Pure Rotational Raman Lidar Research Articles

Comparative Analysis and Optimal Selection of Calibration Functions in Pure Rotational Raman Lidar Technique

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.

Orthogonal retrieval algorithm of atmospheric temperature profiles from pure rotational Raman lidar signals.

Aimed at the stability of calibration coefficients in a general non-orthogonal retrieval algorithm (NRA) of pure rotational Raman lidars (PRRLs), an orthogonal retrieval algorithm (ORA) of atmospheric temperature profiles based on the orthogonal basis function is proposed. This algorithm eliminates the correlation between the calibration coefficients in the NRA to reduce the influence of the number of calibration points and the selection scheme on the calibration coefficients. In this paper, the stabilities of calibration coefficients in the NRA and ORA are compared and analyzed, and the data analysis for atmospheric temperature profiles with a time resolution of minute-level are given, based on the developed Cloud Precipitation Potential Evaluation (CPPV) lidar data and the parallel radiosonde temperature data. The analysis results show that coefficients of variation (CVs) of ORA calibration coefficients are one order of magnitude smaller than those of NRA coefficients. The mean deviation of the ORA retrieval results is roughly reduced by 16.1% compared with the NRA, and the root-mean-square deviation is roughly reduced by 15.0% compared with the NRA. Therefore, the temperature retrieval performance of the ORA is better than that of the NRA.

Atmospheric Refraction Delay Toward Millimeter‐Level Lunar Laser Ranging: Correcting the Temperature‐Induced Error With Real‐Time and Co‐Located Lidar Measurements

AbstractNext‐generation lunar laser ranging (LLR) aims for mm‐level accuracy, significantly promoting the study of gravitational physics. However, atmospheric refraction delay causes an unacceptable ranging error that can be efficiently corrected by neither the atmospheric delay models nor ray‐tracing calculation. Here we report on an improved ray‐tracing method, in which temperature profiles measured by radiosonde are replaced by those measured by a pure rotational Raman lidar, to realize real‐time and co‐located delay correction. Using 9‐night lidar observations, temperature‐induced delays of ±15 mm can be corrected for laser ranging, which is the largest residual in the LLR error budget.

Optical design of a reflective double-grating spectrometer to detect one branch in the pure rotational Raman spectrum of N2.

This paper presents the optical design of a high-resolution double-grating spectrometer for extracting the multiple lines in the Stokes or anti-Stokes branch of the pure rotational Raman spectra of nitrogen. The spectrometer is composed of collimating and focusing mirrors, two reflective gratings, and a linear detector. The structural parameters were calculated using geometric configuration, dispersion, and aberrational theory, and conditions for first-order correction of keystone distortion with divergent grating illumination were derived. Based on this method, we simulated a spectrometer with a 16-channel linear array photomultiplier tube, resulting in uniformly distributed single-branch lines on each detector channel. The resolution reached 0.225nm per channel, and the keystone distortion was less than 0.7%. The spectrometer avoids the interference of elastic signals by not detecting them, enabling the extraction of atmospheric temperature profiles via separated single-branch lines with high precision. Our design provides a promising solution to extract atmospheric temperature profiles for pure rotational Raman lidar.

Errors of Pure Rotational Raman Lidar Absolute Calibration Due to Collisional Line Broadening

Errors of Pure Rotational Raman Lidar Absolute Calibration Due to Collisional Line Broadening

Extreme temperature events monitored by Raman lidar: Consistency and complementarity with spaceborne observations and modelling

AbstractTwo extreme temperature events (ETEs), both triggered by atmospheric blocking situations, were monitored by a pure rotational Raman lidar 20 km south of Paris. The first ETE lasted 6 days in late February 2018 with the onset of a cold wave surging from Siberia, and the second was a short heatwave that occurred at the end of July 2020. After calibration using simultaneous radiosoundings, lidar vertical profiles of temperature are derived with an uncertainty of less than 1 °C within both the planetary boundary layer and the lower/middle free troposphere (~3/6 km above ground level [a.g.l.] for day/night), with a final vertical resolution of 50 m and a temporal resolution of 30 min. Such capabilities fulfil the observational requirements of the World Meteorological Organisation and contribute to fill a gap left behind by current operational instruments, which struggle to follow the diurnal cycle of the planetary boundary layer due to insufficient spatial and temporal resolutions in the low troposphere. These case studies allow to assess how such weather events are represented by numerical weather prediction modelling and whether they can be correctly observed by the Infrared Atmospheric Sounding Interferometer (IASI) spaceborne mission. Our results demonstrate that during these events both ECMWF reanalyses and forecasts are in overall very good accordance with lidar observations (correlation >0.9 in average). Still, they show warm biases (~1°C–2°C) compared with the lidar and improvable temperature field representation in the boundary layer. The radiances measured by IASI, assimilated in the operational model, do not capture temperature profiles adequately below ~2–3 km a.g.l., mainly due to the altitude location of its weighting functions. The bias computed against the lidar reaches 2°C during the heatwave and 4°C during the cold wave case in the first 2 km of the atmosphere, beyond expected errors found in the literature.

