High Spectral Resolution Lidar Research Articles

Simultaneous profiling of dust aerosol mass concentration and optical properties with polarized high-spectral-resolution lidar

Dust particles originating from arid desert regions can be transported over long distances, presenting severe risks to climate, environment, social economics, and human health at the source and downwind regions. However, there has been a dearth of continuous diurnal observations of vertically resolved mass concentration and optical properties of dust aerosols, which hinders our understanding of aerosol mixing, stratification, aerosol-cloud interactions, and their impacts on the environment. To fill the gap of the insufficient observations, to the best of our knowledge, this work presents the first high-spectral-resolution lidar (HSRL) observation providing days of continuous profiles of the mass concentration, along with particle linear depolarization ratio (PLDR), backscattering coefficient, extinction coefficient and lidar ratio (LR), simultaneously. We present the results of two strong dust events observed by HSRL over Beijing in 2021. The maximum particle mass concentrations reached (1.52 ± 3.5) x103 μg/m3 and (19.48 ± 0.36) x103 μg/m3 for the two dust events, respectively. The retrieved particle mass concentrations and aerosol optical depth (AOD) agree well with the observation from the surface PM10 concentrations and sun photometer with correlation coefficients of 0.90 and 0.95, respectively. The intensive properties of PLDR and LR of the dust aerosols are 0.31 ± 0.02 and 39 ± 7 sr at 532 nm, respectively, which are generally close to those obtained from observations in the downwind areas. Moreover, inspired by the observations from HSRL, a universal analytical relationship is discovered to evaluate the proportion of dust aerosol backscattering, extinction, AOD, and mass concentration using PLDR. The universal analytical relationship reveals that PLDR can directly quantify dust aerosol contribution, which is expected to further expand the application of polarization technology in dust detection. These valuable observations and findings further our understanding of the contribution of dust aerosol to the environment and help supplement dust aerosol databases.

Estimates of the spatially complete, observational-data-driven planetary boundary layer height over the contiguous United States

Abstract. This study aims to generate a spatially complete planetary boundary layer height (PBLH) product over the contiguous United States (CONUS). An eXtreme Gradient Boosting (XGB) regression model was developed using selected meteorological and geographical data fields as explanatory variables to fit the PBLH values derived from Aircraft Meteorological DAta Relay (AMDAR) reports hourly profiles at 13:00–14:00 LST (local solar time) during 2005–2019. A preprocessing step was implemented to exclude AMDAR data points that were unexplainable by the predictors, mostly under stable conditions. The PBLH prediction by this work as well as PBLHs from three reanalysis datasets (the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate – ERA5; the Modern-Era Retrospective analysis for Research and Applications, Version 2 – MERRA-2; and the North American Regional Reanalysis – NARR) were compared to reference PBLH observations from spaceborne lidar (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations, CALIPSO), airborne lidar (High Spectral Resolution Lidar, HSRL), and in situ research aircraft profiles from the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaigns. Compared with PBLHs from reanalysis products, the PBLH prediction from this work shows closer agreement with the reference observations, with the caveat that different PBLH products and estimates have different ways of identifying the PBLH; thus, their comparisons should be interpreted with caution. The reanalysis products show significant high biases in the western CONUS relative to the reference observations. One direct application of the dataset generated by this work is that it enables sampling of the PBLH at the sounding locations and times of sensors aboard satellites with an overpass time in the early afternoon, e.g., the Afternoon Train (A-train), the Suomi National Polar-orbiting Partnership (Suomi NPP), the Joint Polar Satellite System (JPSS), and the Sentinel-5 Precursor (Sentinel-5P) satellite sensors. As both AMDAR and ERA5 are continuous at hourly resolution, the observational-data-driven PBLHs may be extended to other daytime hours.

