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Lidar for Advanced Classification and Retrieval of Aerosols

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 20898

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Special Issue Editors

Dr. Daniel Pérez-Ramírez

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Guest Editor

1. Applied Physics Department, University of Granada, 18010 Granada, Spain
2. Andalusian Institute for Earth System Research (IISTA), 18010 Granada, Spain
Interests: atmospheric pollution; satellite image analysis; atmospheric physics
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Haiyun Xia

E-Mail Website
Guest Editor

School of Earth and Space Sciences, University of Sciences and Technology of China, Hefei 230026, China
Interests: lidar; atmospheric aerosols; remote sensing
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Simone Lolli

E-Mail Website
Guest Editor

CNR-IMAA, Contrada S. Loja, 85050 Tito Scalo, PZ, Italy
Interests: radiative transfer; aerosols; lidar; image fusion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Aerosols affect the earth–atmosphere radiative system directly, by scattering and absorbing solar radiation, and indirectly, by altering the lifetime and development of clouds. Reducing the uncertainty in direct aerosol radiative forcing (DARF) is a necessary step in reconciling estimates of radiative forcing and the equilibrium climate sensitivity of the Earth, so that future predictions of surface temperature associated with climate change can be made with confidence. In this sense, LIDAR measurements have huge impacts on the increase in knowledge of aerosol optical properties’ vertical-profiles, but fail to provide accurate retrievals of aerosol microphysical properties. Only multiwavelength lidar measurements that combine independent backscattering and extinction measurements can provide a proxy for aerosol microphysical properties, and further developments are still required to advance code developments and accurate particle scattering and extinction modeling. Nevertheless, the development of multiwavelength depolarization measurements is permitting aerosol typing, but its integration in aerosol microphysical properties’ inversion codes requires further modeling. On the other hand, passive ground-based radiometers and space polarimeters do provide accurate aerosol microphysical properties, but retrieved values are representative of the whole atmospheric column. The integration of these passive remote-sensing devices with lidar measurements can serve to exploit simple lidar instruments, which are only capable of acquiring backscattering signals; however, they operate in a continuous way through lidar networks such as MPLNET or EARLINET-ACTRIS.

Topics covered by this Special Issue may include, but are not limited to:

Use of extensive data from lidar ground-based networks (e.g., MPLNET, EARLINET) for the classification of aerosol optical and microphysical properties;
Use of extensive data from the space-borne lidar system and their synergy with other passive instrumentation for the classification of aerosol optical and microphysical properties;
Developments in modeling aerosol particles’ optical and microphysical properties for lidar applications;
Developments in solving ill-posed problems for the retrieval of aerosol microphysical properties using lidar.

Dr. Daniel Pérez-Ramírez
Prof. Dr. Haiyun Xia
Dr. Simone Lolli
Guest Editors

Manuscript Submission Information

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Keywords

lidar
aerosol microphysical retrievals
aerosol typing
ground-based networks
radiative transfer

Published Papers (10 papers)

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Research

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21 pages, 6854 KiB

Open AccessArticle

Lidar Profiling of Aerosol Vertical Distribution in the Urbanized French Alpine Valley of Annecy and Impact of a Saharan Dust Transport Event

