Ground-based Lidar Observations Research Articles

The impact of volcanic eruptions, pyrocumulonimbus plumes, and the Arctic polar vortex intrusions on aerosol loading over Tomsk (Western Siberia, Russia) as observed by lidar from 2018 to 2022

ABSTRACT Long-term ground-based lidar observations are important in estimating the contribution of different sources (mostly volcanic eruptions and wildfires) to aerosol loading of the atmosphere and in developing and improving various climate models. In this paper, we carefully analyse aerosol scattering ratio profiles and aerosol layers, observed with 532-nm lidar measurements at the Siberian Lidar Station in Tomsk (56.48°N, 85.05°E) over the period 2018–2022, and identify the layers’ potential sources. To compare aerosol loading over Tomsk for the last five years (2018–2022) with that for previous years, we also present and discuss time series of integrated aerosol backscatter coefficient (IABC) for three altitude ranges. The first range (15–30 km) reveals the pure stratospheric aerosol loading provided by volcanic eruptions, the second range (11–15 km) is responsible mainly for aftereffects of wildfire smoke plumes, and the third one (11–30 km) demonstrates aerosol contribution from both sources. In particular, we found for the period 2001–2022 that the annual average IABC reached its maximal values of 2.91 × 10−4 sr−1 (15–30 km) and 8.21 × 10−4 sr−1 (11–30 km) in 2022 due to the Hunga Tonga-Hunga Ha’apai volcanic eruption. The period 2020–2022 exhibited a significant increase in the relative aerosol content at altitudes of 11–15 km in the total aerosol loading at 11–30 km over Tomsk from 54.4% in 2020 to 64.8% in 2022, which indicates a shift of the main part of aerosol loading to altitudes of 11–15 km due to the increased wildfire activity in North America and north-eastern Asia. The Arctic polar vortex is also revealed to distort the real aerosol vertical distribution over Tomsk by replacing it with the aerosol distribution inside the vortex on measurement days when the vortex is over the lidar site.

Characteristics of Cloud and Aerosol Derived from Lidar Observations during Winter in Lhasa, Tibetan Plateau

In order to investigate the variations of cloud and aerosol vertical profiles over the Tibetan Plateau (TP) in winter, we performed ground-based lidar observations in Lhasa, a city on the TP, from November 2021 to January 2022. The profiles of extinction coefficient, depolarization ratio, and signal-to-noise ratio (SNR) were retrieved using the atmospheric echo signals collected by the lidar. Clouds were identified by the range-correction echo signals and classified into water clouds, mixed clouds, horizontally oriented ice crystal clouds (HOICC), and ice clouds by the depolarization ratio and the hourly temperature from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5). The clouds mainly appeared at a height of 3~5 km from 14:00–22:00 Beijing Time throughout the field campaign. The height and frequency (~30%) for cloud appearance were significantly lower than that reported in previous studies in summer. The cloud categories were dominated by mixed clouds and ice clouds during the observation period. The proportions of ice clouds gradually increased with increasing heights. After eliminating profiles influenced by clouds, the aerosol extinction coefficient and depolarization ratio were obtained, and the atmospheric boundary layer height (ABLH) was calculated. The aerosol extinction coefficient decreased with increasing height in the ABLH, and there were no obvious changes for the aerosol extinction coefficient above the ABL. The aerosol extinction coefficients near the Earth’s surface presented two peaks, appearing in the morning and evening, respectively. The high aerosols at the surface in the morning continually spread upward for 4–5 h and finally reached an altitude of 1 km with the development of ABLH. In addition, the depolarization ratio of aerosols decreased slowly with increasing altitudes. There was no obvious diurnal variation for depolarization ratios, indicating partly that the source of aerosols did not change significantly. These results are beneficial in understanding the evolution of cloud and aerosol vertical profiles over the TP.

