Lidar Backscatter Signal Research Articles

Case Study of Coastal Fog Events in Senegal Using LIDAR Ceilometer

This study aims to examine the atmospheric conditions characterising fog phenomena on the Senegalese coast focusing on two specific instances that occurred on April 3 and April 30, 2023. These events were detected by the LIDAR Ceilometer installed at LPAOSF/ESP/UCAD and confirmed on the METARs of the meteorological stations at Dakar and Diass airports. The LIDAR's backscatter signal showed that the fog of April 3 started around midnight with a vertical extension at 100 m altitude and dissipated around 10 a.m. The April 30 event characterized by a good vertical extension from the surface up to 300 m above sea level, was triggered just after 2 a.m. and lasted around 3 hours. The results showed that a decrease in temperature, accompanied by an increase in humidity and light wind, is favorable for the triggering and persistence of fog. Sea Level Pressure (SLP) anomaly fields show two distinct configurations. The April 3 event was characterized by a zonal dipole of SLP anomalies between the Sahara and the northern Senegalese coast, while the April 30 event was characterized by a meridional dipole between the Sahara and the Gulf of Guinea area as far as the equatorial Atlantic. A weakening of the pressure around the study area was observed in both cases, allowing moisture advection to favor the onset of fog. The hovmoller diagrams of relative humidity and wind show that a good vertical extension of humidity associated with a westerly wind in the lower layers plays an important role in the formation and persistence of fog. The presence of dry air associated with a weak easterly wind in the middle layers could explain the low vertical extension of the fog on April 3. A strong wind in the lower layers would be responsible for the premature dissipation of the April 30 fog.

Background noise model of spaceborne photon-counting lidars over oceans and aerosol optical depth retrieval from ICESat-2 noise data

The ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) photon-counting lidar is a revolutionary active remote sensing device and is extremely sensitive to both laser signal and solar background induced noise photons. The weak laser signals, such as aerosol and water subsurface backscattered laser photons, may be buried in noise in the daytime. A noise model for spaceborne photon-counting lidars is of vital importance in understanding and evaluating the performance of a lidar system, as well as in data processing and applications. From the reciprocity perspective, the main noise source for photon-counting lidars is solar background radiation, which in turn is the signal source of ocean color sensors. In the absence of clouds, it is possible to estimate the aerosol information using background noise data of ICESat-2 if the background noise is accurately modeled. In this study, a background noise model of photon-counting lidars over oceans is proposed that carefully considers the contributions of gas molecules, aerosol, water surface, subsurface, and detector dark noise. As the background rate from clouds are much larger than the sum of other factors, in this study, we only consider the cloudless atmosphere by using a cloud screening process. By inputting the system and environmental parameters, the theoretical predictions of noise level in six study areas have an average MAPE of ∼5% compared with ICESat-2 measured noise data. The results also indicate that without clouds, the variation of aerosols dominates the variation of ICESat-2 total background noise in open ocean areas. Then, based on this noise model, a method to estimate aerosol optical depths (AODs) over oceans is proposed solely on the ICESat-2 product including background noise rate and environmental data. Validation against MODIS (Moderate Resolution Imaging Spectroradiometer) daily AODs indicates that the average MAPE is <20% and the average correlation coefficient is 0.95 in six study areas. This method may provide a new AOD retrieval way over oceans in the daytime, when it is difficult to directly calculate AODs using lidar backscattered signal under strong background noise. In addition, the background noise of the ICESat-2 photon-counting lidar in its six channels (or pixels) has the potential to be regarded as the signal of an “ocean color camera” with only a single narrow green band. Based on this consideration, future works may be conducted to combine ocean color remote sensing with ICESat-2 photon-counting lidar.

Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product

Abstract. The EarthCARE satellite mission's objective is to retrieve profiles of aerosol and cloud physical and optical properties using the combination of cloud-profiling radar (CPR), high-spectral-resolution UV lidar (ATLID) and passive multi-spectral imager (MSI) data. Based on synergistic retrievals using data from these instruments, the 3D atmospheric cloud–aerosol state is estimated and then used to model the top-of-atmosphere (TOA) broadband radiances, which may then be compared to co-incident EarthCARE broadband radiometer (BBR) measurements. A high-spectral-resolution lidar enables the independent retrieval of extinction and backscatter but, being space based, suffers from relatively low signal-to-noise ratio (SNR) levels. The ATLID FeatureMask (A-FM) product provides a feature detection mask for the existence of atmospheric features within the lidar profiles based on a number of (statistical) image reconstruction techniques. Next to this, it also identifies those regions where the lidar beam has been fully attenuated and where the surface backscatter has impacted the measured lidar backscatter signals directly above the surface. From the pixels assigned as clear sky (with no features present above), the clear-sky-averaged profiles for the three ATLID channels, the co-polar Mie channel, the total cross channel and the co-polar Rayleigh channel are created. These feature-free or clear-sky profiles are useful for e.g., assessing the quality of the ATLID Level-1 (L1) attenuated backscatters. An important goal of the A-FM product is to guide smoothing strategies within downstream processors e.g., the ATLID profile retrieval (A-PRO) algorithm which directly follows A-FM within the EarthCARE Level-2 (L2) processing chain. Within the A-PRO algorithm, profiles of extinction, backscatter and linear depolarization ratio are retrieved. However, smoothing of the ATLID L1 attenuated backscatter is necessary since the SNR levels present at the ATLID native resolution are generally not sufficient for meaningful retrievals to be conducted. At the same time, to prevent biased retrievals, any smoothing procedure must respect the cloud–aerosol structure and avoid mixing strong features, e.g., clouds, and weak features, e.g., aerosol regions, together. The A-FM product provides the A-PRO algorithm with important information that is used to guide various smoothing procedures. To enable the processing of the large datasets from observation up to L2 retrievals, each EarthCARE orbit is separated into eight frames, divided at latitudes of 22.5∘ N and 22.5∘ S and 62.5∘ N and 62.5∘ S. As a secondary product, A-FM outputs can be used to conduct a frame-by-frame evaluation of the ATLID L1 cross-talk calibration, where an EarthCARE frame is one-eighth of a full orbit. This evaluation can be performed by comparing the retrieved clear-sky profiles to the expected channel profiles. The A-FM product has been applied to both synthetic data from the EarthCARE end-to-end simulator (ECSIM) and the L1 data from the Aeolus wind lidar mission. Comparisons against the ECSIM model truth indicate that A-FM has a percentage correctness &gt; 90 % and is capable of reliably detecting aerosol and cloud regions within extinctions (&gt; 10−5 m−1).

On the relation between ice-crystal scattering phase function at 180° and particle size: implication to lidar-based remote sensing of cirrus clouds.

The lack of knowledge of the relation between a lidar backscatter signal and particle size makes it challenging to retrieve ice-cloud particle size from spaceborne lidar observations. This study employs a synergistic combination of the state-of-the-art invariant imbedding T-matrix method and the physical geometric-optics method (PGOM) to investigate the relation between the ice-crystal scattering phase function at 180° (P11(180°)) and particle size (L) for typical ice-crystal shapes. In particular, the P11(180°) -L relation is quantitatively analyzed. The dependence of the P11(180°) -L relation on particle shape can be used with spaceborne lidar observations to detect ice-cloud particle shapes.

First assessment of Aeolus Standard Correct Algorithm particle backscatter coefficient retrievals in the eastern Mediterranean

