Proceedings of the 30th International Laser Radar Conference

Accurate simulation of rotational Raman (RR) scattering from atmospheric molecules plays an important role in the design and data analysis of elastic, depolarization, extinction, and temperature lidar systems. As the intensity of RR scattering varies with temperature, the intensity of lidar signals is also temperature-dependent, an aspect exacerbated by the use of narrow-band interference filters (IFF) in lidar design. The strongly depolarizing RR lines lead to a shift in the detected molecular depolarization ratio with temperature. For the estimation of the systematic uncertainty of such measurements and its impact on the lidar products, it is important to be able to calculate the contribution of the Rayleigh scattering to the lidar signal intensities. Based on several codes existing in the ACTRIS (Aerosol, Clouds, and Trace Gases Research Infrastructure) community for the calculation of Raman lines, we developed a new, state-of-the-art version for a wide range of laser wavelengths and for the range of temperatures found in the atmosphere. It has been tested against the existing codes and is publicly available for use and further improvement. The code will be integrated into the ACTRIS lidar data analysis software single calculus chain (SCC). We used this new code for the estimation of possible errors due to the abovementioned experimental uncertainties and to estimate the overall error in the calculated molecular depolarization ratios.

We present our prototype for a semiconductor-based high-spectral-resolution LiDAR (HSRL) system with a simplified optical setup. Traditionally, HSRL systems split the received signal into two channels: one channel measures the molecular backscatter, and the other channel measures both molecular and aerosol backscatters. An etalon or molecular vapor absorption line is used to separate out the narrow aerosol spectrum from the Doppler broadened molecular backscatter. By modulating our seed laser between the center of a rubidium absorption line and just off the absorption line, we are able to combine both HSRL channels into a single physical optical path.

An assessment of the aerosol layering module (LTOOL), which has already been added to the European Aerosol Lidar Network’s (EARLINET) Single Calculus Chain (SCC, https://scc.imaa.cnr.it ) algorithm, is presented. Currently, the LTOOL module is applied to the EARLINET lidar data analyzer (ELDA) optical products and has been integrated in the SCC development web interface. The algorithm layering analysis utilizes the wavelet covariance transform method (WCT) for the layer boundary detection in order to extract the layers’ geometrical features, i.e., the planetary boundary layer height and the lofted aerosol layers. LTOOL reproduces automatically the layers’ geometrical properties (i.e., base, top, and center of mass), with a sufficient degree of temporal homogeneity. Sensitivity studies on the application of different dilation values are presented along with the stability of the intensive properties within the layer boundaries, derived from the lidar measurements of Thessaloniki’s lidar station, which is part of EARLINET. The aim is to investigate the algorithms’ accuracy in identifying persistent layers in various atmospheric conditions.

We developed a minimization procedure that can be used for the simultaneous and explicit retrieval of the spectrally and size-independent complex refractive index (CRI) and the corresponding monomodal particle size distribution from 3β + 2α HSRL/Raman lidar measurements. The 3β + 2α optical data are backscatter coefficients measured at 355, 532, and 1064 nm and extinction coefficients measured at 355 and 532 nm. Analysis of the results derived with the minimization procedure shows that the CRI can only be retrieved with preset accuracy if the input optical data are accurate to at least eight significant digits. The CRI cannot be estimated without introducing constraints, even if measurement uncertainties of the optical data are as low as 1–3%. We studied constraints provided by information about relative humidity (RH) and how far these constraints could allow us to restrict the retrieval uncertainties. To validate the results of the CRI retrieval, we analyzed a Raman lidar measurement of a smoke plume for which radiosonde and in situ data are available. The results derived with this novel approach were compared to our two-dimensional regularization algorithm and data taken with in situ instruments. We find good agreement of the results.

Traditionally, quantitative lidar techniques like differential absorption lidar (DIAL) and high-spectral-resolution lidar (HSRL) utilize high-power-aperture product designs, which partially compensates for the need to take discrete derivatives of noisy data in post-processing (for number density for DIAL and extinction for HSRL) and provides for high-performance measurements, i.e., higher resolution, accuracy, or precision. Conversely, low-power-aperture product lidar designs are easier to make eye-safe, reliable, and cost-effective, which are important attributes for network development and field deployment. The atmospheric science community has expressed the need for high-quality, quantitative, robust, network deployable, and cost-effective sensors for a variety of applications such as improved numerical weather forecasting – in essence requiring the best of both worlds without the accompanying drawbacks. In response to this need, the National Center for Atmospheric Research and Montana State University have been developing the MicroPulse DIAL (MPD) architecture for thermodynamic profiling in the lower atmosphere. The MPD architecture takes advantage of the benefits of low-power, low-cost laser diodes, and fiber optics to achieve quantitative profiling leveraging narrowband filtering and efficient elastic scattering. A field-deployable MPD instrument capable of humidity, quantitative aerosol, and temperature profiling has recently been developed. This presentation will describe the current status of this thermodynamic profiler and the initial results from a recent field deployment. Emphasis will be given to the analysis of the temperature data including comparisons to co-located radiosondes to describe current performance.

It is well known that semiconductor lasers offer the important advantages of lower costs, smaller footprint, simplicity, and wider spectral coverage compared to solid-state lasers. However, despite many advances, the output power achievable from semiconductor lasers is still far from solid-state lasers and generally has restricted their use in atmospheric profiling to lidar that does not allow quantitative backscatter information (e.g., ceilometers). Over the past decade, we have been developing lidar architectures using semiconductor sources that provide quantitative observations needed to advance atmospheric science and weather forecasting. This chapter reviews some of the limitations and benefits of this flexible laser technology. We introduce a semiconductor lidar architecture, based on a pulsed overdriven tapered amplifier and traveling wave amplifier, the latter being leveraged as a multifunction switch. This design has been implemented and is being used for the measurement of water vapor, temperature, and calibrated aerosols via DIAL and HSRL techniques. Initial results from an intercomparison with a collocated instrument using our previous baseline architecture will be discussed.

A novel active vapor filtering approach functioning at the third harmonic of the commonly used Nd:YAG laser is introduced. The filter utilizes an excited state absorption feature in atomic barium vapor and is characterized by a unique, highly tunable, cusped, non-Maxwellian absorption curve. With adjustments to the pump intensity, frequency, and path length, the filter function width, depth, and central frequency can all be rapidly modified. A feasibility study for a temperature profiling high-spectral resolution LiDAR employing this notch filter is also presented.

In the last 15 years, the middle-upper-atmosphere lidar observations have evolved from narrow altitude ranges to the significantly extended altitude ranges of neutral profiling from near the ground up to ~200 km and of ion detection up to ~300 km. A latest development was the first detection of helium to ~700 km. These results demonstrate the huge potentials that lidars bring to the ionosphere-thermosphere-mesosphere-stratosphere (ITMS) physics research as well as to the plasma-neutral coupling studies in the near space environment. This chapter highlights several stunning discoveries made from lidar measurements, including the thermosphere-ionosphere metal (TIMt) layers, full coverage of gravity wave temporal spectrum, and multistep vertical coupling, to illustrate the significant progresses in atmosphere-space sciences. Then we focus on identifying future lidar technologies in enabling cutting-edge sciences in the ITMS physics and interactions between plasma space and neutral atmosphere.

Dust orientation is an ongoing investigation in recent years. Its potential proof will be a paradigm shift for dust remote sensing, invalidating the currently used simplifications of randomly oriented particles. Vertically resolved measurements of dust orientation can be acquired with a polarization lidar designed to target the off-diagonal elements of the backscatter matrix which are nonzero only when the particles are oriented. We constructed the “WALL-E” lidar system emitting linear and elliptical polarized light and detecting various states of polarization of the backscattered light. Herein we present measurements of oriented rain, ice, and dust or drizzle particles acquired in Athens, Greece, during the preparation of the system for the ESA Aeolus Cal/Val Campaign “ASKOS” at Cabo Verde (June 2022).

In this work, we propose a low coherence Doppler lidar (LCDL) to measure dust flow at near-surface atmosphere. To get dust flow information at near-surface atmosphere, it is necessary to measure it with high spatial and high temporal resolutions. Low coherence light source of Δλ = 0.5 pm can satisfy this high-resolution criterion of <1 m. In addition, by shortening the integration time to <5 ms, high-speed measurement can be performed on the small spatiotemporal scale of the lower atmosphere. A dust experiment is conducted to evaluate LCDL performance by shaking dust (wheat flour) off into a wind tunnel. The measurement speed of LCDL is compared with the speed of anemometer. At speeds from 0 to 5 m/s, they show good linear agreement. The distribution of dust flow is obtained with the Doppler shift frequency width of >1 MHz. We simulated the experiment condition to calculate it with a viscous resistance. The waveform obtained by the calculation has the same Doppler shift frequency width of >1 MHz with the experiment.

A multiwavelength lidar system with a light-emitting diode (LED)-based light source is designed and developed to continuously monitor near-surface atmosphere at nighttime. The LED light source does not require any heat dissipation system and can emit optical power for long periods with constant output. The LED light sources with wavelengths of 365, 450, 525, and 630 nm are used as lidar transmitters to detect hard target and atmospheric echoes. The pulse circuit for realizing the pulsed oscillation of the LED lights is applied by the avalanche breakdown of the transistor. These LED pulsed lights can be synchronized by serially concatenated to the circuit. The LED has a pulse width of around 17 ns, repetition frequency of over 250 kHz, and each peak power of up to 2 W. With these LED transmitter characteristics, the lidar system accomplishes monitoring the atmosphere’s rapid activities in the near-range measurement. Initial near-surface observation results from 365 and 450 nm show that atmospheric echoes can be monitored in the range of 0–300 m at an accumulation time of a few tens of seconds at nighttime. Analysis of the backscattering light intensity with multiwavelengths from this LED lidar system produces a real-time extinction coefficient near the surface. This report discusses the design and practical test of the multiwavelength LED lidar.

A low-cost high spectral resolution lidar (HSRL) was developed for aerosol profile measurement and to monitor air quality. A multi-longitudinal mode laser, which was widely used for aerosol lidars and lower cost compared to single-mode lasers, was used as the light source of HSRL. The multimode laser was designed to have the same mode spacing as the free spectral range of interferometer optimized for the HSRL measurement. As a result, the laser had a short cavity length and large mode spacing, but it had a narrow spectral width comparable to single-mode lasers. The interferometer was scanned over the range of one fringe, and the interference visibility containing aerosol backscatter information was obtained at each height through fitting analysis of the scan data. The interference visibility and fringe position were calibrated with the reference signals taken from the part of the transmitted laser. We successfully carried out continuous measurement of aerosol profiles during the daytime and nighttime. The performance of the new system was greater than a previous version, which employed a laser with a much longer cavity.

Modified stacked hourglass network is used to capture the height of convective boundary layer (CBLH) from radial wind speed and aerosol backscatter measured by a Doppler wind LiDAR. We collected a year’s LiDAR data and generated over 30,000 maps for training. The results show that the data set of 4-directional wind speeds and aerosol backscatters (without vertical component), the mean absolute error (MAE) of the CBLH estimated by the proposed deep learning methods, is about 60 m. If only aerosol backscatter is used to train the model, the MAEs of CBLH are about 91 m and 86 m for daytime and nighttime measurements, respectively. This chapter shows the advantage of proposed deep learning method in better estimation of CBLH.

In regard to lidar applications, we will explore if the use of information on optical fingerprints (i.e., characteristic optical signals) allows for establishing vertically resolved identification of chemical components of atmospheric pollution. In this work we present hardware and experimental results of Raman and fluorescence spectra of a collection of different dust samples composed of quartz, hematite, kaolinite, barite, and calcite. We investigated these samples under laboratory conditions with two Raman microscopes.

Within the frame of a project (CONCERNING) aimed at the development of a multichannel lidar for atmospheric monitoring, we investigated the current feasibility and the limits of a ground-based Raman lidar system dedicated to the measurement of CO2 profiles. The performance of a state-of-the-art lidar system was investigated through a set of numerical simulations. The possibility of exploiting both CO2 Raman lines of the ν1:2ν2 resonance is explored. An accurate evaluation and quantification of the contribution of the Raman O2 lines on the signal and other (e.g., aerosol, absorbing gases) disturbance sources was carried out. The signal integration over the vertical and over time required to reach a useful signal-to-noise ratio both in daytime and nighttime needed for a quantitative analysis of carbon dioxide sources and sinks was evaluated. The above objectives were obtained developing an instrument simulator code consisting of a radiative transfer model able to simulate, in a spectrally resolved manner (0.0001 nm), all laser light interaction mechanisms with atmospheric constituents, a consistent background signal, and all the devices present in the considered Raman lidar experimental setup. The preliminary results indicate that the simulated lidar system, provided to have a low overlap height, could perform measurements on the low troposphere (<1 km) gradients (1–5 ppm) with sufficient precision both in daytime and nighttime with an integration time of 1–3 h and a vertical resolution of 75 m.

