Search Results (24)

Since its launch in 2018, the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission has provided atmospheric products, including calibrated backscatter profiles and cloud and aerosol layer detection. While not the primary focus of the mission, these products garnered more interest after the end of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) data collection in 2023. In comparing the cloud and aerosol detection frequencies from CALIOP and ICESat-2, we find general agreement in the global patterns. The global cloud detection frequencies were similar in June, July, and August of 2019 (64.7% for ICESat-2 and 59.8% for CALIOP), as were the location and altitude of the tropical maximum; however, low daytime signal-to-noise ratios (SNRs) reduced ICESat-2’s detection frequencies compared to those of CALIOP. The ICESat-2 global aerosol detection frequencies were likewise lower. ICESat-2 generally retrieved a higher average global aerosol optical depth compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) over the ocean, but the two were in closer agreement over regions with higher aerosol concentrations such as the Eastern Atlantic Ocean and the Northern Indian Ocean. The ICESat-2 and CALIOP orbital coincidences reveal highly correlated backscatter profiles as well as similar cloud and aerosol layer top altitudes. Future work with machine learning denoising techniques may allow for improved feature detection, especially during daytime. Full article

Smoke particles from biomass burning events are typically assumed to be spherical despite previous observations of non-spherical smoke. As such, large uncertainties exist in some physical and optical parameters used in lidar aerosol retrievals, including depolarization and lidar ratio of non-spherical smoke aerosols. In this analysis, using NASA’s Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data during the biomass burning season over Africa from 2015 to 2017, we studied the frequency and distribution of non-spherical smoke particles to compare with findings of smoke particle non-sphericity from the Cloud-Aerosol Transport System (CATS) lidar. A supplemental smoke aerosol typing algorithm was developed to identify aerosol layers containing non-spherical smoke particles, which might otherwise be misclassified as desert dust, polluted dust, or dusty marine by the CALIOP standard aerosol typing algorithm. Then, the relationships between smoke particle sphericity, lidar ratio, and relative humidity are analyzed for CATS and CALIOP observations over Africa. Approximately 18% of smoke layers observed by CALIOP over Africa are non-spherical (depolarization ratio > 0.075) and agree with spatial distributions of non-spherical smoke found in CATS observations. A dependance of lidar ratio on relative humidity was found for layers of spherical smoke over Africa in both CATS and CALIOP data; however, no such dependance was evident for the depolarization ratio and layer relative humidity. While the supplemental smoke aerosol typing algorithm presented in this analysis was targeted only for specific biomass burning regions during biomass burning seasons and is not meant for global operational use, it presents one potential method for improved backscatter lidar aerosol typing. These results suggest that a dynamic lidar ratio, based on layer-relative humidity for spherical smoke, could be used to reduce uncertainties in smoke aerosol extinction retrievals for future backscatter lidars. Full article

Space-based atmospheric backscatter lidars provide critical information about the vertical distribution of clouds and aerosols, thereby improving our understanding of the climate system. They are additionally useful for detecting hazards to aviation and human health, such as volcanic plumes and man-made pollution events. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP, 2006–2023), Cloud-Aerosol Transport System (CATS, 2015–2017), and Advanced Topographic Laser Altimeter System (ATLAS 2018–present) are three such lidars that operated within the past 20 years. The signal-to-noise ratio (SNR) for these lidars is significantly lower in daytime data compared with nighttime data due to the solar background signal increasing the detector response noise. Averaging horizontally across profiles has been the standard way to increase SNR, but this comes at the expense of resolution. Modern, deep learning-based denoising algorithms can be applied to improve the SNR without coarsening resolution. This paper describes how one such model architecture, Dense Dense U-Net (DDUNet), was trained to denoise CATS 1064 nm raw signal data (photon counts) using artificially noised nighttime data. Simulated CATS daytime 1064 nm data were then created to assess the model’s performance. The denoised simulated data increased the daytime SNR by a factor of 2.5 (on average) and decreased minimum detectable backscatter (MDB) to ~$7.3\times {10}^{-4}$ km⁻¹sr⁻¹, which is lower than the CALIOP 1064 nm night MDB value of $8.6\times {10}^{-4}$ km⁻¹sr⁻¹. Layer detection was performed on simulated 2 km horizontal resolution denoised and 60 km averaged data. Despite the finer resolution input, the denoised layers had more true positives, fewer false positives, and an overall Jaccard Index of 0.54 versus 0.44 when compared to the layers detected on averaged data. Layer detection was also performed on a full month of denoised daytime CATS data (Aug. 2015) to detect layers for comparison with CATS standard Level 2 (L2) product layers. The detection on the denoised data yielded 2.33 times more, higher-quality bins within detected layers at 2.7–33 times finer resolution than the CATS L2 products. Full article

