The propagation of intense femtosecond laser in air can lead to a phenomenon of long-distance diffraction-free filamentation, accompanied by the generation of supercontinuum white light laser. The supercontinuum white light laser has the characteristics of broad bandwidth spectrum, high directivity and strong backward scattering radiation, which provides an effective technical way for long-distance atmospheric remote sensing detection, i.e., filament supercontinuum lidar technology. As a unique advantage of lidar, high spatio-temporal resolution is closely related to the continuous progress of ultra-fast laser pulse technology. On the other hand, the important parameters such as repetition rate and pulse width of laser jointly determine the ability of lidar system to achieve high spatiotemporal resolution. The research progress of high-repetition rate intense femtosecond laser filamentation for supercontinuum lidar applications is introduced in this paper, including the characterization of high-repetition rate femtosecond filaments, the generation and modulation of high-repetition rate filament-induced supercontinuum spectrum, and the development of supercontinuum lidar technology. The unique advantages of supercontinuum white light produced by high repetition-rate femtosecond laser pulse in the field of atmospheric remote sensing are summarized and forecasted, and the scientific problems and technical challenges are also pointed out.

Atmospheric water vapor plays a significant role in water cycle and climate change, and is closely related to human production and daily life. The timely detection of atmospheric water vapor can offer weather warnings and guide human production and life. After decades of development, Raman lidar technology for water vapor detection has stood out among numerous water vapor detection technologies with its advantages of ultra-high spatio-temporal resolution, long-distance detection, high sensitivity and low labor cost. This article reviews the development of water vapor Raman lidar and its related technologies, with the focus on the calibration and verification of Raman lidar system, spectral splitting techniques, system integration as well as the application and performance of water vapor Raman lidar system.

Atmospheric water vapor is one of the most fundamental meteorological parameters and plays important roles in local meteorology, global climate change, water cycling and atmospheric chemical process. As an active optical remote sensing technology, differential absorption lidar (DIAL) technique can measure atmospheric water vapor with high temporal and spatial resolution, and is widely used in the measurement of atmospheric water vapor profile. In this paper, the research progress of the H2O-DIAL technique and its applications are reviewed comprehensively, and various H2O-DIAL systems based on different laser sources, as well as frequency stabilization technique of laser, are described. In addition, the development trend of H2O-DIAL technology and its application are prospected. In particular, it is pointed out that the tunable optical parametric oscillator and micro-pulse H2O-DIAL at 935 nm band are developing rapidly, which is worthy of attention.

Water vapor is one of the fundamental thermodynamic variables that define the state of the atmosphere. It is not only of great significance to the radiation and energy balance of the Earth's atmosphere, but also closely related to environmental issues such as the greenhouse effect. Therefore, detecting the spatiotemporal distribution of atmospheric water vapor content is of great significance to global or regional meteorological and climate research, weather forecasting, etc. Differential absorption lidar (DIAL) technology mainly utilizes the differential absorption effect of water vapor at two neighboring wavelengths, one wavelength with strong absorption (λon) and the other with much weak absorption (λoff), to detect water vapor profiles. It has the characteristics of strong echo and superior daytime performance. DIAL has been considered as an important candidate for remote sensing of atmospheric water vapor profiles, but so far, there is still a lack of systematic quantitative analysis on the influencing factors in the retrieval of the water vapor profile for 828 nm H2O-DIAL. This article establishes a theoretical model for an 828 nm narrowband H2O-DIAL system based on differential absorption spectroscopy of water vapor and atmospheric lidar theory. And based on Monte Carlo method, the influence of molecular Doppler broadening effect, atmospheric temperature profile, frequency stability of the light source, signal-to-noise ratio, and other factors on the retrieval profile of water vapor have been carefully evaluated. It has been found out that the maximum retrieval error of water vapor concentration profile caused by the Doppler broadening effect can reach up to 7%, the error of retrieving the water vapor profile using the average temperature profile obtained from local radiosonde is generally less than 2.5%, and when the frequency fluctuation of the laser is less than 400 MHz, its impact on the retrieved water vapor profile can be ignored. In addition, it is shown that the noise of echo signal has a significant impact on the inversion result. To maintain an inversion error within 10% at 10 km (fitting distance of 300 m), the signal-to-noise ratio of the differential absorption curve at 10 km should be greater than 30 dB. The evaluation result in this work indicates that the uncertainty of temperature profile and the Doppler broadening effect of molecular scattering should be carefully considered for high precision measurements (< 5%). This work will provide important guidance for the design and optimization of near-infrared 828 nm H2O-DIAL system.