Fast, real-time, and high-precision distance measurement is of great significance to satellite tracking, precision equipment manufacturing, gravitational wave detection, and many other fields. As a new measuring tool, optical frequency comb (OFC) has the characteristics of both wide spectral range and narrow linewidth of each comb. It can give full play to its advantages in the field of large-scale and high-precision absolute distance measurement. This chapter introduces an all fiber free-running dual-comb ranging (DCR) system without any mode locking equipments. In this system, the target distance can be adjusted by variable optical fiber delay line. During the signal processing, the peak position of the signal is accurately extracted by tracking the pulse repetition frequency (PRF) jitter of the optical combs and adaptive signal filtering. The PRF of optical frequency comb is about 180 MHz, and the PRF difference is about 1.8 kHz. The ranging accuracy of this dual-comb system can reach a distance precision of 16.2 microns, which can meet the need of high-precision range detection in many fields. The whole ranging system is connected with all fibers and does not need extra mode-locking equipment. The devices are all mature devices in 1550-nm communication band, which ensure the robust stability of the experiment system. The chapter provides a new way for high-precision distance measurement.

Most LiDARs, though precise, are vulnerable to position and pointing errors, and while fidelity of location/pointing solutions can be extremely high, determination of uncertainty remains relatively basic. As a result, NASA’s 2021 Surface Topography and Vegetation (STV) Incubation Study Report lists vertical, horizontal, and geolocation accuracy as an associated Science and Application Traceability Matrix product parameter for most identified Science and Application Knowledge Gaps (Surface Topography and Vegetation Incubation Study Team, 2021). Currently, standard uncertainty quantification (UQ) approaches are plagued by simplifying approximations, ignored covariances, as well as improperly modeled (often exclusively Gaussian) uncertainty sources. The presented generalized polynomial chaos expansion (gPCE)-based method has wide-ranging applicability to improve vertical, horizontal positioning and geolocation uncertainty estimates, for all STV disciplines, by more completely describing total aggregated uncertainties, from system level to geolocation, and intrinsically accounting for covariance between variables (without the need to manually construct a covariance matrix). gPCE also does not rely on many of the simplifying assumptions used in standard methods. Most importantly, it supports a number of additional (non-Gaussian) uncertainty sources and arbitrarily high orders of variable cross-moments. gPCE is presented here, for the bare Earth case, as a proof of concept.

In photon counting LiDAR, photon detection is generally well described as a Poisson point process as long as photon arrival rates are sufficiently low to avoid significant nonlinear effects in the detection chain (e.g., deadtime). In general, it is straightforward to employ the Poisson-negative log-likelihood as a noise model in order to obtain a maximum likelihood estimate of photon counting LiDAR data. However, data assimilation methods employing Kalman filters (KF) and some processing methods such as optimal estimation method (OEM) were originally designed for observational data with Gaussian distributed noise, thus allowing for closed-form solutions. A common assumption when applying these methods to photon counting LiDAR data is that, by the central limit theorem, the Poisson distributed photon counts follow Gaussian distributions. While this approximation is technically correct at high photon counts (assuming linear detection), the accuracy trade-off of the approximation is not always clear and is likely to depend on the particular estimation problem. In this chapter, we investigate a few simple cases and suggest areas for further research.

Poisson total variation (PTV) is a statistical signal processing technique that employs regularized maximum likelihood estimation with a known signal detection noise model to perform inversions on noisy observations. Here we describe current and possible application of PTV to estimate MicroPulse DIAL data products. We show results from development of water vapor DIAL processing where PTV has reduced errors in the retrieval and extended the instrument’s useful range from 4–6 km up to 8 km. We describe the benefits of applying PTV to temperature estimation using oxygen DIAL. Finally, we highlight how this processing approach can be applied to different signal acquisition approaches by describing how the technique is used to process time-correlated single photon counting data.

In this presentation, we aim to perform statistical comparisons of cloud, aerosol, and planetary boundary layer (PBL) properties derived from Level 3 (L3) MPLNET products to similar properties retrieved from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard CALIPSO as a precursor for retrievals from the Atmospheric Lidar (ATLID) instrument onboard the EarthCARE satellite. The L3 MPLNET products will be monthly diurnal statistical products for each site: hourly mean and median data arranged monthly. The MPLNET L3 products will be supplemented by the development of satellite-specific MPLNET validation products (e.g., L3-EC for EarthCARE or L3-CAL for CALIPSO). The satellite-specific products will utilize the same statistical analysis as developed for L3 but will be constrained to data acquired during satellite overpasses of MPLNET sites. Based on previous comparisons between ground-based and spaceborne sensors, constraining observations to within a 200-km horizontal radius of the MPLNET site and ± 2-h time window of the closest satellite overpass is sufficient to make correlative measurements of both aerosols and clouds. Our CALIPSO-MPLNET analysis will be used to develop a standard operating procedure to be implemented during the EarthCARE mission.

Segmentation and classification methods for 3D lidar point clouds have been an important focus for years as machine learning (ML) methods and computational capabilities have improved exponentially. However, unsupervised 3D point cloud segmentation and classification remain challenging problems for surface topography, vegetation, and shallow water bathymetry applications. The amount of training data required in traditional ML methods can be prohibitively large to produce and label for these environments, which have an extremely diverse spectrum of conditions and objects. (National Aeronautics and Space Administration (NASA), Surface Topography and Vegetation Incubation Study Team White Paper, NASA Earth Science Decadal Survey, 2020). Water turbidity can severely attenuate laser power through absorption and scattering, reducing both the maximum depth penetration and the density of points on the subsurface. Even in shallow waters, lidar bathymetry is highly susceptible to turbidity hindering target detection and identification applications. Contrast and discernibility between points in lidar point clouds can be enhanced by incorporating lidar signal diversity using intensity, polarizability, or spectral response. These additional contextual data, based on physical properties of objects and media, can improve segmentation and classification efforts, especially when point clouds are sparse. Through drone-based scanning lidar measurements, an unsupervised classification scheme is demonstrated using derived data products, based on observed physical properties, that supplement 3D geometric analysis with additional point-descriptors for grouping points and assigning descriptive classification labels. For very large point clouds, pre-classified point cloud data products using lidar signal diversity would augment existing classification schemes and improve target recognition and identification efficiency.

A novel lidar simulator based on first principles is presented. Here we describe our approach and initial results for simulating raw lidar signals and system SNR from system parameters and aerosol optical properties. We also include a validation method and sensitivity studies. The main motivation behind this work is to show how low-cost and physically small lidar systems would perform in various atmospheric conditions.The simulator presented herein uses instrument component parameters and, based on known atmospheric scenarios, returns aerosol optical properties and signals. In particular, the simulator accounts for molecular effects, system overlap, different far boundary solutions, and the possibility of depolarization channels and is programmed to function at any UV- NIR wavelength. The simulator’s performance is currently being validated against EARLINET and PollyNet datasets.

A novel system of a pulsed IR coherent lidar for wind profile measurements is proposed. The characteristics of the lidar were analyzed from the point of view of its maximum detection range and signal-to-noise ratio (SNR). Two variations of the fiber scheme for Doppler lidar were considered: one of them uses an additional optical hybrid and the other system being the conventional scheme. As an optical hybrid operation is known to be based on the principle of splitting backscattered radiation into two parts, we use an additional amplifier in the scheme. The signal-to-noise balance is analyzed considering all the elements of the fiber optical part and the opto-electronic components. Besides, we discuss the signal character in both cases and the specific features of the signal processing both in the systems with an optical hybrid and without one.

Fine-scale wind measurements in the planetary boundary layer are required for understanding turbulence in complex terrain, flux of energy and aerosols, and severe weather events. The University of Colorado, Boulder (UCB), is developing an airborne Doppler lidar (ADL) system with five-fixed-direction beams to improve wind measurements in heterogeneous conditions. The five-fixed-beam system takes continuous radial wind velocity measurements at multiple angles including a dedicated nadir beam for high-resolution vertical measurements. Results of an ADL simulator, based on a large eddy simulation (LES) with 10 m vertical and horizontal resolutions, demonstrated that the five-beam system can reduce wind profile retrieval error due to turbulence by more than 40%, is less sensitive to restrictive design parameters, and can resolve planetary boundary layer 2D roll structures.

The Arctic atmosphere and subauroral region are a natural laboratory for understanding plasma-neutral and dynamical coupling in the atmosphere and geospace. During geomagnetically active periods, the auroral electrojet and auroral precipitation are overhead at the High-Frequency Active Auroral Research Program (HAARP) facility in Gakona, Alaska (62°N, 145°W), and facilitate active experiments. Iron resonance lidar systems are uniquely suited for these active investigations as naturally occurring iron layers extend from the upper mesosphere to the middle thermosphere (~70–150 km). A novel lidar system has been demonstrated at the German Aerospace Center using an Nd:YAG laser that operated at a minor line at 1116 nm and was tripled to the iron resonance line at 372 nm. This prototype laser was fully solid-state without liquid dyes or flashlamps and with diode pumping. We are developing a lidar system based on that prototype system that can operate robustly at the remote location of HAARP. We will employ a diode-pumped Nd:YAG laser with second and third harmonic generations. The laser will be injection-seeded by a tunable diode laser allowing the laser to frequency scan the iron line. The laser pulse spectra will be recorded on a shot-by-shot basis using an etalon imaging system with a spectral reference. The lidar system is will operate at 372 nm, with a pulse repetition rate of 100 pps, a pulse energy of 30 mJ, and a 0.9-m-diameter telescope. We present the system specifications and the expected performance of the system.

To observe tropospheric ozone more effectively, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center Tropospheric Ozone Differential Absorption Lidar (GSFC TROPOZ DIAL) has been developed and validated within the Tropospheric Ozone Lidar Network (TOLNet). Efforts had been made to transform the system for remote observations that can accurately provide and archive continuous information about the vertical variability of ozone without constant supervision.In this work, we describe major hardware and software upgrades implemented within the GSFC TROPOZ DIAL. These upgrades include full automation to the lidar system and controls of various sub-systems to characterize the overall health of the lidar system as well as useful weather data around the system’s housing. Further improvements were made which led to real-time datalogging and daily archiving for internal system data files and crucial information to the NASA TOLnet cloud network. These feats were achieved with two main Python graphical user interface (GUI) programs as well as other smaller specialized programs which provide a consolidation of data from various weather detectors into coherent graphs, equipped with new file saving and back up mechanics. They also act as control centers for the system’s electrical components during remote operation. The purpose of these changes was to allow unattended and scientifically rigorous observations to be collected during deployments. Selected observations produced with the newly updated system are shown to illustrate the final ozone profiles and various metrics provided by the automation software.

A ground-based mobile 3D lidar observatory has been developed for simultaneous measurements of wind speed, temperature, water vapor, and carbon dioxide absorption in the atmosphere. This chapter reports details of the instruments, assesses the current performances, and gives some examples of measurements for different geophysical applications.

We have developed a hyperspectral Scheimpflug lidar for measuring vegetation fluorescence. The fluorescence spectra of leaves from several known Swedish trees were acquired remotely, and a three-dimensional point cloud was acquired from a forest edge with the hyperspectral lidar. The method can retrieve echoes, synchronized in time and space, from details in the vegetation structure across 70 effective bands from 400 to 800 nm. The fluorescence spectra were clustered using dimensionality reduction by spectral binning and singular value decomposition. Our instrument complements canopy lidar range statistics with fluorescence information for increased specificity.

LMOL, the NASA Langley Mobile Ozone LiDAR, is located near NASA’s LaRC steam plant when not deployed in campaigns. The plant produces steam through the incineration of local trash, and its exhaust plume occasionally contains SO 2 $${ }_2$$ .SO 2 $${ }_2$$ is a known, regulated, pollutant that affects O 3 $${ }_3$$ observations in the UV, as is the case with LMOL. In this chapter, we show how we modified LMOL to detect the plant SO 2 $${ }_2$$ plumes and compute its density when the O 3 $${ }_3$$ background is stable; we observed densities compatible with what is expected from the typical plume exhaust. The selection of laser lines so that an O 3 $${ }_3$$ variation would not get confused with a SO 2 $${ }_2$$ detection is explained in detail, and a model capable of simulating the LiDAR signal with (notably) O 3 $${ }_3$$ and SO 2 $${ }_2$$ absorption for the validation of the retrieval resolution and uncertainty is presented. Finally, the comparison between the modeled and observed performances of the system is shown: the maximum altitude, resolution, and error in the modeled signal and the observed signals are the same within reasonable margins.This chapter demonstrates that LMOL is fully capable of working with SO 2 $${ }_2$$ . The next step being the addition of an additional laser channel, which is simplified by the tunable aspect of the LMOL laser, to address O 3 $${ }_3$$ and SO 2 $${ }_2$$ simultaneously, allowing the assessment of SO 2 $${ }_2$$ when O 3 $${ }_3$$ has variations.

The possibility of using fluorescence from the iodine-blocking filter in HSRL to detect the Mie scattering components in the backscattered signals was studied. An experiment was conducted with an HSRL using an iodine-blocking filter by adding a detector for measuring fluorescence from the iodine cell. Atmospheric backscattering signals were successfully measured, although the detection efficiency was limited by the low optical efficiency of collecting fluorescence from the iodine cell. In the atmospheric measurement, it was also shown that about half of Rayleigh scattering Cabannes line was also absorbed by the iodine cell. To improve the detection performance, a method using detector arrays surrounding the fluorescence cell was considered. The fluorescence excitation spectrum is dependent on the location of the fluorescence detectors, i.e., the penetration depth in the cell. Using this effect, it is possible to separate the Mie and Rayleigh components absorbed in the cell by measuring fluorescence intensity at multiple penetration depths.

