Inertial gravity waves observed by a Doppler wind LiDAR and their possible sources

In this paper,we use wind observations by a Doppler wind LiDAR near Delingha(37.4°N,97.4°E),Qinghai,Northwestern China to study the characteristics of inertial gravity waves in the stratosphere.We focus on 10–12 December 2013,a particularly interesting case study.Most of the time,the inertial gravity waves extracted from the LiDAR measurements were stationary with vertical wavelengths of about 9–11 km and horizontal wavelengths of about 800–1000 km.However,for parts of the observational period in this case study,a hodograph analysis indicates that different inertial gravity wave propagation features were present at lower and upper altitudes.In the middle and upper stratosphere(~30–50 km),the waves propagated downward,especially during a period of stronger winds,and to the northwest–southeast.In the lower stratosphere and upper troposphere(~10–20 km),however,waves with upward propagation and northeast–southwest orientation were dominant.By taking into account reanalysis data and satellite observations,we have confirmed the presence of different wave patterns in the lower and upper stratosphere during this part of the observational period.The combined data sets suggest that the different wave patterns at lower and upper height levels are likely to have been associated with the presence of lower and upper stratospheric jet streams.

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.

Photon-counting distributed free-space spectroscopy

Spectroscopy is a well-established nonintrusive tool that has played an important role in identifying and quantifying substances,from quantum descriptions to chemical and biomedical diagnostics.Challenges exist in accurate spectrum analysis in free space,which hinders us from understanding the composition of multiple gases and the chemical processes in the atmosphere.A photon-counting distributed free-space spectroscopy is proposed and demonstrated using lidar technique,incorporating a comb-referenced frequency-scanning laser and a superconducting nanowire single-photon detector.It is suitable for remote spectrum analysis with a range resolution over a wide band.As an example,a continuous field experiment is carried out over 72 h to obtain the spectra of carbon dioxide(CO_(2))and semi-heavy water(HDO,isotopic water vapor)in 6 km,with a range resolution of 60 m and a time resolution of 10 min.Compared to the methods that obtain only column-integrated spectra over kilometer-scale,the range resolution is improved by 2-3 orders of magnitude in this work.The CO_(2)and HDO concentrations are retrieved from the spectra acquired with uncertainties as low as±1.2%and±14.3%,respectively.This method holds much promise for increasing knowledge of atmospheric environment and chemistry researches,especially in terms of the evolution of complex molecular spectra in open areas.