by Patrick Chazette and Julien Totems

Remote Sens. 2023, 15(4), 1070; https://doi.org/10.3390/rs15041070 - 15 Feb 2023

Cited by 2 | Viewed by 1414

Abstract

The vertical aerosol layering of the troposphere is poorly documented in mountainous regions, particularly in the Alpine valleys, which are influenced by valley and mountain winds. To improve our knowledge of particulate matter trapped in the Annecy valley, synergetic measurements performed by a ground-based meteorological Raman lidar and a Rayleigh-Mie lidar aboard an ultralight aircraft were implemented as part of the Lacustrine-Water vApor Isotope inVentory Experiment (L-WAIVE) over Lake Annecy. These observations were complemented by satellite observations and Lagrangian modeling. The vertical profiles of aerosol optical properties (e.g., aerosol extinction coefficient (AEC), lidar ratio (LR), particle linear depolarization ratio (PDR)) are derived from lidar measurements at 355 nm during the period between 13 and 22 June 2019. The background aerosol content with an aerosol optical thickness (AOT) of 0.10 ± 0.05, corresponding to local–regional conditions influenced by anthropogenic pollution, has been characterized over the entirety of Lake Annecy thanks to the mobile ultralight payload. The aerosol optical properties are shown to be particularly variable over time in the atmospheric column, with mean LRs (PDRs) varying between 40 ± 8 and 115 ± 15 sr (2 ± 1 and 35 ± 2%). Those conditions can be disturbed by air masses that have recirculated over the valley, as well as by contributions from neighboring valleys. We have observed an important disruption in the atmospheric aerosol profiles by the arrival of an exceptionally dry air mass (RH ~ 30%), containing aerosols identified as coming from the Great Western Erg (AOT ~ 0.5, LR = 65 ± 10 sr, PDR = 20–35%) in the Sahara. These desert dust particles are shown to influence the entire atmospheric column in the Annecy valley. Such an experimental approach, coupling upward and downward lidar and spaceborne observation/Lagrangian modelling, was shown to be of significant interest for the long-term monitoring of the evolution of aerosol loads over deep valleys. It allows a better understanding of the influence of dust storms in the presence of severe convective weather processes. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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Graphical abstract

23 pages, 4132 KiB

Open AccessArticle

Added Value of Aerosol Observations of a Future AOS High Spectral Resolution Lidar with Respect to Classic Backscatter Spaceborne Lidar Measurements

by Flavien Cornut, Laaziz El Amraoui, Juan Cuesta and Jérôme Blanc

Remote Sens. 2023, 15(2), 506; https://doi.org/10.3390/rs15020506 - 14 Jan 2023

Cited by 1 | Viewed by 1452

Abstract

In the context of the Atmosphere Observing System (AOS) international program, a new-generation spaceborne lidar is expected to be in polar orbit for deriving new observations of aerosol and clouds. In this work, we analyze the added values of these new observations for characterizing aerosol vertical distribution. For this, synthetic observations are simulated using the BLISS lidar simulator in terms of the backscatter coefficient at 532 nm. We consider two types of lidar instruments, an elastic backscatter lidar instrument and a high spectral resolution lidar (HSRL). These simulations are performed with atmospheric profiles from a nature run (NR) modeled by the MOCAGE chemical transport model. In three case studies involving large events of different aerosol species, the added value of the HSRL channel (for measuring aerosol backscatter profiles with respect to simple backscatter measurements) is shown. Observations independent of an a priori lidar ratio assumption, as done typically for simple backscattering instruments, allow probing the vertical structures of aerosol layers without divergence, even in cases of intense episodes. A 5-day study in the case of desert dust completes the study of the added value of the HSRL channel with relative mean bias from the NR of the order of 1.5%. For low abundances, relative errors in the backscatter coefficient profiles may lay between +40% and −40%, with mean biases between +5% and −5%. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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Figure 1

24 pages, 6972 KiB

Open AccessArticle

Retrieval of Aerosol Microphysical Properties from Multi-Wavelength Mie–Raman Lidar Using Maximum Likelihood Estimation: Algorithm, Performance, and Application

by Yuyang Chang, Qiaoyun Hu, Philippe Goloub, Igor Veselovskii and Thierry Podvin

Remote Sens. 2022, 14(24), 6208; https://doi.org/10.3390/rs14246208 - 07 Dec 2022

Cited by 2 | Viewed by 1446

Abstract

Lidar plays an essential role in monitoring the vertical variation of atmospheric aerosols. However, due to the limited information that lidar measurements provide, ill-posedness still remains a big challenge in quantitative lidar remote sensing. In this study, we describe the Basic algOrithm for REtrieval of Aerosol with Lidar (BOREAL), which is based on maximum likelihood estimation (MLE), and retrieve aerosol microphysical properties from extinction and backscattering measurements of multi-wavelength Mie–Raman lidar systems. The algorithm utilizes different types of a priori constraints to better constrain the solution space and suppress the influence of the ill-posedness. Sensitivity test demonstrates that BOREAL could retrieve particle volume size distribution (VSD), total volume concentration (V_t), effective radius (R_eff), and complex refractive index (CRI = n − ik) of simulated aerosol models with satisfying accuracy. The application of the algorithm to real aerosol events measured by LIlle Lidar AtmosphereS (LILAS) shows it is able to realize fast and reliable retrievals of different aerosol scenarios (dust, aged-transported smoke, and urban aerosols) with almost uniform and simple pre-settings. Furthermore, the algorithmic principle allows BOREAL to incorporate measurements with different and non-linearly related errors to the retrieved parameters, which makes it a flexible and generalized algorithm for lidar retrieval. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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14 pages, 3085 KiB