A diversified and interdisciplinary lidar research program has been pursued during the recent 10 years at South China Normal University in Guangzhou, China. The activities include time-of-flight (TOF) lidar applications with pulsed lasers for differential absorption (DIAL), laser-induced fluorescence (LIF), and laser-induced break-down spectroscopy (LIBS) studies. Further, range-resolving (bi-static) lidars, based on Scheimpflug arrangements, have been employed. Mobile, drone-based, and hand-held systems were developed. Monitoring has been directed toward air pollutants, vegetation and crops, flying insects (agricultural pests and disease vectors), and water pollutants and fauna.A mobile TOF lidar system was developed as a multipurpose platform for field work. A special adaption of the system is range-resolved monitoring of atomic mercury (absorbing around 254 nm) using the DIAL approach. A high-light was the mapping of mercury fumes from the underground burial chamber of the “Terracotta Army Emperor” Qin’s mausoleum in Xi’an. Further, mercury in major cities as well as in a mining areas was studied. Remote LIF studies included corn and rice fields and concerned species characterization and fertilizer levels.Two different compact LIF systems carried by a drone were developed for vegetation and water pollution studies, with typical flying heights of tens of m. The vegetation probing system and an underwater LIF monitoring system provide range-resolution combined with full-spectral recordings. Such systems could be complemented with compact hand-held instrumentation.Scheimpflug CW lidar systems are powerful in monitoring flying insects. Characteristic information on reflectance, depolarization, and wing-beat frequencies can readily be obtained.

As a branch of atmospheric lidar, polarization lidar plays a significant role in characterizing the properties of cirrus clouds, classifying aerosol types, retrieving aerosol microphysical properties, etc. In this work, a dual-polarization imaging lidar technique, employing two continuous-wave laser diodes (458 nm and 808 nm) as light sources and two polarization cameras with a micro-polarizer array as detectors, has been proposed and demonstrated for all-day field measurements of atmospheric aerosols. Each polarization camera is able to capture a four-directional polarized image of the transmitted laser beam, from which four polarized atmospheric backscattering signals with 0°, 45°, 90°, and 135° polarization angles can be simultaneously measured. Thus, the linear volume depolarization ratio (LVDR) and the offset angles can be retrieved at wavelengths of 458 nm and 808 nm without employing additional optical components and sophisticated system adjustments. Atmospheric validation measurements on a near horizontal path have been carried out from February 18 to February 23, 2022 in Dalian, Northern China. The measurement results showed that the dual-polarization lidar technique opens up many possibilities for characterizing aerosol optical properties.

We develop an algorithm to retrieve aerosol optical properties using data of 355-nm high spectral resolution lidar (HSRL) with depolarization measurement function “ATLID” onboard EarthCARE satellite. The ATLID has three channel data of Mie copolar, Mie crosspolar, and Rayleigh attenuated backscatter coefficients at 355 nm. Using the three channel data, the developed algorithm estimates (1) extinction coefficient (α), backscatter coefficient (β), and depolarization ratio (δ) of particles (aerosols and clouds) without assuming a particle lidar ratio (S); (2) identifies molecule-rich, aerosol-rich, or cloud-rich slab layers; (3) classifies aerosol type (e.g., dust and maritime) using the derived β, S, and δ by a threshold method; (4) retrieve planetary boundary layer height using the feature mask products (i.e., (2)); and (5) estimate extinction coefficients for several main aerosol components in the atmosphere (e.g., dust, sea salt, carbonaceous, and water-soluble aerosols) using difference in depolarization and light absorption properties of the aerosol components from the retrieved α, β, and δ. Furthermore, we develop an aerosol retrieval algorithm using both the ATLID and multi-spectral imager “MSI” onboard EarthCARE. This algorithm retrieves vertically mean mode-radii for dust and fine-mode aerosols as well as the extinction coefficients for the four aerosol components using the three channels of the ATLID and radiances at 670 nm and 865 nm of MSI. These products above are planned to be distributed by JAXA, Japan. We develop the aerosol component retrieval algorithm based on our developed algorithm for the Mie scattering lidar CALIOP onboard CALIPSO satellite.

The LiDAR observatory at Dome C, Antarctica, has been active since 2014. Its main goal is the observation of polar stratospheric clouds during the Antarctic winter, from early May until the end of September. Polar stratospheric clouds typically occur at altitudes between 12 and 26 km, when the stratospheric temperature is low enough to form liquid STS (Supercooled Ternary Solutions), solid NAT (Nitric Acid Trihydrate), and ice crystals. These aerosols reflect part of the light emitted by the LiDAR, and its backscattered fraction as well as its polarization can be measured. The recorded optical signals can then be used to distinguish the various aerosols composing the polar stratospheric clouds (PSCs). PSCs are important for the catalytic destruction of ozone and for the removal of nitric acid and water vapor from the stratosphere.The Dome C LiDAR observatory is one of the few Antarctic stations accredited as a main station of the NDACC (Network for the Detection of Atmospheric Composition Change). The LiDAR can be remotely controlled and operates several times per day during the austral winter. Recently, a tropospheric channel has been added for the observation of cirrus clouds.

In polarization lidar field experiments, the particles depolarization ratio (PDR) is key for accurate retrievals of particles backscattering vertical profiles specific to nonspherical particles, such as mineral dust. Precise values of the intrinsic depolarization of mineral dust are however difficult to obtain, due to the complexity of mineral dust in size, shape, and complex refractive index, which prevents from analytical solutions to the Maxwell’s equations. In this contribution, a new approach is proposed, based on a laboratory experiment, to provide accurate evaluations of the lidar PDR of mineral dust and soot particles in laboratory (Miffre et al., J Quant Spectrosc Radiat Transf 169:79–90, 2016). This laboratory aerosol Pi-polarimeter takes benefit from the scattering matrix formalism to provide accurate evaluations of the lidar PDR in laboratory in the exact lidar backscattering direction of 180.0°, which is a world first (Miffre et al., J Quant Spectrosc Radiat Transf 169:79–90, 2016). After detailing the principle of the Pi-polarimeter, case studies are considered to reveal the intrinsic PDR of several mineral dust samples differing in size and mineralogy, allowing for the first time to our knowledge, to experimentally investigate the dependence of the lidar PDR with size and complex refractive index. The case study of soot particles (lidar PDR in the 10% range) is also studied (Paulien et al., J Quant Spectrosc Radiat Transf 260:107451, 2021), together with that of core-shell organic sulfates (Dubois et al., Phys Chem Chem Phys 23:5927–5935, 2021). We believe these laboratory findings, which provide accurate evaluations of lidar PDR at 180.0° lidar angle, may be used by the lidar community to interpret the complexity and the wealth of polarization lidar signals, which are every day worldwide acquired.

On 14 August 2021, the Lidar Raman MUSA and the CIMEL CE-318 sun photometer (operating at CIAO atmospheric observatory of CNR-IMAA in Potenza, Italy) observed an extremely fresh smoke plume. The forest fire started at 16:00 UTC, and the biomass burning plume, occurred at 1 km from CIAO, was transported over the CNR IMAA. The Lidar measurements have been carried out from 22:27 to 02:16 UTC. In the time interval from 22:27 to 23:19 UTC; measurements reveal a biomass burning layer below 2.7 km. The particle depolarization at 532 nm is 0.025, and Lidar ratios at 355 and 532 nm are, respectively, 40 and 38 sr. For all wavelengths, the mean value of Ångström exponent is 1.5. The value of surface concentration is 410 μm2cm−3, the volume concentration is 21 μm3 cm−3, and the number density is 2300 cm−3. The size distribution is bi-modal with a peak at 0.13 μm in the accumulation mode. The effective radius has a mean value of about 0.15 μm. Single-scattering albedo is approximately 0.96 at all wavelengths. Finally, the real part of the refractive index is 1.58, and the imaginary one is 0.006, indicating low absorption probably due to a negligible presence of black carbon. The measurements of the CIMEL 318 sun photometer at 05:34 UTC confirm the analysis of MUSA despite the lower concentration of the smoke plume at that time. The values of single scattering albedo at 440 nm are around 0.95, very similar to those observed with lidar.

RAMSES (Raman lidar for atmospheric moisture sensing) is the operational spectrometric fluorescence and water Raman lidar of the German Meteorological Service at its Lindenberg site, Germany. With its three spectrometers covering the ultraviolet-A and visible wavelength range, it is optimally equipped to study the inelastic properties of aerosols. During its routine operation in 2020 and 2021, RAMSES collected a vast data set of atmospheric aerosol measurements covering distinct events such as wildfires, volcanic eruptions, Saharan dust outbreaks, and domestic biomass burning. In this contribution, results are presented for aerosols advected from Canadian and Russian wildfires. The associated fluorescence spectra exhibit a pronounced maximum in the visible light range and high fluorescence capacity. The center wavelength of the fluorescence maximum may shift, depending on a number of factors of which source region, atmospheric residence time, and trajectory history seem to be the most important. Correlation between aerosol elastic and inelastic optical properties can be high but is strongly case-dependent. To exploit the full information content of aerosol fluorescence, spectral measurements prove to be paramount, measurements with a discrete receiver channel are insufficient.

Local transport of radioactive dust can put the environment and nearby people at risk. A plan to continuously monitor radioactive dust using synchronized measurements from horizontally pointing lidar and other instruments (e.g., weather monitor, dust sampler, particle counters) in uninhabited areas in Fukushima, Japan, is being considered. Data from continuous observations near a radioactive area can elucidate the effects of weather on the optical properties of aerosols. They can also provide information on how radioactive dust is transported when used in transport models. A pre-deployment continuous observations using a horizontal lidar and weather sensors were made on August and 21 December 2021. Results show that extinction coefficients are relatively higher (~4 × 10−3 m−1) in August compared to the values observed in December (~2.5 × 10−3 m−1). Diurnal effects on aerosol optical properties are highly observed in the depolarization ratio values. High depolarization ratios are observed during the daytime. A higher depolarization ratio (~0.12) is also measured in winter, and this can be attributed to changes in aerosol type due to changes in wind direction.

The work proposes the original algorithm of the Monte Carlo method for simulating the propagation of laser pulses in the atmosphere taking into account high order scattering. The results of studying the features of pulse transfer and the formation of echo signals during remote sensing of a cloudy atmosphere are discussed. As clouds, cirrus cloudiness represented by a continuous homogeneous layer is considered. The capabilities of the original software developed for modeling lidar echo signals are briefly described.

We describe a mobile vehicle lidar that enables near-range observations to achieve continuous monitoring of atmospheric aerosols with high spatiotemporal resolutions. The lidar employed a short-pulse laser of 355-nm wavelength. After passing the beam expander, the outgoing laser energy satisfied the eye-safety requirements, and the laser suspended the emission when detecting an overpass structure in the vehicle’s travel direction. The near-range observation was implemented by slanting a part of the receiving optical axis by placing several wedge prisms in front of the receiver telescope. Normally, lidar observations were made in the vertical direction while driving the vehicle at speeds slower than 50 km/h. Two additional mirrors installed above the car’s sunroof changed the directions of the laser beam and telescope field-of-view to achieve horizontal observation, if necessary. We demonstrated the capability of the proposed lidar system in detecting near-surface aerosol along a travel path of 25 km in the Tokyo Bay area, with an altitude range coverage between 7 and 650 m. Higher boundary layer heights with more significant aerosol loading were found in inland areas than over the coastal streets. Also, we observed aerosols over a rice paddy field of 600 m × 600 m by employing the horizontal observation mode.

Several large-scale networks using automated ceilometers and LiDARs now exist. Some networks, such as MPLNET, have developed algorithms that can be applied uniformly across all instruments. However, cross-network tools are not so readily available such as those used for cloud base height comparison. The London (CDN) node of the CANadian Micro-pulse LiDAR Network (MPLCAN) hosts both a miniHD MPL (MPLNET) and Lufft 15k ceilometer (European E-PROFILE network). Each has its own algorithm to estimate cloud base height. The MPL algorithm was developed by the NASA Langley MPLNET team, and the ceilometer has the manufacturers provided Sky Condition Algorithm. The cloud base should be in principle the same for these co-located instruments. Using the MPLNET vs. Lufft measurements for the first year of operation, the monthly correlation coefficient, R, varies between 0.45 and 0.97. This difference between instruments is mostly accounted for by a poor comparison below 1 km due to aerosols, precipitation, and overlap uncertainties. Applying a gradient-based algorithm (GBD) onto the measurements improves the worst comparison to greater than R = 0.9 $$R = 0.9$$ . However, this GBD algorithm has low accuracy with decreased signal to noise. Thus, we can utilize this tool to help verify the overall agreement of measurements between these 2 instruments, and it offers a tool for standard processes of the 2 instruments.

We have installed a scanning two-channel (532 nm) polarization lidar at the southwest coast of the hypersaline Urmia Lake since September 2018. Our measurements show dust layers are frequently transported to the region from sources like; Sahara, Mesopotamia, and Arabian Peninsula. Particles that are appearing at altitudes less than 2 km, have PDR < 25%, and mostly have local origins. From June to October, these lower altitudes atmospheric aerosols mostly are rising either from the dried lake bed or its coastal area. During cold months, atmospheric thermal inversion considerably increases the concentration of anthropogenic particles at altitudes less than 1 km AGL. Such particles possess PDR < 10%. We haven’t been able to detect dust or salt-dust particles that are originated from the lake bed and transported to altitudes above 3 km AGL.

