Articles | Volume 11, issue 9
https://doi.org/10.5194/amt-11-5075-2018
https://doi.org/10.5194/amt-11-5075-2018
Research article
 | 
07 Sep 2018
Research article |  | 07 Sep 2018

Graphics algorithm for deriving atmospheric boundary layer heights from CALIPSO data

Boming Liu, Yingying Ma, Jiqiao Liu, Wei Gong, Wei Wang, and Ming Zhang

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Cited articles

Bonin, T., Chilson, P., Zielke, B., and Fedorovich, E.: Observations of the early evening boundary-layer transition using a small unmanned aerial system, Bound.-Lay. Meteorol., 146, 119–132, 2013. 
Brooks, I. M.: Finding boundary layer top: Application of a wavelet covariance transform to lidar backscatter profiles, J. Atmos. Ocean. Tech., 20, 1092–1105, 2003. 
Davis, K. J., Gamage, N., Hagelberg, C. R., Kiemle, C., Lenschow, D. H., and Sullivan, P. P.: An Objective Method for Deriving Atmospheric Structure from Airborne Lidar Observations, J. Atmos. Ocean. Tech., 17, 1455–1468, 2000. 
Flamant, C., Pelon, J., and Flamant, P.: Lidar determination of the entrainment zone thickness at the top of the unstable marine atmospheric boundary layer, Bound.-Lay. Meteorol., 83, 247–284, 1997. 
Guo, J., Miao, Y., Zhang, Y., Liu, H., Li, Z., Zhang, W., He, J., Lou, M., Yan, Y., Bian, L., and Zhai, P.: The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data, Atmos. Chem. Phys., 16, 13309–13319, https://doi.org/10.5194/acp-16-13309-2016, 2016a. 
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