Abstract. Since 2018, the Aeolus satellite of the European Space Agency (ESA) has acquired wind HLOS (horizontal line-of-sight) profiles throughout the troposphere and up to the lower stratosphere, filling a critical gap in the Global Observing System (GOS). Aeolus, carrying ALADIN (Atmospheric LAser Doppler INstrument), the first UV HSRL (High Spectral Resolution Lidar) Doppler lidar ever placed in space, provides also vertically resolved optical properties of particulates (aerosols and clouds). The present study focuses on the assessment of Aeolus L2A particulate backscatter coefficient (baseline 2A11), retrieved by the Standard Correct Algorithm (SCA), in the eastern Mediterranean, a region hosting a variety of aerosol species. Ground-based retrievals acquired by lidar instruments operating in Athens (central Greece), Thessaloniki (northern Greece) and Antikythera (southwestern Greece) serve as reference. All lidar stations provide routine measurements to the PANACEA (PANhellenic infrastructure for Atmospheric Composition and climatE chAnge) network. A set of ancillary data, including sun-photometric observations (AERONET), reanalysis products (CAMS and MERRA-2), satellite observations (MSG-SEVIRI and MODIS Aqua) and backward-trajectories modelling (FLEXPART), is utilized towards an optimum characterization of the probed atmospheric conditions under the absence of a classification scheme in Aeolus SCA profiles. First, emphasis is given on the assessment of Aeolus SCA backscatter coefficient under specific aerosol scenarios over Antikythera island. Due to the misdetection of the cross-polar component of the backscattered lidar signal, Aeolus underestimates the aerosol backscatter coefficient by up to 33 % when non-spherical mineral particles are recorded (10 July 2019). A good performance is revealed on 3 July 2019, when horizontally homogeneous loads of fine spherical particles are confined below 4 km. For other two cases (8 July 2020 and 5 August 2020), due to noise issues, the SCA performance degrades in terms of depicting the stratification of aerosol layers composed of particles of different origin. According to the statistical assessment analysis of 43 identified cases, a poor-to-moderate performance is revealed for the unfiltered (aerosols plus clouds) SCA profiles, which improves substantially when cloud-contaminated profiles are excluded from the collocated sample. This improvement is evident at both Aeolus vertical scales (regular scales have 24 bins and mid-bin scales have 23 bins), and it is justified by the drastic reduction in the bias (from 0.45 to 0.27 Mm−1 sr−1 for SCA and from 0.69 to 0.37 Mm−1 sr−1 for SCA mid-bin) and root mean square error (from 2.00 to 1.65 Mm−1 sr−1 for SCA and from 1.88 to 1.00 Mm−1 sr−1 for SCA mid-bin) scores. In the vertical, the SCA performance degrades at the lowermost bins due to either the contamination from surface signals or the increased noise levels for the aerosol retrievals. Among the three PANACEA stations, the best agreement is found at the remote site of Antikythera with respect to the urban sites of Athens and Thessaloniki. Finally, all key Cal/Val (calibration and validation) aspects necessary for future relevant studies, the recommendations for a possible Aeolus follow-on mission and an overview of the ongoing related activities are thoroughly discussed.

Resonant Scattering by Excited Gaseous Components as an Indicator of Ionization Processes in the Atmosphere

The results of lidar sensing of the atmosphere at altitudes in the range of 25–600 km from the Kamchatka Lidar Station (53° N, 158° E) obtained in 2008–2022 are presented. The results of an analysis of the data of two-frequency lidar sensing of the thermosphere are given. The increased scattering at wavelengths of 532 and 561 nm is due to resonant scattering by excited atomic nitrogen and oxygen ions. Manifestations of resonant scattering in the middle atmosphere are also discussed. It is demonstrated that these ions are excited during the process of the ionization of the main atmospheric species by the precipitation of energetic electrons. The findings show that, during lidar soundings of the middle atmosphere, the ionization process can form imaginary aerosol formations. The spectrum of precipitating electrons can be estimated from the shape and position of the maximum of the lidar signal profile. It is shown that the process of the excitation of ions in the ground state does not play any significant role in the formation of the backscattered lidar signal. The signal does not carry information about the content and height profile of ions at the ground state. The appearance of resonant scattering in the atmosphere indicates the presence of the ionization sources.

Computation of the Attenuated Backscattering Coefficient by the Backscattering Lidar Signal Simulator (BLISS) in the Framework of the CALIOP/CALIPSO Observations

This paper presents the Backscattering Lidar Signal Simulator (BLISS), an end-to-end lidar simulator developed by the Centre National d’Etudes Spatiales (CNES). We computed the constant multiple-scattering (MS) coefficient of BLISS with a Monte Carlo (MC) code in the framework of CALIOP/CALIPSO observations for different homogeneous and plane-parallel stratocumulus and cirrus cloud geophysical scenes. The MS coefficient varies from 0.46 to 0.63. Then we evaluated the Level 1 products of BLISS. Above and in-cloud relative difference between the attenuated backscattering coefficient vertical profile simulated by BLISS and by the MC code is smaller than 0.5% under single-scattering regime and smaller than 10% (30% if optical depth of cirrus is large) under multiple-scattering regime, thus confirming the robustness of BLISS.