In this work, we present case studies from PSC cases observed over the European Arctic in the winter 2021/22 which consisted of spherical particles. Due to the possibility to apply clear sky conditions above and below the PSCs, it was possible to estimate the lidar ratio (LR355 = 20–25sr; LR532 = 55–60sr) for two PSC cases. Also, the uncertainties of the retrieved backscatter and extinction coefficients were estimated. Using these optical coefficients as an input for the inversion of microphysical properties, we derived mono-modal volume distributions with an effective radius around 0.35 μm and a refractive index of about 1.54 + i * 0.02. We repeated each inversion 10 times with different error realizations from the optical input data to confirm that the inverted results are stable concerning the volume distribution function, effective radius, and refractive index. Finally, also the single scattering albedo has been calculated, which is around 0.9 at 532 nm and lower (around 0.82) in the UV.

Assessing the cirrus cloud radiative effect is crucial to establish their feedback on the Earth-atmosphere system. For this reason, cirrus clouds are of paramount importance in climate. Moreover, these tiny ice clouds are the most common cloud gene, continuously covering 30% of the Earth’s surface, peaking to 70% in the tropical and equatorial regions. The same authors, in three different recent studies, assessed the yearly cirrus cloud radiative effects characteristics for other NASA MPLNET permanent observational sites, deployed at different latitudes, e.g., Goddard Space Flight Center, Singapore, and Fairbanks Alaska. The analysis put in evidence that the cirrus cloud can be both cooling and warming agents of the Earth-atmosphere system during the daytime, depending on their latitude. The cirrus clouds are warming agents in equatorial/tropical regions because of the higher averaged solar zenith angle and become neutral at mid-latitudes. At polar latitudes, cirrus clouds become cooling agents because of the lower solar zenith angle. In this analysis instead, of using the Fu–Liou–Gu radiative transfer model, we assess how the cirrus cloud radiative effects, at the both top of the atmosphere and surface, changed over twenty years. The analysis is extended also to evaluate also changes in cloud optical depth over the same period. This is unprecedented research, because to our knowledge, no other analysis has been carried out from ground-based measurement for such a long period. As a future perspective, the analysis will be repeated for the different observational sites of the MPLNET LiDAR network to evaluate cirrus cloud radiative effects on a global scale.

The main objective of this study is to assess the lidar-derived aerosol optical depth retrievals from the upgraded lidar system by comparing them with the new well-established sun-sky-lunar photometric measurements (CIMEL 318-T), located in the Laboratory of Atmospheric Physics (LAP), at Thessaloniki, Greece. The two instruments represent two individual networks, the European Lidar Aerosol Network (EARLINET) and the Aerosol Robotic Network (AERONET) following different measurement schedules. Thessaloniki lidar system (THELISYS; Raymetrics LR321-D400), part of the EARLINET, has been recently upgraded regarding its operational wavelengths and the detection configuration. Commissioning of the upgraded system operation started in October 2021. The new sun-lunar photometer (CE-318T) is capable to perform a complete cycle of diurnal photometric measurements at both day- and nighttime. The new improvements of this new device permit this new photometer version to extend the photometric information at nighttime using the moon as a light source. Quality-assured cases in cloudy-free conditions are selected to demonstrate the synergistic performance of the two instruments. Timeseries of the AOD measured by lidar and sun/lunar photometer provide a long-term aerosol monitoring for the investigation of the amount, sources, and atmospheric processes over Thessaloniki.

A comparative analysis of long-range inflows of desert dust and its mixtures over Central Poland, in particular optical properties, were obtained from lidar surveys. The mineral dust inflows over Warsaw were identified based on lidar measurements and three independent models (HYSPLIT, BSC-DREAM8b, and NAAPS), which resulted in preparing unique database of optical properties of mineral dust and its mixtures. This has a potential to be used for further studies of aerosol microphysical properties. Aerosol properties during inflows were also analyzed in relation to meteorological parameters and local climatic data revealing an increase in the number and duration of observed episodes of mineral dust intrusions over Poland. Optical properties of mineral dust vary with the amount and type of admixtures of other aerosols.

The MicroPulse DIAL (MPD) is a diode-laser-based instrument for thermodynamic profiling in the lower troposphere. These instruments are eye-safe, low-cost, and can operate unattended, making them well-suited for network deployment. These instruments combine the differential absorption lidar and the high-spectral-resolution lidar techniques to provide range-resolved vertical profiles of atmospheric water vapor, temperature, and aerosol optical properties. As these instruments are deployed for field experiments, efforts are being made to add additional data products, such as the planetary boundary layer height (PBLH). This chapter describes a technique for using MPD-measured aerosol and water vapor profiles to locate the PBLH.

Researchers at Montana State University (MSU) and the National Center for Atmospheric Research (NCAR) are developing diode laser-based (DLB) MicroPulse DIAL (MPD) instruments for thermodynamic profiling of the lower atmosphere. Current instruments include the capability of measuring humidity, temperature, aerosol profiles, and boundary layer structure to address the needs expressed by the science community for cost-effective networkable ground-based thermodynamic profiling instruments. In this paper, the efficacy of adding the capability of vertical wind profiling using the DLB MPD architecture is discussed. A design for a dual-edge direct detection Doppler wind lidar channel is presented with a retrieval method that utilizes an ancillary measurement of the aerosol backscatter ratio. Performance modeling results indicate that an error in the retrieved wind velocity measurement of 0.56 m/s can be achieved with a 150-m range resolution and a 5-min averaging time. These results indicate that vertical wind profiling capability can successfully be added to the MPD thermodynamic profiling instruments.

Water vapor is an important parameter in understanding extreme weather events, and a Raman lidar is a useful technique to measure distribution of water vapor at high spatiotemporal resolution. We have been developing a Raman lidar with a 266-nm laser due to low solar background radiation below a wavelength of 300 nm by ozone absorption and demonstrated the results of continuous water vapor profiles throughout a year at an observatory surrounded by forest. In this study, we report the observation results of water vapor with the Raman lidar in an urban area, Tokyo, to evaluate the impact of the surface ozone.

We developed a simple 355-nm direct-detection Doppler wind lidar (DWL) for atmospheric motion study. The 355-nm direct-detection DWL uses the double-edge technique for a receiver with Fabry-Perot etalon interferometer and a wedge prism to form a double-edge filter. Preliminary experimental line-of-sight (LOS) wind measurements were made to investigate wind measurement performance of the 355-nm direct-detection DWL on July 22, 2021. Although the observational range limit depends on its telescope area and atmospheric conditions, the 355-nm direct-detection DWL for three different accumulation times (10 min, 15 min, 30 min) could make wind measurement with random error of less 1 m/s at altitudes of 1.8, 2.1, and 2.7 km, respectively. In this chapter, we describe development and preliminary experimental result of the 0.355-μm direct-detection DWL.

Aircraft wake vortices are serious threats to aviation safety and limit airport capacity greatly. The pulsed coherent Doppler lidar (PCDL) has been widely used in the observation of aircraft wake vortex due to its advantages of high spatial-temporal resolution and high precision. However, the post-processing algorithm cannot meet the needs of real-time detection of wake vortices at airports due to the long-time consumption. This chapter focuses on the development of a real-time wake vortex monitoring system which will significantly improve the detection efficiency of the wake vortex and the introduction of a quick image recognition method to identify the wake vortex based on convolutional neural network (CNN) models. In this method, a large amount of wake vortices generated by multiple aircrafts in different weather conditions are collected to build the radial velocity and spectrum width (RV-SW) data sets and to be trained using the CNN models, including the target recognition model and the image classification model. The speed and accuracy of recognition and classification could be improved significantly especially when atmospheric turbulence or other interferences exist. The results show that deep learning models can significantly improve the recognition and classification efficiency of aircraft wake vortices. This method is expected to be applied to the development of a real-time wake vortex monitoring system and further compress the existing wake vortex spacing criteria, which has broad application prospects in the field of airport aviation security assurance.

A collaborative research effort by Montana State University and the National Center for Atmospheric Research has led to the development of a MicroPulse DIAL (MPD) instruments for water vapor profiling, aerosol profiling, boundary layer structure, and temperature profiling of the lower troposphere. The MPD instruments utilize a diode-laser-based instrument architecture, have demonstrated long-term autonomous network operation, and have the potential to address the needs of the science community for networkable ground-based thermodynamic profilers that can provide data in near real time. In this chapter, the recent improvements to the temperature retrieval using the MPD instruments are discussed and initial results from the improved temperature retrieval algorithm are presented.

Raman LiDARs are an important tool for measuring the water vapor content and temperature of the troposphere. We present a technique to calibrate temperature measurements from a rotational Raman LiDAR using solar background (internal method), as opposed to requiring a radiosonde measurement (external method) for each calibration. The method is tested using measurements from the Raman LiDAR for Meteorological Observations (RALMO), located at the Swiss Meteorological Services (MeteoSwiss) facility in Payerne, Switzerland. For an accurate temperature or relative humidity trend analysis, minimizing the uncertainties of the LiDAR measurements is vital. The calibration factor used for the temperature measurements is one of the major components contributing to the uncertainty budget of the temperatures. Our goal was to first establish a temperature calibration time series based on the external method using Vaisala RS92 radiosonde measurements certified by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN). Next, we produced a temperature calibration time series based on the background method. Then, we compared and merged the two calibration data sets to produce a more accurate temperature calibration time series. Finally, we used the calibration constants obtained from the background and the external methods to compare nine RALMO temperature profiles from the end of 2011 to the end of 2014. The maximum temperature difference, mean bias, and standard deviation of temperature obtained through external vs. background methods are 0.27 K, 0.013 K, and 0.035 K, respectively. While the maximum temperature difference (1 night) was larger for the comparison set used in this study, the mean bias and standard deviation were less than the traditional method applied to RALMO.

A high-power Raman LiDAR system has been installed at the mountain research station Schneefernerhaus (UFS, Garmisch-Partenkirchen, Germany) at 2675 m a.s.l. on Mt. Zugspitze. An industrial XeCl laser (350 W, 308 nm) was modified for linearly polarized narrowband single-line operation at an average power of up to 180 W. Together with a receiving telescope with a diameter of 1.5 m, this allows for a sounding range of up to 25 km for water vapor within a measurement time of just 1 h, at an uncertainty level of the mixing ratio in the stratosphere of 1 to 4 ppm. The LiDAR was successfully validated with a balloon-borne cryogenic frost-point hygrometer. In addition, 1-h temperature profiles are retrieved to altitudes beyond 80 km that agree well with temperature profiles from radiosondes, NCEP, and satellites, as well as mesospheric OH fluorescence data. Routine temperature measurements under remote control have been started.

Precipitation plays an important role in meteorology, hydrology, and the coupling of water, energy, and biogeochemical cycles in the Earth system. Lidar can be utilized as a valuable remote sensing instrument to detect rain because of its high temporal and spatial resolutions. This paper introduces the observation of rainfall velocity and raindrop size by analyzing the power spectrum of coherent Doppler lidar taking vertical staring mode. The rain measurement campaign was conducted at the Laoshan campus of Ocean University of China. A ground-based coherent Doppler lidar and a Parsivel2 disdrometer deployed on the top of the building with a height of 12 m are used for comparative measurements. The rain and wind power spectrum can be identified simultaneously by using a two-component Gaussian model. The spectrum width of lidar during the rain events is wider than that on a clear day. Unlike the disdrometer, the lidar provides the rainfall velocity profiles at different heights. This chapter also investigates the raindrop size distribution from the lidar spectrum. Furthermore, the comparison of rainfall velocity distribution between lidar and disdrometer is presented in this chapter as well.

To evaluate the performance of water vapor lidars for measuring the vertical distribution in the lower troposphere and its potential utility for numerical weather prediction, the vertical distributions of water vapor mixing ratio (w) were measured with a Raman lidar developed by the Meteorological Research Institute (MRI-RL) and a differential absorption lidar that is being developed by Vaisala (Vaisala-DIAL) at Tsukuba, Japan, during the summer of 2020. The measured values were compared with those obtained with collocated radiosondes. The MRI-RL-derived w values mostly agreed within 1 g/kg with those obtained with the radiosonde between altitudes of 0.2 and 3 km and were 0.2–0.5 g/kg higher than them at 0.1 km. The Vaisala-DIAL-derived w values were 0.6–0.7 g/kg lower than those obtained with the radiosonde below 0.5 km and 1–2 g/kg higher than them above 1 km.We assimilated the lidar-derived w in the initial condition of the mesoscale model (MSM) developed by the Japan Meteorological Agency using a four-dimensional variational (4D-Var) method to study the impact of the lidar data on the water vapor field predicted by the model. The results of the assimilation showed that w values predicted by MSM got closer to the radiosonde-derived values by assimilating MRI-RL and Vaisala-DIAL data. The correction by assimilating MRI-RL data was slightly better than the Vaisala-DIAL data. Our results showed that (1) assimilating the lidar water vapor data in the model can improve the predicted water vapor field and (2) the data with smaller bias and RMSD have a better impact on the prediction of water vapor field.

Based on the long-term observations of Hainan lidar (19.9°N, 110.3°E) during 2010–2020, temperature variation characteristics in the middle atmosphere (32–64 km) are investigated by analyzing the Rayleigh backscattering data. The stratopause over Haikou was in the altitude range of 42–51 km, with a maximum temperature of ~262 K. After an annual plus semiannual and seasonal fit was applied to lidar observation results, it is found that temperature variation in the stratosphere exhibited a prominent annual oscillation tendency while temperature variations in the stratopause and the lower mesosphere were dominated by annual and semiannual oscillations. Interannual variation of stratopause temperature is compared to the change of solar activity, and it is revealed that stratopause temperature had a good response to the index change of solar radiation while the solar radiation flux F10.7 varied significantly. However, when the solar activity became calm, there was no correlation in the variation tendency between them. These observation results could be significant to the comprehensive understanding of global climate change.

