Observation of Stable Marine Boundary Layer by Shipborne Coherent Doppler Lidar and Radiosonde over Yellow Sea

Shipborne observations obtained with the coherent Doppler lidar(CDL)and radiosonde during 2014 campaign were used to study the structure of marine boundary layer in the Yellow Sea.Vertical wind profiles corrected for ship motion was used to derive higher-order statistics,showing that motion correction is required and significant for turbulence analysis.During a day with weak mesoscale activity,a complexed three-layer structure system was observed.The lowest layer showed a typical stable boundary layer structure feature.An aerosol layer with abrupt variation in wind speed and relative humidity always appeared at the middle layer,the formation of which may be due to Kelvin-Helmholz instability.The top layer encountered a dramatic change in wind direction,which may result from the warm advection from the Eurasian continent on the basis of backward trajectory analysis.Furthermore,the MABL height in stable regime was derived from potential temperature,CDL signal-to-noise ratio(SNR)and CDL vertical velocity variance,respectively.The stable boundary layer(SBL)height in SBL can be derived from the inversion layer of potential temperature profile,and the mixing height in SBL can be retrieved from the vertical velocity variance gradient method.Neither the SBL height nor the mixing height is in agreement with the height retrieved from CDL SNR gradient method because of different definition and criterion.One of the limitations of SNR gradient method for MABL retrieval is that it is easier to be affected by the lofted decoupled aerosol layer,where the retrieved result is less suitable.Finally,the higher-order vertical velocity statistics within the marine stable boundary layer were investigated and compared with the previous studies,and different turbulence mechanisms have an important effect on the statistics deviation.

Coherent Doppler lidar wind retrieval for a typhoon based on the genetic simulated annealing algorithm

A method of spectrum estimation based on the genetic simulated annealing(GSA)algorithm is proposed,which is applied to retrieve the three-dimensional wind field of typhoon Nangka observed by our research group.Compared to the genetic algorithm(GA),the GSA algorithm not only extends the detection range and guarantees the accuracy of retrieval results but also demonstrates a faster retrieval speed.Experimental results indicate that both the GA and GSA algorithms can enhance the detection range by 35%more than the least squares method.However,the convergence speed of the GSA algorithm is 17 times faster than that of the GA,which is more beneficial for real-time data processing.

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

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 free-space 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.