Inter-comparison of atmospheric boundary layer (ABL) height estimates from different profiling sensors and models in the framework of HyMeX-SOP1

Abstract. This paper reports results from an inter-comparison effort involving different sensors and models used to measure the atmospheric boundary layer height (ABLH). The effort took place in the framework of the first Special Observing Period of the Hydrological Cycle in the Mediterranean Experiment (HyMeX-SOP1), with the Raman lidar system BASIL deployed in Candillargues (southern France) and operating in almost continuous mode over the time period September–November 2012. ABLH estimates were obtained based on the application of the Richardson number technique to Raman lidar and radiosonde measurements and to ECMWF-ERA5 reanalysis data. In the effort we considered radiosondes launched in the proximity of the lidar site, as well as radiosondes launched from the closest radiosonde station included in the Integrated Global Radiosonde Archive (IGRA). The inter-comparison effort also includes ABLH measurements from the wind profiler, which rely on the turbulence method, as well as measurements obtained from elastic backscatter lidar signals. The Richardson number approach applied to the on-site radiosonde data is taken as reference. Measurements were carried out throughout the month of October 2012. The inter-comparison is extended to both daytime and night-time data. Results reveal a very good agreement between the different approaches, with values of the correlation coefficient R2 for all compared data pairs in the range 0.94–0.98. Values of the slope of the fitting line in the regression analysis are in the range 0.91–1.08 for daytime comparisons and in the range 0.95–1.03 for night-time comparisons, which testifies to the presence of the very small biases affecting all five ABLH estimates with respect to the reference ABLH estimate, with slightly smaller bias values found at night. Results also confirm that the combined application of different methods to the sensors and model data allows us to get accurate and cross-validated estimates of the ABL height in a variety of weather conditions. Correlations between the ABLH measurements and other atmospheric dynamic and thermodynamic variables, such as CAPE (convective available potential energy), friction velocity and relative humidity, are also evaluated to infer possible mutual dependences.

New Ocean Subsurface Optical Properties From Space Lidars: CALIOP/CALIPSO and ATLAS/ICESat‐2

AbstractRemote sensing from Earth‐observing satellites is now providing valuable information about ocean phytoplankton distributions. This paper presents the new ocean subsurface optical properties obtained from two space‐based lidars: the Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite and the Advanced Topographic Laser Altimeter System (ATLAS) aboard the Ice, Cloud, and land Elevation Satellite‐2 satellite. Obtaining reliable estimates of subsurface biomass necessitates removing instrument artifacts peculiar to each sensor, that is, polarization crosstalk artifacts in the CALIOP signals and after pulsing effects arising from the ATLAS photodetectors. We validate the optical properties derived from the corrected lidar backscatter signals using MODerate‐resolution Imaging Spectroradiometer ocean color measurements and autonomous biogeochemical Argo float profiles. Our results support the continued use of present and future spaceborne lidars to study the global plankton system and characterize its vertical structures in the upper ocean.

Estimating the optical extinction of liquid water clouds in the cloud base region

Abstract. Accurate lidar-based measurements of cloud optical extinction, even though perhaps limited to the cloud base region, are useful. Arguably, more advanced lidar techniques (e.g. Raman) should be applied for this purpose. However, simpler polarisation and backscatter lidars offer a number of practical advantages (e.g. better resolution and more continuous and numerous time series). In this paper, we present a backscatter lidar signal inversion method for the retrieval of the cloud optical extinction in the cloud base region. Though a numerically stable method for inverting lidar signals using a far-end boundary value solution has been demonstrated earlier and may be considered as being well established (i.e. the Klett inversion), the application to high-extinction clouds remains problematic. This is due to the inhomogeneous nature of real clouds, the finite range resolution of many practical lidar systems, and multiple scattering effects. We use an inversion scheme, where a backscatter lidar signal is inverted based on the estimated value of cloud extinction at the far end of the cloud, and apply a correction for multiple scattering within the cloud and a range resolution correction. By applying our technique to the inversion of synthetic lidar data, we show that, for a retrieval of up to 90 m from the cloud base, it is possible to obtain the cloud optical extinction within the cloud with an error better than 5 %. In relative terms, the accuracy of the method is smaller at the cloud base but improves with the range within the cloud until 45 m and deteriorates slightly until reaching 90 m from the cloud base.

