Cloud-Aerosol Lidar And Infrared Pathfinder Satellite Observations Research Articles

An iterative algorithm to simultaneously retrieve aerosol extinction and effective radius profiles using CALIOP

Abstract. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite has been widely used in climate and environment studies to obtain the vertical profiles of atmospheric aerosols. To retrieve the vertical profile of aerosol extinction, the CALIOP algorithm assumes column-averaged lidar ratios based on a clustering of aerosol optical properties measured at surface stations. On one hand, these lidar ratio assumptions may not be appropriate or representative at certain locations. One the other hand, the two-wavelength design of CALIOP has the potential to constrain aerosol size information, which has not been considered in the operational algorithm. In this study, we present a modified inversion algorithm to simultaneously retrieve aerosol extinction and effective radius profiles using two-wavelength elastic lidars such as CALIOP. Specifically, a lookup table is built to relate the lidar ratio with the Ångström exponent calculated using aerosol extinction at the two wavelengths, and the lidar ratio is then determined iteratively without a priori assumptions. The retrieved two-wavelength extinction at each layer is then converted to the particle effective radius assuming a lognormal distribution. The algorithm is tested on synthetic data, Raman lidar measurements and then finally the real CALIOP backscatter measurements. Results show improvements over the CALIPSO operational algorithm by comparing with ground-based Raman lidar profiles.

Validation of Satellite‐Based Cloud Phase Distributions Using Global‐Scale In Situ Airborne Observations

AbstractUnderstanding distributions of cloud thermodynamic phases is important for accurately representing cloud radiative effects and cloud feedback in a changing climate. Satellite‐based cloud phase data have been frequently used to compare with climate models, yet few studies validated them against in situ observations at a near‐global scale. This study aims to validate three satellite‐based cloud phase products using a compositive in situ airborne data set developed from 11 flight campaigns. Latitudinal‐altitudinal cross sections of cloud phase occurrence frequencies are examined. The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) show the most similar vertical profiles of ice phase frequencies compared with in situ observations. The CloudSat data overestimate mixed‐phase frequencies up to 15 km but provide better sampling through cloud layers than lidar data. The DARDAR (raDAR/liDAR) data show a sharp transition between ice and liquid phase and overestimate ice phase frequency at most altitudes and latitudes. The satellite data are further evaluated for various latitudes, longitudes, and seasons, which show higher ice phase frequency in the extratropics in their respective wintertime and smaller impacts from longitudinal variations. The Southern Ocean shows a thicker mixing region where liquid and ice phases have similar frequencies compared with tropics and Northern Hemisphere (NH) extratropics. Two comparison methods with different spatiotemporal windows show similar results, which demonstrates the statistical robustness of these comparisons. Overall, this study develops a near global‐scale in situ observational data set to assess the accuracy of satellite‐based cloud phase products and investigates the key factors affecting the distributions of cloud phases.

CALIPSO Observed Low Clouds Over the Subtropical Northeast Pacific: Summer Climatology and Interannual Variability

AbstractThis study examines the spatial distribution and temporal variations of low‐cloud top over the subtropical northeast Pacific (NEP), using observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). A comparison between CALIPSO observations and in‐situ soundings reveals a distinct bimodal distribution of low‐cloud tops, characterized by peaks near the inversion base and transition layer, corresponding to shallow cumulus clouds below the stratocumulus deck and boundary‐layer decoupling phenomena. Climatologically, while traversing along a great circle from Los Angeles to Honolulu, the frequency of low cloud occurrence experiences a gradual reduction from 80% to 30%. Meanwhile, cloud top height increases from 0.6 to 1.6 km, and surface roughness varies from 50 to 300 m. This study marks the first presentation of long‐term characteristics of low clouds over a vast, remote area, expanding beyond discrete field campaign observations. Accurately characterizing the marine atmospheric boundary layer (MABL) including its depth and degree of decoupling, enables further investigation into the interannual variations of low clouds, using 14 years of CALIPSO observations. Significant interannual variability in areal fraction and vertical bimodality of low clouds emerges downstream of the anomalously cold water; increased cloud cover with weakened bimodality is associated with a shallow weakly decoupled MABL. This research emphasizes the need to consider the downstream effects in studying low cloud‐sea surface temperature feedback within climate models.

