the ABL evolution period.