A New Semi-Analytical MC Model for Oceanic LIDAR Inelastic Signals

The design and processing algorithm of oceanic LIDAR requires an effective lidar simulator. Currently, most simulation methods for lidar signal propagation in seawater use elastic scattering. In this study, a new semi-analytical Monte Carlo (MC) model for oceanic lidar inelastic signals is developed to investigate chlorophyll fluorescence and Raman scattering in seawater. We also used this model to simulate the echo signal of high spectral resolution lidar (HSRL) in the particulate and water molecular channels. Using this model, the effects of chlorophyll concentration, multiple scattering, receiving field of view (FOV), scattering phase function (SPF), receiver full width at half maximum (FWHM) and inhomogeneous seawater were investigated. The feasibility and effectiveness of the model were verified by the lidar equation under small and large FOVs. The results showed that chlorophyll concentration and vertical structure and multiple scattering have considerable and integrated effects on echo signals, which could provide a reference for the design of oceanic fluorescence and HSRL lidar systems and contribute to the development of processing algorithms.

Blowing Snow at McMurdo Station, Antarctica During the AWARE Field Campaign: Multi‐Instrument Observations of Blowing Snow

AbstractIn polar regions, blowing snow (BLSN) can play a substantial role in regional thermodynamics and radiation properties. The extent of the impact depends upon the depth of the BLSN layer, a property that is difficult to measure and not well understood. The West Antarctic Radiation Experiment (AWARE) Field Campaign saw the deployment of a large suite of observational instruments to McMurdo Station, Antarctica, allowing for in‐depth investigation of BLSN. During the year of the campaign, BLSN occurred ∼7.4% of the time. In this study, additional remote sensing observations are used to supplement an existing ceilometer‐based BLSN characterization algorithm creating a multi‐instrument (MI) depth estimation algorithm to yield layer depths with more certainty. Backscatter coefficient and linear depolarization ratios from the micropulse and high spectral resolution lidar (HSRL) are incorporated along with color ratio derived from HSRL backscatter and Ka‐band radar reflectivity observations. This provided estimates of BLSN depth that were less impacted by noise/artifacts in any one set of observations. When applied to the data from AWARE, the MI algorithm yielded an average depth of 168.2 m with ∼60% of plumes less than 200 m in depth. Events occurring with precipitation saw the most value in the additional instruments, with the suite of observations allowing for more separation of BLSN particles from fallstreaks.

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

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%.

Accurate measurement of aerosol optical properties using the multilongitudinal mode high-spectral-resolution lidar with self-tuning Mach–Zehnder interferometer

The multilongitudinal mode (MLM) high-spectral-resolution lidar (HSRL) based on the Mach–Zehnder interferometer (MZI) is constructed in Xi’an for accurate measurements of aerosol optical properties. The critical requirement of the optimal match between the free spectral range of MZI and the longitudinal mode interval of the MLM laser is influenced by the laboratory temperature, pressure, and vibration. To realize the optimal separation of aerosol Mie scattering signals and molecular Rayleigh scattering signals excited by the MLM laser, a self-tuning technique to dynamically adjust the optical path difference (OPD) of the MZI is proposed, which utilizes the maximum ratio between the received power of the Mie channel and Rayleigh channel as the criterion of the OPD displacement. The preliminary experiments show the feasibility of the MLM-HSRL with self-tuning MZI and the stable performance in the separation of aerosol Mie scattering signals and molecular Rayleigh scattering signals.

Aerosol Layer Height Retrieval Over Ocean From the Advanced Himawari Imager Using Spectral Reflectance Sensitivity

Aerosol layer height (ALH) has been retrieved using multi-angle observations or the O2–O2 and O2–A/B absorption bands. This study attempted to retrieve ALH using the Advanced Himawari Imager (AHI), a single passive imager onboard Himawari-8 and -9. ALH retrieval using geostationary Earth orbit (GEO) satellites is advantageous for monitoring diurnal changes in ALH and understanding long-range transport. Before retrieving the ALH, the aerosol optical properties (AOPs) are retrieved using the green-near infrared (NIR) band, which is relatively insensitive to aerosol height. The retrieved AOPs are used as input to the radiative transfer calculation to compute the top-of-atmosphere (TOA) reflectance of a highly sensitive band (the blue band in this study). Then, the ALH is retrieved using the observed and calculated TOA reflectances. Since the retrieval accuracy of the aerosol optical depth (AOD) is better over the ocean, the retrieval was performed only over the ocean during the Korea–United States Air Quality Study (KORUS-AQ) campaign period. The retrieved ALH was validated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and high-spectral-resolution Lidar (HSRL).