The statistical characteristics of combined lidar and radiometric measurements obtained from satellite lidar CALIOP and ground-based sun-radiometer stations were used as input datasets to retrieve the altitude profiles of aerosol parameters (LRS-C technique). The signal-to-noise ratio of the input satellite lidar signals increased when averaging over a large array of measured data. An algorithm and software package for processing the input dataset of the LRS-C sounding of atmospheric aerosol in regions with medium and low aerosol loads was developed. This paper presents the results of studying long-term changes in the concentration profiles of aerosol modes in regions of East Europe (AERONET site Minsk, 53.92° N, 27.60° E) and East Antarctic (AERONET site Vechernaya Hill, 67.66° S, 46.16° E). Full article

North Africa, the Middle East, and Europe (NAMEE domain) host a variety of suspended particles characterized by different optical and microphysical properties. In the current study, we investigate the importance of the lidar ratio (LR) on Cloud-Aerosol Lidar with Orthogonal Polarization–Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIOP-CALIPSO) aerosol retrievals towards assessing aerosols’ impact on the Earth-atmosphere radiation budget. A holistic approach has been adopted involving collocated Aerosol Robotic Network (AERONET) observations, Radiative Transfer Model (RTM) simulations, as well as reference radiation measurements acquired using spaceborne (Clouds and the Earth’s Radiant Energy System-CERES) and ground-based (Baseline Surface Radiation Network-BSRN) instruments. We are assessing the clear-sky shortwave (SW) direct radiative effects (DREs) on 550 atmospheric scenes, identified within the 2007–2020 period, in which the primary tropospheric aerosol species (dust, marine, polluted continental/smoke, elevated smoke, and clean continental) are probed using CALIPSO. RTM runs have been performed relying on CALIOP retrievals in which the default and the DeLiAn (Depolarization ratio, Lidar ratio, and Ångström exponent)-based aerosol-speciated LRs are considered. The simulated fields from both configurations are compared against those produced when AERONET AODs are applied. Overall, the DeLiAn LRs leads to better results mainly when mineral particles are either solely recorded or coexist with other aerosol species (e.g., sea-salt). In quantitative terms, the errors in DREs are reduced by ~26–27% at the surface (from 5.3 to 3.9 W/m²) and within the atmosphere (from −3.3 to −2.4 W/m²). The improvements become more significant (reaching up to ~35%) for moderate-to-high aerosol loads (AOD ≥ 0.2). Full article

A persistent stratospheric aerosol layer first appeared during July 2019 above Thessaloniki, Greece (40.5°N, 22.9°E). It was initially at 12 km and, during August 2019, was even up to 20 km, with increased thickness and reduced attenuated backscatter levels till the end of the year. In this study, we analyze the geometrical and optical properties of this stratospheric layer, using ground-based Lidar measurements, CALIOP/CALIPSO & OMPS-LP space-borne observations, as well as CAMS/ECMWF assimilation experiments. The main aim of the paper is to present an overview of this atmospheric feature and to identify any temporal changes in the aerosol properties that would signify substantial changes in the composition of this long-lasting stratospheric plume over Thessaloniki. This aim is further enhanced by emphasizing the importance of the combined information based on active ground- and space-borne lidars, passive remote sensing, and models during the complex stratospheric aerosol conditions as those encountered during 2019. The layer’s origin is linked to the Raikoke volcanic eruption in the Kuril Islands in June 2019, yielding a particle linear depolarization ratio less than 0.05, while some indications exist that the intense forest fires at mid and high northern latitudes throughout the summer of 2019 also contributed to the persistent layer. We report that in July, mainly volcanic sulphate aerosol layers with a 1–3 km vertical extent were identified in the stratosphere at ~15 km over Thessaloniki, while after August and until the end of 2019, the plume heights showed a significant month-to-month variability and a broadening (with thickness greater than 3 km) towards lower altitudes. The aerosol optical thickness was found to be in the range between 0.004 and 0.125 (visible) and 0.001 and 0.095 (infrared) and the particle depolarization of the detected stratospheric plume was found to be 0.03 ± 0.04, indicative of spherical particles, such as sulphate aerosols. Full article

