Search Results (16)

The temperature of the middle atmosphere is of great significance in the coupled study of the upper and lower layers. A pure rotational Raman–Rayleigh scattering LiDAR system was developed for profiling the middle atmospheric temperature at daytime and nighttime continuously by employing an ultra-narrow band interferometer. The comparisons between LiDAR detections and radiosonde data show that the LiDAR system has temperature detection capabilities of 80 km and 60 km at night and during the day, respectively. The results demonstrate that our method can reliably detect the atmospheric temperature in the middle atmosphere. The significant non-uniformity in the horizontal distribution of temperature in the middle atmosphere and the vertical gradient of atmospheric temperature could be observed by using the developed LiDAR. Full article

Localized operating conditions inside boilers, heat recovery steam generators, or other large thermal systems have a huge impact on the efficiency, environmental performance, and lifetime of components. It is extremely difficult to measure species accurately within these systems due to the high temperatures and harsh environments, locally oxidizing or reducing atmospheres, ash, other particulates, and other damaging chemical species. Physical probes quickly suffer damage and are rendered nonfunctional. This work has attempted to adapt the measurement approach based on Scheimpflug light detection and ranging (S-LIDAR) for the remote sensing of gas species inside the high-temperature boiler environment. For a proof-of-concept, the detection of Raman signals of N₂, O₂, and CO₂ and their behavior with increasing temperature have been presented. Full article

This study aims to achieve the classification of the cirrus clouds over the Observatory of Haute-Provence (OHP) in France. Rayleigh–Mie–Raman lidar measurements, in conjunction with the ERA5 dataset, are analyzed to provide geometrical morphology and optical cirrus properties over the site. The method of cirrus cloud climatology presented here is based on a threefold classification scheme based on the cirrus geometrical and optical properties and their formation history. Principal component analysis (PCA) and subsequent clustering provide four morphological cirrus classes, three optical groups, and two origin-related categories. Cirrus clouds occur approximately 37% of the time, with most being single-layered (66.7%). The mean cloud optical depth (COD) is 0.39 ± 0.46, and the mean heights range around 10.8 ± 1.35 km. Thicker tropospheric cirrus are observed under higher temperature and humidity conditions than cirrus observed in the vicinity of the tropopause level. Monthly cirrus occurrences fluctuate irregularly, whereas seasonal patterns peak in spring. Concerning the mechanism of the formation, it is found that the majority of cirrus clouds are of in situ origin. The liquid-origin cirrus category consists nearly entirely of thick cirrus. Overall results suggest that in situ origin thin cirrus, located in the upper tropospheric and tropopause regions, have the most noteworthy occurrence over the site. Full article

The pure rotational Raman (PRR) lidar technique relies on calibration functions (CFs) to extract temperature information from raw detection data. The choice of CF significantly impacts the accuracy of the retrieved temperature. In this study, we propose a method that combines multiple Monte Carlo simulation experiments with a statistical analysis, and we first conduct simulated comparisons of the calibration effects of different CFs while considering the impact of noise. We categorized ten common CFs into four groups based on their functional form and the number of calibration coefficients. Based on functional form, specifically, we defined 1/T = f(lnQ) as a forward calibration function (FCF) and lnQ = g(1/T) as a backward calibration function (BCF). Here, T denotes temperature, and Q denotes the signal intensity ratio. Their performance within and outside the calibration interval is compared across different integration times, smoothing methods, and reference temperature ranges. The results indicate that CFs of the same category exhibit similar calibration effects, while those of different categories exhibit notable differences. Within the calibration interval, the FCF performs better, especially with more coefficients. However, outside the calibration interval, the linear calibration function (which can be considered a two-coefficient FCF) has an obvious advantage. Conclusions based on the simulation results are validated with actual data, and the factors influencing calibration errors are discussed. Utilizing these findings to guide CF selection can enhance the accuracy and stability of PRR lidar detection. Full article

The diel vertical variations of chlorophyll a (Chl-a) concentration are thought of primarily as an external manifestation of regulating phytoplankton’s biomass, which is essential for dynamically estimating the biogeochemical cycle in inland waters. However, information on these variations is limited due to insufficient measurements. Undersampled observations lead to delayed responses in phytoplankton assessment, impacting accurate evaluations of carbon export and water quality in dynamic inland waters. Here, we report the first lidar-observed diel vertical variations of inland Chl-a concentration. Strong agreement with r² of 0.83 and a root mean square relative difference (RMSRD) of 9.0% between the lidar-retrieved and in situ measured Chl-a concentration verified the feasibility of the Mie–fluorescence–Raman lidar (MFRL). An experiment conducted at a fixed observatory demonstrated the lidar-observed diel Chl-a concentration variations. The results showed that diel variations of Chl-a and the formation of subsurface phytoplankton layers were driven by light availability and variations in water temperature. Furthermore, the facilitation from solar radiation-regulated water temperature on the phytoplankton growth rate was revealed by the high correlation between water temperature and Chl-a concentration anomalies. Lidar technology is expected to provide new insights into continuous three-dimension observations and be of great importance in dynamic inland water ecosystems. Full article