Characteristics and seasonal variations of cirrus clouds from ground-based lidar and satellite observations over Shouxian Area, China

This study investigates the macroscopic and optical properties of cirrus clouds in the 32N region from July 2016 to May 2017, leveraging data from ground-based lidar observations and CALIOP to overcome the inconsistencies in detected cirrus cloud samples. Through extensive data analysis, statistical characteristics of cirrus clouds were discerned, revealing lidar ratio values of 28.5 ± 10.8 from ground-based lidar and 27.4 ± 11.2 from CALIOP. Validation with a decade of CALIOP data (2008-2018) confirmed these findings, presenting a consistent lidar ratio of 27.4 ± 12.0. A significant outcome of the analysis was the identification of a positive correlation between the lidar ratio and cloud centroid temperature, indicating a gradual decrease in the lidar ratio as temperatures dropped. The study established a fundamental consistency in their macroscopic properties, including cloud base height, cloud top height, cloud thickness, cloud centroid height, and cloud centroid temperature. The results for ground-based lidar (CALIOP) are: 10.0 ± 2.1 km (10.0 ± 2.2 km), 11.8 ± 2.1 km (11.5 ± 2.3 km), 1.87 ± 0.83 km (1.52 ± 0.71 km), and 10.5 ± 2.2 km, -46.9 ± 9.7°C (-47.1 ± 10.0°C).These properties exhibited seasonal variations, with cirrus clouds reaching higher altitudes in summer and lower in winter, influenced by the height of the tropopause. The optical properties of cirrus clouds were also analyzed, showing an annual average optical depth of 0.31 ± 0.35 for ground-based lidar and 0.32 ± 0.44 for CALIOP. The study highlighted the distribution of subvisible, thin, and thick cirrus clouds, with a notable prevalence of subvisible clouds during summer, suggesting their frequent formation above 14 km. Furthermore, the study observed linear growth in geometric thickness and optical depth up to 2.5 km from CALIOP and 2.9 km from ground-based lidar. Maximum optical depth was observed at cloud centroid temperatures of -35°C for CALIOP and -40°C for ground-based lidar, with optical depth decreasing as temperatures fell. This suggests that fully glaciated cirrus clouds exhibit the highest optical depth at warmer temperatures, within the complete glaciation temperature range of -35°C to -40°C.

Trans-Boundary Dust Transport of Dust Storms in Northern China: A Study Utilizing Ground-Based Lidar Network and CALIPSO Satellite

During 14–16 March 2021, a large-scale dust storm event occurred in the northern region of China, and it was considered the most intense event in the past decade. This study employs observation data for PM2.5 and PM10 from the air quality monitoring station, the HYSPLIT model, ground-based polarized Lidar networks, AGRI payload data from Fengyun satellites and CALIPSO satellite Lidar data to jointly explore and scrutinize the three-dimensional spatial and temporal characteristics of aerosol transport. Firstly, by integrating meteorological data for PM2.5 and PM10, the air quality is assessed across six stations within the Lidar network during the dust storm. Secondly, employing a backward trajectory tracking model, the study elucidates sources of dust at the Lidar network sites. Thirdly, deploying a newly devised portable infrared 1064 nm Lidar and a pulsed 532 nm Lidar, a ground-based Lidar observation network is established for vertical probing of transboundary dust transport within the observed region. Finally, by incorporating cloud imagery from Fengyun satellites and CALIPSO satellite Lidar data, this study revealed the classification of dust and the height distribution of dust layers at pertinent sites within the Lidar observation network. The findings affirm that the eastward movement and southward compression of the intensifying Mongolian cyclone led to severe dust storm weather in western and southern Mongolia, as well as Inner Mongolia, further transporting dust into northern, northwestern, and northeastern parts of China. This dust event wielded a substantial impact on a broad expanse in northern China, manifesting in localized dust storms in Inner Mongolia, Beijing, Gansu, and surrounding areas. In essence, the dust emanated from the deserts in Mongolia and northwest China, encompassing both deserts and the Gobi region. The amalgamation of ground-based and spaceborne Lidar observations conclusively establishes that the distribution height of dust in the source region ranged from 3 to 5 km. Influenced by high-pressure systems, the protracted transport of dust over extensive distances prompted a gradual reduction in its distribution height owing to sedimentation. The comprehensive analysis of pertinent research data and information collectively affirms the precision and efficacy of the three-dimensional aerosol monitoring conducted by the ground-based Lidar network within the region.

