This study explores the analysis of hydrogen gas from a distance using a Raman lidar spectrometer. Hydrogen gas is a flammable gas with risk of explosion, making accurate and quick detection crucial. ...In this study, we evaluated the performance of a Raman lidar spectrometer for detecting hydrogen gas from a distance. Experiments were conducted at distances of 1, 3, 5, 10, 20, and 30 m. To assess the long-range measurement capability at various hydrogen concentrations, we analyzed the accuracy and sensitivity. The findings suggest that the sensor can perform quick and accurate detection even at low concentrations, maintaining high sensitivity at a distance. Thus, Raman lidar spectrometers are promising for real-time remote detection of hydrogen gas. This study provides guidance for the effective utilization of Raman lidar sensors for hydrogen gas detection and monitoring in diverse application areas such as industrial fire prevention, safety management, environmental monitoring, and energy production.
•We propose a rapid and accurate method for detecting hydrogen gas at long distances using Raman LIDAR spectrometers.•Exploring the critical applications in safety management and fire prevention due to the explosive nature of hydrogen gas.•Evaluating Raman LIDAR spectrometer performance at distances ranging from 1 m to 30 m while maintaining high sensitivity.•Demonstrating the capability to swiftly and precisely detect even low concentrations of hydrogen gas and providing essential guidelines for long-range hydrogen gas analysis using Raman LIDAR spectrometers.•Raman LIDAR spectrometers in various fields, including industrial settings, environmental monitoring, and energy production.
Clouds play an important role in the energy balance and water cycle for the Earth-Atmosphere system, and the accurate measurement of their macro-and microphysical properties is important for ...understanding atmospheric physical processes, studying aerosol-cloud interactions and improving numerical model parameterization schemes. In this paper, a multiple scattering Raman lidar system is developed, which greatly simplifies the structure of the optical system and solves the complexity of the optical system in detecting the cloud characteristic parameters by adopting the dual field-of-view (FOV) technique. Based on the Quasi-Small-Angle (QSA) approximation model, the forward single or multiple scattering signals of cloud droplet particles at the bottom of the cloud layer at the dual-FOV channel and the vibrational Raman backscattering signals of nitrogen molecules are simultaneously detected. Using the correlation between the width of the forward scattering peak and the particle size of the cloud droplets, an iterative algorithm for the Raman signal is proposed for retrieving cloud parameters such as the extinction coefficient, the effective radius, and the liquid water content (LWC). To verify the feasibility of the system and retrieval algorithms, some preliminary measurements were carried out and the resulting liquid water content was compared and verified by combined observations with a co-located microwave radiometer. The experimental results show that the average deviation of the liquid water content is 0.004 g/m3, and the relative error is 20%. The system has an ability to invert cloud microphysical properties, which provides an effective method for further study of aerosol-cloud interactions.
•The analytical modeling for multiple scattering Raman lidar is proposed.•The method for detecting microphysical properties of clouds is analyzed.•An iterative algorithm for inverting microphysical properties of clouds is proposed.
Raman scattering in the Earth’s atmosphere is caused predominantly by its most abundant molecular components, N2 and O2. After the computation of the optical properties that govern the spectral and ...angular redistribution of light due to various inelastic scattering events, viz. rotational Raman scattering (RRS), vibrational Raman scattering (VRS), and rovibrational Raman scattering (RVRS), covered in Part I of this series, the next challenge in the simulation of inelastic scattering in the Earth’s atmosphere is to carry out radiative transfer (RT) computations across several wavelengths simultaneously.
In this part of our work, we provide the RT formulation for fully polarized simulations of inelastic scattering using the matrix-operator-method-based RT model vSmartMOM. The formalism is optimized for easy use with GPUs, allowing an unprecedented speedup of accurate multi-wavelength RT computations of inelastic scattering using the full Stokes-vector, thus allowing its operational use without coarse spectral binning (Rozanov and Vountas, 2014), or single scattering approximations (Sioris and Evans, 1999) at longer wavelengths.
After comparing our model against the current state-of-the-art, we demonstrate the use of vSmartMOM to simulate Raman lidar measurements, the Ring effect, the ghosting of Fraunhofer lines due to vibrational Raman scattering and spectral corrections due to inelastic scattering in the O2 A-band in the Earth’s atmosphere. We use our model (1.) to validate the convention of neglecting the contribution of VRS and RVRS, and (2.) to quantify the speed and accuracy of the single scattering approximation in the O2 A-band.
•First exact polarized simulations of rotational, vibrational and rovibrational Raman scattering.•GPU acceleration achieves unprecedented speed-ups, allowing operational use.•Applications include Raman Lidar, Ring effect, ghosting of Fraunhofer lines, and the infilling of telluric lines of absorption lke the O2 A-band.•Exciting implications for trace gas retrievals in the UV/Vis, greenhouse gas retrievals, and fluorescence studies.