Temperature measurement of cloud or haze layers based on Raman rotational and vibrational spectra.

Pure rotational Raman lidar is often used for atmospheric temperature profile measurements. However, high elastic scattering suppression ratios (>107) are required for temperature measurement in clouds and haze, which imposes stringent requirements on spectral separation techniques. To solve this problem, a lidar measurement technique based on vibrational and rotational Raman spectra is proposed. Using nitrogen vibrational and rotational Raman scattering to obtain temperature profiles under strong elastic scattering, combined with the dual-rotational Raman temperature measurements under weak elastic scattering, a vertical distribution of atmospheric temperature including cloud and haze layers, can be obtained. The feasibility of the method was verified by numerical simulation. The Raman lidar for temperature measurements was established in Xi'an University of Technology, and the obtained temperature results show good agreement with the radiosonde measurements. The proposed method combines the high sensitivity of the dual-rotational Raman method and the high Mie-scattering suppression of the vibrational Raman method, thus further improving the adaptability of Raman lidar to cloudy and hazy air conditions and supporting atmospheric and cloud physics research.

Optical properties of aerosol and cloud particles measured by a single-line-extracted pure rotational Raman lidar.

Conventional lidar methods for deriving particle optical properties suffer from the fact that two unknowns (backscatter and extinction coefficients) need to be determined from only one lidar equation. Thus, additional assumptions (constant lidar ratio or Ångström relationship) have to be introduced to settle this problem. In contrast, a single-line-extracted pure-rotational-Raman (PRR) lidar method allows the strict retrieval of backscatter and extinction coefficients without additional assumptions. Based on the observations of our single-line-extracted PRR lidar from February 2016 to December 2017, the optical properties (backscatter coefficient, extinction coefficient and lidar ratio) of continental polluted aerosols, dust aerosols, and cirrus cloud particles over Wuhan (30.5°N, 114.4°E) are well characterized. The mean values of the measured lidar ratios are respectively 60 ± 7 sr for continental polluted aerosols, 47 ± 4 sr for dust aerosols and 22 ± 4 sr for cirrus cloud particles. The backscatter and extinction coefficients measured by the single-line-extracted PRR lidar deviate as a whole by 7-13% and 13-16%, respectively, from those retrieved by the traditional Fernald method. The optical properties measured by the single-line-extracted PRR lidar can serve as observational standards for particle optical properties (backscatter/extinction coefficient and lidar ratio) at 532 nm wavelength.

Pure rotational Raman lidar for full-day troposphere temperature measurement at Zhongshan Station (69.37°S, 76.37°E), Antarctica.

A pure rotational Raman lidar (PRRL) for full-day troposphere temperature measurement was deployed in February 2020 at Zhongshan Station (69.37°S, 76.37°E), Antarctica, by the 36th Chinese National Antarctic Research Expedition. The PRRL emits a 532.23-nm laser light and employs a 203.2-mm telescope to collect atmospheric backscatter. Cubic nonpolarizing beam splitters are introduced to yield a compact optics arrangement. A quasi-single-line-extraction technique is proposed for extracting the molecular Stokes line signals. A lidar container with a window system is customized to house the whole PRRL system for long-term stable operation. An approach using a laser plummet is developed for fast and convenient adjustment of the telescope zenithward. A home-made calibration module is utilized for straightforward visual optics adjustment with ∼35.3-μrad angular positioning accuracy. Both typical daytime and nighttime temperature measurement examples are presented to verify the lidar performance. From a 30-h continuous temperature measurement result, it is found the tropopause is located at ∼10.8 km above ground level with a mean temperature of ∼203 K; significant temperature variability occurs only at the inversion areas, while off which the 1-h temperature profiles are relatively similar in form with an average lapse rate of -8.3 K/km.

Temporal stability of calibration functions in the traditional pure rotational Raman lidar technique

Pure rotational Raman (PRR) lidars should be calibrated to measure atmospheric temperature. In the frame of the traditional PRR technique, the lidar calibration represents the determination of calibration function (CF) coefficients using a reference temperature profile from an atmosphere model or radiosonde data. When a measurement campaign lasts several days, the accuracy of temperature retrieval from PRR lidar signals depends on the temporal stability of the selected CF. In this paper, we present a simple way to intercompare different CFs and determine the most stable function in time among them. We study to what extent the CF coefficients determined on one of the measurement campaign days may be used for temperature retrieval on the other days. We also examine the situation when reference radiosonde data are absent on one of the measurement days and, therefore, the CF coefficients need to be determined from reference data over the remaining days. The 1-week and 3-day temporal stabilities of five CFs are studied on the example of nighttime temperature profiles retrieved from PRR lidar measurements of 1, 6, 7, and 8 April 2015. The stability of these CFs is studied for the first time. The measurements were performed in Tomsk (56.48°N, 85.05°E, Western Siberia, Russia) using a PRR lidar of the Institute of Monitoring of Climatic and Ecological Systems (IMCES). The CF retrieving temperature of the troposphere (3–9 km) with the highest accuracy for the considered 1-week and 3-day measurement periods is determined for the IMCES lidar.