Estimates of Southern Hemispheric Gravity Wave Momentum Fluxes across Observations, Reanalyses, and Kilometer-Scale Numerical Weather Prediction Model

Abstract Gravity waves (GWs) are among the key drivers of the meridional overturning circulation in the mesosphere and upper stratosphere. Their representation in climate models suffers from insufficient resolution and limited observational constraints on their parameterizations. This obscures assessments of middle atmospheric circulation changes in a changing climate. This study presents a comprehensive analysis of stratospheric GW activity above and downstream of the Andes from 1 to 15 August 2019, with special focus on GW representation ranging from an unprecedented kilometer-scale global forecast model (1.4 km ECMWF IFS), ground-based Rayleigh lidar (CORAL) observations, modern reanalysis (ERA5), to a coarse-resolution climate model (EMAC). Resolved vertical flux of zonal GW momentum (GWMF) is found to be stronger by a factor of at least 2–2.5 in IFS compared to ERA5. Compared to resolved GWMF in IFS, parameterizations in ERA5 and EMAC continue to inaccurately generate excessive GWMF poleward of 60°S, yielding prominent differences between resolved and parameterized GWMFs. A like-to-like validation of GW profiles in IFS and ERA5 reveals similar wave structures. Still, even at ∼1 km resolution, the resolved waves in IFS are weaker than those observed by lidar. Further, GWMF estimates across datasets reveal that temperature-based proxies, based on midfrequency approximations for linear GWs, overestimate GWMF due to simplifications and uncertainties in GW wavelength estimation from data. Overall, the analysis provides GWMF benchmarks for parameterization validation and calls for three-dimensional GW parameterizations, better upper-boundary treatment, and vertical resolution increases commensurate with increases in horizontal resolution in models, for a more realistic GW analysis. Significance Statement Gravity wave–induced momentum forcing forms a key component of the middle atmospheric circulation. However, complete knowledge of gravity waves, their atmospheric effects, and their long-term trends are obscured due to limited global observations, and the inability of current climate models to fully resolve them. This study combines a kilometer-scale forecast model, modern reanalysis, and a coarse-resolution climate model to first compare the resolved and parameterized momentum fluxes by gravity waves generated over the Andes, and then evaluate the fluxes using a state-of-the-art ground-based Rayleigh lidar. Our analysis reveals shortcomings in current model parameterizations of gravity waves in the middle atmosphere and highlights the sensitivity of the estimated flux to the formulation used.

Evolution of aerosol plumes from 2019 Raikoke volcanic eruption observed with polarization lidar over central China

The Raikoke volcano erupted on 21–22 June 2019 and emitted large amounts of volcanic ash into the upper troposphere, and later might impose long-term effects on the global and regional radiation budget after the long-range transport of volcanic aerosol plumes. Height-resolved ground-based lidar observations are beneficial to trace and cross-check the 3-D evolution of complicated aerosol plumes, which are, however, scarce at mid-latitude regions. Here, we present a rare ground-based lidar observation of Raikoke aerosol plumes in the mid-latitudes of the Northern Hemisphere (site: Wuhan; location: 30.5°N, 114.4°E) from 25 July to 30 September 2019. The main aerosol plume first arrived at Wuhan on 25 July and was intermittently observed during the following 2 months at altitudes of 15.0–20.5 km. From 22 August to 23 September, this aerosol plume underwent two quasi-elliptical transport pathways in East Asia driven by an Asian monsoon anticyclone. The particle depolarization ratio of volcanic aerosols is < 0.05. The layer-integrated AODs (aerosol optical depths) of 0.001–0.017 are smaller than those observed from other high-altitude sites previously owing to the dispersal of particles. Interestingly, another separated dense aerosol cloud was observed twice, closely followed by a thin and horizontally extended aerosol plume (named ‘trail’). This study provides valuable information for studying the evolution of the vertical distribution and optical properties of Raikoke volcanic aerosols, which is anticipated to be a crucial supplement/reference for dispersion model simulation, data assimilation, and forecasting refinement.