Due to the influence of geometric factors, the temperature and humidity profile of lidar’s near-field signal was warped when sensing the air environment. In order to perform geometric factor correction on near-field signals, this article proposes different correction solutions for the Mie and Raman scattering channels. Here, the Mie scattering channel used the Raman method to invert the aerosol backscatter coefficient and correct the extinction coefficient in the transition zone. The geometric factor was the ratio of the measured signal to the forward-computed vibration Raman scattering signal. The aerosol optical characteristics were reversed using the corrected echo signal, and the US standard atmospheric model was added to the missing signal in the blind zone, reflecting the aerosol evolution process. The stability and dependability of the proposed algorithm were validated by the consistency between the visibility provided by the Environmental Protection Agency and the visibility acquired via lidar retrieval data. The near-field humidity data were supplemented by the interpolation method in the Raman scattering channel to reflect the water vapor transfer process in the temporal dimension. The measured transmittance curve of the filter, the theoretical normalized spectrum, and the sounding data were used to compute the delay geometric factor. The temperature was retrieved and the near-field signal distortion issue was resolved by applying the corrected quotient of the temperature channel. The proposed algorithm exhibited robustness and universality, enhancing the system’s detection accuracy compared to the temperature and humidity data constantly recorded by the probes in the meteorological gradient tower, which have a high correlation with the lidar observation data. The comparison between lidar data and instrument monitoring data showed that the proposed algorithm could effectively correct distorted echo signals in the transition zone, which was of great value for promoting the application of lidar in the meteorological monitoring of the urban canopy layer. Full article

It was for a long time believed that lidar systems based on the use of high-repetition micro-pulse lasers could be effectively used to only stimulate atmospheric elastic backscatter echoes, and thus were only exploited in elastic backscatter lidar systems. Their application to stimulate rotational and roto-vibrational Raman echoes, and consequently, their exploitation in atmospheric thermodynamic profiling, was considered not feasible based on the technical specifications possessed by these laser sources until a few years ago. However, recent technological advances in the design and development of micro-pulse lasers, presently achieving high UV average powers (1–5 W) and small divergences (0.3–0.5 mrad), in combination with the use of large aperture telescopes (0.3–0.4 m diameter primary mirrors), allow one to presently develop micro-pulse laser-based Raman lidars capable of measuring the vertical profiles of atmospheric thermodynamic parameters, namely water vapor and temperature, both in the daytime and night-time. This paper is aimed at demonstrating the feasibility of these measurements and at illustrating and discussing the high achievable performance level, with a specific focus on water vapor profile measurements. The technical solutions identified in the design of the lidar system and their technological implementation within the experimental setup of the lidar prototype are also carefully illustrated and discussed. Full article

From December 2021 to May 2022, MeteoSwiss and Meteomatics conducted a proof of concept to demonstrate the capability of automatic drones to provide data of sufficient quality and reliability on a routine operational basis. Over 6 months, Meteodrones MM-670 were operated automatically eight times per night at Payerne, Switzerland. In total, 864 meteorological profiles were measured and compared to co-located standard measurements, including radiosoundings and remote sensing instruments. To our knowledge, this is the first time that Meteodrone’s atmospheric profiles have been evaluated in such an extensive campaign. The paper highlights two case studies that showcase the performance and challenges of measuring temperature, humidity, and wind with a Meteodrone. It also focuses on the overall quality of the drone measurements. Throughout the campaign, the availability of Meteodrone measurements was 75.7%, with 82.2% of the flights reaching the nominal altitude of 2000 m above sea level. The quality of the measurements was assessed against the WMO’s (World Meteorological Organization) requirements. The temperature measurements gathered by the Meteodrone met the “breakthrough” target, while the humidity and wind profiles met the “threshold” target for high-resolution numerical weather prediction. The temperature measurement quality was comparable to that of a microwave radiometer, and the humidity quality was similar to that obtained from a Raman LiDAR. However, the wind measurements gathered by a Doppler LiDAR were more accurate than the estimation provided by the Meteodrone. This campaign marks a significant step towards the operational use of automatic drones for meteorological applications. Full article