Three-dimensional reconstruction of aerosols based on spectral radiance matching

This paper evaluates a three-dimensional scene construction algorithm that assigns CALIPSO-observed profiles to receiving pixels in MODIS imagery through spectral radiance matching (SRM), so that a limited number of vertically resolved aerosol observations can be expanded into a regionally continuous three-dimensional aerosol structure. The SRM algorithm was tested using moderate resolution imaging spectro-radiometer (MODIS) and cloud-aerosol lidar and infrared pathfinder satellite observation (CALIPSO) data for the period of April 10–25, 2015. First, the spectral radiance channel and the surface reflectance channel were selected for combination tests to select the best channel combination 01-04-07-26 for the application of SRM algorithm in the field of aerosol three-dimensional reconstruction. The average aerosol matching rate for this channel combination can reach 90.57%, 81.64%, 78.6%, 74.12%, and 65.96% at extended distances of 5, 20, 30, 50, and 100 km, respectively. In addition, the combination of the average correct match rate and the reconstructed aerosol structure revealed that the most suitable extension distance is up to 100 km. Then, for the reconstruction profile validation, lidar sites under four weather conditions (clean sky, aerosol loading, thin clouds, and thick clouds) were selected for validation. The comparison results reveal that the average relative errors are about 30%, 60%, 30%–60%, and 70% for these four conditions, respectively. Overall, the average relative error of the reconstructed profiles within 100 km of the orbital track of CALIPSO (except under thick cloud conditions) is less than 60%, which is within a reasonable error envelop. There are also some limitations that can be improved later by adding more constraints: 1) it is difficult to reconstruct some short-time, small-scale aerosol or cloud features; 2) it is difficult to reconstruct some hierarchical structures under thick clouds due to signal attenuation caused by thick clouds; 3) there is an underestimation of the attenuated backscatter coefficient under clouds. Finally, for aerosol optical depth (AOD), the SRM algorithm largely underestimates AOD. The reconstructed AOD is in good agreement with aerosol robotic network (AERONET), with R2=0.8231 after removal of outliers.

A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations

Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product (Bertrand et al. 2023, https://doi.org/10.5281/zenodo.8057791), a globally gridded (level 3S) community data product summarizing geometrical profiles (GEOPROF) of hydrometeor occurrence from combined (COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level-2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10° spatial resolutions and monthly and seasonal temporal resolutions. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as four comparable surface-based sites, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud–climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.

Validation of initial observation from the first spaceborne high-spectral-resolution lidar with a ground-based lidar network

Abstract. On 16 April 2022, China successfully launched the world's first spaceborne high-spectral-resolution lidar (HSRL), which is called the Aerosol and Carbon Detection Lidar (ACDL), on board the Atmospheric Environment Monitoring Satellite known as Daqi-1 (DQ-1). The ACDL is expected to precisely detect the three-dimensional distribution of aerosol and cloud globally with high spatial–temporal resolutions. To assess the performance of the newly launched satellite lidar, the ACDL-retrieved observations were compared with ground-based lidar measurements of atmospheric aerosol and cloud over northwest China from May to July 2022 using the Belt and Road lidar network (BR-lidarnet) initiated by Lanzhou University in China and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations. A total of six cases in the daytime and nighttime, including clear days, dust events, and cloudy conditions, were selected for further analysis. Moreover, profiles of the total attenuated backscatter coefficient (TABC) and the volume depolarization ratio (VDR) at 532 nm measured by the ACDL, the CALIPSO lidar, and ground-based lidar are compared in detail. Comparison is made between the 532 nm extinction coefficient and lidar ratio obtained from ACDL HSRL retrieval and the Raman retrieval results obtained from BR-lidarnet. The achieved results revealed that the ACDL observations were in good agreement with the ground-based lidar measurements during dust events with a relative deviation of about −10.5 ± 25.4 % for the TABC and −6.0 ± 38.5 % for the VDR. Additionally, the heights of the cloud top and bottom from these two measurements were well matched and comparable. Compared with the observation of CALIPSO, the ACDL also shows high consistency. This study proves that the ACDL provides reliable observations of aerosol and cloud in the presence of various climatic conditions, which helps to further evaluate the impacts of aerosol on climate and the environment, as well as on the ecosystem in the future.