Model parametrisations in the convective boundary layer are still at work especially in the interfacial layers with the surface and the free troposphere. This chapter reports simultaneous turbulence-scale lidar observations of wind speed, temperature, and specific humidity in the convective boundary layer in temperate and semiarid regions. The collected data are used to assess new parametrisations in particular in the entrainment layer.

Shipboard ceilometer observation was conducted during May 2021 on R/V Shinsei-maru in the southwest region of the middle of Japan to study the effects of the large meandering warm Kuroshio current on the atmosphere. Here we focus on the observations across the Kuroshio from the offshore to a colder sea inshore under clear sky condition. The atmospheric boundary (ABL) heights determined by the BL-View software coincide well with those obtained by the radiosonde observation. The height of the ABL over the Kuroshio varied at 500–800 m. At the transitional region between the Kuroshio and the cold sea inshore, spontaneous lifts of the ABL by 400 m were observed, which might be caused by the passage of the front of anticyclone over the Honshu island, Japan. Over the cold sea, a shallower ABL appeared, while the upper ABL was continuously observed at the same level as over the Kuroshio. The upper ABL is considered as the residual layer from the Kuroshio region. The lower ABL developed up to 300 m in the afternoon. Thus, highly temporal variation of the structure of the ABL was observed by the ceilometer associated with the BL-View analyses.

This work stems from the idea of improving the study and characterization of ABL at high resolution and in unstable weather conditions, characterized by strong turbulence and precipitation. A new approach based on the rotational temperature signals of a lidar system (BASIL) is used for the characterization of the ABL in the lower troposphere. The elastic signals at wavelength 532 nm and pure rotational Raman signals (strongly dependent on temperature variation) at 355 nm are considered. In particular, the case study considered to evaluate the ABL refers to observations made during HyMex campaign from 16th to 21th day of October 2012. The ABL heights retrieved by the new approach have been compared against the corresponding ones obtained by using other innovative methods such as a recently published algorithm based on morphological image processing techniques named MIPA as well as the ones retrieved by using more traditional methods based on gradients on temperature or water vapor profiles. For each methodology, a statistical analysis of the corresponding data is carried out.

We describe an algorithm that can be applied to horizontally scanning atmospheric aerosol LiDAR data to determine canopy wave orientation and wavelength objectively. We applied it to over 1500 images of canopy waves from 53 episodes collected during the Canopy Horizontal Array Turbulence Study (CHATS) that took place in Dixon, California, in 2007. By doing so, we created time series of wavelength and wave crest orientation. Results from episode 25 from April 30 are presented.

We have investigated the evolution or growth of planetary boundary layer (PBL) height for the first time over a mountain topography at a Western Himalayan station Palampur (32.11° N, 76.54° E, 1347 m altitude amsl). For this, we have used ground-based Raman lidar measurements from June 2016 to May 2019 to determine the monthly and seasonal variations in PBL height using wavelet covariance transform (WCT) method. Results reveal that the PBL height was observed lower in the colder months of December and January with lowest in January having an average value of 524 ± 83 m and higher PBL heights were observed in the May and June. The seasonal PBL height was calculated as 631 ± 208 for winter (December, January, February, March), 1308 ± 595 for summer (April, May, June), 1413 ± 460 for monsoon (July, August, September), and 904 ± 190 for post monsoon (October, November). Although the highest monthly and seasonal PBL height was observed in the month of July and post monsoon season respectively, that can be due to the lesser number of observation days because of rain. The obtained PBL variations have also been studied with the meteorological conditions which includes ambient temperature, relative humidity (RH), wind velocity, and atmospheric pressure, and the results show that the PBL height was showing a strong positive correlation with correlation coefficient as 0.89 with average temperature and a strong negative correlation with atmospheric pressure (r = −0.92). However, the results suggested a weak positive (r = 0.34) and a weak negative correlation (r = −0.18) with relative humidity and wind speed, respectively.

The Fire Influence on Regional-to-Global-Environments Experiment – Air Quality (FIREX-AQ) – offered an opportunity to interrogate the dynamics of wildfire plumes with an airborne Doppler lidar system. A technique was developed to target updrafts embedded in wildfire plumes in order to analyze the complex interaction that developing updrafts have with the neighboring environment. The general characteristics of updrafts are described from the current sample size, and the fine structure details related to impacts of counter-rotating vortex (CRV) structures on developing updrafts are examined. The development of these techniques comes in a timely manner since the California Fire Dynamics Experiment (CalFiDE) is planned to target wildfires during late summer 2022. It is the goal of this study to improve upon scanning strategies to better target wildfire plumes in order to understand the governing dynamics that dictate their evolution.

Mixing layer height (MLH) and land-sea breeze in the coastal area play an important role in ozone (O3) dispersion and transport. This study presents the multiple-platform observations of MLH dynamics for a high O3 event during Long Island Sound Tropospheric Ozone Study (LISTOS) in summer 2018. The diurnal evolution and spatial variability of MLH are observed from ground-based aerosol Lidar, Vaisala Ceilometer, Coherent Doppler Wind Lidar, and airborne lidar in New York City (NYC) urban and the coastal area in Long Island on August 28–29, 2018. The results indicate that the MLH growth in the morning shows a time lag of 1–2 h in the coastal area versus that in the NYC urban area. The spatial gradient variation of MLH from the urban to the coastal area is demonstrated from the NASA High Altitude Lidar Observatory (HALO) airborne high spectral resolution lidar (HSRL) observations by showing lower values in the coastal and marine area. Meanwhile, the ground O3 are consistently much higher at noon in the coastal sites than those in the NYC urban sites reaching the maximum value of 100–120 ppb in exceedance of the O3 NAAQS, which is closely relevant to the urban pollutant transport, MLH dynamics, and sea breeze. The observation data are further used to assess the model product of PBLH and O3 at the NYC urban and coastal sites.

The spatial distribution and temporal variations of aerosols within the planetary boundary layer is of special interest for the city of Stuttgart, which is located in a basin. To characterize the evolution of boundary layer structure and its relation to surface-level aerosol concentrations, we collected comprehensive datasets from February 5 to March 5, 2018 in the urban background of downtown Stuttgart. The boundary layer height was determined from lidar and radiosonde measurements. Furthermore, aerosol particle number, size, chemical composition, and various trace gases were measured at 3.7 m above the ground level, by employing a mobile container equipped with various instruments including an aerosol mass spectrometer. The main novelty of our study is that our scanning lidar conducted zenith scanning measurements from 90 ∘ $${ }^\circ $$ to 5 ∘ $${ }^\circ $$ . These measurements allow us to investigate the evolution of details of the boundary layer structure and aerosol spatial distributions and furthermore to retrieve optical parameters of the aerosol near the ground level that can be compared with the in situ measurements. The boundary layer heights retrieved from lidar data show a good agreement with radiosonde data and ECMWF Reanalysis v5 (ERA5) data from different meteorological situations. As expected, the ground-level aerosol concentrations showed a negative correlation with boundary layer height. In addition, meteorological conditions like wind speed, temperature, solar radiation, and relative humidity affect not only the structure of the boundary layer but also the relationship between boundary layer heights and surface aerosol concentrations.

NASA Langley Research Center (LaRC) fielded its second-generation multiwavelength high spectral resolution lidar (HSRL-2), which also includes wavelengths to enable ozone differential absorption lidar (DIAL) measurements, aboard the NASA Gulfstream-V (G-V) aircraft during September 2021. Flying at 9 km, the lidar provided nadir profiles of ozone and aerosol backscatter, extinction, and depolarization over the Houston metropolitan region, including Galveston Bay and the Houston Ship Channel. These observations were part of a larger air quality assessment of the region, TRACER-AQ (Tracking Aerosol Convection ExpeRiment – Air Quality), which is NASA mission conducted in collaboration with an effort led by the DOE (Department of Energy) and TRACER (Tracking Aerosol Convection Interactions ExpeRiment). Additional participants including from academia and TCEQ (Texas Commission on Environmental Quality) provided meteorological and atmospheric constituent measurements from ground sites, mobile laboratories, and from boats. Here we present a description of HSRL-2 measurement capabilities and examples of tropospheric ozone and aerosol measurements collected during TRACER-AQ. The flight tracks were overlapping raster patterns repeated three times throughout the day to measure the temporal and spatial variability in ozone and aerosols over the region. These measurements will help understand and evaluate space-based air quality observations from future satellite passive UV-VIS sensors such as the NASA TEMPO satellite.

CO2 is the primary greenhouse gas emitted through human activities. For the detailed analysis of forest carbon dynamics and CO2 fluxes in urban areas, vertical CO2 concentration profiles with high spatial and temporal resolution in the lower atmosphere have been conducted by a differential absorption lidar (DIAL). We have developed the range-resolved DIAL with the 1.6 μm wavelength for measurements of the vertical CO2 concentration profiles. Several vertical profiles of CO2 concentrations for nighttime and daytime from 0.45 to 2.5 km altitude with range resolution of 300 m and an integration time of 1 h have been measured. In order to estimate the extraction of information on the origin of the CO2 masses, one-day back trajectories were calculated by using a three-dimensional (3D) atmospheric transport model.

The conversion efficiency and flexibility of using single Raman cell with a mixture of high-pressure Raman active gases H 2 $${ }_{2}$$ and CH 4 $${ }_{4}$$ have been tested and reported in this chapter. Though the higher conversion efficiency could be achieved with independent gases, the pre-mixed gas combination could emit a coaxial beam of two wavelengths 288.4 nm and 299.1 nm with a total conversion efficiency of about 45% along with the residual 266 nm coaxial beam. However, a suitable gas mixing ratio needs to be selected to avoid carbon particle formation inside the cell which attenuates the laser energy. In the present case, a volume mixing ratio of 2:1 (H 2 $${ }_{2}$$ +CH 4 $${ }_{4}$$ ) at a total cell pressure of 18 bar is found optimum for the generation of required wavelengths with almost equal energies. This configuration of generating coaxial beam of multiple SRSs with a single Raman cell greatly reduces the optical configuration and makes the DIAL system compact for mobile operations for ozone profiling.

The research project CONCERNING was funded by the Italian Ministry of University and Scientific Research as part of the “Special Integrative Research Fund (FISR) 2019” Call. The project is aimed at the design and experimental development of an innovative Raman lidar system for measuring the vertical profiles of the two main greenhouse gases present in the atmosphere, that is CO2 and water vapor, as well as temperature and multi-wavelength particle backscatter, extinction, fluorescence, and depolarization profiles. The capability to measure this suite of atmospheric compositional and thermodynamic properties represents an important observational potential for improving our understanding of feedback and coupling mechanisms of these two species with the biogeochemical cycles in the Earth system.The low-weight compact ground-based system illustrated in this paper has been sized to accurately measure the abovementioned parameters with high time and space resolution to allow for the resolution of convection scales and turbulent processes. Such a system, exploiting both the rotational and vibrational Raman lidar techniques in the UV through cutting-edge technologies for spectral selection, optical signal detection, and data acquisition, is hosted in sealed and rugged container, equipped with fused-silica windows, and capable to operate in all weather conditions. The development of the prototype and the verification of its measurement capabilities, possibly assisted by specific measurement campaigns, will allow to demonstrate the enormous potential impact of a network of such systems.

A CIMEL CE376 GPN micro-LiDAR was installed at the facilities of the Izaña Atmospheric Research Center (2368 m a.s.l., Tenerife, Canary Islands) in August 2021, and it operates in continuous mode since then. During this period, the pristine dust-free clean conditions that characterize this mountain-top site have been mainly disrupted by two-type aerosol events: the Saharan dust outbreaks that pass over the site on their way toward the Atlantic and the eruption of Cumbre Vieja Volcano (La Palma, Canary Islands) last fall (September 19, 2021). We show two study cases that provide a brief overview of aerosol properties under Saharan dust conditions and volcanic emissions using volume depolarization ratio (VDR), particle linear depolarization ratio (PLDR) at 532 nm, and lidar extinction coefficient products from the CE376 at 532 and 808 nm, as well as aerosol optical depth from AERONET photometers. We also performed a 20-day intercomparison between the CE376 and MPL-4B LiDAR from the NASA Micro-Pulse Lidar Network (MPLNET). The retrieved aerosol products show the good performance of the CE376 micro-LiDAR as a tool for the characterization of the vertical distribution of atmospheric aerosols.

Ozone (O 3 $${ }_3$$ ) pollution episodes often occur on hot days in summer in the New York City (NYC) metropolitan area and its downwind coastal area due to large amounts of urban emissions, chemical productions, and meteorological and regional transport effects. To understand the formation process of high ozone, it is important to observe the ozone vertical distribution and its evolution. In this chapter, we reported an Ozone Differential Absorption Lidar (DIAL) developed at the City College New York (CCNY) and present the initial observations. The results show that the CCNY O 3 $${ }_3$$ -DIAL is able to retrieve O 3 $${ }_3$$ concentration from 0.2 to 8.5 km altitude with 10-minute time resolution, depending on operation conditions. The O 3 $${ }_3$$ retrievals from the near-range and far-range channels have good consistency at 0.9–1.8 km altitude. In addition, under favorable weather conditions, the O 3 $${ }_3$$ retrievals at near-surface show a consistent temporal variation with the co-located in situ O 3 $${ }_3$$ measurements. Our observation cases indicated the elevated O 3 $${ }_3$$ concentration above the planetary boundary layer (PBL) which might be associated with the regional pollution transport such as the wildfire smoke plumes. The CCNY-Ozone DIAL will be installed in a trailer in the near future which allows mobile observation for the field campaign.