A simulation comparison of calibration functions for different sets of spectral filter passbands in the traditional pure rotational Raman lidar technique

The accuracy of tropospheric temperature measurements with pure rotational Raman (PRR) lidars is affected by the collisional broadening of N2 and O2 PRR lines. In this paper, we intercompare nine calibration functions (CFs) in the traditional PRR lidar technique via simulation. Taking into account the PRR line broadening, the simulation is performed for five sets of spectral filters (SFs) with different passbands in a PRR lidar receiving system. For simplicity of calculations, the transmission function of each SF is approximated by a rectangular function on the wavenumber interval, within which a SF passes the bulk of the backscattered signal intensity in the corresponding PRR lidar channel. A narrow-linewidth laser operating at wavelengths of 354.67 and 532 nm is considered as a lidar transmitter. The CF best suited for tropospheric temperature retrievals from raw PRR lidar data for each set of SFs and laser wavelength is determined by comparative analysis of calibration errors ΔT produced using these CFs. The absolute error |ΔT| does not exceed the value of 3 × 10–3 K when using the best three-coefficient CF, while |ΔT| < 4 × 10–4 K for the best four-coefficient CF regardless of the laser wavelength and SF set used.

Diurnal temperature variations in the lower troposphere as measured by an all-day-operational pure rotational Raman lidar

We describe a pure rotational Raman lidar for measuring the all-day temperature profiles in the lower troposphere. The lidar is made up of a frequency-tripled Nd:YAG laser at 354.82 nm with ∼250mJ pulse energy at the 30 Hz repetition rate, a 200 mm receiving telescope, and narrow-band interference-filter-based detection optics. The lidar performance is shown by measured examples. Under clear sky conditions, with an integration time of 60 min and a vertical resolution of 90 m, the 1-σ statistical uncertainty does not exceed 1 K up to the altitude of ∼4.1km during nighttime, while the corresponding altitude is ∼2.3km at noon. The diurnal temperature variation characteristics have been revealed by the lidar measurements with the 1-σ statistical uncertainty <1K between altitudes ranging from 0.6 to ∼2.0km at Wuhan, China (30.53°N, 114.37°E). The atmospheric temperature shows a strong diurnal oscillation and moderate semidiurnal oscillation at altitudes 0-1.4 km for two days in July 2019 (July period), 0-1.4 km for four days in September 2019 (September period), and 0-0.8 km for three days in January 2018 (January period), respectively. The mean diurnal and semidiurnal amplitudes of the nine days are respectively ∼1.4K and ∼0.5K at the 0.6 km altitude, while the corresponding surface values are ∼4.2K and ∼1.4K, respectively. The diurnal amplitudes tend to weaken with increasing altitude. At altitudes >0.6km, the diurnal amplitude in the September period is less than that in the July period, but greater than that in the January period. The phase delays of the diurnal oscillations are ∼3h in the July period, 5-6 h in the September period, and 5-7 h in the January period compared to those at the surface, respectively. Both the diurnal amplitudes and phase delays indicate a possible seasonal dependence.

Miniature double-grating monochromator with Littman configuration for pure rotational Raman LIDAR

Conventional double-grating monochromators used in pure rotational Raman (PRR) temperature LIDAR usually adopt the Littrow configuration to separate backscattered PRR lines. A mirror is added to this configuration, thereby producing the Littman configuration. The dispersion of the modified configuration is greater than thrice that of the Littrow configuration for incident angles larger than 60 deg. A spectroscopy system with a linear dispersion better than 0.9 mm / nm is designed for the 532-nm excitation laser wavelength, and the selected N2 PRR lines are effectively separated. The overall system is simulated using only off-the-shelf optical components, and the results show that the volume is smaller than 240 × 200 × 80 mm3.