The range of detection and accuracy of currently available Raman temperature LiDAR systems are primarily improved by increasing the energy or the aperture of the receiving telescope. However, this does not lead to a corresponding linear increase in the distance of detection and accuracy of the system. In this paper, the authors construct a simulation model and optimize its parameters to develop a Raman temperature LiDAR with low energy and a small aperture that has a maximum distance of detection of over 5 km during the day and over 10 km at night. The profile of the atmospheric temperature obtained through field tests was in good agreement with the results of a radiosonde. The maximum correlation between the Raman temperature LiDAR and the radiosonde was 0.94 at night and 0.81 during the day. The results showed that the proposed Raman temperature LiDAR, with low energy and a small aperture, can provide reliable data on the temperature in the troposphere throughout the day. Full article

This work stems from the idea of improving the capability to measure the atmospheric boundary layer height (ABLH) in variable or unstable weather conditions or in the presence of turbulence and precipitation events. A new approach based on the use of rotational and roto-vibrational Raman lidar signals is considered and tested. The traditional gradient approach based on the elastic signals at wavelength 532 nm is also considered. Lidar data collected by the University of Basilicata Raman lidar (BASIL) within the Special Observation Period 1 (SOP 1) in Cardillargues (Ceveninnes–CV supersite) during the Hydrological Cycle in the Mediterranean Experiment (HyMeX) were used. Our attention was specifically focused on the data collected during the period 16–21 October 2012. ABLH estimates from the Raman lidar were compared against other innovative methods, such as the recently established Morphological Image Processing Approach (MIPA) and the temperature gradient technique applied to potential temperature obtained from radio-sounding data. For each considered methodology, a statistical analysis was carried out. In general, the results from the different methodologies are in good agreement. Some deviations have been observed in correspondence with quite unstable weather conditions. Full article

Temperature inversion plays an important role in the accumulation and diffusion of aerosols. In this study, the relationship between temperature inversion and the vertical distribution of aerosols is investigated based on Raman lidar observations taken from January 2010 to September 2015 at the Atmospheric Radiation Measurement site in the Southern Great Plains, USA. First, the diurnal and seasonal variations of the surface-based inversion (SBI) and elevated temperature inversion (EI) are investigated. The results indicate that the occurrence frequency of SBI and EI have different seasonal trends. SBI has the highest frequency in summer, while EI has the highest frequency in winter. The diurnal variation of SBI is obvious, with a higher frequency in nighttime and a lower frequency in daytime. The inversion intensity (ΔT) and inversion depth (ΔZ) of SBI and EI have consistent diurnal and seasonal trends. The effects of SBI and EI on the vertical distribution of aerosols are then analyzed. The mean aerosol optical depth (AOD) below the SBI height shows a clear seasonal variation, which is consistent with the seasonal trends of ΔT and ΔZ. This phenomenon also occurs on the AOD below EI top height. The sensitivity analysis shows that the mean AOD below SBI height or EI top height increases with an increase of the ΔT and ΔZ of SBI (EI). It indicates that ΔT and ΔZ are the key factors affecting the vertical distribution of aerosols. In addition, the variation of AOD below and above EI top height is opposite to that of AOD below and above EI bottom height under different ΔT and ΔZ conditions. The correlation coefficients between ΔT (ΔZ) of EI with AOD in EI were 0.62 (0.65). These results indicate that the space between EI bottom height and EI top height can store aerosols. The larger the ΔZ of EI, the more aerosols are stored. These findings contribute to our understanding of the effect of temperature inversion on the vertical distribution of aerosols. Full article

In this work, we present Raman lidar data (from a Nd:YAG operating at $355$ nm, $532$ nm and $1064$ nm) from the international research village Ny-Ålesund for the time period of January to April 2020 during the Arctic haze season of the MOSAiC winter. We present values of the aerosol backscatter, the lidar ratio and the backscatter Ångström exponent, though the latter depends on wavelength. The aerosol polarization was generally below 2%, indicating mostly spherical particles. We observed that events with high backscatter and high lidar ratio did not coincide. In fact, the highest lidar ratios (LR > 75 sr at $532$ nm) were already found by January and may have been caused by hygroscopic growth, rather than by advection of more continental aerosol. Further, we performed an inversion of the lidar data to retrieve a refractive index and a size distribution of the aerosol. Our results suggest that in the free troposphere (above ≈2500 m) the aerosol size distribution is quite constant in time, with dominance of small particles with a modal radius well below $100$ nm. On the contrary, below ≈2000 m in altitude, we frequently found gradients in aerosol backscatter and even size distribution, sometimes in accordance with gradients of wind speed, humidity or elevated temperature inversions, as if the aerosol was strongly modified by vertical displacement in what we call the “mechanical boundary layer”. Finally, we present an indication that additional meteorological soundings during MOSAiC campaign did not necessarily improve the fidelity of air backtrajectories. Full article

