4.6 Article

Robust Solution for Boundary Layer Height Detections with Coherent Doppler Wind Lidar

Journal

ADVANCES IN ATMOSPHERIC SCIENCES
Volume 38, Issue 11, Pages 1920-1928

Publisher

SCIENCE PRESS
DOI: 10.1007/s00376-021-1068-0

Keywords

boundary layer height; coherent Doppler wind lidar; carrier-to-noise ratio; turbulent kinetic energy dissipation rate

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A robust solution for BLH detection with CDWL is proposed, retrieving MLH from TKEDR and SBLH/RLH from CNR. An intercomparison experiment with two identical CDWLs reveals that CNR may introduce bias due to instrument instability, while MLH from TKEDR remains robust.
Although coherent Doppler wind lidar (CDWL) is promising in detecting boundary layer height (BLH), differences between BLH results are observed when different CDWL measurements are used as tracers. Here, a robust solution for BLH detections with CDWL is proposed and demonstrated: mixed layer height (MLH) is retrieved best from turbulent kinetic energy dissipation rate (TKEDR), while stable boundary layer height (SBLH) and residual layer height (RLH) can be retrieved from carrier-to-noise ratio (CNR). To study the cause of the BLH differences, an intercomparison experiment is designed with two identical CDWLs, where only one is equipped with a stability control subsystem. During the experiment, it is found that the CNR could be distorted by instrument instability because the coupling efficiency from freespace to the polarization-maintaining fiber of the telescope is sensitive to the surrounding environment. In the ML, a bias up to 2.13 km of the MLH from CNR is found, which is caused by the CNR deviation. In contrast, the MLH from TKEDR is robust as long as the accuracy of wind is guaranteed. In the SBL (RL), the CNR is found capable to retrieve SBLH and RLH simultaneously and robustly. This solution is tested during an observation period over one month. Statistical analysis shows that the root-mean-square errors (RMSE) in the MLH, SBLH, and RLH are 0.28 km, 0.23 km, and 0.24 km, respectively.

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