Spectral correction of turbulent energy damping on wind lidar measurements due to spatial averaging

Abstract. Continuous advancements in pulsed wind lidar technology have enabled compelling wind turbulence measurements within the atmospheric boundary layer with probe lengths shorter than 20 m and sampling frequency on the order of 10 Hz. However, estimates of the radial velocity from the back-scattered lidar signal are inevitably affected by an averaging process within each probe volume, generally modeled as a convolution between the true velocity projected along the lidar line-of-sight and an unknown weighting function representing the energy distribution of the laser pulse along the probe length. As a result, the spectral energy of the turbulent velocity fluctuations is damped within the inertial subrange, thus not allowing one to take advantage of the achieved spatio-temporal resolution of the lidar technology. We propose to correct the turbulent energy damping on the lidar measurements by reversing the effect of a low-pass filter, which can be estimated directly from the power spectral density of the along-beam velocity component. Lidar data acquired from three different field campaigns are analyzed to describe the proposed technique, investigate the variability of the filter parameters and, for one dataset, assess the corrected velocity variance against sonic anemometer data. It is found that the order of the low-pass filter used for modeling the energy damping on the lidar velocity measurements has negligible effects on the correction of the second-order statistics of the wind velocity. In contrast, the cutoff wavenumber plays a significant role in spectral correction encompassing the smoothing effects connected with the lidar probe length. Furthermore, the variability of the spatial averaging on wind lidar measurements is investigated for different wind speed, turbulence intensity, and sampling height. The results confirm that the effects of spatial averaging are enhanced with decreasing wind speed, smaller integral length scale and, thus, for smaller sampling height. The method proposed for the correction of the second-order turbulent statistics of wind-velocity lidar data is a compelling alternative to existing methods because it does not require any input related to the technical specifications of the used lidar system, such as the energy distribution over the laser pulse and lidar probe length. On the other hand, the proposed method assumes that surface-layer similarity holds.

Initial assessment of lidar signal and the first result of a Raman lidar installed at a high altitude station in India

Abstract: The lidar backscattered signal can be simultaneously received in both analog (in millivolts) and photon counting (PC in MHz) modes to achieve the better signal for both low and high altitudes. One way to get a better signal is by gluing both signals into a single profile and this single profile contains the high linearity and high sensitivity of the analog and PC signals respectively. In this paper, the experimentally obtained lidar backscattered signal from a high altitude station in Himachal Pradesh region of India is used for gluing and various steps involved in the gluing technique are described. Glued Signal has been used to verify the correct alignment of the lidar system and to obtain the vertical distribution of optical profiles of aerosol and clouds such as backscatter coefficient, extinction coefficient, linear depolarization ratio, optical depth from lidar and Microtop Sunphotometer, Planetary boundary layer (PBL) height etc. The results reveal that the most of the aerosols are confined in the lower troposphere within 4 km and above 4 km, the backscattered signal was mainly due to the molecules during the observed period. The mean lidar ratio (LR) values werefound to be 38.5 ± 14.5sr and 35.75 ± 14.75sr in the month of June and November 2016 respectively suggesting presence of urban aerosols and the observed depolarization ratio values suggest the dominance of spherical particles. The average PBL height was observed as 738 ± 423m and 542 ± 273m in the month of June and November 2016.