The atmospheric molecular number density can be obtained from atmospheric temperature and pressure profiles and is a significant input parameter for the inversion of lidar measurements. When measurements of vertical profiles of temperature and pressure are not available, atmospheric models are typically considered a valid alternative option. This paper investigates the influence of different atmospheric models (forecast and reanalysis) on the retrieval of aerosol optical properties (extinction and backscatter coefficients) by applying Raman and elastic-only methods to lidar measurements, to assess their use in lidar data processing. In general, reanalyzes are more accurate than forecasts, but, typically, they are not delivered in time for allowing near-real-time lidar data analysis. However, near-real-time observation is crucial for real-time monitoring of the environment and meteorological studies. The forecast models used in the paper are provided by the Integrated Forecasting System operated by the European Centre for Medium-Range Weather Forecasts (IFS_ECMWF) and the Global Data Assimilation System (GDAS), whereas the reanalysis model is obtained from the fifth-generation European Centre for Medium-Range Weather Forecasts ReAnalysis v5 (ERA5). The lidar dataset consists of measurements collected from four European Aerosol Research Lidar Network (EARLINET) stations during two intensive measurement campaigns and includes more than 200 cases at wavelengths of 355 nm, 532 nm, and 1064 nm. We present and discuss the results and influence of the forecast and reanalysis models in terms of deviations of the derived aerosol optical properties. The results show that the mean relative deviation in molecular number density is always below ±3%, while larger deviations are shown in the derived aerosol optical properties, and the size of the deviation depends on the retrieval method together with the different wavelengths. In general, the aerosol extinction coefficient retrieval is more dependent on the model used than the aerosol backscatter retrievals are. The larger influence on the extinction retrieval is mainly related to the deviation in the gradient of the temperature profile provided by forecast and reanalysis models rather than the absolute deviation of the molecular number density. We found that deviations in extinction were within ±5%, with a probability of 83% at 355 nm and 60% at 532 nm. Moreover, for aerosol backscatter coefficient retrievals, different models can have a larger impact when the backscatter coefficient is retrieved with the elastic method than when the backscatter coefficient is calculated using the Raman method at both 355 nm and 532 nm. In addition, the atmospheric aerosol load can also influence the deviations in the aerosol extinction and backscatter coefficients, showing a larger impact under low aerosol loading scenarios. Full article

The design and operation of a custom-built LIDAR-compatible, four-channel Raman spectrometer integrated to a 532 nm pulsed laser is presented. The multichannel design allowed for simultaneous collection of Raman photons at two spectral regions identified as highly sensitive to changes in water temperature. For each of these spectral bands, the signals having polarization parallel to (∥) and perpendicular to (⟂), the excitation polarization were collected. Four independent temperature markers were calculated from the Raman signals: two-colour(∥), two-colour(⟂), depolarization(A) and depolarization(B). A total of sixteen datasets were analysed for one ultrapure (Milli-Q) and three samples of natural water. Temperature accuracies of ±0.4 °C–±0.8 °C were achieved using the two-colour(∥) marker. When multiple linear regression models were constructed (linear combination) utilizing all simultaneously acquired temperature markers, improved accuracies of ±0.3 °C–±0.7 °C were achieved. Full article

To evaluate the potential of Raman lidar observations for measuring precipitable water vapor (PWV), PWV variations and distribution characteristics were investigated in Xi’an (34.233°N, 108.911°E), and its comparisons with meteorological parameters were also analysed. Comparisons of lidar PWV with radiosonde PWV verified the ability and accuracy of using Raman lidars for PWV measurements. The diurnal and monthly variation trends in PWV in different layers are first discussed via the statistical analysis of lidar data from November 2013 to July 2016; different proportions of PWV were found in different layers, and the PWV in each layer presented a slight diurnal change trend and consistent seasonal variation, which was relatively rich in summer, less so in spring and autumn, and relatively deficient in winter. Furthermore, correlation analyses between lidar PWV and meteorological parameters are explored. Water vapor pressure and surface temperature revealed the same inter-seasonal oscillation of PWV, with a correlation coefficient of ~0.90. However, incomplete synchronization was found between PWV and relative humidity and precipitation parameters. Higher humidity appeared in the late summer and the beginning of autumn of each year, which was also the case for precipitation and precipitation efficiency. In addition, atmospheric water vapor density profiles and the obtained PWV by Raman lidar are discussed employing a rainfall case, and a comprehensive analysis with meteorological parameters is undertaken. The intensifying characteristics of vertical change in water vapor and the accumulation of PWV in the lower troposphere can be captured by lidar before the onset of rainfall. In contrast to the obvious diurnal change trend, such meteorological parameters as relative humidity, water vapor pressure, and dew-point temperature difference are accompanied with stable trends with a change rate of close to 0 in the rainfall processes; they also show high correlated variations with lidar PWV. Thus, with the advantage of lidar detection, investigation of water vapor profiles and PWV by Raman lidar, and the comprehensive correlation analyses with synchronic meteorological parameters can prove to be good indications of rainfall. Full article