DeLiAn – a growing collection of depolarization ratio, lidar ratio and Ångström exponent for different aerosol types and mixtures from ground-based lidar observations

Abstract. 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.

Self-lofting of wildfire smoke in the troposphere and stratosphere: simulations and space lidar observations

Abstract. Wildfire smoke is known as a highly absorptive aerosol type in the shortwave wavelength range. The absorption of sunlight by optically thick smoke layers results in heating of the ambient air. This heating is translated into self-lofting of the smoke up to more than 1 km in altitude per day. This study aims for a detailed analysis of tropospheric and stratospheric smoke lofting rates based on simulations and observations. The main goal is to demonstrate that radiative heating of intense smoke plumes is capable of lofting them from the lower and middle free troposphere (injection heights) up to the tropopause without the need of pyrocumulonimbus (pyroCb) convection. The further subsequent ascent within the lower stratosphere (caused by self-lofting) is already well documented in the literature. Simulations of absorbed solar radiation by smoke particles and resulting heating rates, which are then converted into lofting rates, are conducted by using the ECRAD (European Centre for Medium-Range Weather Forecasts Radiation) scheme. As input parameters thermodynamic profiles from CAMS (Copernicus Atmosphere Monitoring Service) reanalysis data, aerosol profiles from ground-based lidar observations, radiosonde potential temperature profiles, CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) aerosol measurements, and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth retrievals were used. The sensitivity analysis revealed that the lofting rate strongly depends on aerosol optical thickness (AOT), layer depth, layer height, and black carbon (BC) fraction. We also looked at the influence of different meteorological parameters such as cloudiness, relative humidity, and potential temperature gradient. To demonstrate the applicability of our self-lofting model, we compared our simulations with the lofting processes in the stratosphere observed with CALIOP after major pyroCb events (Canadian fires in 2017, Australian fires in 2019–2020). We analyzed long-term CALIOP observations of smoke layers and plumes evolving in the UTLS (upper troposphere and lower stratosphere) height region over Siberia and the adjacent Arctic Ocean during the summer season of 2019. Our results indicate that self-lofting contributed to the vertical transport of smoke. We hypothesize that the formation of a near-tropopause aerosol layer, observed with CALIOP, was the result of self-lofting processes because this is in line with the simulations. Furthermore, Raman-lidar-based aerosol typing (in Leipzig and the High Arctic) clearly indicated the dominance of smoke in the UTLS aerosol layer since August 2019, most probably also the result of smoke self-lofting.

Classification of Cloud Phase Using Combined Ground-Based Polarization Lidar and Millimeter Cloud Radar Observations Over the Tibetan Plateau

Classification of Cloud Phase Using Combined Ground-Based Polarization Lidar and Millimeter Cloud Radar Observations Over the Tibetan Plateau

Lidar-based daytime boundary layer height variation and impact on the regional satellite-based PM2.5 estimate

Satellite-derived aerosol optical depth (AOD) is popularly used to infer ground-level PM2.5 concentration due to its wide coverage. The fact that aerosols are largely confined in the atmospheric boundary layer makes boundary layer height (BLH) an important scale factor for AOD-based PM2.5 estimates. Our recent ground-based lidar observations, nevertheless, indicate that aerosol particles are heterogeneously mixed within the boundary layer, and even frequently reside above BLH, forming the residual layers (RL)-like pattern. To better sort out the underlying mechanism behind the above-mentioned phenomenon and the impact on hourly ground-level PM2.5 estimates from satellite-based AOD, we firstly propose a novel notion of haze layer height (HLH), which is calculated from Micro-Pulse Lidar (MPL) profile. Combined analysis of 3.5-year ground-based lidar profiles, CE-318 AOD, and PM2.5 measurements show that the coefficient of determination (R2) between PM2.5 and AOD normalized with HLH increases from 0.49 to 0.61 for 90% of the dataset. Second, we applied HLH to an Auto-encoder-based Deep Residual Network (ADRN) and tested the effect on satellite AOD-based PM2.5 estimation within a 300 km range surrounding the MPL station. With the aid of the AOD imputation technique, a similar improvement of using HLH instead is found on the regional scale PM2.5 estimation, which can be demonstrated by the comparison with air quality measurements and other machine learning models. The results show that using ADRN with HLH achieves the highest performance (mean R2 = 0.87, RMSE = 10.12 μg/m3) among 4 machine learning models. This new approach, largely combining active and passive remote sensing data through artificial neural networks (CAPTA), shows improved accuracy and coverage of hourly PM2.5 estimation with aerosol vertical information and AOD calculation under clouds. In addition, further analysis showed that the average difference between morning and daily PM2.5 concentration could equate to an accuracy of 0.19–2.57 yrs. in terms of life expectancy, indicating that our new approach to the determination of PM2.5 from space sheds new insight into the assessment of the aerosol impact on public health.