The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020

Abstract. A comprehensive and robust dataset of tropospheric aerosol properties is important for understanding the effects of aerosol–radiation feedback on the climate system and reducing the uncertainties of climate models. The “Third Pole” of Earth (Tibetan Plateau, TP) is highly challenging for obtaining long-term in situ aerosol data due to its harsh environmental conditions. Here, we provide the more reliable new vertical aerosol index (AI) parameter from the spaceborne-based lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) on board CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) for daytime and nighttime to investigate the aerosol's climatology over the TP region during 2007–2020. The calculated vertical AI was derived from the aerosol extinction coefficient (EC), which was rigorously quality-checked and validated for passive satellite sensors (MODIS) and ground-based lidar measurements. Generally, our results demonstrated that there was agreement of the AI dataset with the CALIOP and ground-based lidar. In addition, the results showed that, after removing the low-reliability aerosol target signal, the optimized data can obtain the aerosol characteristics with higher reliability. The data also reveal the patterns and concentrations of high-altitude vertical structure characteristics of the tropospheric aerosol over the TP. They will also help to update and make up the observational aerosol data in the TP. We encourage climate modelling groups to consider new analyses of the AI vertical patterns, comparing the more accurate datasets, with the potential to increase our understanding of the aerosol–cloud interaction (ACI) and aerosol–radiation interaction (ARI) and their climate effects. Data described in this work are available at https://doi.org/10.11888/Atmos.tpdc.300614 (Huang, 2023).

Seasonal vertical distributions of diurnal variation of ice cloud frequency by CATS measurements over a global region (51°S-51°N)

Ice clouds can strongly affect the radiation budget through the reflection (absorption) of solar shortwave (longwave) radiation in the Earth-atmosphere system. Unlike water clouds, ice clouds present a longer lifetime in the upper troposphere. Therefore, the vertical patterns of diurnal variation of ice clouds are of very importance to understand climate change in the globe. The present paper investigates the diurnal variation of ice cloud frequency (ICF) from March 2015 to October 2017 over the global scale (51 ° S and 51 ° N) by CATS (Cloud-Aerosol Transport System) LiDAR onboard the International Space Station (ISS) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) LiDAR measurements. Our results suggest that: (1) ICF derived from the CATS and CALIPSO LiDAR presents the similar geographical variations. (2) The vertical distribution of ICF in land area over the North Hemisphere (NH) is found larger than in the South Hemisphere (SH) likely due to the more dust aerosols as ice nuclei to influence ice cloud formation over the NH. (3) ICF at nighttime (00:00–06:00 and 18:00–23:00) exhibits higher value than daytime (06:00–18:00), especially in high altitude (more than 12 km) ice clouds in the tropics. (4) The number of ice cloud samples is higher in spring and winter compared to summer and autumn, and the highest amount of ice cloud samples in spring(winter) occurs during nighttime(daytime) for most hours. These findings provide significant insights that may help improving the ice cloud's representation in climate models.

Lessons Learned from the Updated GEWEX Cloud Assessment Database

AbstractSince the first Global Energy and Water Exchanges cloud assessment a decade ago, existing cloud property retrievals have been revised and new retrievals have been developed. The new global long-term cloud datasets show, in general, similar results to those of the previous assessment. A notable exception is the reduced cloud amount provided by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Science Team, resulting from an improved aerosol–cloud distinction. Height, opacity and thermodynamic phase determine the radiative effect of clouds. Their distributions as well as relative occurrences of cloud types distinguished by height and optical depth are discussed. The similar results of the two assessments indicate that further improvement, in particular on vertical cloud layering, can only be achieved by combining complementary information. We suggest such combination methods to estimate the amount of all clouds within the atmospheric column, including those hidden by clouds aloft. The results compare well with those from CloudSat-CALIPSO radar–lidar geometrical profiles as well as with results from the International Satellite Cloud Climatology Project (ISCCP) corrected by the cloud vertical layer model, which is used for the computation of the ISCCP-derived radiative fluxes. Furthermore, we highlight studies on cloud monitoring using the information from the histograms of the database and give guidelines for: (1) the use of satellite-retrieved cloud properties in climate studies and climate model evaluation and (2) improved retrieval strategies.

