We present a fully integrated InGaAs/InP negative feedback avalanche diode (NFAD) based free-running single-photon detector (SPD) designed for accurate lidar applications. A free-piston Stirling cooler is used to cool down the NFAD with a large temperature range, and an active hold-off circuit implemented in a field programmable gate array is applied to further suppress the afterpulsing contribution. The key parameters of the free-running SPD including photon detection efficiency (PDE), dark count rate (DCR), afterpulse probability, and maximum count rate (MCR) are dedicatedly optimized for lidar application in practice. We then perform a field experiment using a Mie lidar system with 20 kHz pulse repetition frequency to compare the performance between the free-running InGaAs/InP SPD and a commercial superconducting nanowire single-photon detector (SNSPD). Our detector exhibits good performance with 1.6 Mcps MCR (0.6 μs hold-off time), 10% PDE, 950 cps DCR, and 18% afterpulse probability over 50 μs period. Such performance is worse than the SNSPD with 60% PDE and 300 cps DCR. However, after performing a specific algorithm that we have developed for afterpulse and count rate corrections, the lidar system performance in terms of range-corrected signal (Pr²) distribution using our SPD agrees very well with the result using the SNSPD, with only a relative error of ∼2%. Due to the advantages of low-cost and small size of InGaAs/InP NFADs, such detector provides a practical solution for accurate lidar applications.

A mobile Rayleigh Doppler lidar based on double-edge technique is developed for mid-altitude wind observation. To reduce the systematic error, a system-level optical frequency control method is proposed and demonstrated. The emission of the seed laser at 1064 nm is used to synchronize the FPI in the optical frequency domain. A servo loop stabilizing the frequency of the seed laser is formed by measuring the absolute frequency of the second harmonic against an iodine absorption line. And, the third harmonic is used for Rayleigh lidar detection. The frequency stability is 1.6 MHz at 1064 nm over 2 minutes. A locking accuracy of 0.3 MHz at 1064 nm is realized. In comparison experiments, wind profiles from the lidar, radiosonde and European Center for Medium range Weather Forecast (ECMWF) analysis show good agreement from 8 km to 25 km. Wind observation over two months is carried out in Urumqi ($42.1°N,87.1°E$), northwest of China, demonstrating the stability and robustness of the system. For the first time, quasi-zero wind layer and dynamic evolution of high-altitude tropospheric jet are observed based on Rayleigh Doppler lidar in Asia.

Heatwaves (HWs) paired with higher ozone (O₃) concentration at the surface level pose a serious threat to human health. Their combined modulation of synoptic patterns and urbanization remains unclear. Using 5 years of summertime temperature and O₃ concentration observation in Beijing, this study explored potential drivers of compound HWs and O₃ pollution events and their public health effects. Three favorable synoptic weather patterns were identified to dominate the compound HWs and O₃ pollution events. These weather patterns contributing to enhance those conditions are characterized by sinking air motion, low boundary layer height, and high temperatures. Under the synergy of HWs and O₃ pollution, the mortality risk from all non-accidental causes increased by approximately 12.31 % (95 % confidence interval: 4.66 %, 20.81 %). Urbanization caused a higher risk of HWs and O₃ in urban areas than at rural stations. Particularly, due to O₃ depletion caused by NO titration at traffic and urban stations, the health risks related to O₃ pollution in different regions are characterized as follows: suburban stations > urban stations > rural stations > traffic stations. In general, favorable synoptic patterns and urbanization enhanced the health risk of these compound events in Beijing by 33.09 % and 18.95 %, respectively. Our findings provide robust evidence and implications for forecasting compound HWs and O₃ pollution events and their health risks in Beijing or in other urban areas all over the world that have high concentrations of O₃ and high-density populations.

Researches on the atmospheric boundary layer (ABL) need accurate measurements with high temporal and spatial resolutions from a series of different instruments. Here, a method for identifying cloud, precipitation, windshear, and turbulence in the ABL using a single coherent Doppler wind lidar (CDWL) is proposed and demonstrated. Based on deep analysis of the power spectrum of the backscattering signal, multiple lidar products, such as carrier-to-noise (CNR), spectrum width, spectrum skewness, turbulent kinetic energy dissipation rate (TKEDR), and shear intensity are derived for weather identification. Firstly, the cloud is extracted by Haar wavelet covariance transform (HWCT) algorithm based on the CNR after range correction. Secondly, since the spectrum broadening may be due to turbulence, windshear or precipitation, the spectrum skewness is introduced to distinguish the precipitation from two other conditions. Whereas wind velocity is obtained by single peak fitting in clear weather condition, the double-peak fitting is used to retrieve wind and rainfall velocities simultaneously in the precipitation condition. Thirdly, judging from shear intensity and TKEDR, turbulence and windshear are classified. As a double check, the temporal continuity is used. Stable wind variances conditions such as low-level jets are identified as windshear, while arbitrary wind variances conditions are categorized as turbulence. In the field experiment, the method is implemented on a micro-pulse CDWL to provide meteorological services for the 70th anniversary of the China’s National Day, in Inner Mongolia, China (43°54′N, 115°58′E). All weather conditions are successfully classified. By comparing lidar results to that of microwave radiometer (MWR), the spectrum skewness is found be more accurate to indicate precipitation than spectrum width or vertical speed. Finally, the parameter relationships and distributions are analyzed statistically in different weather conditions.

A dual-frequency direct detection Doppler lidar is demonstrated using a superconducting nanowire single-photon detector (SNSPD) at 1.5 μm. The so-called double-edge technique is implemented by using a dual-frequency laser pulse, rather than using a double-channel Fabry–Perot interferometer. Such a modification to the reported lidars enhances the frequency stability in the system level. Using the time-division multiplexing method, only one piece of SNSPD is used in the optical receiver, making the system simplified and robust. The SNSPD is adopted to enhance the temporal resolution since it offers merits of high quantum efficiency, low dark count noise, no after-pulsing probability, and a high maximum count rate. Two telescopes that point westward and northward at a zenith angle of 30° are used to detect the line-of-sight wind components, which are used to synthesize the horizontal wind profile. Horizontal wind profiles up to an altitude of about 2.7 km are calculated with vertical spatial/temporal resolution of 10 m/10 s. Wind dynamic evolution and vertical wind shears are observed clearly.

Doppler wind lidar is an effective tool for wind detection with high temporal and spatial resolution. However, precise wind profile measurement under rainy conditions is a challenge, due to the interfering signals from raindrop reflections. In this work, a compact all-fiber coherent Doppler lidar (CDL) at working wavelength of 1.5 µm is applied for simultaneous wind and precipitation detection. The performance of the lidar is validated by comparison with the weather balloons. Thanks to the ability of precise spectrum measurement, both aerosol and rainfall signals can be detected by the CDL under rainy conditions. The spectrum width is used to identify the precipitation events, during which the two-peak Doppler spectrum is observed. The spectrum is fitted by a two-component Gaussian model and two velocities are obtained. By using the velocity-azimuth display (VAD) scanning technique, wind speed and rainfall speed are simultaneously retrieved. The false detection probability of wind speed in the rainy conditions is thus reduced.