We present the new Atmospheric Raman Temperature and Humidity Sounder (ARTHUS). We demonstrate that ARTHUS measurements resolve (1) the strength of the inversion layer at the planetary boundary layer ...top, (2) elevated lids in the free troposphere during daytime and nighttime, and (3) turbulent fluctuations in water vapor and temperature, simultaneously, also during daytime. Very stable and reliable performance was demonstrably achieved during more than 2,500 hr of operations time experiencing a huge variety of weather conditions. ARTHUS provides temperature profiles with resolutions of 10–60 s and 7.5–100 m vertically in the lower free troposphere. During daytime, the statistical uncertainty of the water vapor mixing ratio is <2 % in the lower troposphere for resolutions of 5 min and 100 m. Temperature statistical uncertainty is <0.5 K even up to the middle troposphere. ARTHUS fulfills the stringent WMO breakthrough requirements on nowcasting and very short range forecasting.
Plain Language Summary
The observation of atmospheric moisture and temperature profiles is essential for the understanding and prediction of earth system processes. These are fundamental components of the global and regional energy and water cycles; they determine the radiative transfer through the atmosphere and are critical for the cloud formation and precipitation. Also, it is expected that the assimilation of high‐quality, lower tropospheric WV and T profiles will result in a considerable improvement of the skill of weather forecast models particularly with respect to extreme events. Here we present the Atmospheric Raman Temperature and Humidity Sounder, an exceptional tool for observations in the atmospheric boundary layer during daytime and nighttime with a very short latency. This performance serves very well the next generation of very fast rapid‐update‐cycle data assimilation systems for nowcasting and short‐range weather forecasting. Ground‐based stations and networks can be set up or extended for climate monitoring, verification of weather, climate and earth system models, and data assimilation for improving weather forecasts.
Key Points
Fulfills World Meteorological Organization breakthrough requirements for nowcasting/very short range forecasting in the lower troposphere
Resolves strength of the inversion layer at the planetary boundary layer top and elevated lids above during daytime and nighttime
Provides statistics on turbulent fluctuations in water vapor and temperature simultaneously in the lower troposphere
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.
Aerosol vertical distribution plays a crucial role in cloud development and thus precipitation since both aerosol indirect and semi-direct effects significantly depend on the relative position of ...aerosol layer in reference to cloud, but its precise influence on cloud remains unclear. In this study, we integrated multi-year Raman Lidar measurements of aerosol vertical profiles from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) facility with available Value-Added Products of cloud features to characterize aerosol vertical distributions and their impacts on warm clouds over the continental and marine ARM atmospheric observatories, i.e., Southern Great Plains (SGP) and Eastern North Atlantic (ENA). A unimodal seasonal distribution of aerosol optical depths (AODs) with a peak in summer is found at upper boundary layer over SGP, while a bimodal distribution is observed at ENA for the AODs at lower levels with a major winter-spring maximum. The diurnal mean of upper-level AOD at SGP shows a maximum in the early evening. According to the relative positions of aerosol layers to clouds we further identify three primary types of aerosol vertical distribution, including Random, Decreasing, and Bottom. It is found that the impacts of aerosols on cloud may or may not vary with aerosol vertical distribution depending on environmental conditions, as reflected by the wide variations of the relations between AOD and cloud properties. For example, as AOD increases, the liquid water paths (LWPs) tend to be reduced at SGP but enhanced at ENA. The relations of cloud droplet effective radius with AOD largely depend on aerosol vertical distributions, particularly showing positive values in the Random type under low-LWP condition (<50 g m−2). The distinct features of aerosol-cloud interactions in relation to aerosol vertical distribution are likely attributed to the continental-marine contrast in thermodynamic environments and aerosol conditions between SGP and ENA.
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•Upper-level AOD at SGP peaks in summer and early evening.•A bimodal seasonal distribution is observed at ENA for lower-level AOD.•Random, Decreasing, and Bottom are the primary vertical distributions at both sites.•Aerosols tend to suppress cloud water production at SGP but invigorate it at ENA.•AOD-droplet effective radius relations vary with aerosol vertical distributions.