Analysis of Aerosol Types and Vertical Distribution in Seven Typical Cities in East Asia

Identifying the types and vertical distribution of aerosols plays a significant role in evaluating the influence of aerosols on the climate system. Based on the aerosol optical properties obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), this study analyzed the long-term aerosol characteristics of seven cities in East Asia (Ulaanbaatar, Beijing, Lanzhou, Shanghai, Lhasa, Hong Kong, and Bangkok) from 2007 to 2021, including the spatiotemporal variations of aerosol optical depth (AOD), the vertical stratification characteristics of aerosols, and the main aerosol subtype. The results showed that, except for Lhasa, the AOD values of all cities exhibited a trend of initially increasing and then decreasing over the years. Except for Shanghai, the high values of AOD in the other cities occurred in the spring and summer seasons, while the low values occurred in the autumn and winter seasons. In all four seasons, the AOD contribution within the 1–3 km range accounted for more than 50% of the total. In the autumn and winter seasons, this proportion reached over 80%. The main types of aerosols and their contributions varied at different altitudes. Overall, dust, polluted continental/smoke, polluted dust, and elevated smoke dominated in all aerosol layers across each city. On the other hand, clean marine, clean continental, and dusty marine had very small proportions, accounting for less than 5% of all the cities’ aerosol layers.

Remote Sensing Retrieval of Cloud Top Height Using Neural Networks and Data from Cloud-Aerosol Lidar with Orthogonal Polarization.

In order to enhance the retrieval accuracy of cloud top height (CTH) from MODIS data, neural network models were employed based on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. Three types of methods were established using MODIS inputs: cloud parameters, calibrated radiance, and a combination of both. From a statistical standpoint, models with combination inputs demonstrated the best performance, followed by models with calibrated radiance inputs, while models relying solely on calibrated radiance had poorer applicability. This work found that cloud top pressure (CTP) and cloud top temperature played a crucial role in CTH retrieval from MODIS data. However, within the same type of models, there were slight differences in the retrieved results, and these differences were not dependent on the quantity of input parameters. Therefore, the model with fewer inputs using cloud parameters and calibrated radiance was recommended and employed for individual case studies. This model produced results closest to the actual cloud top structure of the typhoon and exhibited similar cloud distribution patterns when compared with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) CTHs from a climatic statistical perspective. This suggests that the recommended model has good applicability and credibility in CTH retrieval from MODIS images. This work provides a method to improve accurate CTHs from MODIS data for better utilization.

Cloud Overlap Features from Multi-Year Cloud Radar Observations at the SACOL Site and Comparison with Satellites

Cloud overlap, referring to distinct cloud layers occurring over the same location, is essential for accurately calculating the atmospheric radiation transfer in numerical models, which, in turn, enhances our ability to predict future climate change. In this study, we analyze multi-year cloud overlap properties observed from the Ka-band Zenith Radar (KAZR) at the Semi-Arid Climate and Environment Observatory of Lanzhou University’s (SACOL) site. We conduct a series of statistical analyses and determine the suitable temporal-spatial resolution of 1 h with a 360 m scale for data analysis. Our findings show that the cloud overlap parameter and total cloud fraction are maximized during winter-spring and minimized in summer-autumn, and the extreme value of decorrelation length usually lags one or two seasons. Additionally, we find the cloud overlap assumption has distinct effects on the cloud fraction bias for different cloud types. The random overlap leads to the minimum bias of the cloud fraction for Low-Middle-High (LMH), Low-Middle (LM), and Middle-High (MH) clouds, while the maximum overlap is for Low (L), Middle (M), and High (H) clouds. We also incorporate observations from satellite-based active sensors, including CloudSat, Cloud-Aerosol Lidar, and Infrared Pathfinder Satellite Observations (CALIPSO), to refine our study area and specific cases by considering the total cloud fraction and sample size from different datasets. Our analysis reveals that the representativeness of random overlap strengthens and then weakens with increasing layer separations. The decorrelation length varies with the KAZR, CloudSat-CALIPSO, CloudSat, and CALIPSO datasets, measuring 1.43 km, 2.18 km, 2.58 km, and 1.11 km, respectively. For H, MH, and LMH clouds, the average cloud overlap parameter from CloudSat-CALIPSO aligns closely with KAZR. For L, M, and LM clouds, when the level separation of cloud layer pairs are less than 1 km, the representative assumption obtained from different datasets are maximum overlap.

A Regional Aerosol Model for the Middle Urals Based on CALIPSO Measurements

The present work aims to develop a regional Middle Urals Aerosol model (MUrA model) based on the joint analysis of long-term ground-based photometric measurements of the Aerosol Robotic NETwork (AERONET) and the results of lidar measurements of the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite relying on information on the air trajectories at different altitudes calculated using the HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory model) software package. The MUrA model contains parameters of normalized volume size distributions (NVSDs) characterizing the tropospheric aerosol subtypes detected by the CALIPSO satellite. When comparing the MUrA model with the global CALIPSO Aerosol Model (CAMel), we found significant differences in NVSDs for elevated smoke and clean continental aerosol types. NVSDs for dust and polluted continental/smoke aerosol types in the global and regional models differ much less. The total volumes of aerosol particles along the atmospheric column reconstructed from satellite measurements of the attenuation coefficient at a wavelength of 532 nm based on the regional MUrA model and global CAMel are compared with the AERONET inversion data. The mean bias error for the regional model is 0.016 μm3/μm2, and 0.043 μm3/μm2 for the global model.