Remote Sensing of Atmospheric Methane with IR OPO Lidar System

A differential absorption lidar (DIAL) system designed on the basis of optical parametric oscillators (OPO) with nonlinear KTiOAsO4 (KTA) and KTiOPO4 (KTP) crystals is described. The crystals allow laser radiation tuning in the infrared region (IR) wavelength region. The measurements in the 3.30–3.50 μm spectral range, which includes a strong absorption band of methane, are carried out. Lidar backscattered signals in the spectral band 3.30–3.50 μm has been measured and analyzed along the horizontal path in the atmosphere. Based on the experimental results, CH4 concentrations ~2.085 ppm along a 800 m surface path are retrieved in the spectral range under study with a spatial resolution of 100 m.

Design of a high-spectral-resolution lidar for atmospheric temperature measurement down to the near ground.

In this paper, a high-spectral-resolution lidar (HSRL) for profiling atmospheric temperature from the ground to 10 km is proposed. A double Nd:YAG laser produces the transmitted laser at 532 nm. The backscattering lidar signal is passed through two different saturated iodine-vapor filters and thus obtains molecular scattering signals that can be employed to determine the temperature. A coaxial postposition transceiver is constructed with an off-axis aspheric reflective telescope (OART). The design of the transceiver and that of the OART are demonstrated. With this transceiver, the lidar blind zone where the overlap factor is zero can be reduced greatly, and accurate temperature measurement for full elevation can be achieved. The whole system is optimized with theoretical models based on geometrical optics and statistical error analyses. Monte Carlo simulations display the performance of the designed HSRL, showing that the all-day temperature retrieval error is better than 1.4 K from the ground to 10 km. The proposed HSRL is expected to provide more accurate atmospheric auxiliary parameters for the detection of aerosols' optical characteristics.

Analyzing the atmospheric boundary layer using high-order moments obtained from multiwavelength lidar data: impact of wavelength choice

Abstract. The lowest region of the troposphere is a turbulent layer known as the atmospheric boundary layer (ABL) and characterized by high daily variability due to the influence of surface forcings. This is the reason why detecting systems with high spatial and temporal resolution, such as lidar, have been widely applied for researching this region. In this paper, we present a comparative analysis on the use of lidar-backscattered signals at three wavelengths (355, 532 and 1064 nm) to study the ABL by investigating the high-order moments, which give us information about the ABL height (derived by the variance method), aerosol layer movement (skewness) and mixing conditions (kurtosis) at several heights. Previous studies have shown that the 1064 nm wavelength, due to the predominance of particle signature in the total backscattered atmospheric signal and practically null presence of molecular signal (which can represent noise in high-order moments), provides an appropriate description of the turbulence field, and thus in this study it was considered a reference. We analyze two case studies that show us that the backscattered signal at 355 nm, even after applying some corrections, has a limited applicability for turbulence studies using the proposed methodology due to the strong contribution of the molecular signature to the total backscatter signal. This increases the noise associated with the high-order profiles and, consequently, generates misinformation. On the other hand, the information on the turbulence field derived from the backscattered signal at 532 nm is similar to that obtained at 1064 nm due to the appropriate attenuation of the noise, generated by molecular component of backscattered signal by the application of the corrections proposed.

Aerosol optical properties in the Arctic: The role of aerosol chemistry and dust composition in a closure experiment between Lidar and tethered balloon vertical profiles