During the Intensive Observing Period 15b of the first Special Observation Period of the Hydrological Cycle in the Mediterranean Experiment (HyMeX), a variety of mesoscale convective systems (MCSs) ...impacted the Cevennes‐Vivarais (CV) target area leading to over 100 mm of 24 h accumulated rainfall on 20 and 21 October 2012. The CV area was first impacted by a V‐shaped MCS developing over the Cevennes mountains, then by a MCS initiated on the eastern foothills of the Pyrenees and finally by three MCSs initiating over the sea. The MCSs initiated and propagated along a well‐defined storm track ahead of an approaching upper‐level trough, as observed with the 15 min resolution Spinning Enhanced Visible and Infrared Imager. The storm track was characterized by strong southeasterly winds over the Mediterranean and high integrated water vapour content (IWVC), as derived from observations from the Moderate‐resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). The ground‐based Water‐vapour Raman Lidar, located in the Balearic Islands, captured the increasing moistening of the free troposphere, up to 5 km, associated with the eastward propagation of the surface low from Gibraltar to a location west of the Balearic Islands. MODIS and AIRS observations, together with Weather Research and Forecasting (WRF) model simulations, revealed the tropical origin of the high moisture content characterizing the storm track, with IWVC values on the order of 35 kg m−2, and enhanced moisture being observed below 500 hPa. The WRF simulations also showed that the MCS initiation offshore was very likely caused by low‐level wind convergence and conditionally unstable air along the storm track, between North Africa and southern France. Low‐level convergence resulted from the interaction between a strong southwesterly swirling flow around the low‐pressure centre and an easterly low‐level jet present along the southern France coastline.
We have constructed a Bayesian neural network able of retrieving tropospheric temperature profiles from rotational Raman-scatter measurements of nitrogen and oxygen and applied it to measurements ...taken by the RAman Lidar for Meteorological Observations (RALMO) in Payerne, Switzerland. We give a detailed description of using a Bayesian method to retrieve temperature profiles including estimates of the uncertainty due to the network weights and the statistical uncertainty of the measurements. We trained our model using lidar measurements under different atmospheric conditions, and we tested our model using measurements not used for training the network. The computed temperature profiles extend over the altitude range of 0.7 km to 6 km. The mean bias estimate of our temperatures relative to the MeteoSwiss standard processing algorithm does not exceed 0.05 K at altitudes below 4.5 km, and does not exceed 0.08 K in an altitude range of 4.5 km to 6 km. This agreement shows that the neural network estimated temperature profiles are in excellent agreement with the standard algorithm. The method is robust and is able to estimate the temperature profiles with high accuracy for both clear and cloudy conditions. Moreover, the trained model can provide the statistical and model uncertainties of the estimated temperature profiles. Thus, the present study is a proof of concept that the trained NNs are able to generate temperature profiles along with a full-budget uncertainty. We present case studies showcasing the Bayesian neural network estimations for day and night measurements, as well as in clear and cloudy conditions. We have concluded that the proposed Bayesian neural network is an appropriate method for the statistical retrieval of temperature profiles.
Vertical distribution of phytoplankton is crucial for assessing the trophic status and primary production in inland waters. However, there is sparse information about phytoplankton vertical ...distribution due to the lack of sufficient measurements. Here, we report, to the best of our knowledge, the first Mie–fluorescence–Raman lidar (MFRL) measurements of continuous chlorophyll a (Chl-a) profiles as well as their parametrization in inland water. The lidar-measured Chl-a during several experiments showed good agreement with the in situ data. A case study verified that MFRL had the potential to profile the Chl-a concentration. The results revealed that the maintenance of subsurface chlorophyll maxima (SCM) was influenced by light and nutrient inputs. Furthermore, inspired by the observations from MFRL, an SCM model built upon surface Chl-a concentration and euphotic layer depth was proposed with root mean square relative difference of 16.5% compared to MFRL observations, providing the possibility to map 3D Chl-a distribution in aquatic ecosystems by integrated active–passive remote sensing technology. Profiling and modeling Chl-a concentration with MFRL are expected to be of paramount importance for monitoring inland water ecosystems and environments.
In the framework of regular European Aerosol Research Lidar Network (EARLINET) observations, aerosol layers have been monitored with a multiwavelength aerosol Raman lidar in the upper troposphere and ...lower stratosphere over Leipzig (51.4°N, 12.4°E), Germany, since the summer of 2008. The origins of these layers are eruptions of different volcanoes on the Aleutian Islands, Kamchatka, Alaska, and on the Kuril Islands. FLEXPART transport simulations show that the volcanic aerosol is advected from Alaska to central Europe within about 7 days. The aerosol layers typically occurred in the upper troposphere above 5 km height and in the lower stratosphere below 25 km height. The optical depths of the volcanic aerosol layers are mostly between 0.004 and 0.025 at 532 nm. The wavelength dependence of the backscatter coefficients and extinction coefficients indicate Ångström exponents from 1.0–2.0. Lidar ratios in the stratosphere are found in the range from 30–60 sr (355 nm) and 30–45 sr (532 nm). The estimation of the effective radius, surface‐area, and mass concentrations of a volcanic aerosol layer, observed well within the stratosphere at end of August 2009, reveals values of 0.1–0.2 μm, 5–10 μm2 cm−3, and 0.3–0.5 μg m−3, respectively.
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