Multi-faceted analysis of dust storm from satellite imagery, ground station, and model simulations, a study in China

An intense dust storm from 8 April to 11 April 2023 originated from the Gobi deserts bordering Mongolia and Inner Mongolia of China and affected most parts of northern, central, and eastern China, the Korean Peninsula, and Japan. It has a significant impact on air quality in these regions and alters the optical and microphysical properties of the aerosols. In this work, a comprehensive analysis of the storm was carried out by using reanalysis data, model simulation, satellite, and ground-based observations. The geopotential height along with the wind flow reveals that the development, transportation, and dissipation of the dust storms were closely related to the movement of the Mongolia cyclones caused by Mongolia low and its surrounding highs. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data showed a two-layer dust vertical distribution, with the bottom one below 5 km and the upper one stretching from 5 to 10 km over the Japan Sea. The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) backward trajectory uncovered Central Mongolia being the origin of the dust storm that arrived over the Japan Sea on April 9, 2022, and the forward trajectory revealed that the dust aerosols would be further transported to the Pacific Ocean. Air quality analysis demonstrated that the regions of inner Mongolia (IMG) and Jing-Jin-Ji (JJJ) suffered the most from the dust storm events, followed by the Yangtze River Delta (YRD), while the Pearl River Delta (PRD) was hardly affected, as indicated by the regional-averaged PM10 and PM2.5. It was also found that the dust storm event has almost no significant influence on the other air quality indicators including CO, NO2, O3, and SO2. Historical record tracking revealed that the springtime averaged PM10 and PM2.5 of the year 2023 are comparable to those in 2021 which has the record-breaking dust storm case. AERONET data indicated dramatic increments of aerosol optical depth at 550 nm (AOD550) and effective radius of total size (ReffT) in regions of Gobi and JJJ, accompanied by low Angstrom Exponent (AE), and high SSA870 values, while in the regions of Korea and Japan, minor increments of AOD550 and ReffT were found. This study provides a holistic scientific view of the dust storm which could aid in the implementation of protective measures against dust storms.

Three-Dimensional Distribution and Transport Features of Dust and Polluted Dust over China and Surrounding Areas from CALIPSO

Dust plays a very important role in the Earth’s climate system by its direct and indirect effects. Deserts in northwestern China contribute a large amount of dust particles, both inland and outside, while the vertical distribution and transport mechanism of dust still have many uncertainties. Using Level 3 cloud-free monthly aerosol products of the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) system from 2007 to 2020, we analyzed the spatial and temporal variations and transport features for dust and polluted dust aerosols over China and the surrounding areas. The results show that the Taklimakan Desert (TD) and the Thar Desert (TRD) always act as the high-value centers of dust optical depth (DOD), while the centers of polluted dust optical depth (PDOD) are located in eastern China, the Sichuan Basin and the Indian subcontinent. The DOD shows an increasing trend in most areas, while the PDOD presents a significant decrease and increase in eastern China and central India, respectively. The largest DOD appears in spring over the TD and the Gobi Desert (GD), while the largest DOD in summer is over the TRD. Although most dusts in the TD and TRD are concentrated below 4 km, they may be higher over the TD. Most of the polluted dusts are confined to under 2 km. The dust input to the Tibetan Plateau (TP) could come from both the TD and TRD and occurs mostly in spring and summer, respectively. The polluted dusts of South Asia and the Indian subcontinent are mostly contained in the boundary layer in winter, but they could extend much higher in spring and summer, which favors their transport into southwestern China. The dust layer shows apparent seasonality. Its top reaches a higher level in spring and summer, while the base stays at a similar height in all seasons. The dust layer appears to be the thickest in spring over most areas, while the thickest layer in summer is over the TD and TRD. The polluted dust layer is thickest in the Indian subcontinent in spring. The overlapping of dust and polluted dust layers present different patterns in different regions, which suggests diverse mixture processes of dusts and pollutants. Finally, we compared and found different influences of meteorological factors, such as wind field, boundary layer height and precipitation, on the variations in DOD and PDOD over dust sources and other areas.