Observations of cold-cloud properties in the Norwegian Arctic using ground-based and spaceborne lidar

Abstract. The role of clouds in the surface radiation budget is particularly complex in the rapidly changing Arctic. However, despite their importance, long-term observations of Arctic clouds are relatively sparse. Here, we present observations of cold clouds based on 7 years (2011–2017) of ground-based lidar observations at the Arctic Lidar Observatory for Middle Atmosphere Research (ALOMAR) in Andenes in the Norwegian Arctic. In two case studies, we assess (1) the agreement between a co-located cirrus cloud observations from the ground-based lidar and the spaceborne lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and (2) the ground-based lidar's capability to determine the cloud phase in mixed-phase clouds from depolarization measurements. We then compute multiyear statistics of cold clouds from both platforms with respect to their occurrence, cloud top and base height, cloud top temperature, and thermodynamic phase for the 2011–2017 period. We find that satellite- and ground-based observations agree well with respect to the coincident cirrus measurement and that the vertical phase distribution within a liquid-topped mixed-phase cloud could be identified from depolarization measurements. On average, 8 % of all satellite profiles were identified as single-layer cold clouds with no apparent seasonal differences. The average cloud top and base heights, combining the ground-based and satellite measurements, are 9.1 and 6.9 km, respectively, resulting in an average thickness of 2.2 km. Seasonal differences between the average top and base heights are on the order of 1–2 km and are largest when comparing fall (highest) and spring (lowest). However, seasonal variations are small compared with the observed day-to-day variability. Cloud top temperatures agree well between both platforms, with warmer cloud top temperatures in summer. The presented study demonstrates the capabilities of long-term cloud observations in the Norwegian Arctic from the ground-based lidar at Andenes.

Record-breaking dust loading during two mega dust storm events over northern China in March 2021: aerosol optical and radiative properties and meteorological drivers

