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Haze refers to an atmospheric phenomenon with extremely low visibility, which has significant impacts on human health and safety. Water vapor alters the scattering properties of atmospheric particulate matter, thus affecting visibility. A comprehensive analysis of the role of water vapor in haze formation is of great scientific significance for forecasting severe pollution weather events. This study investigates the distribution characteristics and variations of water vapor during haze weather in Changchun City (44°N, 125.5°E) in autumn and winter seasons, aiming to reveal the relationship between haze and atmospheric water vapor content. Analysis of observational results for a period of two months (October to November 2023) from a three-wavelength Raman lidar deployed at the site reveals that atmospheric water vapor content is mainly concentrated below 5 km, accounting for 64% to 99% of the total water vapor below 10 km. Furthermore, water vapor content in air pollution exhibits distinct stratification characteristics with altitude, especially within the height range of 1–3 km, where significant water vapor variation layers exist, showing spatial consistency with inversion layers. Statistical analysis of haze events at the site indicates a high correlation between the concentration variations of PM2.5 and PM10 and the variations in average water vapor mixing ratio (WVMR). During haze episodes, the average WVMR within 3 km altitude is 3–4 times higher than that during clear weather. Analysis of spatiotemporal height maps of aerosols and water vapor during a typical haze event suggests that the relative stability of the atmospheric boundary layer may hinder the vertical transport and diffusion of aerosols. This, in turn, could lead to a sharp increase in aerosol extinction coefficients through hygroscopic growth, thereby possibly exacerbating haze processes. These observational findings indicate that water vapor might play a significant role in haze formation, emphasizing the potential importance of observing the vertical distribution of water vapor for better simulation and prediction of haze events. [ABSTRACT FROM AUTHOR]

This study analyzes the vertical distribution, optical properties, radiative forcing, and several perturbation events of stratospheric aerosols using observations from a ground-based polarization lidar in Wuhan (30.5° N, 114.4° E) from 2010 to 2021. The background stratospheric aerosol optical depth (sAOD) was 0.0044 ± 0.0019 at 532 nm , as calculated during a stratosphere-quiescent period from January 2013 to August 2017. In addition, several cases of volcanic aerosol and wildfire-induced smoke were observed. Volcanic aerosols from the Nabro (2011) and Raikoke (2019) eruptions (both in boreal summer) increased the sAOD to 2.9 times the background level. Tracers of smoke from the Canadian wildfire in the summer of 2017 were observed twice, at 19–21 km on 14–17 September and at 20–23 km on 28–31 October, with a plume-isolated aerosol optical depth (AOD) of 0.002–0.010 and a particle linear depolarization ratio δp of 0.14–0.18, indicating the dominance of non-aged smoke particles. During these summertime events, the injected stratospheric aerosols were captured by the large-scale Asian monsoon anticyclone (AMA), confining the transport pathway to mid-latitude Asia. On 8–9 November 2020, smoke plumes originating from the California wildfire in October 2020 appeared at 16–17 km , with a mean δp of 0.13. Regarding seasonal variation, the sAOD in the cold half-year (0.0054) is 69 % larger than in the warm half-year (0.0032) due to stronger meridional transport of stratospheric aerosols from the tropics to middle latitudes. The stratospheric radiative forcing was - 0.11 Wm-2 during the stratosphere-quiescent period and increased to - 0.31 Wm-2 when volcanic aerosols were largely injected. These findings contribute to our understanding of the sources and transport patterns of stratospheric aerosols over mid-latitude Asia and serve as an important database for the validation of model outputs. [ABSTRACT FROM AUTHOR]

Aerosol microphysical properties, including aerosol particle size distribution, complex refractive index and concentration properties, are key parameters evaluating the impact of aerosols on climate, meteorology, and human health. High Spectral Resolution Lidar (HSRL) is an efficient tool for probing the vertical optical properties of aerosol particles, including the aerosol backscatter coefficient (β) and extinction coefficient (α), at multiple wavelengths. To swiftly process vast data volumes, address the ill-posedness of retrieval problems, and suit simpler lidar systems, this study proposes an algorithm (modified algorithm) for retrieving microphysical property profiles from the HSRL optical data targeting fine-mode aerosols, building upon a previous algorithm (basic algorithm). The modified algorithm is based on a look-up table (LUT) approach, combined with the k-nearest neighbor (k-NN) and random forest (RF) algorithms, and it optimizes the decision tree generation strategy, incorporating a self-posed scheme. In numerical simulation tests for different lidar configurations, the modified algorithm reduced retrieval errors by 41%, 30%, and 32% compared to the basic algorithm for 3β + 2α, 3β + 1α, and 2β + 1α, respectively, with a remarkable improvement of stability. In two observation scenes of a field campaign, the median relative errors of the effective radius for 3β + 2α were 6% and −3%, and the median absolute errors of single-scattering albedo were 0.012 and 0.005. This method represents a further step toward the use of the LUT approach, with the potential to provide effective and efficient aerosol microphysical retrieval for simpler lidar systems, which could advance our understanding of aerosols' climatic, meteorological, and health impacts. [ABSTRACT FROM AUTHOR]