The overarching objective of the present study is to assess the quality of the CALIOP–CALIPSO aerosol retrievals towards understanding their advantages and deficiencies. Such analysis is a prerequisite prior to their utilization in a radiation transfer model (RMT) for estimating the clear-sky shortwave (SW) aerosol-induced direct radiative effects (DREs) within the Earth–Atmosphere system. The study region encompasses North Africa, the Middle East, and Europe (NAMEE domain), and the period of interest ranges from 2007 to 2020. A holistic approach has been adopted involving spaceborne retrievals (CALIOP–CALIPSO and MODIS-Aqua) and ground-based measurements (AERONET). Overall, CALIOP underestimates columnar aerosol optical depth (AOD), particularly in dust-rich areas, attributed to various factors (e.g., lidar ratio). In order to demonstrate the significance of an appropriate definition of the lidar ratio, focusing on DREs, three example dust cases are investigated. The CALIPSO dust extinction coefficient profiles are used as inputs to the libRadtran Radiative Transfer Model (RTM) along with other crucial parameters. For each study case, two RTM runs are performed using the default (CALIPSO) and an updated (DeliAn) dust lidar ratio. Our results indicate remarkable differences (up to ~22%) on the surface and atmospheric DREs while varying from 17% to 27% at TOA. Full article

In this study, a combination of ground-based particulate matter measurements in synergy with space-borne CALIOP lidar recordings, meteorological observations, and reanalysis models have been used to study atmospheric air pollution over Amman, Jordan. The measurement was conducted over a 24-month period spanning from January 2018 to the end of December 2019. The CALIOP aerosol profiles and aerosol layer products version 4.21, level 2, with 5 km horizontal resolution were used to evaluate the vertical structure of the atmospheric constituent over the Amman region. The particle depolarization ratio (PDR) was extracted from CALIOP recordings and has been utilized to classify the type of atmospheric aerosols. This method reveals that the atmosphere above Amman mostly contains three different aerosol types including coarse-mode dust, fine-mode dust (polluted dust), and non-dust aerosols (pollution). Aerosols with 0 < ${\delta }_{\mathrm{p}}\le$ 0.075 are categorized as pollution, aerosols with 0.075 < ${\delta }_{\mathrm{p}}\le$ 0.20 as polluted dust, and aerosols with 0.20 < ${\delta }_{\mathrm{p}}\le$ 0.40 are classified as dust. Both the one- and two-step POlarization-LIdar PHOtometer Networking (POLIPHON) approaches have been applied to the CALIOP aerosol profile product to retrieve the vertical profile of the optical and micro-physical properties of each aerosol type. Lofted-layer top heights and layer thickness in the atmosphere above Amman during the study period were also extracted from the CALIOP aerosol layer products. The highest frequency of occurrence was observed for layers with a top height of 0.5 to 2.5 km with a second smaller peak at 3.5 km. The maximum frequency of the lofted layers (40% of cases) were observed with layer thickness below 0.5 km. For layers with a top height lower than 500 m above ground level, the atmosphere was mostly impacted by polluted dust and pollution aerosols. On the other hand, for layers with a top height above 2500 m agl, the atmosphere was contaminated by depolarizing dust particles. Full article

