Articles | Volume 14, issue 2
Atmos. Meas. Tech., 14, 1099–1110, 2021
https://doi.org/10.5194/amt-14-1099-2021
Atmos. Meas. Tech., 14, 1099–1110, 2021
https://doi.org/10.5194/amt-14-1099-2021

Research article 10 Feb 2021

Research article | 10 Feb 2021

Assimilation of lidar planetary boundary layer height observations

Andrew Tangborn et al.

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Cited articles

Anderson, J. L., Hoar, T., Raeder, K., Liu, H., Collins, N., Torn R., and Arellano, A.: The Data Assimilation Research Testbed: A Community Facility, B. Am. Meteorol. Soc., 90, 1283–1296, https://doi.org/10.1175/2009BAMS2618.1, 2009. 
Bonin, T. A., Carroll, B. J., Hardesty, R. M., Brewer, W. A., Hajney, K., Salmon, O. E., and Shepson P.B.: Doppler Lidar Observations of the Mixing Height in Indianapolis Using an Automated Composite Fuzzy Logic Approach, J. Atmos. Ocean. Tech., 35, 473–490, 2018. 
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. 
Burgers, G., Van Leeuwen, P. J., and Evensen, G.: Analysis scheme in the ensemble Kalman filter, Mon. Weather Rev., 126, 1719–1724, https://doi.org/10.1175/1520-0493(1998)126<1719:ASITEK>2.0.CO;2, 1998. 
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Short summary
Accurate prediction of the planetary boundary layer is essential to both numerical weather prediction (NWP) and pollution forecasting. This paper presents a methodology to combine these measurements with the models through a statistical data assimilation approach that calculates the correlation between the PBLH and variables like temperature and moisture in the model. The model estimates of these variables can be improved via this method, and this will enable increased forecast accuracy.