Open AccessArticle

Characterization of Extremely Fresh Biomass Burning Aerosol by Means of Lidar Observations

by Benedetto De Rosa, Francesco Amato, Aldo Amodeo, Giuseppe D’Amico, Claudio Dema, Alfredo Falconieri, Aldo Giunta, Pilar Gumà-Claramunt, Anna Kampouri, Stavros Solomos, Michail Mytilinaios, Nikolaos Papagiannopoulos, Donato Summa, Igor Veselovskii and Lucia Mona

Remote Sens. 2022, 14(19), 4984; https://doi.org/10.3390/rs14194984 - 07 Oct 2022

Cited by 3 | Viewed by 1526

Abstract

In this paper, characterization of the optical and microphysical properties of extremely fresh biomass burning aerosol is presented. This work aims to characterize, for the first time to our knowledge, freshly formed smoke particles observed only a few minutes after they were emitted from a nearby forest fire. The smoke particles were detected by combining passive (sun-photometer) and active (Raman lidar) techniques. On 14 August 2021, an EARLINET (European Aerosol Research Lidar Network) multi-wavelength Raman lidar and a co-located AERONET sun-photometer in Potenza, South Italy, observed an extremely fresh smoke plume. The lidar measurements, carried out from 22:27 to 02:16 UTC, revealed a thick biomass burning layer below 2.7 km. The particle depolarization ratio at 532 nm was 0.025, and lidar ratios at 355 and 532 nm were, respectively, 40 and 38 sr. The mean value of the Ångström exponent was 1.5. The derived size distribution was bimodal with a peak at 0.13 µm, an effective radius mean value of 0.15 µm, and a single scattering albedo of 0.96 at all wavelengths. The real part of the refractive index was 1.58 and the imaginary was 0.006. The AERONET measurements at 5:34 UTC confirmed the lidar measurements. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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24 pages, 3708 KiB

Open AccessArticle

Methodology for Lidar Monitoring of Biomass Burning Smoke in Connection with the Land Cover

by Mariana Adam, Konstantinos Fragkos, Stavros Solomos, Livio Belegante, Simona Andrei, Camelia Talianu, Luminița Mărmureanu, Bogdan Antonescu, Dragos Ene, Victor Nicolae and Vassilis Amiridis

Remote Sens. 2022, 14(19), 4734; https://doi.org/10.3390/rs14194734 - 22 Sep 2022

Viewed by 1697

Abstract

Lidar measurements of 11 smoke layers recorded at Măgurele, Romania, in 2014, 2016, and 2017 are analyzed in conjunction with the vegetation type of the burned biomass area. For the identified aerosol pollution layers, the mean optical properties and the intensive parameters in the layers are computed. The origination of the smoke is estimated by the means of the HYSPLIT dispersion model, taking into account the location of the fires and the injection height for each fire. Consequently, for each fire location, the associated land cover type is acquired by satellite-derived land cover products. We explore the relationship between the measured intensive parameters of the smoke layers and the respective land cover of the burned area. The vegetation type for the cases we analyzed was either broadleaf crops or grasses/cereals. Overall, the intensive parameters are similar for the two types, which can be associated with the fact that both types belong to the broader group of agricultural crops. For the cases analyzed, the smoke travel time corresponding to the effective predominant vegetation type is up to 2.4 days. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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25 pages, 9355 KiB

Open AccessArticle

Turbulence Detection in the Atmospheric Boundary Layer Using Coherent Doppler Wind Lidar and Microwave Radiometer

by Pu Jiang, Jinlong Yuan, Kenan Wu, Lu Wang and Haiyun Xia

Remote Sens. 2022, 14(12), 2951; https://doi.org/10.3390/rs14122951 - 20 Jun 2022

Cited by 8 | Viewed by 2620

Abstract

The refractive index structure constant (

C_{n}^{2}

) is a key parameter used in describing the influence of turbulence on laser transmissions in the atmosphere. Three different methods for estimating

C_{n}^{2}

were analyzed in detail. A new method that [...] Read more.