Abstract. Although a remarkable reduction in the frequency of sand and dust storms (SDSs) in the past several decades has been reported over northern China (NC), two unexpected mega SDSs occurred on 15–20 and 27–29 March 2021 (abbreviated as the “3.15” and “3.27” SDS events), which has reawakened widespread concern. This study characterizes the optical, microphysical, and radiative properties of aerosols and their meteorological drivers during these two SDS events using the Sun photometer observations in Beijing and a comprehensive set of multiple satellite (including MODIS, VIIRS, CALIOP, and Himawari-8) and ground-based observations (including the CMA visibility network and AD-Net) combined with atmospheric reanalysis data. Moreover, a long-term (2000–2021) dust optical depth (DOD) dataset retrieved from MODIS measurements was also utilized to evaluate the historical ranking of the dust loading in NC during dust events. During the 3.15 and 3.27 events, the invasion of dust plumes greatly degraded the visibility over large areas of NC, with extreme low visibility of 50 and 500 m recorded at most sites on 15 and 28 March, respectively. Despite the shorter duration of the 3.27 event relative to the 3.15 event, sun photometer and satellite observations in Beijing recorded a larger peak AOD (∼2.5) in the former than in the latter (∼2.0), which was mainly attributed to the short-term intrusion of coarse-mode dust particles with larger effective radii (∼1.9 µm) and volume concentrations (∼2.0 µm3 µm−2) during the 3.27 event. The shortwave direct aerosol radiative forcing induced by dust was estimated to be −92.1 and −111.4 W m−2 at the top of the atmosphere, −184.7 and −296.2 W m−2 at the surface, and +92.6 and +184.8 W m−2 in the atmosphere in Beijing during the 3.15 and 3.27 events, respectively. CALIOP observations show that during the 3.15 event the dust plume was lifted to an altitude of 4–8 km, and its range of impact extended from the dust source to the eastern coast of China. In contrast, the lifting height of the dust plume during the 3.27 event was lower than that during the 3.15 event, which was also confirmed by ground-based lidar observations. The MODIS-retrieved DOD data registered these two massive SDS events as the most intense episode in the same period in history over the past 2 decades. These two extreme SDS events were associated with both atmospheric circulation extremes and local meteorological anomalies that favored enhanced dust emissions in the Gobi Desert (GD) across southern Mongolia and NC. Meteorological analysis revealed that both SDS events were triggered by an exceptionally strong Mongolian cyclone generated at nearly the same location (along the central and eastern plateau of Inner Mongolia) in conjunction with a surface-level cold high-pressure system at the rear, albeit with differences in magnitude and spatial extent of impact. In the GD, the early melting of spring snow caused by near-surface temperature anomalies over dust source regions, together with negative soil moisture anomalies induced by decreased precipitation, formed drier and barer soil surfaces, which allowed for increased emissions of dust into the atmosphere by strongly enhanced surface winds generated by the Mongolian cyclone.

Polarization Lidar Measurements of Dust Optical Properties at the Junction of the Taklimakan Desert–Tibetan Plateau

Previous studies have shown that dust aerosols may accelerate the melting of snow and glaciers over the Tibetan Plateau. To investigate the vertical structure of dust aerosols, we conducted a ground-based observation by using multi-wavelength polarization lidar which is designed for continuous network measurements. In this study, we used the lidar observation from September to October 2020 at the Ruoqiang site (39.0°N, 88.2°E; 894 m ASL), located at the junction of the Taklimakan Desert–Tibetan Plateau. Our results showed that dust aerosols can be lifted up to 5 km from the ground, which is comparable with the elevation of the Tibetan Plateau in autumn with a mass concentration of 400–900 μg m−3. Moreover, the particle depolarization ratio (PDR) of the lifted dust aerosols at 532 nm and 355 nm are 0.34 ± 0.03 and 0.25 ± 0.04, respectively, indicating the high degree of non-sphericity in shape. In addition, extinction-related Ångström exponents are very small (0.11 ± 0.24), implying the large values in size. Based on ground-based lidar observation, this study proved that coarse non-spherical Taklimakan dust with high concentration can be transported to the Tibetan Plateau, suggesting its possible impacts on the regional climate and ecosystem.

Aerosols Direct Radiative Effects Combined Ground-Based Lidar and Sun-Photometer Observations: Cases Comparison between Haze and Dust Events in Beijing

Aerosols can affect vertical thermal structure during heavily polluted episodes (HPEs). Here, we selected four typical HPEs in 2018, which were further subdivided into dust and haze events. The vertical distribution of aerosols extinction coefficient (EC) and variations in columnar optical properties were investigated based on sun-photometer and Lidar observation at an urban site in Beijing. The vertical characteristics in shortwave radiative heating rate (HR) of aerosols were studied using NASA/Goddard radiative transfer model along with observational data. In the haze episode, EC layer is less than 1.5 km and shows strong scattering, with single-scattering albedo (SSA440nm) of ~0.97. The heating effects are observed at the middle and upper atmosphere, and slight heating effects are found at the lower layer. The mean HR within 1.5 km can be up to 16.3 K day−1 with EC of 1.27 km−1, whereas the HR within 0.5 km is only 1.3 K day−1. In the dust episode, dust aerosols present the absorption with SSA440nm of ~0.88, which would heat the lower atmosphere to promote vertical turbulence, and the height of EC layer can be up to 2.0–3.5 km. In addition, the strong heating effects of dust layer produced cooling effects near the surface. Therefore, the accurate measurement of aerosols optical properties in HPEs is of great significance for modeling aerosols direct radiative effects.