Comprehensive, Continuous, and Vertical Measurements of Seawater Constituents with Triple-Field-of-View High-Spectral-Resolution Lidar.

Measuring the characteristics of seawater constituent is in great demand for studies of marine ecosystems and biogeochemistry. However, existing techniques based on remote sensing or insitu samplings present various tradeoffs with regard to the diversity, synchronism, temporal-spatial resolution, and depth-resolved capacity of their data products. Here, we demonstrate a novel oceanic triple-field-of-view (FOV) high-spectral-resolution lidar (HSRL) with an iterative retrieval approach. This technique provides, for the first time, comprehensive, continuous, and vertical measurements of seawater absorption coefficient, scattering coefficient, and slope of particle size distribution, which are validated by simulations and field experiments. Furthermore, it depicts valuable application potentials in the accuracy improvement of seawater classification and the continuous estimation of depth-resolved particulate organic carbon export. The triple-FOV HSRL with high performance could greatly increase the knowledge of seawater constituents and promote the understanding of marine ecosystems and biogeochemistry.

Impacts of regional wind circulations on aerosol pollution and planetary boundary layer structure in Metro Manila, Philippines

Fine particulate matter (PM2.5) concentrations in Metro Manila, Philippines have consistently exceeded the guideline values set by the World Health Organization (WHO). Although there has been much progress in understanding the components and sources of PM2.5, limited research has been done on the influence of meteorological factors. In particular, the influence of the planetary boundary layer height (PBLH) on PM2.5 concentration has not been studied due to inadequate observations. From January 2019–June 2020, measurements from a High Spectral Resolution Lidar (HSRL) filled this gap and allowed for PBLH estimation and aerosol typing. This paper investigates the roles of PBLH and regional and local wind circulations on the temporal evolution of aerosol pollution. Results show that daytime and nighttime PBLH variability is associated with solar heating and radiative cooling, respectively. Cloud-free conditions during the dry season yield a higher PBL growth rate than during the wet season when lower daytime and elevated nighttime PBLH are observed. Lower PM2.5 levels are generally observed during daytime when PBLH is at its maximum. However, the PBLH has a significant inverse correlation with PM2.5 only in the months of December-January-February. We find that horizontal directional wind shear between synoptic and mesoscale circulations confounds the PM2.5 - PBLH relationship by creating stagnant conditions conducive to aerosol accumulation. The lower 20% of PM2.5 concentrations occur during the prevalence of strong monsoon winds. On the other hand, the upper 80% are found during the occurrence of compound mesoscale winds (i.e., sea/land/lake/valley/mountain breezes and channeling monsoon winds). In addition, mountain breeze is found to be associated with lifting of aerosols, resulting in multi-layering within the PBL. The findings in the present study emphasize the role of complex topography and mesoscale scale winds arising from the landscape on aerosol pollution variability.

Seasonal Variation of Dust Aerosol Vertical Distribution in Arctic Based on Polarized Micropulse Lidar Measurement

This study investigates the seasonal variation of dust aerosol vertical distribution using polarized Micropulse lidar (MPL) measurements at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) observatory from January 2013 to September 2017. For the first time, multi-year aerosol backscatter coefficients are retrieved at the ARM NSA site from MPL measurements and are consistent with co-located high spectral resolution lidar (HSRL) measurements. The high-quality aerosol backscatter coefficient retrievals are used to derive the particle depolarization ratio (PDR) at the wavelength of 532 nm, which is used to identify the presence of dust aerosols. The annual cycles of the vertical distributions of dust backscatter coefficient and PDR and dust aerosol optical depth (DAOD) show that aerosol loading has a maximum in late winter and early spring but a minimum in late summer and early autumn. Vertically, dust aerosol occurs in the entire troposphere in spring and winter and in the low and middle troposphere in summer and autumn. Because dust aerosols are effective ice nuclei, the seasonality of dust aerosol vertical distribution has important implications for the Arctic climate through aerosol–cloud–radiation interactions, primarily through impacting mixed-phase cloud processes.