The refractive index structure constant (

C_{n}^{2}

) is a key parameter used in describing the influence of turbulence on laser transmissions in the atmosphere. Three different methods for estimating

C_{n}^{2}

were analyzed in detail. A new method that uses a combination of these methods for continuous

C_{n}^{2}

profiling with both high temporal and spatial resolution is proposed and demonstrated. Under the assumption of the Kolmogorov “2/3 law”, the

C_{n}^{2}

profile can be calculated by using the wind field and turbulent kinetic energy dissipation rate (TKEDR) measured by coherent Doppler wind lidar (CDWL) and other meteorological parameters derived from a microwave radiometer (MWR). In a horizontal experiment, a comparison between the results from our new method and measurements made by a large aperture scintillometer (LAS) is conducted. The correlation coefficient, mean error, and standard deviation between them in a six-day observation are 0.8073, 8.18 × 10⁻¹⁶ m^−2/3 and 1.27 × 10⁻¹⁵ m^−2/3, respectively. In the vertical direction, the continuous profiling results of

C_{n}^{2}

and other turbulence parameters with high resolution in the atmospheric boundary layer (ABL) are retrieved. In addition, the limitation and uncertainty of this method under different circumstances were analyzed, which shows that the relative error of

C_{n}^{2}

estimation normally does not exceed 30% under the convective boundary layer (CBL). Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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Other

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13 pages, 6727 KiB

Open AccessTechnical Note

Eye-Safe Aerosol and Cloud Lidar Based on Free-Space Intracavity Upconversion Detection

by Wenjie Yue, Tao Chen, Wei Kong, Xin Chen, Genghua Huang and Rong Shu

Remote Sens. 2022, 14(12), 2934; https://doi.org/10.3390/rs14122934 - 19 Jun 2022

Cited by 3 | Viewed by 1976

Abstract

We report an eye-safe aerosol and cloud lidar with an Erbium-doped fiber laser (EDFL) and a free-space intracavity upconversion detector as the transmitter and receiver, respectively. The EDFL was home-made, which could produce linearly-polarized pulses at a repetition rate of 15 kHz with pulse energies of ~70 μJ and pulse durations of ~7 ns centered at 1550 nm. The echo photons were upconverted to ~631 nm via the sum frequency generation process in a bow-tie cavity, where a Nd:YVO₄ and a PPLN crystal served as the pump and nonlinear frequency conversion devices, respectively. The upconverted visible photons were recorded by a photomultiplier tube and their timestamps were registered by a customized time-to-digital converter for distance-resolved measurement. Reflected signals peaked at ~6.8 km from a hard target were measured with a distance resolution of 0.6 m for an integral duration of 10 s. Atmospheric backscattered signals, with a range of ~6 km, were also detectable for longer integral durations. The evolution of aerosols and clouds were recorded by this lidar in a preliminary experiment with a continuous measuring time of over 18 h. Clear boundary and fine structures of clouds were identified with a spatial resolution of 9.6 m during the measurement, showing its great potential for practical aerosol and cloud monitoring. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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Graphical abstract

9 pages, 3388 KiB

Open AccessTechnical Note

Marine Mixed Layer Height Detection Using Ship-Borne Coherent Doppler Wind Lidar Based on Constant Turbulence Threshold

by Lu Wang, Jinlong Yuan, Haiyun Xia, Lijie Zhao and Yunbin Wu

Remote Sens. 2022, 14(3), 745; https://doi.org/10.3390/rs14030745 - 05 Feb 2022

Cited by 5 | Viewed by 1664

Abstract

Marine mixed layer height (MLH) detection using a ship-borne coherent Doppler wind lidar (CDWL) based on a constant turbulent kinetic energy dissipation rate (TKEDR) threshold is realized and experimentally demonstrated. The MLH can be retrieved from the TKEDR estimated by the CDWL via setting an appropriate threshold. Here, the value of threshold is determined by a reference MLH retrieved from aerosol backscattered signal. The threshold of 10⁻⁴ m² s⁻³ is found to be applicable in retrieving both inland and marine MLHs. In the experiments, to validate the reliability of the constant threshold, the MLH diurnal cycles at inland and marine sites are retrieved by using a ground-based CDWL. The MLH retrieval result at the marine site shows good agreement with radiosonde-derived MLH. After that, by using a ship-borne CDWL, the marine MLH along the ship’s route in South China Sea is successfully detected in real time. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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Graphical abstract