Detection by Space-Borne and Ground-Based Lidar Observations of Air Pollution on the Example of the Hefei Area

Detection by Space-Borne and Ground-Based Lidar Observations of Air Pollution on the Example of the Hefei Area

Microphysical process of precipitating hydrometeors from warm-front mid-level stratiform clouds revealed by ground-based lidar observations

Abstract. Mid-level stratiform precipitations during the passage of warm fronts were detailedly observed on two occasions (light and moderate rain) by a 355 nm polarization lidar and water vapor Raman lidar, both equipped with waterproof transparent roof windows. The hours-long precipitation streaks shown in the lidar signal (X) and volume depolarization ratio (δv) reveal some ubiquitous features of the microphysical process of precipitating hydrometeors. We find that for the light-rain case precipitation that reaches the surface begins as ice-phase-dominant hydrometeors that fall out of a shallow liquid cloud layer at altitudes above the 0 ∘C isotherm level, and the depolarization ratio magnitude of falling hydrometeors increases from the liquid-water values (δv&lt;0.09) to the ice/snow values (δv&gt;0.20) during the first 100–200 m of their descent. Subsequently, the falling hydrometeors yield a dense layer with an ice/snow bright band occurring above and a liquid-water bright band occurring below (separated by a lidar dark band) as a result of crossing the 0 ∘C level. The ice/snow bright band might be a manifestation of local hydrometeor accumulation. Most falling raindrops shrink or vanish in the liquid-water bright band due to evaporation, whereas a few large raindrops fall out of the layer. We also find that a prominent δv peak (0.10–0.40) always occurs at an altitude of approximately 0.6 km when precipitation reaches the surface, reflecting the collision–coalescence growth of falling large raindrops and their subsequent spontaneous breakup. The microphysical process (at ice-bright-band altitudes and below) of moderate rain resembles that of the light-rain case, but more large-sized hydrometeors are involved.

Tropospheric and stratospheric wildfire smoke profiling with lidar: mass, surface area, CCN, and INP retrieval

Abstract. We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area, and number concentrations in the case of wildfire smoke layers as well as estimates of smoke-related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations from backscatter lidar measurements on the ground and in space. Conversion factors used to convert the optical measurements into microphysical properties play a central role in the data analysis, in addition to estimates of the smoke extinction-to-backscatter ratios required to obtain smoke extinction coefficients. The set of needed conversion parameters for wildfire smoke is derived from AERONET observations of major smoke events, e.g., in western Canada in August 2017, California in September 2020, and southeastern Australia in January–February 2020 as well as from AERONET long-term observations of smoke in the Amazon region, southern Africa, and Southeast Asia. The new smoke analysis scheme is applied to CALIPSO observations of tropospheric smoke plumes over the United States in September 2020 and to ground-based lidar observation in Punta Arenas, in southern Chile, in aged Australian smoke layers in the stratosphere in January 2020. These case studies show the potential of spaceborne and ground-based lidars to document large-scale and long-lasting wildfire smoke events in detail and thus to provide valuable information for climate, cloud, and air chemistry modeling efforts performed to investigate the role of wildfire smoke in the atmospheric system.

Constraining Ice Water Content of Thin Antarctic Cirrus Clouds Using Ground-Based Lidar and Satellite Data

AbstractWe combine observations of optically thin cirrus clouds made by lidar at Davis, Antarctica (69°S, 78°E), during 14–15 June 2011 with a microphysical retrieval algorithm to constrain the ice water content (IWC) of these clouds. The cirrus clouds were embedded in a tropopause jet that flowed around a ridge of high pressure extending southward over Davis from the Southern Ocean. Cloud optical depths were 0.082 ± 0.001, and subvisual cirrus were present during 11% of the observation period. The macrophysical cirrus cloud properties obtained during this case study are consistent with those previously reported at lower latitudes. MODIS satellite imagery and AIRS surface temperature data are used as inputs into a radiative transfer model in order to constrain the IWC and ice water path of the cirrus. The derived cloud IWC is consistent with in situ observations made at other locations but at similarly cold temperatures. The optical depths derived from the model agree with those calculated directly from the lidar data. This study demonstrates the value of a combination of ground-based lidar observations and a radiative transfer model in constraining microphysical cloud parameters that could be utilized at locations where other lidar measurements are made.

