Meteorology and Atmospheric Physics

, Volume 131, Issue 5, pp 1235–1248 | Cite as

Sensitivity of urban boundary layer simulation to urban canopy models and PBL schemes in Beijing

  • Meng Huang
  • Zhiqiu GaoEmail author
  • Shiguang Miao
  • Fei Chen
Original Paper


Mesoscale models with urban canopy models (UCM) have been increasingly used to study urban boundary layer processes. Using the data from a high-resolution Doppler lidar, automatic weather stations (AWS), and a flux tower located in the urban site, we assessed the performance of the urbanized Weather Research and Forecasting (WRF) model through three urban canopy models (the single-layer UCM, and the multi-layer BEP and BEM models) and four planetary boundary layer (PBL) schemes (the non-local first-order YSU, SH and ACM2 schemes, as well as the local TKE-based BouLac scheme) for one cloudy and one clear sky days. Results show that the WRF-Urban generally overestimates the sensible heat flux and underestimates the latent heat flux. The simulated 2-m temperature and 10-m wind speed are more sensitive to UCMs than to PBL schemes. Using the BouLac PBL scheme and the multi-layer BEP generates the best agreement with AWS observations. Simulations with the multi-layer BEM produce the highest mixing-layer heights. The convective boundary layer (CBL) from the single-layer UCM experiment develops at the slowest pace when compared with other two multi-layer UCMs. When the single-layer UCM is used, simulations with the non-local mixing YSU, SH and ACM2 schemes perform better than the TKE-based scheme (BouLac) for representing the CBL structure. Additionally, the scale-aware SH scheme considering the effect of grid resolution on the vertical dimension, simulates the potential temperature profiles that are closest to observations.



This work was supported by the National Key Projects of Ministry of Science and Technology of China (Grant nos. 2017YFA0604002, 2016YFC0203304, and 2015DFA20870); the National Natural Science Foundation of China (Grant no. 41275022); the Startup Foundation for Introducing Talent of NUIST (Grant no. 2017R088); the National Center for Atmospheric Research/Water System Program; and U.S. Department of Agriculture/National Institute of Food and Agriculture (Grant no. 20156700323460). We greatly appreciate two anonymous reviewers for their careful review and valuable comments which led to substantial improvement of this manuscript.


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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Atmospheric PhysicsNanjing University of Information Science and TechnologyNanjingChina
  2. 2.State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  3. 3.Institute of Urban MeteorologyChina Meteorological AdministrationBeijingChina
  4. 4.National Center for Atmospheric ResearchBoulderUSA
  5. 5.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijingChina

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