In this study, we present a methodology for the calculation of the retardation and rotation errors introduced from a nonideal quarter-wave plate (QWP). We performed laboratory measurements in a lidar ellipsometer (LEM) in Raymetrics S.A., Athens, and also on-field with the EVE (Enhancement and Validation of ESA products) lidar in order to test a high-energy Crystalline Quartz zero-order QWP at 355 nm from Altechna. We found an absolute retardation error of about 4.8° ± 0.6° and 4.9° ± 0.4° when we performed the test directly on EVE and using its two lasers A and B, respectively. It was possible to repeat the same test directly in the laboratory with an ellipsometer using a QWP produced in the same batch as the one installed in EVE. We measured a similar absolute retardation error of 4.7° ± 1.1°. Nonideal retardation in the QWP directly affects the calibration factor and the volume and particle circular depolarization profiles of EVE. Quantifying it is also important because if it is known, it can be corrected with the GHK method.

A persistent stratospheric layer first appeared during July 2019 above Thessaloniki, Greece (40.5°N, 22.9°E), initially at 12 km and during August 2019 even up to 20 km, with increased thickness and reduced attenuated backscatter levels. In this study, we analyze the geometrical and optical properties of this stratospheric layer, using both the ground-based multi-wavelength depolarization measurements performed with Thessaloniki’s lidar system (THELISYS), which is part of the European Aerosol Research Lidar NETwork (EARLINET) and the spaceborne lidar CALIOP retrievals (Cloud–Aerosol Lidar with Orthogonal Polarization), onboard CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation). The origin of the plume is linked with the two major sources of stratospheric air pollution that were active in the summer of 2019, the Raikoke volcano eruption in the Kuril Islands and the intense forest fires at mid and high northern latitudes. Thus, in July, pure volcanic sulfate aerosol layers (particle linear depolarization ratio < 0.05) are mainly identified in the stratosphere, while in August, wildfire smoke is dominating. Temporal changes in the aerosol properties throughout the 2019 measuring period that signify changes in the composition of the long-lasting stratospheric plume over Thessaloniki are identified and discussed.

Lidar observations offer a valuable window into gravity waves due to their high temporal and spatial resolutions. However, second-order parameters of these waves calculated via lidar have an inherent bias. Over the years, a few methods have been developed to correct this. This study tests noise-variance subtraction, spectral proportion, and the interleaved method and compares their results using data and a forward model. Variance subtraction is found to only work on high SNR data, spectral proportion works with high- to mid-SNR data, and interleaved works on all data but requires more data to reliably use.

Temperature and wind measurements in the mesosphere and lower thermosphere (MLT) can be obtained from resonance fluorescence LIDARs utilizing the principles of Doppler effects or Boltzmann distributions. The calculations for determining temperature and wind speed from photon counts are more sensitive to noise than simply determining density, so a more limited range is available for observations. The traditional approach for extending the observation range is to increase the bin size used for the calculations, by integrating over a larger altitude range, time range, or both. However, a larger bin size will limit the resolutions and small details will be missed. The layered binning technique is a data analysis method that extends the range of observation while keeping much of the fine detail. This technique is able to increase the range of observations by dynamically adjusting the binning in areas of low signal or high noise. Examples of using this technique have been able to extend the range of temperature and wind speed measurements by nearly 45%.

Interaction between the sea surface and the lower atmosphere is important. Especially in the shore, such interaction becomes more fruitful but complex because the sea wave dynamics and wind will mix in the interaction. It is worthwhile to monitor such interaction for geophysics, marine science, and technologies for revetment and boat maneuver. In this study, we focused on the above interaction monitoring and its visualization. The LED-based mini-lidar is developed to visualize the interaction. To follow the high temporal and spatial dynamics in the shore, the LED lidar system has the high resolutions’ performance of 0.2 s summation time and 0.15 m spatial intervals. We have been continued the field experiments in an inland sea (Tokyo bay) and oceans (Pacific ocean). The wave motions are confessedly different linking to the sea floor orientation, tide current, and weather. The LED lidar system set to the near horizontal direction at shallow angle. The interactions between the sea wave and the wind have been captured under the several weather conditions and observation locations. By the synchronized measurement with weather sensor, the sea wave dynamics are discussed with the wind profile.

During the last decade, new applications exploiting data from satellite-borne lidar measurements demonstrated that these sensors can give valuable information about ocean optical properties. Within this framework, COLOR (CDOM-proxy retrieval from aeOLus ObseRvations) is an ongoing (KO: 10/3/2021) 18-month feasibility study approved by ESA within the Aeolus+ Innovation program. COLOR objective is to evaluate and document the feasibility of deriving an in-water AEOLUS prototype product from the analysis of the ocean subsurface backscattered component of the 355 nm signal. In particular, COLOR project focuses on the AEOLUS potential retrieval of (1) diffuse attenuation coefficient for downwelling irradiance (Kd [m−1]) and (2) subsurface hemispheric particulate backscatter coefficient (bbp [m−1]).The core activity of the project is the characterization of the signal from the AEOLUS ground bin. In principle, the ground bin backscattered radiation signal is generated by the interaction of the emitted laser pulse radiation with two media (atmosphere and ocean) and their interface. To characterize this ground bin, two parallel and strongly interacting activities were developed: (a) radiative transfer numerical modelling and (b) AEOLUS data analysis.The preliminary results about the abovementioned activities will be here presented.

Air-sea coupling and energy circulation inside the ocean are the frontiers of ocean science and important directions of Earth’s system science. Researchers have carried out extensive research on multi-scale dynamic characteristics and ecological environment parameter based on the development of advanced remote sensing technology. However, the lack of the noninvasive in situ detection technology for the high-resolution measurement of the marine micro-scale characteristics, biological, physical, and chemical restricted the study of the microscale phenomenon and biological optics inside the ocean. The development of in situ detection techniques for microscale turbulence and particle size distribution in the ocean mixing layer would improve the understanding of the energy and matter transport inside the ocean. This article focuses on the great demand for the high-resolution in situ detection technology during the study of micro-scale turbulent flow structure and the size distribution measurement of micro-scale suspended particles. A laser Doppler current probe (LDCP) has been designed for the measurement of distributed two-component velocity with high spatial resolution. The sensor is an extension of the principle of laser Doppler anemometry (LDA). It is nonintrusive, highly accurate, and able to highly resolve the flow both in the time and spatial extensions. The LDCP has been proved to be effective tools to capture the micro-scale oceanic turbulence by carrying out field campaign at Yellow Sea. Algorithm to calculate the distribution of the suspended particles with small scale (1–10 μm) has developed, and it has been validated by the laboratory campaign.

Since mid-2016, the frequency of low energy laser pulses emitted by the CALIPSO lidar has been slowly increasing due to pressure losses in the canister housing the laser. While originally confined primarily to the South Atlantic Anomaly (SAA) region, these low energy pulses now occur intermittently around the globe. Low energy pulses can cause calibration biases and degrade the science quality of level 2 retrievals. We describe a new low energy mitigation (LEM) algorithm that will be implemented incrementally in future versions of the CALIOP data processing to identify and reject affected profiles during calibration and feature detection. The LEM algorithm effectively eliminates low energy calibration biases, improves level 2 retrievals, and minimizes level 2 data loss.

CALIGOLA, while having a primary focus on atmospheric monitoring, presents also a strong potential in the characterization and study of the ocean-Earth-atmosphere system and the mutual interactions within it. Exploiting the three Nd: YAG laser emissions at 354.7, 532, and 1064 nm and the elastic (Rayleigh-Mie), depolarized, and Raman lidar echoes from atmospheric constituents, CALIGOLA will carry out 3λ profile measurements of the particle backscatter coefficient and depolarization ratio and 2λ profile measurements of the particle extinction coefficient from aerosols and clouds. These measurements will be used for the purpose of aerosol typing and for determining particle size and microphysical properties (Di Girolamo et al., Atmos Environ, 50: 66–78, 2012; J Geophys Res Atmos, 127:e2021JD036086, 2022). Furthermore, measurements of the elastic and depolarized backscattered echoes from the sea surface and the underlying layers will be exploited to characterize optical properties of the marine surface (ocean color) and of the suspended particulate matter. Two specific measurement channels at 460 and 680 nm will be used to measure fluorescent scattering from marine chlorophyll and atmospheric aerosols for the characterization of the ocean primary production and for the purpose of aerosol typing, respectively. CALIGOLA will also allow accurate measurements of the small-scale variability of the Earth’s surface elevation, primarily associated with variations in the terrain, vegetation, and forest canopy height. The space mission CALIGOLA is explicitly included in the ongoing ASI Three-Year Activity Plan (2021–2023), with a scheduled tentative launch window of 2026–2028.

NASA has established the Earth System Observatory (ESO) to fulfill the science needs presented in the 2017 Earth Science Decadal Survey, and the Atmosphere Observing System (AOS) is a key component of ESO. The AOS mission will make measurements of aerosols, clouds, convection, and precipitation, which represents two of the designated observables in the decadal survey, to advance our understanding of the processes that drive cloud and precipitation properties (for low, high, convective, and frozen/mixed-phase clouds), convective vertical motion, air quality, aerosol redistribution, radiative transfer, and the relationships between these processes. AOS employs a two-orbit architecture (a polar orbit and an inclined orbit), thereby allowing AOS to cover a wide range of temporal and spatial scales and transforming our understanding of this critical part of the Earth’s system. The inclined-orbit sensor suite (AOS-I, 55-degree inclination, 407 km altitude, notional launch in July 2028) includes a backscatter lidar called the Atmospheric Lidar Instrument for Clouds and Aerosol Transport (ALICAT), a Ku-band Doppler radar, and two microwave radiometers that provide short-time-differenced measurements. The goal of AOS-I is to determine the varying-time-of-day processes that control aerosol-convection-precipitation interactions, as well as the diurnal variability of convection, precipitation, high clouds, aerosol emissions, and air quality. This extended abstract provides (1) an overview of the AOS-I mission, (2) a description of the AOS-I science objectives, and (3) a preview of the critical role ALICAT plays in AOS-I science, applications, and synergy.

Measurements of water vapor profiles are very important in the studies of atmospheric dynamics, clouds, aerosols, and radiation. Water vapor is the predominant greenhouse gas, and its vertical distributions are especially important in the global climate system. Water vapor data would lead to benefits in numerical weather predictions for localized heavy rainfall events and typhoon forecasting. We have proposed two-beam space-borne water vapor DIAL with the OPG/OPA transmitter using the absorption line of the 1300 nm band. An error simulation is performed assuming that the platform altitude is 250 km, the receiver diameter is 0.8 m, the laser energy is 20 mJ, and the repetition rate of the laser shot pair (on-off) is 500 Hz. It is shown that water vapor profile measurement relative error of less than 10% is possible between 0 and 2 km altitudes with spatial resolutions of 300 m vertically and 20 km horizontally in East Asia in summer.

For the AOS (Atmosphere Observing System) mission, we analyze the contribution of the future 532 nm-HSR (high spectral resolution) spaceborne Lidar measurements implementing an Observing System Simulation Experiment (OSSE) based on the MOCAGE (Modèle de Chimie Atmosphérique de Grande Echelle) (Sič, Amélioration de la représentation des aérosols dans un modèle de chimie-transport: Modélisation et assimilation de données, 2014) Chemistry Transport Model (CTM). This first case study focuses on a Saharan dust event on March 2018 reaching Greece. Nature Run is extracted along the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) trajectory for a two-week period. Two simulations are computed, one with a standard “Klett” inversion (CALIOP-like) and an AOS lidar with HSR at 532 nm. The first results showed a better performance of the assimilation of AOS particulate backscatter products, both during intense and weak episodes. This ability to constrain extends over the entire domain in model space and allows improvements of a factor of ~1.5 and ~1.6 in terms of bias and RMSE compared to the assimilation of a CALIOP-like product on the description of desert dust AOD (AOD_DD) or vertical profiles.

Solar eclipses represent the unique event to study the atmospheric response to the large scale and sharply variation of the incoming solar radiation. Because of the event’s infrequency, only few studies have been conducted using Raman lidar to characterize this phenomenon (Kolev, Int J Remote Sens 26(16): 3567–3584, 2005). According to astronomical data, the eclipse in India started at about 8:00 IST and ended at 11:30 IST reaching the maximum eclipse coverage (44.7%) at about 9:30 IST. The aim of this paper is to document its effect in the troposphere through Raman lidar located at Palampur (India). This study reports the analysis of Raman lidar measurements taken during the December 26, 2019, annular solar eclipse. Raman lidar measurement at 355 nm has been performed at Palampur (latitude 32.1109° N and longitude 76.5363° E) in Western Himalayas, to investigate for the first time the impact of the annular solar eclipse on both the planetary boundary layer (PBL) height and the aerosol optical properties in entire aerosol column.