Synergy processing of diverse ground-based remote sensing and in situ data using the GRASP algorithm: applications to radiometer, lidar and radiosonde observations

Abstract. The exploration of aerosol retrieval synergies from diverse combinations of ground-based passive Sun-photometric measurements with collocated active lidar ground-based and radiosonde observations using versatile Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm is presented. Several potentially fruitful aspects of observation synergy were considered. First, a set of passive and active ground-based observations collected during both day- and nighttime was inverted simultaneously under the assumption of temporal continuity of aerosol properties. Such an approach explores the complementarity of the information in different observations and results in a robust and consistent processing of all observations. For example, the interpretation of the nighttime active observations usually suffers from the lack of information about aerosol particles sizes, shapes and complex refractive index. In the realized synergy retrievals, the information propagating from the nearby Sun-photometric observations provides sufficient constraints for reliable interpretation of both day- and nighttime lidar observations. Second, the synergetic processing of such complementary observations with enhanced information content allows for optimizing the aerosol model used in the retrieval. Specifically, the external mixture of several aerosol components with predetermined sizes, shapes and composition has been identified as an efficient approach for achieving reliable retrieval of aerosol properties in several situations. This approach allows for achieving consistent and accurate aerosol retrievals from processing stand-alone advanced lidar observations with reduced information content about aerosol columnar properties. Third, the potential of synergy processing of the ground-based Sun-photometric and lidar observations, with the in situ backscatter sonde measurements was explored using the data from KAUST.15 and KAUST.16 field campaigns held at King Abdullah University of Science and Technology (KAUST) in the August of 2015 and 2016. The inclusion of radiosonde data has been demonstrated to provide significant additional constraints to validate and improve the accuracy and scope of aerosol profiling. The results of all retrieval setups used for processing both synergy and stand-alone observation data sets are discussed and intercompared.

Long-range transport of Siberian biomass burning emissions to North America during FIREX-AQ

Biomass burning from wildfires is a significant global source of aerosol and trace gases which impact air quality, tropospheric and stratospheric composition, and climate. During the summer of 2019, wildfire activity in central and eastern Siberia occurred during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign conducted in the United States between July 24 and September 6, 2019. Ground-based lidar observations from the Autonomous Mobile Ozone Lidar for Tropospheric Experiments (AMOLITE) system in Alberta, Canada retrieved frequent ozone (O3) and aerosol lamina in the free troposphere during the campaign. Simulated data from NASA's GEOS Composition Forecast (GEOS-CF) coupled chemistry meteorology model, TROPOspheric Monitoring Instrument (TROPOMI), and ground-based in situ measurements were applied to define the trans-Pacific and trans-Arctic transport pathways of Siberian biomass burning emissions resulting in the enhanced O3 and aerosol lamina observed by AMOLITE in western Canada. Siberian wildfires had some influence on North American air quality resulting in enhancements of surface carbon monoxide (CO) and fine particulate matter (PM2.5) concentrations in western Canada; however, minimal increases in surface-level O3 were measured as well as modeled by GEOS-CF. The impact in western Canada was larger in the free troposphere, demonstrated by GEOS-CF modeled and AMOLITE observed O3 lamina >20 ppb above background values and coincident model-predicted PM2.5 lamina >30 μg m−3. This study demonstrated that the Siberian biomass burning emissions in the summer of 2019 impacted tropospheric composition in western Canada, and potentially could have influenced areas in the vicinity of FIREX-AQ airborne and ground-based measurements in the United States, and should be considered in future studies.