Technical note: Boundary layer height determination from Lidar for improving air pollution episode modelling: development of new algorithm and evaluation
Ting Yang1, Zifa Wang1, Wei Zhang2, Alex Gbaguidi1, Nubuo Sugimoto3, Xiquan Wang1, Ichiro Matsui3, and Yele Sun11State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China 2Aviation Meteorological Center of China, Beijing 100021, China 3National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, 305-8506, Japan
Received: 12 Nov 2016 – Accepted for review: 03 Jan 2017 – Discussion started: 03 Jan 2017
Abstract. Predicting air pollution events in low atmosphere over megacities requires thorough understanding of the tropospheric dynamic and chemical processes, involving notably, continuous and accurate determination of the boundary layer height (BLH). Through intensive observations experimented over Beijing (China), and an exhaustive evaluation existing algorithms applied to the BLH determination, persistent critical limitations are noticed, in particular over polluted episodes. Basically, under weak thermal convection with high aerosol loading, none of the retrieval algorithms is able to fully capture the diurnal cycle of the BLH due to pollutant insufficient vertical mixing in the boundary layer associated with the impact of gravity waves on the tropospheric structure. Subsequently, a new approach based on gravity wave theory (the cubic root gradient method: CRGM), is developed to overcome such weakness and accurately reproduce the fluctuations of the BLH under various atmospheric pollution conditions. Comprehensive evaluation of CRGM highlights its high performance in determining BLH from Lidar. In comparison with the existing retrieval algorithms, the CRGM potentially reduces related computational uncertainties and errors from BLH determination (strong increase of correlation coefficient from 0.44 to 0.91 and significant decrease of the root mean square error from 643 m to 142 m). Such newly developed technique is undoubtedly expected to contribute to improve the accuracy of air quality modelling and forecasting systems.
Yang, T., Wang, Z., Zhang, W., Gbaguidi, A., Sugimoto, N., Wang, X., Matsui, I., and Sun, Y.: Technical note: Boundary layer height determination from Lidar for improving air pollution episode modelling: development of new algorithm and evaluation, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-1010, in review, 2017.