Atmospheric constituents feature a large vertical gradient in concentration, especially at the first few hundred meters over the earth's surface. Atmospheric lidar usually cannot cover this range due to the incomplete overlap effect or the limited dynamic range of detectors. This drawback is well known as the blind zone effect, which hinders the application of atmospheric lidars in many aspects. In this work, a method based on an optical fiber bundle was proposed to mitigate the blind zone effect. An optical fiber head with several stages, installed at the focal plane of the telescope, is used to receive backscatter light from different range levels. The design of the optical fiber head is analyzed with the ray-tracing technique. The optical fiber installed at the highest stage of the fiber head can collect far-range light like a small aperture, and all the other optical fibers are bundled into a near-range detection channel to receive backscatter light from the first few hundred meters. This special design can avoid the near-range light loss in conventional lidar systems, usually equipped with a small aperture. Different optical attenuations are then applied to near-range and far-range channels to suppress the overall signal dynamic range. This light-receiving method was applied in a 1030 nm elastic lidar, in which a fiber bundle with a three-stage fiber head was fabricated and installed. A test experiment was performed to verify this approach. A good agreement between simulations and in-system results was found. Based on this design, the blind zone of the lidar system is less than 50 m, and the detectable range can be over 10 km along the lidar's line of sight with a single telescope receiver. This approach brings a new way of designing atmospheric lidar with a low blind zone and can strengthen our ability to monitor urban pollution and promote land-atmosphere interaction research. [ABSTRACT FROM AUTHOR]

Aerosol lidars play a vital role in the investigations of atmospheric pollution formation and meteorological processes. The intensity of lidar return signals in the near range changes much faster compared with the one in the far range, so extremely wide dynamic outputs from the photomultiplier tube (PMT) are needed to avoid saturation in the near range. Usually, to obtain the wide dynamic range, simultaneously, a transient digitizer (Licel) is applied to provide an analog detection chain for strong signals and a photon counting (PC) detection chain for weak signals. However, the near-range signals are still often saturated due to the very high aerosol loading. In this paper, we proposed to use a new PMT module with eight orders of magnitude for a low blind zone lidar, which can achieve both analog and PC separately. A comprehensive evaluation of this potential PMT, which could perform better in near-range detection, compared with the ordinary PMT was tested, but similar features are maintained in the far-range. The photon count rate and signal-to-noise ratio were tested for both the new PMT module and the ordinary PMT module. The results showed that the new PMT module is useful to extend the dynamic range of lidar detection. [ABSTRACT FROM AUTHOR]

Cirrus clouds play an essential role in regulating the global radiative balance and climate by both reflecting the incoming shortwave solar radiation and reserving the outgoing longwave radiation in the atmosphere. The cirrus-induced net radiative forcing is mainly determined by their microphysical properties, which are strongly associated with the competition between two ice-nucleating mechanisms, i.e., heterogeneous and homogeneous nucleation. However, it is still not well understood whether the long-range transoceanic dust can potentially urge heterogeneous nucleation to the initial ice formation in cirrus clouds even farther over vast remote ocean regions and the response of dominant ice-nucleating mechanism to the concentrations of available ice nucleating particles (INPs). Here we report on the influence of transpacific dust plumes on the ice formation in cirrus clouds via heterogeneous nucleation based on the combined observations of space-borne instruments, i.e., the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR). Two cases near Midway Island (28.21° N, 177.38° W), located in the central Pacific, are studied, in which the long-range transported dust plumes originate from intense Asian dust events. For both cases, partial cloud parcels show the typical in-cloud ice crystal number concentrations (ICNC) of <100 L-1 for heterogeneous nucleation with a good agreement (within an order of magnitude) of in-cloud ICNC and nearby dust-related INP concentration (INPC) values, indicating that dust-related heterogeneous nucleation is dominated in ice formation. In addition, for the other parts of clouds without sufficient INP supply, homogeneous nucleation can still be dominated with ICNC values exceeding 300 L-1. Therefore, dust events with sufficient intensity are capable of conducting long-range transport and influencing cirrus formation over remote ocean regions. This study shows that the natural supply of effective INPs to the upper troposphere, such as long-range transported dust aerosols can increase the cloud cover to reflect more solar radiation over oceanic regions and modulate the microphysical properties of cirrus clouds through different ice-nucleating regimes, both of which may further result in a cooling effect on global climate and should be well considered in climate evaluation. [ABSTRACT FROM AUTHOR]