14 pages, 6848 KiB

Open AccessTechnical Note

Cloud Seeding Evidenced by Coherent Doppler Wind Lidar

by Jinlong Yuan, Kenan Wu, Tianwen Wei, Lu Wang, Zhifeng Shu, Yuanjian Yang and Haiyun Xia

Remote Sens. 2021, 13(19), 3815; https://doi.org/10.3390/rs13193815 - 23 Sep 2021

Cited by 17 | Viewed by 3590

Abstract

Evaluation of the cloud seeding effect is a challenge due to lack of directly physical observational evidence. In this study, an approach for directly observing the cloud seeding effect is proposed using a 1548 nm coherent Doppler wind lidar (CDWL). Normalized skewness was employed to identify the components of the reflectivity spectrum. The spectrum detection capability of a CDWL was verified by a 24.23-GHz Micro Rain Radar (MRR) in Hefei, China (117°15′ E, 31°50′ N), and different types of lidar spectra were detected and separated, including aerosol, turbulence, cloud droplet, and precipitation. Spectrum analysis was applied as a field experiment performed in Inner Mongolia, China (112°39′ E, 42°21′ N ) to support the cloud seeding operation for the 70th anniversary of China’s national day. The CDWL can monitor the cloud motion and provide windshear and turbulence information ensuring operation safety. The cloud-precipitation process is detected by the CDWL, microwave radiometer (MWR) and Advanced Geosynchronous Radiation Imager (AGRI) in FY4A satellites. In particular, the spectrum width and skewness of seeded cloud show a two-layer structure, which reflects cloud component changes, and it is possibly related to cloud seeding effects. Multi-component spectra are separated into four clusters, which are well distinguished by spectrum width and vertical velocity. In general, our findings provide new evidence that the reflectivity spectrum of CDWL has potential for assessing cloud seeding effects. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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13 pages, 785 KiB

Open AccessTechnical Note

Aerosol Direct Radiative Effects under Cloud-Free Conditions over Highly-Polluted Areas in Europe and Mediterranean: A Ten-Years Analysis (2007–2016)

by Tony C. Landi, Paolo Bonasoni, Michele Brunetti, James R. Campbell, Jared W. Marquis, Paolo Di Girolamo and Simone Lolli

Remote Sens. 2021, 13(15), 2933; https://doi.org/10.3390/rs13152933 - 26 Jul 2021

Cited by 6 | Viewed by 2090

Abstract

This study investigates changes in aerosol radiative effects on two highly urbanized regions across the Euro-Mediterranean basin with respect to a natural desert region as Sahara over a decade through space-based lidar observations. The research is based on the monthly-averaged vertically-resolved aerosol optical [...] Read more.

1^{\circ} \times 1^{\circ}

horizontal grid, obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument measurements aboard the Cloud-Aerosol lidar and Infrared Pathfinder Satellite Observation (CALIPSO). To assess the variability of the anthropogenic aerosols on climate, we compared the aerosol vertical profile observations to a one-dimensional radiative transfer model in two metropolitan climate sensible hot-spots in Europe, namely the Po Valley and Benelux, to investigate the variability of the aerosol radiative effects over ten years. The same analysis is carried out as reference on the Sahara desert region, considered subject just to natural local emission. Our findings show the efficacy of emission reduction policies implemented at government level in strongly urbanized regions. The total atmospheric column aerosol load reduction (not observed in Sahara desert region) in Po Valley and Benelux can be associated with: (i) an increase of the energy flux at the surface via direct effects confirmed also by long term surface temperature observations, (ii) a general decrease of the atmospheric column, and likely (iii) an increase in surface temperatures during a ten-year period. Summarizing, the analysis, based on the decade 2007–2016, clearly show an increase of solar irradiation under cloud-free conditions at the surface of +3.6 % and +16.6% for the Po Valley and Benelux, respectively, and a reduction of −9.0% for the Sahara Desert. Full article

(This article belongs to the Special Issue Lidar for Advanced Classification and Retrieval of Aerosols)

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