The NASA Langley Research Center (LaRC) has designed the Clio High Spectral Resolution Lidar (HSRL) instrument concept for NASA’s Atmosphere Observing System (AOS). The AOS mission is being developed by NASA in response to the National Academy of Sciences Decadal Survey for Earth Observations from Space and addresses two of five core science foci recommended through the Decadal Survey process: a focus on aerosol impacts on climate and air quality and a focus on global hydrological cycle and cloud-climate feedbacks. The AOS mission implementation, which follows the NASA Aerosol-Cloud-Convection-Precipitation (ACCP) Study recommendations, includes several instruments deployed in two orbital planes, one inclined and one polar. Clio is designed for deployment to the polar orbital plane along with a Doppler radar, microwave radiometer, polarimeter, long-wave IR imaging radiometer, and aerosol and water vapor limb sounders and contributes to both the aerosol and cloud science foci of the mission. Clio capabilities would provide major advances in aerosol and cloud measurements over those available from past spaceborne cloud/aerosol lidars in terms of accuracy, precision, sensitivity, and information content.

The Methane Remote Sensing Lidar Mission (MERLIN) aims at global observations of spatial and temporal gradients of atmospheric methane (CH4) using spaceborne active measurements based on an integrated path differential absorption (IPDA) nadir-viewing lidar instrument. It is a joint French and German space mission which is currently in its phase D with a planned launch date in 2027. The main scientific goal of the mission is to provide the column-integrated dry-air mixing ratio of CH4 (XCH4) for all latitudes and for all seasons of the year with very small systematic errors. These precise spaceborne data will enable to significantly improve our knowledge of CH4 sources especially in regions like the tropics and high latitudes where data is still sparse compared to other regions of the world.

The Cloud-Aerosol Transport System (CATS) elastic backscatter lidar flew on the International Space Station (ISS) as a technology demonstration from 2015 to 2017. Ahead of the CATS launch, we developed a capability to simulate the projected performance of CATS for various simple, synthetic atmospheric scenes. The simulator served a critical role in the development and testing of CATS operational and near real-time algorithms prior to launch. Following CATS, we advanced our lidar simulator capability to simulate more complex scenes using inputs from global aerosol transport models and airborne/ground-based lidar observations to improve scene realism, complexity, and variability. This capability served a key role during the Earth Science Decadal Survey (ESDS) Aerosols, Clouds, Convection, and Precipitation (ACCP) study phase toward the development of the Atmospheric Lidar Instrument for Clouds and Aerosol Transport (ALICAT) elastic backscatter lidar planned to fly in the 55-degree inclined orbit of the upcoming Atmospheric Observing System (AOS) mission with an anticipated launch in 2028. Here, we present an overview of our lidar simulation capability, an overview of the ALICAT instrument, and projected performance compared to CATS and AOS science requirements.

Lidars in space have advanced our knowledge in several research fields. With respect to aerosol and clouds, long-term observations have been acquired and intensively studied for more than 15 years starting with CALIPSO. Recently Aeolus was launched, and EarthCARE – another lidar-equipped mission – is scheduled for launch in 2024. The coexistence of these three (at the moment) different lidar-equipped missions in space cannot but point out their different capabilities, especially with respect to aerosol typing. The lidars onboard the aforementioned satellites operate at different wavelengths, target the observation of different atmospheric components (e.g., wind, aerosol), and, hence, often utilize different measuring techniques and principles (e.g., HSRL, circular vs. linear polarization). To overcome this issue, synergistic approaches between ground-based and spaceborne lidars should be utilized. In addition, the need for harmonization of the observations from those multiple satellites is more evident than ever, as it would provide new aerosol (and cloud) products with improved temporal coverage.

Version 4.51 (V4.5) of the CALIPSO lidar level 1 (LL1) data products is targeted for public release in summer 2022. One of the most far-reaching changes implemented in this release is to the polarization gain ratio (PGR), which quantifies the gain between the 532 nm parallel and perpendicular channels in the CALIPSO receiver. The PGR is an essential calibration coefficient required for computing both the attenuated backscatter coefficients reported in the LL1 product and the volume depolarization ratios. Prior to V4.5, the PGR was assumed to be a slowly varying constant that remained invariant throughout both the day and night portions of any CALIPSO orbit. However, in response to recent discoveries, in V4.5 the PGR now varies diurnally. In this work, we describe the motivation for this change, briefly review the technique used to compute daytime PGR estimates, provide an overview of the V4.5 PGR implementation, and compare the V4.5 PGRs to those used in previous data releases.

ATLAS, the Atmospheric Thermodynamic LidAr in Space, is a project aimed at developing the first spaceborne Raman Lidar capable to measure simultaneously water vapor mixing ratio and temperature profiles with high temporal and spatial resolution at global level. Within the project, proposed to the European Space Agency as a mission concept in the frame of “Earth Explorer-11 Mission Ideas,” an end-to-end simulator has been developed to verify the technical and technological solutions of the different transmitting and receiving subsystems and to estimate the performance of ATLAS in different atmospheric conditions. The simulator consists of two separate modules that allow to calculate the roto-vibrational and pure rotational Raman signals. The simulated signals are then analyzed through consolidated techniques, in order to obtain retrieved profiles of water vapor mixing ratio and atmospheric temperature, together with their statistical and systematic uncertainties. As input data for the simulations, thermodynamic and optical parameters from the non-hydrostatic mesoscale model GEOS-5 Nature Run Ganymed Release were used. Data were extracted to simulate the performances along several dawn-dusk orbits around the Earth for different days of the year, accurately chosen to consider different background conditions in dependence of the solar zenith angle variability. Both clear and cloudy sky conditions were considered, highlighting the capability of space lidars to obtain accurate measurements in variable atmospheric conditions.

The Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite has been making near-global measurements of clouds and aerosols since mid-June 2006. Among the properties reported in CALIPSO data products are estimates of total column optical depth (COD) obtained by integrating the retrieved extinction coefficients of detected particulates (i.e. aerosols and clouds) from 36 km to the surface. However, due to algorithm detection limits and instrument sensitivities, particulates can go undetected when the particulate loading is especially diffuse or in regions where the signal is attenuated by overlying layers. Because extinction is not calculated where features are not detected, these undetected particulates can introduce low biases into the reported COD. Lidar ratio assumptions used in the extinction retrievals can also introduce errors. To minimize these biases, future releases of the CALIPSO lidar data products will implement an ocean-derived column optical depth (ODCOD) retrieval. The following paper briefly describes the algorithm, the current status of the algorithm development and verification efforts, and preliminary comparisons to collocated COD estimates derived using other retrieval schemes and obtained from other sensors.

The EUMETSAT ADD-CROSS project aims to demonstrate the benefits of assimilating Aeolus L2A cloud and aerosol optical products for NWP, with and without possible expansions of the current instrument capabilities permitted by the new structural design envisaged for a future AEOLUS 2 mission. At the present, ALADIN transceiver enables the detection only of the returned co-polar component of the transmitted light. The use of a circularly polarized emission and the detection of the cross-polar component of the backscattered light are two potential options for the future. In order to assess their benefit, different experimental datasets (355 nm – w/wo cross-channel/linear and circular) to be used in the ECWWF’s 4D-Var, have been produced based on CALIPSO profiles of particulate depolarization ratio and backscatter coefficient in the mid-visible. The specific objectives of ADD-CROSS are to (1) quantify the impact of the cross-channel on data assimilation in air quality and NWP models and (2) to quantify the impact of linear vs circular configuration in the absence of the cross-polar channel. The ADD-CROSS assimilation experiments will focus on the Western Sahara and the Tropical Atlantic Ocean in a 1-month time frame (September 2021 during which a major international campaign was carried out in the region, thus providing interesting independent data). Here, preliminary results of the under-development CALIPSO-based products to be used in the ECWWF’s 4D-Var are presented.

Our group in the University of Wisconsin–Madison has developed several high-spectral-resolution lidars (HSRLs). The lidars we describe here use relatively high-power injection-seeded Nd:YAG lasers and iodine adsorption cells to separate Mie and Rayleigh scattered photons in the lidar returns. The instruments are eye safe for direct viewing and capable of continuous, remote operation with little maintenance. They have been deployed in numerous field campaigns in many locations around the globe. Over the years, these HSRL lidars had undergone multiple modifications improving the performance and adding new measurement capabilities such as extinction cross-section measurements, dual wavelength operation, and telescope elevation scanning. Here we provide a history of HSRL upgrades and a description of the latest upgrade.

This chapter describes two novel algorithms for cloud and aerosol property retrievals that are being implemented in the ALADIN operational processor. These two algorithms are known as AEL-FM and AEL-PRO. AEL-FM provides a “feature-mask” based on ALADIN cross-talk corrected particulate (“Mie”) and molecular (“Rayleigh”) attenuated backscatter profiles. AEL-PRO, which uses AEL-PRO as an input (as well as the attenuated backscatter profiles), provides profiles of particulate backscatter and extinction. Both these algorithms are based on algorithms previously developed for application to the ATLID lidar onboard EarthCARE.

The CIMEL CE376 micro-pulse lidar providing measurements at 532 and 808 nm and depolarization at 532 nm coupled with sun/moon photometers providing spectral aerosol optical depth (AOD) are integrated for synergetic mobile monitoring of aerosols properties. A first dataset of CE376 lidar-photometer performing on-road measurements was obtained during the FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) field campaign deployed in summer 2019 over the Northwestern US. Despite the extreme environmental conditions limited the performance of instruments, we were able to investigate smoke optical properties close to the fire source. Backscatter, extinction profiles, column-integrated lidar ratio (LR) at 532 and 808 nm, in addition to volume linear depolarization ratio (VLDR) profiles at 532 nm, were obtained for a quality assured dataset. Since then, instrumental and algorithmic assessments took place at ATOLL (Atmospheric Observatory of liLLe) platform in Lille, France. METIS, an operational CE376 micro-pulse lidar, continuously performing and co-located with sun/moon photometers and with LILAS high-power multiwavelength lidar, part of EARLINET (European Aerosol Research LIdar NETwork), are considered for test and data validation prior other mobile campaign. Therefore, an event of Saharan dust transported to Lille in March–April 2021 is shown along with comparisons of aerosols retrievals from both METIS and LILAS lidars. Extinction profiles from both lidars are in good agreement, and absolute differences of 0.03 on the VLDR profiles are observed that are mainly related to differences in the optical design of the systems.

The coronavirus (COVID-19) spread around the world lead to the application of restrictions and strict stay-at-home mandates in the majority of the European countries, during the first quarter of 2020. An intensive observation campaign was organized during May 2020 by the European Aerosol Research Lidar Network (EARLINET), part of ACTRIS (Aerosols, Clouds and Trace Gases Research Infrastructure), to investigate possible aerosol-type changes in the lower troposphere due to the decreased emissions during the COVID-19 lockdown and relaxation period. The current work is part of an extended study related to potential changes in the aerosol load over Europe. The dominant aerosol types are identified with NATALI aerosol classification scheme, applied upon the aerosol lidar-derived intensive products. The aerosol types within January–May 2020 are compared to the aerosol types from the reference period between 2015 and 2019.

As part of the Cevennes-Vivarais site, the University of Basilicata Raman lidar system BASIL was deployed in Candillargues (Cévennes-Vivarais, Southern France Lat: 43°37′ N; Long: 04°04′ E; Elev: 1 m) and operated throughout the duration of HyMeX-SOP 1 (September–November 2012), providing high-resolution and accurate measurements, both in daytime and nighttime, of atmospheric temperature, water vapour mixing ratio and particle backscattering and extinction coefficient at three wavelengths.Measurements carried out by BASIL on 28–29 September 2012 reveal a water vapour field characterized by a quite complex vertical structure. Reported measurements were run in the time interval between two consecutive heavy precipitation events, from 15:30 UTC on 28 September to 03:30 UTC on 29 September 2012. Throughout most of this observation period, lidar measurements reveal the presence of four distinct humidity layers.This research effort aims at assessing the origin and transport path of the different humidity filaments observed by BASIL on this day. In the research work, we also try to identify the presence of dry layers and cold pools and assess their role in the genesis of the mesoscale convective systems and the heavy precipitation events (HPEs) observed on 28–29 September 2012. Virtual potential temperature and equivalent potential temperature are considered as prognostic variables to identify cold pools, with the considered threshold value for virtual potential temperature and equivalent potential temperature being 23 °C and 52 °C, respectively. The study is based on the combined use of water vapour mixing ratio and temperature profile measurements from BASIL and water vapour mixing ratio profile measurements from the water vapour differential absorption lidar LEANDRE 2, supported by simulations from the mesoscale non-hydrostatic model MESO-NH.

Recent advances in field observations relating to quantifying pollution transport from instrument suites operated by NASA and collaborating institutions occurred in September 2021 during TRACER-AQ (website: https://www-air.larc.nasa.gov/missions/tracer-aq/ ). This study in Houston TX was designed to measure air quality relevant constituents at high-spatial and temporal resolutions, which brought together many of these instrument profiling platforms. This paper will explore and highlight the remotely sensed (both active and passive) and in situ profiling capabilities of ground-based platforms such as ozone lidars, aerosol lidars, Pandora spectrometers, and balloons. Airborne profiles will also be emphasized to provide further regional context for the select case study date of September 9, 2021.