Short-term stability of temperature retrieval functions in the traditional pure rotational Raman lidar technique

Short-term stability of temperature retrieval functions in the traditional pure rotational Raman lidar technique

Double-Receiver-Based Pure Rotational Raman LiDAR for Measuring Atmospheric Temperature at Altitudes Between Near Ground and Up To 35 km

We report on a double-receiver-based pure rotational Raman (PRR) LiDAR that can, for the first time, obtain nighttime temperature profiles simultaneously at altitudes between 0.05 and 35 km. The LiDAR emits a 532.2-nm laser light and collects atmospheric backscatters with near-range (0.05–10 km) and far-range (8–35 km) receivers. The two receivers differ in telescope apertures and design of receiving optics. A unique calibration module with ~35.3- $\mu $ rad angular positioning accuracy is developed for easy and convenient optical adjustment of the receiving optics. Typical LiDAR-retrieved temperature profiles on a clear-sky observational night are provided and compared with data from radiosonde launched at Wuhan Weather Station (~23.4-km northwest of the LiDAR site). For a 15-min temporal and 90-m spatial resolution, the 1- $\sigma $ statistical uncertainty has a maximum of 1.9 K at 35 km, while the maximum absolute temperature deviation between the LiDAR and concurrent radiosonde reaches only 2 K at altitudes of 0.05–30 km under the conditions of stable atmosphere and no inversion layers. The temperature variability has been studied. The 15-min-to-15-min temperature variability tends to rise with increasing altitude in the altitude range from 2.2 to 35 km as a whole. In the troposphere, the significant variability is found to occur only at the inversion layer altitudes.

Accurate inversion of tropospheric bottom temperature using pure rotational Raman lidar in polluted air condition

For pure rotational Raman temperature-measurement lidar, the suppression of elastic signals has always been a core technical issue. In practice, however, the surge of aerosol concentration, such as mist, haze, and short-time air pollution, tends to cause the intensity of the elastic scattering light to exceed the generally applicable suppression ratio of the lidar system, and the leaked elastic signal will result in some distortions of the Raman signals, especially in the near-field region. To solve this problem, here we propose to correct the signal distortion by forming a correction coefficient from the expression of the signal intensity ratio of the two Raman channels, which has been proven to be highly correlated with the intensity of the elastic signals. Simulated and experimental verification have been performed on the proposed method. The results demonstrated that using this coefficient to correct the Raman data will significantly improve the signal quality and the corresponding temperature inversion accuracy. Meanwhile, the correction coefficient can also be applied to modify the lidar returns in a similar atmospheric environment so as to enhance the detecting performance of the pure rotational Raman lidar in polluted air condition.

全天时大气温度探测的纯转动拉曼激光雷达系统设计与仿真

全天时大气温度探测的纯转动拉曼激光雷达系统设计与仿真

Single-line-extracted pure rotational Raman lidar to measure atmospheric temperature and aerosol profiles.

We have built a pure rotational Raman (PRR) lidar system that effectively detects two isolated N2 molecule PRR line signals and elastic backscatter signals. This system enables all-day temperature profiles to be accurately obtained without calibration, according to the simple two-parameter functional relationship between the temperature and ratio of the two PRR line signals. Based on the derived temperature profiles, the aerosol backscatter and extinction profiles can be further determined strictly from one measured PRR line signal and elastic backscatter signal without additional assumptions. The two aerosol parameters and resultant lidar ratio provide strict standards for the lidar measurements of aerosol.

A Novel Calibration Method for Pure Rotational Raman Lidar Temperature Profiling

AbstractWe propose a new calibration method for pure rotational Raman (PRR) lidar temperature profiling based on the different temperature sensitivities of Stocks and anti‐Stocks PRR lines. This method reconstructs the expression of the differential backscatter cross section according to the temperature dependencies of each component and forms a temperature factor and a calibration factor in the intensity ratio. With these factors, the temperature is retrievable from the lidar return. The effectiveness and accuracy of the proposed method have been verified through simulations and experiments. The inversion error can be reduced by ~50% compared with the commonly used calibration methods in weak signal‐to‐noise situations.

Comparative analysis of calibration functions in the pure rotational Raman lidar technique

Calibration functions (CFs) are required for the pure rotational Raman (PRR) technique to retrieve atmospheric temperature profiles from raw lidar data. The accuracy of temperature retrievals essentially depends on the selected CF, especially in the troposphere where the molecular collision effect dominates over the Doppler one. In this paper, we theoretically and experimentally compare nine different CFs (five of which are suggested for the first time) to determine the best function for the tropospheric temperature retrievals. All the CFs represent special cases of the general CF that takes into account the collisional broadening of individual atmospheric N2 and O2 PRR lines. The comparative analysis of calibration errors ΔTerr produced using these CFs in a simulation study showed that the best CF among them gives |ΔTerr| < 4 × 10− 5 K. To determine the best CF from a practical standpoint, we apply all the functions to nighttime measurement data obtained in Tomsk (56.48°N, 85.05°E, Western Siberia, Russia) with a PRR lidar designed in the Institute of Monitoring of Climatic and Ecological Systems (IMCES). The CF best-suited for the tropospheric temperature measurements with the IMCES PRR lidar is the same as determined by simulation.