Concentrations of particulate aerosols and their vertical placement in the atmosphere determine their interaction with the Earth system and their impact on air quality. Space-based lidar, such as the Cloud–Aerosol Transport System (CATS) technology demonstration instrument, is well-suited for determining the vertical structure of these aerosols and their diurnal cycle. Through the implementation of aerosol-typing algorithms, vertical layers of aerosols are assigned a type, such as marine, dust, and smoke, and a corresponding extinction-to-backscatter (lidar) ratio. With updates to the previous aerosol-typing algorithms, we find that CATS, even as a technology demonstration, observed the documented seasonal cycle of aerosols, comparing favorably with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) space-based lidar and the NASA Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) model reanalysis. By leveraging the unique orbit of the International Space Station, we find that CATS can additionally resolve the diurnal cycle of aerosol altitude as observed by ground-based instruments over the Maritime Continent of Southeast Asia. Full article

In recent years, climate change and the intervention of anthropogenic activities have altered the seasonal features of Asian dust storms. This may also cause seasonal variations (including dust occurrence frequency and optical/microphysical properties) in dust aerosols transported to downstream regions. The Jianghan Plain is dramatically influenced by multiple dust sources due to its geographical location in central China. In this study, we focused on the climatology of dust aerosols over the Jianghan Plain based on the 15-year (2006–2021) continuous space-borne observations of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) as well as Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) reanalysis data. A typical dust event that intrudes the Jianghan Plain was studied in detail. According to the statistical results, dust aerosols frequently intrude into the Jianghan Plain in spring and winter, with occurrence frequencies (under cloud free condition hereafter) exceeding 0.70 and higher altitudes of 4–6 km. The dust occurrence frequency declined to approximately 0.40 in autumn and nearly zero in summer, while the dust plumes were generally located at lower altitudes of 1–3 km. The dust plumes observed in the Jianghan Plain were simultaneously linked to the Taklimakan Desert and Gobi Desert in spring and mainly originated from the Taklimakan Desert in winter and autumn. The dust particles were mainly distributed below 4-km altitude, with the largest dust extinction coefficients and dust mass concentrations in spring. In all seasons, the particle depolarization ratios are 0.1–0.2 below 4-km altitude, suggesting a possible mix with local anthropogenic aerosols. The mean dust column mass concentrations in spring showed an evident declining trend from 210 µg m⁻² in 2006 to 100 µg m⁻² in 2021 in the Jianghan Plain, attributed to the reduced dust activity in the source regions of Asian dust. Full article

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. Full article

Recent studies indicate that the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite provides valuable information about ocean phytoplankton distributions. CALIOP’s attenuated backscatter coefficients, measured at 532 nm in receiver channels oriented parallel and perpendicular to the laser’s linear polarization plane, are significantly improved in the Version 4 data product. However, due to non-ideal instrument effects, a small fraction of the backscattered optical power polarized parallel to the receiver polarization reference plane is misdirected into the perpendicular channel, and vice versa. This effect, known as polarization crosstalk, typically causes the measured perpendicular signal to be higher than its true value and the measured parallel signal to be lower than its true value. Therefore, the ocean optical properties derived directly from CALIOP’s measured signals will be biased if the polarization crosstalk effect is not taken into account. This paper presents methods that can be used to estimate the CALIOP crosstalk effects from on-orbit measurements. The global ocean depolarization ratios calculated both before and after removing the crosstalk effects are compared. Using CALIOP crosstalk-corrected signals is highly recommended for all ocean subsurface studies. Full article