Assessment of NAAPS-RA performance in Maritime Southeast Asia during CAMP2Ex

Abstract. Monitoring and modeling aerosol particle life cycle in Southeast Asia (SEA) is challenged by high cloud cover, complex meteorology, and the wide range of aerosol species, sources, and transformations found throughout the region. Satellite observations are limited, and there are few in situ observations of aerosol extinction profiles, aerosol properties, and environmental conditions. Therefore, accurate aerosol model outputs are crucial for the region. This work evaluates the Navy Aerosol Analysis and Prediction System Reanalysis (NAAPS-RA) aerosol optical thickness (AOT) and light extinction products using airborne aerosol and meteorological measurements from the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) conducted in 2019 during the SEA southwest monsoon biomass burning season. Modeled AOTs and extinction coefficients are compared to those retrieved with a high spectral resolution lidar (HSRL-2). Agreement between simulated and retrieved AOT (R2= 0.78, relative bias =-5 %, normalized root mean square error (NRMSE) = 48 %) and aerosol extinction coefficients (R2= 0.80, 0.81, and 0.42; relative bias = 3 %, −6 %, and −7 %; NRMSE = 47 %, 53 %, and 118 % for altitudes between 40–500, 500–1500, and >1500 m, respectively) is quite good considering the challenging environment and few opportunities for assimilations of AOT from satellites during the campaign. Modeled relative humidities (RHs) are negatively biased at all altitudes (absolute bias =-5 %, −8 %, and −3 % for altitudes <500 500–1500 and >1500 m, respectively), motivating interest in the role of RH errors in AOT and extinction simulations. Interestingly, NAAPS-RA AOT and extinction agreement with the HSRL-2 does not change significantly (i.e., NRMSE values do not all decrease) when RHs from dropsondes are substituted into the model, yet biases all move in a positive direction. Further exploration suggests changes in modeled extinction are more sensitive to the actual magnitude of both the extinction coefficients and the dropsonde RHs being substituted into the model as opposed to the absolute differences between simulated and measured RHs. Finally, four case studies examine how model errors in RH and the hygroscopic growth parameter, γ, affect simulations of extinction in the mixed layer (ML). We find NAAPS-RA overestimates the hygroscopicity of (i) smoke particles from biomass burning in the Maritime Continent (MC) and (ii) anthropogenic emissions transported from East Asia. This work mainly provides insight into the relationship between errors in modeled RH and simulations of AOT and extinction in a humid and tropical environment influenced by a myriad of meteorological conditions and particle types. These results can be interpreted and addressed by the modeling community as part of the effort to better understand, quantify, and forecast atmospheric conditions in SEA.

Polar Aerosol Vertical Structures and Characteristics Observed with a High Spectral Resolution Lidar at the ARM NSA Observatory

Aerosol vertical distributions impact both the direct and indirect radiative effects of aerosols. High Spectra Resolution Lidar (HSRL) separates between atmospheric molecular signals and aerosol particle signals and therefore can provide reliable measurements of aerosol properties. Six years of HSRL measurements between 2014 and 2019 from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) atmospheric observatory at Utqiaġvik are used to statistically analyze Arctic aerosol vertical distributions. The annual cycle of aerosol vertical distributions in terms of aerosol particulate backscatter coefficient (βp), lidar scattering ratio (SR), and aerosol particulate depolarization ratio (δp) profiles at the wavelength of 532 nm shows that Arctic Haze events are prevalent in later winter and spring at the NSA site. Mineral dust is frequently presented in strong aerosol layers in the spring, fall, and winter seasons. Over the summer season, the NSA site has large aerosol loadings that are dominated by small spherical aerosol particles.