A new version of automatic lidar calibration and processing program was developed to process the data from multiwavelength Raman polarization lidar. The absolute lidar calibration and water vapor calibration algorithms were applied. The program can provide plentiful products, like aerosol backscatter and extinction coefficients, lidar ratio, Ångström exponent, volume and particle depolarization ratios, water vapor mixing ratio and aerosol target classification. Good agreement was found in the comparison with manual quality-assured profiles or radiosonde measurement. Lidar calibration based on the aerosol optical properties retrieved with Raman method, Klett method and AOD-Constrained method were implemented. Good consistency was found.

This paper presents a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection, named DeLiAn, is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements, conducted mainly with lidars that have been developed at the Leibniz Institute for Tropospheric Research. The intensive optical properties are presented at two wavelengths, 355 and 532 nm, for 13 aerosol categories. The categories cover the basic aerosol types (i.e., marine, pollution, continental European background, volcanic ash, smoke, mineral dust), as well as the most frequently observed mixtures they form. This extensive collection also incorporates more peculiar aerosol categories, including dried marine aerosol that, compared to marine aerosol, exhibits a significantly enhanced depolarization ratio (up to 15 %). Besides Saharan dust, additional mineral dust types related to their source region were identified due to their lower lidar ratios (Central Asian and Middle Eastern dust). In addition, extreme wildfire events (such as in north America and Australia) emitted smoke into the stratosphere showing significantly different optical properties, i.e., high depolarization values (up to 25 %), compared to tropospheric smoke. The data collection reflects and underlines the variety of aerosol mixtures in the atmosphere and can be used for the development of aerosol-typing schemes. The paper contains the most up-to-date and comprehensive overview of optical properties from aerosol lidar measurements and, therefore, provides a solid basis for future aerosol retrievals in the frame of both spaceborne and ground-based lidars. Furthermore, DeLiAn can assist the efforts for the harmonization of satellite records of aerosol properties performed at different wavelengths. [ABSTRACT FROM AUTHOR]

Aerosol–cloud interactions (ACIs) are the largest contributor to the uncertainty in the global radiation budget. To improve the current consideration of ACIs in global circulation models, it is necessary to characterize the 3-D distribution of dust-related cloud condensation nuclei concentration (CCNC) and ice-nucleating particle concentration (INPC) globally. This can potentially be realized using the POlarization LIdar PHOtometer Networking (POLIPHON) method together with spaceborne lidar observations. However, dust-related conversion factors that convert bulk aerosol optical properties from lidar measurements to aerosol microphysical properties are still less constrained in many regions, which limits the applications of the POLIPHON method. Here we retrieve the essential dust-related conversion factors at remote oceanic and coastal sites using the historical AErosol RObotic NETwork (AERONET) database. Depolarization-ratio-based dust ratios Rd at 1020 nm are applied to identify the dust-occurring cases, thus enabling us to contain fine-mode dust-dominated cases (after the preferential removal of large-sized dust particles during transport), study the evolution of dust microphysical properties along the transoceanic pathway, and mitigate occasional interference of large-sized marine aerosols. The newly proposed scheme is proven to be valid and feasible by intercomparisons with previous studies at nine sites in/near deserts. The dust-related conversion factors are calculated at 20 oceanic and coastal sites using both pure dust (PD) and PD plus dust-dominated mixture (PD+DDM) datasets. At nearly half of the sites, the conversion factors are solely calculated using the PD datasets, while at the remaining sites, the participation of DDM datasets is required to ensure a sufficient number of data for the calculation. Evident variation trends in conversion factors are found for cv,d (extinction-to-volume concentration, gradually decreasing), c250,d (extinction-to-particle (with a radius > 250 nm) number concentration, gradually increasing), and cs,d (extinction-to-surface-area concentration, gradually decreasing) along both the transpacific and transatlantic dust transport pathways. The retrieved dust-related conversion factors are anticipated to inverse 3-D dust-related CCNC and INPC distributions globally, thereby improving the understanding of ACIs in atmospheric circulation models. [ABSTRACT FROM AUTHOR]