This paper introduces an all-solid-state lidar system based on optical parametric oscillator (OPO) and optical parametric amplification (OPA) technology, and its application in the detection of atmospheric metal components. The lidar system is distinguished by its high output energy (up to 100 mJ), narrow linewidth (< 200 MHz), and the excellent uniformity of laser spot, which significantly enhances its sensitivity for detecting metal ions in the atmosphere, and a detection sensitivity of 0.02 cm-3 for metal ions can be achieved at 1 km in 1 hour integration time. In the field experiments conducted in Beijing, Mohe, and other sites, the overnight evolution data of calcium atoms and ions were successfully obtained using the lidar system, and calcium ion layers extending up to 300 km in altitude were detected. These results indicate that, compared with traditional dye laser technology, the all-solid-state lidar has the advantages of high sensitivity and high resolution, and a series of new phenomena detected are expected to promote the discovery of new processes and mechanisms in space physics. In addition, this paper also discusses the prospective applications of this technology in advancing lidar detection capabilities.

Exploring the detection performance of coherent Doppler wind lidar (CDWL) under different meteorological conditions is of great significance for the network observation of aviation meteorological equipment. Using the CDWL deployed at Guangzhou Baiyun International Airport, combined with aviation routine weather reports and meteorological data from the National Centers for Environmental Information of the United States, this study analyzed the effects of different cloud cover and daily cumulative precipitation on the effective detection range and signal-to-noise ratio of the CDWL, and further explored the dynamic impacts of visibility and precipitation weather phenomena on the detection performance of CDWL through typical observation cases. The experimental results show that under non precipitation conditions, the effective detection distance and signal-to-noise ratio of CDWL show a decreasing trend with the increase of cloud cover and the decrease of visibility, and the case analysis shows that, when the visibility is less than 3 km, the effective detection range of CDWL decreases significantly, with a detection range of only 2–4 km. While under precipitation conditions, the intensity and spatiotemporal distribution characteristics of precipitation will affect the detection performance of CDWL, and the case analysis shows that under weak precipitation intensity, the suppression of intermittent precipitation on CDWL detection performance is more significant than that under thunderstorm conditions, and even under heavy rainstorm conditions, CDWL can still maintain a detection range of 2 km.

In order to study the distribution of PM2.5 mass concentration in China and monitor the changes of atmospheric environment in China, based on the Aerosol and Carbon dioxide Detection Lidar (ACDL) aerosol data of atmospheric environment monitoring satellites (DQ-1) and the ground-based PM2.5 observation data of China, the correlation between aerosol optical depth (AOD) and PM2.5 data was improved through vertical correction and humidity correction, and the seasonal variation of PM2.5 mass concentration changes in China from June 2022 to May 2023 was estimated using the semi-empirical method. The results show that during the period from June 2022 to May 2023, the PM2.5 mass concentration in China is the lowest in summer and the highest in winter. Due to the existence of desert in Xinjiang, the annual PM2.5 mass concentration is relatively high. The PM2.5 mass concentration in most parts of China is about 30 &mu;g/m3, and the correlation between remote sensing estimation of PM2.5 annual mean and station data is better than 0.71. This study is of certain significance for enriching regional PM2.5 inversion methods and expanding the application of ACDL atmospheric data.

The vertical structure of atmospheric aerosols affects aerosol optical characteristics, the distribution of atmospheric environmental pollution, and regional climate change. Based on the verification by using ground-based data, this paper studies the seasonal distribution and annual variation characteristics of the vertical structure of aerosols over sea and land in central Yangtze River Delta region from 2013 to 2022, using the aerosol extinction coefficient and its type information inverted from the cloud-aerosol lidar and infrared pathfinder satellite observer (CALIPSO) observations. The results show that the aerosol extinction coefficient over land is significantly higher than that over sea, and polluted continental and polluted dust aerosols dominate over land, while clean marine and dusty marine aerosols are predominant over sea. Specifically, in spring, under the influence of dust from the Mongolian Plateau and the Taklimakan Desert, as well as northerly winds, dust aerosols are transported over long distances to central Yangtze River Delta region, affecting both land and sea region. In summer, the rising smoke aerosols from urban and industrial development primarily concentrate at the altitude of 1.5&ndash;3.5 km over land, whereas marine aerosols dominate over sea, with their extinction coefficients at the altitude of 0&ndash;1.5 km significantly lower than those in other seasons. During autumn and winter, polluted dust and polluted continental aerosols over land accumulate mainly within the altitude of 0&ndash;1 km, with the ground-level aerosol extinction coefficient reaching its annual peak in winter (approximately 0.5 km-1), however, marine aerosols consistently account for a high proportion over sea, resulting in minimal seasonal variation of aerosol extinction coefficient. Overall, over the past decade, the aerosol optical depth (AOD) in the vertical column over both land and sea regions in central Yangtze River Delta region has shown a declining trend year by year.