The accurate recognition of the cloud phase has a great influence on the retrieval of the cloud top height. In order to improve the accuracy of obtaining the cloud top height with OCO-2, we proposed a cloud phase recognition algorithm based on the threshold of parameter $\alpha$; $\alpha$ is defined as the reflectivity ratio of the region with weak continuous absorption of the oxygen A band to the region with weak continuous absorption of the CO₂ 1.6 µm band. The $\alpha$ under different solar zenith angles and different ground albedos was calculated. The results show the following: under the same surface albedo and solar zenith angle, $\alpha$ was large for ice clouds and small for water clouds. Under the same surface albedo, the greater the solar zenith angle, the smaller the $\alpha$ of the ice cloud, and the larger the $\alpha$ of the water cloud. Under the same solar zenith angle, the greater the surface albedo, the smaller the $\alpha$; when the solar zenith angle was less than 70°, $\alpha$ can be used to effectively distinguish between the ice cloud and water cloud. This study used OCO-2 data of a single orbit over ocean to verify the feasibility of the algorithm through comparison with the CALIOP cloud phase product, which provided a basis for OCO-2 cloud top height estimation. Full article

Coincident profiles from the space-borne and ground-based lidar measurements provide a unique opportunity to estimate the planetary boundary layer height (PBLH). In this study, PBLHs derived from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) were assessed by comparing them with those obtained from the ground-based lidar at Seoul National University (SNU) in Korea for both day and night from 2006 to 2019, and sounding data. CALIOP-derived PBLHs using wavelet covariance transform (WCT) are generally higher than those derived from the SNU lidar for both day and night. The difference in PBLH tends to increase as the signal-to-noise ratio for CALIOP decreases. The difference also increases as aerosol optical depth increases, implying that the PBLH estimated from CALIOP could be higher than that determined from the SNU lidar because of the signal attenuation within the aerosol layer under optically thick aerosol layer conditions. The higher PBLH for CALIOP in this study is mainly attributed to multiple aerosol layers. After eliminating multilayer cases, the PBLHs estimated from both the lidars showed significantly improved agreement: a mean difference of 0.09 km (R = 0.81) for daytime and 0.25 km (R = 0.51) for nighttime. The results from this study suggest that PBL detection using CALIOP is reliable for daytime if multilayer cases are removed. For nighttime, PBLHs derived from the SNU lidar and CALIOP showed a relatively large difference in frequency distribution compared with sounding data. It suggests that further investigations are needed for nighttime PBLHs, such as investigations about discriminating the residual layer and the difference between lidar-derived PBLH based on the aerosol layer and thermally derived PBLH from radiosonde data for the stable boundary layer during the nighttime. Full article

Airborne backscatter lidar at 532 nm and in-situ measurements of black carbon (BC), carbon monoxide excess above background (ΔCO), and aerosol size distribution were carried out over Siberia in July 2013 and June 2017 in order to sample several kinds of aerosol sources. Aerosol types are derived using the Lagrangian FLEXible PARTicle dispersion model (FLEXPART) simulations and satellite observations. Six aerosol types could be identified in this work: (i) dusty aerosol mixture, (ii) Ob valley gas flaring emission, (iii) fresh forest fire, (iv) aged forest fire, (v) urban emissions over the Tomsk/Novosibirsk region (vi) long range transport of Northern China urban emission. The altitude range of aerosol layers is discussed for each aerosol type, showing transport above the boundary layer for long range transport of Northern China emissions or fresh forest fire. Comparisons of aerosol optical properties, BC and ΔCO are made between aged and fresh plumes for both the urban and forest fire emissions. An increase of aerosol optical depth at 532 nm (AOD${}_{532}$), aerosol particle size and ΔCO is found for aged forest fire plumes. Similar results are obtained when comparing the aged urban plume from Northern China with fresh urban emissions from Siberian cities. A flight above gas flaring emissions corresponds to the largest AOD${}_{532}$ and provides a possible range of 50–60 sr for the lidar ratio of these aerosol plumes often encountered in Siberia. Black carbon concentrations are relatively higher for the flaring plume (0.4–0.5 μ$\mathsf{\mu }\mathrm{g}.{\mathrm{m}}^{-3}$) than for the urban plume (0.2 μ$\mathsf{\mu }\mathrm{g}.{\mathrm{m}}^{-3}$). The largest BC concentrations are found for the fresh forest fire plume. The aerosol type identification and AOD${}_{532}$ provided by CALIOP Version 4.2 data products in air masses with similar origin generally agree with the results obtained from our detailed analysis of the aerosol plume origins. Full article