A closure experiment was conducted over Svalbard by comparing Lidar measurements and optical aerosol properties calculated from aerosol vertical profiles measured using a tethered balloon. Arctic Haze was present together with Icelandic dust. Chemical analysis of filter samples, aerosol size distribution and a full set of meteorological parameters were determined at ground. Moreover, scanning electron microscopy coupled with energy-dispersive X-ray (SEM-EDS) data were at disposal showing the presence of several mineralogical phases (i.e., sheet silicates, gypsum, quartz, rutile, hematite).The closure experiment was set up by calculating the backscattering coefficients from tethered balloon data and comparing them with the corresponding lidar profiles. This was preformed in three subsequent steps aimed at determining the importance of a complete aerosol speciation: (i) a simple, columnar refractive index was obtained by the closest Aerosol Robotic Network (AERONET) station, (ii) the role of water-soluble components, elemental carbon and organic matter (EC/OM) was addressed, (iii) the dust composition was included.When considering the AERONET data, or only the ionic water-soluble components and the EC/OM fraction, results showed an underestimation of the backscattering lidar signal up to 76, 53 and 45% (355, 532 and 1064 nm). Instead, when the dust contribution was included, the underestimation disappeared and the vertically-averaged, backscattering coefficients (1.45 ± 0.30, 0.69 ± 0.15 and 0.34 ± 0.08 Mm−1 sr−1, at 355, 532 and 1064 nm) were found in keeping with the lidar ones (1.60 ± 0.22, 0.75 ± 0.16 and 0.31 ± 0.08 Mm−1 sr−1). Final results were characterized by low RMSE (0.36, 0.08 and 0.04 Mm−1 sr−1) and a high linear correlation (R2 of 0.992, 0.992 and 0.994) with slopes close to one (1.368, 0.931 and 0.977, respectively). This work highlighted the importance of all the aerosol components and of the synergy between single particle and bulk chemical analysis for the optical property characterization in the Arctic.

A Turbulence-Oriented Approach to Retrieve Various Atmospheric Parameters Using Advanced Lidar Data Processing Techniques

The article is aimed at presenting a semi-empirical model coded and computed in the programming language Python, which utilizes data gathered with a standard biaxial elastic lidar platform in order to calculate the altitude profiles of the structure coefficients of the atmospheric refraction index C N 2 ( z ) and other associated turbulence parameters. Additionally, the model can be used to calculate the PBL (Planetary Boundary Layer) height, and other parameters typically employed in the field of astronomy. Solving the Fernard–Klett inversion by correlating sun-photometer data obtained through our AERONET site with lidar data, it can yield the atmospheric extinction and backscatter profiles α ( z ) and β ( z ) , and thus obtain the atmospheric optical depth. Finally, several theoretical notions of interest that utilize the solved parameters are presented, such as approximated relations between C N 2 ( z ) and the atmospheric temperature profile T ( z ) , and between the scintillation of backscattered lidar signal and the average wind speed profile U ( z ) . These obtained profiles and parameters also have several environmental applications that are connected directly and indirectly to human health and well-being, ranging from understanding the transport of aerosols in the atmosphere and minimizing the errors in measuring it, to predicting extreme, and potentially-damaging, meteorological events.

Upconversion detector for range-resolved DIAL measurement of atmospheric CH4.

We demonstrate a robust, compact, portable and efficient upconversion detector (UCD) for a differential absorption lidar (DIAL) system designed for range-resolved methane (CH4) atmospheric sensing. The UCD is built on an intracavity pump system that mixes a 1064 nm pump laser with the lidar backscatter signal at 1646 nm in a 25-mm long periodically poled lithium niobate crystal. The upconverted signal at 646 nm is detected by a photomultiplier tube (PMT). The UCD with a noise equivalent power around 127 fW/Hz1/2 outperforms a conventional InGaAs based avalanche photodetector when both are used for DIAL measurements. Using the UCD, CH4 DIAL measurements have been performed yielding differential absorption optical depths with relative errors of less than 11% at ranges between 3 km and 9 km.

Monitoring of dispersed smoke-plume layers by determining locations of the data-point clusters

A modified data-processing technique of the signals recorded by zenith-directed lidar, which operates in smoke-polluted atmosphere, is discussed. The technique is based on simple transformations of the lidar backscatter signal and the determination of the spatial location of the data point clusters. The technique allows more reliable detection of the location of dispersed smoke layering. Examples of typical results obtained with lidar in a smokepolluted atmosphere are presented.

Application of a multiple scattering model to estimate optical depth, lidar ratio and ice crystal effective radius of cirrus clouds observed with lidar.

Lidar measurements of cirrus clouds are highly influenced by multiple scattering (MS). We therefore developed an iterative approach to correct elastic backscatter lidar signals for multiple scattering to obtain best estimates of single-scattering cloud optical depth and lidar ratio as well as of the ice crystal effective radius. The approach is based on the exploration of the effect of MS on the molecular backscatter signal returned from above cloud top.