Temperature and humidity Raman lidar can detect atmospheric temperature and humidity with high spatiotemporal resolution and high accuracy. Based on the principles of atmospheric Raman scattering lidar, a comprehensive simulation model encompassing laser emission system, atmospheric target characteristics, optical transmission properties, and optical reception and detection systems was constructed in this work. Then the four-channel detection signals of Raman lidar was simulated and inverted, and the simulation results were compared with the actual measurements. The comparison results demonstrated that the determination coefficients of temperature and humidity are 0.999 and 0.907 respectively, validating the accuracy of the simulation model. On this basis, the simulation model was further employed to optimize the parameters of the Raman lidar system. By iterating the parameters of the emission and detection modules, the wavelength of 355 nm was determined as the center wavelength of the excitation light of the lidar system, and 353.5 nm and 354 nm were selected as the center wavelengths of the rotating Raman filters to improve the detection sensitivity and accuracy.

Cirrus clouds, typically found at altitudes above 6 km, consist of non-spherical ice crystals and play a crucial role in the earth's radiation balance. Previous in-situ observation experiments have revealed a significant presence of hollow ice crystals in cirrus clouds. However, due to the absence of appropriate forward model, the existence of these hollow ice crystals is often overlooked in lidar observation studies. Based on prior in-situ observations, this paper establishes an empirical relationship between the hollowness and the length of hollow ice crystals, addressing the limitations of the fixed hollowness assumption used in previous hollow ice crystal models. The derivation of the physical optics approximation method based on beam-splitting and the calculation process for the backscattering properties of hollow ice crystals are introduced in detail. The simulation results show that both the wavelength depolarization ratio and the color ratio of ice crystals at 532 nm and 1064 nm are dependent on crystal size, and especially, the color ratio of ice crystal dooecreases monotonically with the increase of crystal size.

In practical applications, lidar signals are often subject to interference from solar background light and the dark current of photodetectors, which compromises the accuracy and reliability of data. To effectively eliminate the noise within the signal, this paper introduces a denoising method based on successive variational mode decomposition (SVMD) and singular value decomposition (SVD). Firstly, the red-tailed hawk (RTH) algorithm is employed to optimize the parameters of SVMD, enabling a more precise decomposition of lidar signals and extraction of intrinsic mode functions (IMFs). Then, the entropy of each IMF is assessed by calculating permutation entropy (PE), which is categorized into effective components and noise component, and the effective component will be undergone SVD-based denoising. Simulation and empirical results demonstrate that, compared with the other methods, the proposed method yields the smoothest signal waveform after denoising, with the highest signal-to-noise ratio and the lowest root mean square error, and can effectively suppresses long-distance noise without distortion, showing superior denoising performance under the same conditions.

Bioaerosols are a major hazard to public safety, and fluorescence lidar is a powerful tool for remote sensing to obtain bioaerosol information. In order to solve the problem of optimising the design of key system parameters in the development of fluorescence lidar, a test platform for fluorescence signal detection is designed and constructed in this work. In the platform, a UV laser with adjustable emission energy is adopted as excitation light source to test the effect of excitation energy on the detection capability, a grating monochromator with a wide range of adjustable central wavelength is used in the receiving optical path for fluorescence signal extraction, which is convinent to optimize the central wavelength of fluorescence detection for bioaerosols. At the same time, the bandwidth of the fluorescence signal reception for the platform is adjustable, which is used to optimize the optical bandwidth of the lidar, and the optoelectronic signal detection unit adopts photon counting mode for weak lidar signal detection. The experimental results show that, the laser emission energy, fluorescence receiving wavelength, and optical bandwidth the platform are flexibly adjustable, and and the detection performance of lidar can be optimized by adjusting these key parmeters, which is conducive to the study of the fluorescence spectra and fluorescence peak characteristics of bioaerosols. The platform can provide guidance for the design of fluorescence lidar system and the experimental study of fluorescence spectroscopy of bioaerosols.

Accurate sea surface positioning and extraction are critical factors influencing the measurement precision and bathymetric accuracy of airborne oceanographic lidar. When 532 nm lidar is used for sea surveying and mapping, the scattering and absorption of sea surface waves and near-surface water after laser penetrating through the air-sea interface will degrade the accuracy of sea surface positioning at this wavelength. This study employed a Bidirectional Long Short-Term Memory (Bi-LSTM) network for sea surface positioning. According to Bi-LSTM method, the complete sea surface return waveforms from dual-wavelength detection (1064 nm and 532 nm) were used for training, and then the 1064 nm detection results were used as ground truth to determine the sea surface positions of 532 nm channel. Application of the trained model to 532 nm detection data showed that the average positioning bias using Bi-LSTM algorithm was 0.03 m, while that of conventional peak detection algorithm was -0.21 m. Bi-LSTM algorithm was further used to quantitatively evaluate the influence of seawater diffuse attenuation coefficient on the bias, and the results showed that the minimum bias of 0.03 m occurred when the seawater diffuse attenuation coefficient was in the range of 0.05–0.15 m-1.