Extending water vapor measurement capability of photon-limited differential absorption lidars through simultaneous denoising and inversion

Abstract. The micropulse differential absorption lidar (MPD) was developed at Montana State University (MSU) and the National Center for Atmospheric Research (NCAR) to perform range-resolved water vapor (WV) measurements using low-power lasers and photon-counting detectors. The MPD has proven to produce accurate WV measurements up to 6 km altitude. However, the MPD's ability to produce accurate higher-altitude WV measurements is impeded by the current standard differential absorption lidar (DIAL) retrieval methods. These methods are built upon a fundamental methodology that algebraically solves for the WV using the MPD forward models and noisy observations, which exacerbates any random noise in the lidar observations. The work in this paper introduces the adapted Poisson total variation (PTV) specifically for the MPD instrument. PTV was originally developed for a ground-based high spectral resolution lidar, and this paper reports on the adaptations that were required in order to apply PTV on MPD WV observations. The adapted PTV method, coined PTV-MPD, extends the maximum altitude of the MPD from 6 to 8 km and substantially increases the accuracy of the WV retrievals starting above 2 km. PTV-MPD achieves the improvement by simultaneously denoising the MPD noisy observations and inferring the WV by separating the random noise from the non-random WV. An analysis with 130 radiosonde (RS) comparisons shows that the relative root-mean-square difference (RRMSE) of WV measurements between RS and PTV-MPD exceeds 100 % between 6 and 8 km, whereas the RRMSE between RS and the standard method exceeds 100 % near 3 km. In addition, we show that by employing PTV-MPD, the MPD is able to extend its useful range of WV estimates beyond that of the ARM Southern Great Plains Raman lidar (RRMSE exceeding 100 % between 3 and 4 km); the Raman lidar has a power-aperture product 500 times greater than that of the MPD.

Shipborne oceanic high-spectral-resolution lidar for accurate estimation of seawater depth-resolved optical properties

Lidar techniques present a distinctive ability to resolve vertical structure of optical properties within the upper water column at both day- and night-time. However, accuracy challenges remain for existing lidar instruments due to the ill-posed nature of elastic backscatter lidar retrievals and multiple scattering. Here we demonstrate the high performance of, to the best of our knowledge, the first shipborne oceanic high-spectral-resolution lidar (HSRL) and illustrate a multiple scattering correction algorithm to rigorously address the above challenges in estimating the depth-resolved diffuse attenuation coefficient Kd and the particulate backscattering coefficient bbp at 532 nm. HSRL data were collected during day- and night-time within the coastal areas of East China Sea and South China Sea, which are connected by the Taiwan Strait. Results include vertical profiles from open ocean waters to moderate turbid waters and first lidar continuous observation of diel vertical distribution of thin layers at a fixed station. The root-mean-square relative differences between the HSRL and coincident in situ measurements are 5.6% and 9.1% for Kd and bbp, respectively, corresponding to an improvement of 2.7–13.5 and 4.9–44.1 times, respectively, with respect to elastic backscatter lidar methods. Shipborne oceanic HSRLs with high performance are expected to be of paramount importance for the construction of 3D map of ocean ecosystem.

Retrieved XCO2 Accuracy Improvement by Reducing Aerosol-Induced Bias for China’s Future High-Precision Greenhouse Gases Monitoring Satellite Mission

China is developing the High-precision Greenhouse gases Monitoring Satellite (HGMS), carrying a high-spectral-resolution lidar (HSRL) for aerosol vertical profiles and imaging grating spectrometers for CO2 measurements at the same time. By providing simultaneous evaluation of the aerosol scattering effect, HGMS would reduce the bias of the XCO2 retrievals from the passive sensor. In this work, we propose a method to reduce aerosol-induced bias in XCO2 retrievals for the future HGMS mission based on the correlation analysis among simulated radiance, XCO2 bias, and aerosol optical depth (AOD) ratio. We exercise the method with the Orbiting Carbon Observatory-2 (OCO-2) XCO2 retrievals and AOD ratio inferred from the OCO-2 O2 A-band aerosol parameters at 755 nm and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD at 532 nm at several Total Carbon Column Observing Network (TCCON) sites in Europe. The results showed that 80% of measurements from OCO-2 were improved, and data from six TCCON sites show an average of 2.6 ppm reduction in mean bias and a 68% improvement in accuracy. We demonstrate the advantage of fused active–passive observation of the HGMS for more accurate global XCO2 measurements in the future.

