Articles | Volume 7, issue 1
Atmos. Meas. Tech., 7, 173–182, 2014
Atmos. Meas. Tech., 7, 173–182, 2014

Research article 22 Jan 2014

Research article | 22 Jan 2014

Lidar-based remote sensing of atmospheric boundary layer height over land and ocean

T. Luo et al.

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Cited articles

Ahlgrimm, M. and Randall, D. A.: Diagnosing Monthly Mean Boundary Layer Properties from Reanalysis Data using a Bulk Boundary Layer Model, J. Atmos. Sci., 63, 998–1012,, 2006.
Ao, C. O., Waliser, D. E., Chan, S. K., Li, J.-L., Tian, B., Xie, F., and Mannucci, A. J.: Planetary boundary layer heights from GPS radio occultation refractivity and humidity profiles, J. Geophys. Res., 117, D16117,, 2012.
Baars, H., Ansmann, A., Engelmann, R., and Althausen, D.: Continuous Monitoring of the Boundary-layer Top with Lidar. Atmos. Chem. Phys., 8, 7281–7296,, 2008.
Boers, R. and Eloranta, E. W.: Lidar Measurements of the Atmospheric Entrainment Zone and Potential Temperature Jump across the Top of the Mixed Layer, Bound.-Lay. Meteorol., 34, 357–375, 1986.
Boers, R., Eloranta, E. W., and Coulter, R. L.: Lidar Observations of Mixed Layer Dynamics: Tests of Parametrized EntrainmentModels of Mixed Layer Growth Rate, J. Clim. Appl. Meteorol., 23, 247–266, 1984.