This work aims to assess some aerosol properties retrieved by GRASP algorithm whose inputs are degree of linear polarization (DOLP), radiances and aerosol optical depth (AOD) from new photometer at 7λ (level 1.5, version 3) and range-corrected signal (RCS) from lidar system at 3λ in the Universitat Politècnica de Catalunya (UPC). The volume size distribution (VSD), real/imaginary part of the refractive index (RRI and IRI) present accentuated under overestimations at shorter wavelengths in non-polarized configurations for a dust case while the polarized configurations improve the coarse mode of VSD and the underestimations in RRI. The vertical distribution of volume concentration (VC) and backscatter profiles identify an aerosol layer between 3 and 4 km in which there is presence of small particles according to fine VC profiles and backscatter profile at 355 nm. The polarized data demonstrated improvements in the retrieved properties by GRASP algorithm.

The atmospheric layer near the tropical tropopause (14–18.5 km), referred to as the Tropical Tropopause Layer (TTL), is a key region of the Earth’s atmosphere and the gateway to the stratosphere. Along their ascent through the extremely cold TTL ( < 200 $${<}200$$ K), air parcels undergo ice formation and freeze-drying, which is ultimately responsible for the dryness of the stratosphere, of dramatic importance for stratospheric chemistry and the Earth’s radiative balance. TTL ice clouds (cirrus) also directly affect the Earth’s radiative budget. Combined lidar and radiometric measurements onboard stratospheric balloons make it possible to estimate their radiative forcing at a fine scale.

The aim of this study is to report on a detailed validation of the aerosol layer height (ALH) satellite product derived from the TROPOMI/S5P instrument, using as reference spatially and temporally colocated measurements from the well-established EARLINET lidars (Pappalardo G, et al. Atmos Meas Tech 7:2389–2409. https://doi.org/10.5194/amt-7-2389-2014 , 2014) and CALIOP/CALIPSO observations (Winker DM, et al. Bull Am Meteor Soc 91:1211–1229. https://doi.org/1310.1175/2010BAMS3009.1 , 2010) over the Mediterranean. The time period from 2018 to 2022 is selected for the validation analysis. The TROPOMI Level-2 ALH (Veefkind JP, et al. Remote Sens Environ 120:70–83. https://doi.org/10.1016/16j.rse.2011.09.027 , 2012) is an operational product since 2019 focusing on the retrieval of vertically localized aerosol layers in the free troposphere (desert dust, biomass burning aerosol, and volcanic ash plumes) for cloud-free cases. Knowledge of the ALH is essential for understanding the impact of aerosols on the climate system. Lidar instruments are a good source for validating retrieved ALHs from passive satellite sensors since they provide aerosol profile information, such as the backscatter and extinction coefficients, at different wavelengths with a vertical resolution of a few meters. The comparison between TROPOMI and lidar plume heights shows that, on average, the TROPOMI aerosol layer heights are slightly lower, compared to CALIPSO (−0.75 ± 0.98km) and EARLINET (−1.02 ± 0.96km), which is likely due to the different measurement techniques and the TROPOMI product limitations.

The eVe lidar is a novel ground-based lidar system designed to provide ground reference measurements of aerosols and clouds optical properties facilitating the validation of the corresponding Aeolus products of aerosols and clouds. The lidar is implemented in a dual-laser/dual-telescope configuration that emits linearly and circularly polarized light at 355 nm and detects the depolarization in the elastically backscattered lidar signals as well as the inelastically backscattered both from linear and circular emission. eVe mimics the observational geometry and configuration of Aeolus whereas is capable to operate as a traditional ground-based linear polarization lidar system. The lidar was deployed in the Joint Aeolus Tropical Atlantic Campaign (JATAC) for the validation of the Aeolus products. During JATAC operations, an unpreceded eVe dataset was acquired aiming to facilitate the Aeolus calibration and validation efforts. In addition, the good performance of the eVe lidar was validated against an EARLINET approved lidar system, the PollyXT that was also deployed for the JATAC operations.

A large effort has been made to establish ozone lidars across the mid-Atlantic region of the United States. By 2023, there will be 4 Tropospheric Ozone Lidar Network (TOLNet) sites across the mid-Atlantic region: Hampton, VA with Hampton University and NASA Langley Research Center (LMOL); Greenbelt, MD with NASA Goddard Space Flight Center (TROPOZ); and Manhattan, NY will have one at the City College of New York (CCNY). This novel venture will bring much-needed profiling of ozone to key areas in the region; however, its networked coverage will be sparse with sites being ≤200 miles apart. To extend the utility of both the TOLNet and Pandora networks, we have begun using their observational products to interpret boundary layer abundances to extract new science and understanding of pollution dynamics. We present a case study of this effort from a NAAQS ozone exceedance episode from May 19 to 21, 2021. High-resolution observations from active and passive remote sensors capture the evolution of this event. The ozone episode evolved from entrainment of a transported polluted air mass followed by recirculation in the region leading to a quick lofting by down-slope winds (as noted by ceilometer backscatter and vertically resolved wind profiles), which are situated in the plume for next-day entrainment. Collocated wind, aerosols, and ozone profiles in the Beltsville – Greenbelt, MD area indicated an air-mass change occurring near 14 LT May 20, 2021, marking the arrival of a well-mixed layer of ozone from the north. For this case, the Pandora total column ozone enhancement showed good agreement both temporally and quantitatively with TROPOZ 0–2 km integrated column (a TEMPO-like proxy). This shows the potential for future synergy in air quality event identification and characterization, especially in those that are driven by meteorological enhancement and transport. A byproduct of this work is an analysis of the seasonal variability of ozone in the mid-Atlantic domain using TOLNet, Pandora, sondes, and surface trace-gas monitors. This work aims to aid in the resolution of NASA decadal surface questions, support the upcoming TEMPO mission, and serves to demonstrate the usefulness of multi-instrument perspectives in the analysis of air quality event evolution and spatio-temporal variability. Further work will focus on the comparison of these datasets with NASA GEOS-CF and current satellite products.

The depolarization ratio near the surface measured by lidars in AD-Net (Asian dust and aerosol lidar observation network) was utilized to distinguish the long-range transported Asian dust and locally generated dust over Japan. In February 2017, locally generated dusts were frequently observed in Tsukuba, and May 2017 was a typical month of Asian dust. Thus, two histograms of depolarization ratio constructed from observational data of these 2 months were compared, and a 0.4 (40%) was identified as a threshold of two kinds of mineral dust particles: locally generated (large) dust and long-range transported Asian dust. A climatological analysis of data obtained by four lidars in Japan revealed that the local dust events were not observed in other regions of Japan.

Using the so-called Hu diagram relating layer-integrated depolarization ratio (δv) and layer-integrated attenuated backscatter at 532 nm (γ′532), the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar can effectively discriminate between liquid water clouds, clouds composed of randomly oriented ice (ROI) crystals, and ice clouds that contain some fraction of horizontally oriented ice (HOI) crystals. A recently proposed Hu diagram update splits the original water region into a more compact pure liquid regime and two mixed-phase regions. We propose an extended Hu diagram that additionally identifies mixed-phase clouds by incorporating perfectly colocated microphysical index (βeff) and effective diameter (De) retrievals in the thermal infrared window obtained from the CALIPSO imaging infrared radiometer (IIR). First, using the βeff index, we identify regions of the Hu diagram which are seemingly associated with mixed-phase clouds. Second, we characterize opaque water clouds in the updated Hu diagram. Water clouds with top temperatures lower than 238 K, when ice is expected in the upper portion of the cloud, fall distinctly into a proposed mixed-phase region. IIR De varies as expected with lidar ratio in the tighter liquid water region and is larger due to the presence of ice in the mixed-phase region. Finally, we show that the HOI class clusters into two main families of δv-γ′532 relationships, suggesting mixed-phase clouds with smaller De and pure ice clouds with larger De, which is confirmed by Monte Carlo simulations published in the literature.

We have developed a mobile observation platform, named the Rocket-city Ozone Quality Evaluation in the Troposphere (RO3QET), for studying air quality and its health impacts. The integrated system consists of an O3 differential absorption lidar with both vertical and scanning measurement capabilities for measuring O3 and aerosol profiles, an ozonesonde station, surface O3 monitors, an unmanned aerial vehicle, and an instrument for regular meteorological observations. Affiliated with the Tropospheric Ozone Lidar Network (TOLNet), this mobile system performs routine operations at its home station, the campus of the University of Alabama in Huntsville, and at field campaign deployments in remote sites. This short chapter reports the capabilities of this new platform and presents some experimental data.

An algorithm based on the maximum likelihood estimation (MLE) to retrieve height-resolved aerosol microphysical properties from Mie-Raman lidar measurements is proposed. Compared to the linear inversion methods with regularization, this algorithm greatly reduces the number of individual solutions of the underdetermined lidar inverse system and adds flexibility in incorporating different types of measurements and a priori information. The algorithm is used to retrieve the particle size distribution (PSD), total volume concentration (Vt), effective radius (Reff) and complex refractive index m = n − ik by inverting ‘3β + 2α’ measurements and the retrieval accuracies with and without the influence of random measurement error are evaluated through numerical simulations. To further examine the performance of the algorithm, it is applied to several aerosol events detected by the Mie-Raman-polarization-fluorescence lidar, LILAS. We conclude that the 3β + 2α could provide enough information on retrieving PSD, Vt, Reff and the real part of m (n), but the retrieval of the imaginary part of m (k) relies more on a priori information. Moreover, it is also insufficient to calculate the retrieval uncertainty by error propagation.

Multiple scattering is always present in LiDAR measurements. It is a major cause of signal depolarization in water clouds. For a given probing wavelength, the LiDAR signal is a function of the aerosol size distribution, of the cloud range, of the cloud optical depth, and of the LiDAR Field of View. A relatively simple polarimetric multiple scattering model is presented. It uses Poisson statistics to determine the distribution of the photon’s scattering order at a given optical depth and takes into account the aerosol’s properties as well as the optical characteristics of the LiDAR. The results are compared with Monte Carlo simulations performed on three cloud types and on a moderate water fog. Good agreement is demonstrated for the total LiDAR signal and the depolarization parameter.

The assimilation of radar reflectivity and radial velocity from the WSR-88D radar and lidar water vapor profile observations could improve the forecast of location and timing of bore associated with nocturnal convection. This study describes the assimilation of such data observed during the 2015 Plains Elevated Convection at Night (PECAN) field campaign. The model and data assimilation system employed is the Pennsylvania State University Weather Research and Forecasting model Ensemble Kalman Filter (PSU-WRF-EnKF) cycling data assimilation system. The lidars include the Atmospheric Lidar for Validation, Interagency Collaboration and Education (ALVICE), University of Wyoming King Air compact Raman lidar, Atmospheric Radiation Measurement (ARM) Raman lidar, and National Center for Atmospheric Research (NCAR) micropulse Differential Absorption Lidar (DIAL). The bore propagation was observed by both radar and ALVICE lidar in Kansas, on 14 July 2015, and a nocturnal convection initiated near the bore/density current. Without assimilating any observations, the WRF model didn’t well simulate the location of the bore, even though it captured the bore structure quite well. The assimilation of WSR-88D radar observations improved the location and timing forecasts of the nocturnal convection and the associated bore.

We report the first discovery of regular occurrence of mid-latitude thermosphere-ionosphere Na (TINa) layers (110–150 km) over Boulder (40.13°N, 105.24°W), Colorado. Detection of tenuous Na layers (~0.1–1 cm−3 from 150 to 130 km) was enabled by high-sensitivity Na Doppler lidar. A new data processing technique is applied to pave the way for the discovery, which is Na volume mixing ratio calculations. For the first time, TINa layers are observed occurring regularly in various months and years, descending from ~125 km after dusk and from ~150 km before dawn. About 7 years of lidar observations reveal Boulder TINa dawn layers with nearly 100% occurrence rate (160 out of 164 nights of observations). These layers provide a natural laboratory for studying the ion-neutral coupling and act as tracers for extending the profiling of neutral wind and temperature into the E to lower F regions. Such potentials offered by the TINa layers promote future advancement of lidar technologies for even higher detection sensitivities to enable new science endeavors.

The performance of a model field-widened Michelson interferometer (FWMI) as the spectral discriminator for a 1064-nm high-spectral resolution lidar (HSRL) channel is presented. The technique of HSRL separates the Doppler-broadened molecular backscatter from the narrow Mie scattering from atmospheric aerosols using a fine-tuned narrowband filter or spectral discriminator. Our simulated FWMI consists of one glass arm and one air spaced arm with a composite metal spacer designed to make the interferometer thermally invariant. The FWMI is pressure tuned to the desired wavelength.

Lidars are excellent tools for routine profile measurements of ozone, temperature, and aerosol in the stratosphere. Different from most other techniques, the lidar measurements are essentially self-calibrating. This inherently insures long-term stability and has made lidars a key component of the Network for the Detection of Atmospheric Composition Change (NDACC). Some NDACC lidar stations have provided measurement records covering almost 40 years and are expected to continue for many years. We present some milestones in the development of these lidars and show long-term atmospheric changes they have measured. The lidar data are also used as a reference for validation and for merging of (generally shorter) satellite records.

The long-term lidar measurement series of stratospheric aerosol started in 1976 has been continued in third generation with a new lidar system since 2017. This was just in time to cover a new period of elevated-aerosol events. The new system yields high-quality backscatter coefficients up to almost 50 km. This was important during the period 2020 to spring 2021 when a small amount of particles was observed at altitudes of up to 40 km, possibly originating from the tropical eruption of Ulawun in June 2019. Most of the aerosol spikes in the recent period of the time series are related to an unprecedented rise in strong biomass-burning injections into the stratosphere resulting in aerosol signatures in part up to more than 20 km. It is hard to ascribe this sudden rise in occurrence just to a slowly developing climate change.