Evaluation of the High Altitude Lidar Observatory (HALO) methane retrievals during the summer 2019 ACT-America campaign

Abstract. The NASA Langley Research Center High Altitude Lidar Observatory (HALO) is a multi-functional and modular lidar developed to address the observational needs of NASA's weather, climate, carbon cycle, and atmospheric composition focus areas. HALO measures atmospheric H2O mixing ratios, CH4 mole fractions, and aerosol/cloud optical properties using the differential absorption lidar (DIAL) and high-spectral-resolution lidar (HSRL) techniques. In 2019 HALO participated in the NASA Atmospheric Carbon and Transport – America campaign on board the NASA C-130 to complement a suite of greenhouse gas in situ sensors and provide, for the first time, simultaneous measurements of column CH4 and aerosol/cloud profiles. HALO operated in 18 of 19 science flights where the DIAL and integrated path differential absorption (IPDA) lidar techniques at 1645 nm were used for column and multi-layer measurements of CH4 mole fractions, and the HSRL and backscatter techniques were used at 532 and 1064 nm, respectively, for retrievals of aerosol backscatter, extinction, depolarization, and mixing layer heights. In this paper we present HALO's measurement theory for the retrievals of column and multi-layer XCH4, retrieval accuracy, and precision including methods for bias correction and a comprehensive total column XCH4 validation comparison to in situ observations. Comparisons of HALO XCH4 to in situ-derived XCH4, collected during spiral ascents and descents, indicate a mean difference of 2.54 ppb and standard deviation (SD) of the differences of 16.66 ppb when employing 15 s along-track averaging (<3 km). A high correlation coefficient of R=0.9058 was observed for the 11 in situ spiral comparisons. Column XCH4 measured by HALO over regional scales covered by the ACT-America campaign is compared against in situ CH4 measurements carried out within the planetary boundary layer (PBL) from both the C-130 and B200 aircraft. Favorable correlation between the in situ point measurements within the PBL and the remote column measurements from HALO elucidates the sensitivity of a column-integrating lidar to CH4 variability within the PBL, where surface fluxes dominate the signal. Novel capabilities for CH4 profiling in regions of clear air using the DIAL technique are presented and validated for the first time. Additionally, profiling of CH4 is used to apportion the PBL absorption from the total column and is compared to previously reported IPDA cloud slicing techniques that estimate PBL columns using strong echoes from fair weather cumulus. The analysis presented here points towards HALO's ability to retrieve accurate and precise CH4 columns with the prospects for future multi-layer profiling in support of future suborbital campaigns.

Vertical structure of biomass burning aerosol transported over the southeast Atlantic Ocean

Abstract. Biomass burning in southwestern Africa produces smoke plumes that are transported over the Atlantic Ocean and overlie vast regions of stratocumulus clouds. This aerosol layer contributes to direct and indirect radiative forcing of the atmosphere in this region particularly during the months of August, September, and October. There was a multi-year international campaign to study this aerosol and its interactions with clouds. Here, we report on the evolution of aerosol distributions and properties as measured by the airborne high spectral resolution lidar (HSRL-2) during the ORACLES (Observations of Aerosols above Clouds and their intEractionS) campaign in September 2016. The NASA Langley HSRL-2 instrument was flown on the NASA ER-2 aircraft for several days in September 2016. Data were aggregated at two pairs of 2∘ × 2∘ grid boxes to examine the evolution of the vertical profile of aerosol properties during transport over the ocean. Results showed that the structure of the profile of aerosol extinction and microphysical properties is maintained over a 1 to 2 d timescale. In the 3–5 km altitude range, 95 % of the aerosol extinction was contributed by particles in the 0.05–0.50 µm radius size range with the aerosol in this size range having an average effective radius of 0.16 µm. This indicates that there is essentially no scavenging or dry deposition at these altitudes. Moreover, there is very little day-to-day variation in these properties, such that time sampling as happens in such campaigns may be representative of longer periods such as monthly means. Below 3 km, there is considerable mixing with larger aerosol, most likely continental source near land. Furthermore, these measurements indicated that there was often a distinct gap between the bottom of the aerosol layer and cloud tops at the selected locations as evidenced by a layer of several hundred meters that contained relatively low aerosol extinction values above the clouds.

Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration

Aerosols and clouds greatly affect the Earth’s radiation budget and global climate. Light detection and ranging (lidar) has been recognized as a promising active remote sensing technique for the vertical observations of aerosols and clouds. China launched its first space-borne aerosol-cloud high-spectral-resolution lidar (ACHSRL) on April 16, 2022, which is capable for high accuracy profiling of aerosols and clouds around the globe. This study presents a retrieval algorithm for aerosol and cloud optical properties from ACHSRL which were compared with the end-to-end Monte-Carlo simulations and validated with the data from an airborne flight with the ACHSRL prototype (A2P) instrument. Using imaging denoising, threshold discrimination, and iterative reconstruction methods, this algorithm was developed for calibration, feature detection, and extinction coefficient (EC) retrievals. The simulation results show that 95.4% of the backscatter coefficient (BSC) have an error less than 12% while 95.4% of EC have an error less than 24%. Cirrus and marine and urban aerosols were identified based on the airborne measurements over different surface types. Then, comparisons were made with U.S. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) profiles, Moderate-resolution Imaging Spectroradiometer (MODIS), and the ground-based sun photometers. High correlations (R > 0.79) were found between BSC (EC) profiles of A2P and CALIOP over forest and town cover, while the correlation coefficients are 0.57 for BSC and 0.58 for EC over ocean cover; the aerosol optical depth retrievals have correlation coefficient of 0.71 with MODIS data and show spatial variations consistent with those from the sun photometers. The algorithm developed for ACHSRL in this study can be directly employed for future space-borne high-spectral-resolution lidar (HSRL) and its data products will also supplement CALIOP data coverage for global observations of aerosol and cloud properties.

Polarimeter + Lidar–Derived Aerosol Particle Number Concentration

In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved Na product to in situNa data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11 separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter Na agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged Na. We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged Na and the lidar + polarimeter vertically resolved Na are of similar magnitude and represent a significant improvement upon current remote sensing estimates of Na.

Cloud and Precipitation Particle Identification Using Cloud Radar and Lidar Measurements: Retrieval Technique and Validation

AbstractThis paper describes a technique for identifying hydrometeor particle types using airborne HIAPER Cloud Radar (HCR) and High Spectral Resolution Lidar (HSRL) observations. HCR operates at a frequency of 94 GHz (3 mm wavelength), while HSRL is an eye‐safe lidar system operating at a wavelength of 532 nm. Both instruments are deployed on the NSF‐NCAR HIAPER aircraft. HCR is designed to fly in an underwing pod and HSRL is situated in the cabin. The HCR and HSRL data used in this study were collected during the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES). Comprehensive observations of the vertical distributions of liquid and mixed‐phase clouds were obtained using in situ probes on the aircraft and remote sensing instruments. Hydrometeor particle types were retrieved from HCR, HSRL, and temperature fields with a newly developed fuzzy logic particle identification (PID) algorithm. The PID results were validated with in situ measurements collected onboard the HIAPER aircraft by a 2D‐Stereo (2D‐S) cloud probe. Particle phases derived from the PID results compare well with those obtained from the 2D‐S observations and agree in over 70% of cases. Size distributions are also consistent between the two methods of observation. Knowledge of the particle type distribution gained from the PID results can be used to constrain microphysical parameterizations and improve the representation of cloud radiative effects in weather and climate models.