Climatology and trends of cirrus geometrical and optical properties in the Amazon region from 7-yr of CALIPSO observations

Recent studies have shown that the presence of cirrus clouds in the Amazon is higher than in other tropical regions, but also that convective activity in the region is decreasing, which could mean a decrease in high clouds. We used data from 2009 to 2016 from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), aboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), to study cirrus over the Amazon. Here we report on an analysis of the frequency of occurrence, base and top altitude, geometric thickness, and optical depth for the whole Amazon, as well as their spatial distribution and medium-term trends. A total of 1,473,863 vertical profiles were analyzed containing 728,123 cirrus layers, being 37.0% in the wet and 21.2% in the dry season. They are evenly distributed throughout the region during the wet season and concentrated in the northwest of the Amazon during the dry season. In terms of cloud optical depth (COD), most cirrus were optically thin (0.03<COD<0.3), with a relative frequency of 43.9%, while subvisual (COD<0.03) and thick (COD>0.3) corresponded to 22.0 and 34.1%, respectively. The results indicate a significant reduction in the frequency of cirrus occurrence of 1.3 ± 0.3% per year in the wet season, accompanied by a reduction of the geometric thickness of the thickest cirrus by 57 ± 18 m. This corroborates previous reports of a reduction of convective activity and high cloud fraction in the region.

Observing a dust aerosol layer at a height of 3–4 km above the ground on the southern margin of the Tarim Basin

The vertical distribution and transport properties of dust aerosols play a key role in regional and even global climate and environmental changes. However, there are still gaps in understanding the optical properties, transport mechanisms, and topographic effects on dust in the dust-prone area-southern margin of the Tarim Basin. In this study, we use the Ground-Based Aerosol Lidar (GBQL-01) installed in Hotan and Minfeng in cooperation with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) to synthesize and analyze the dust formation process at the southern margin of the basin once, and to test the reliability of the ground-based aerosol lidar. The variability characteristics of meteorological elements during this dust process will be discussed. Furthermore, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) was used to reproduce this dust process. The results show that the vertical transport of dust particles reaches about 4 km and 3 km in Hotan and Minfeng, respectively, and the dust aerosol stratification intensity is obvious within 1 km height in both places, and there is a dust aerosol layer at 3 km height in both places. The high winds are blocked by the large topography of the Tianshan Mountains and the northern slopes of the Tibet Plateau, and they change to northeasterly winds, triggering dusty weather outbreaks at the southern margin of the Tarim Basin. When the dusty weather subsided, dust aerosols with concentrations of 300–400 μg m−3 were still present at an altitude of 4 km, and a clear suspended dust phenomenon was formed. Meanwhile, the increase of wind speed and relative humidity, as well as the decrease of temperature, easily contribute to the occurrence of dusty weather and the transport of particulate matter. This work provides a useful reference for the study of regional climate change, topographic effects and "suspended dust".

Roles of tropical cyclones with varying intensities in the re-distribution of aerosols

The study analyzes three tropical cyclones (TC) with varying intensities, namely BOB02, a deep depression in the Bay of Bengal; Tauktae, an extremely severe cyclone in the Arabian Sea (AS); and Amphan, a supercyclone in the Bay of Bengal, which developed on October 11, 2020, May 13, 2021, and May 16, 2020, respectively. The analysis focuses on studying the re-distribution of the aerosols over the Indian region using these distinct datasets: Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRA2), Integrated Multi-Satellite Retrievals for GPM (IMERG), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). Throughout the cyclonic period, which includes the period from the inception of the low-pressure area to its dissipation as well as the pre-cyclonic and post-cyclonic periods (one week prior to and after the cyclonic period, respectively), various parameters related to aerosols and background meteorological conditions were collected. The primary parameter of interest was the aerosol optical depth (AOD). The analysis revealed significant variations in meteorological parameters such as wind speed, temperature, relative humidity, and rainfall along the cyclone track during both the cyclonic and post-cyclonic conditions compared to the pre-cyclonic conditions of these TCs. The AOD surrounding the cyclone track decreases during cyclonic and post-cyclonic conditions compared to pre-cyclonic conditions. This is due to the scavenging of both anthropogenic and natural (dust) aerosols. Conversely, AOD increases along the cyclone track, mainly due to an increase in natural (sea salt) aerosols. During pre-cyclonic conditions, both natural (dust) and anthropogenic (black carbon, organic carbon, and sulfate) aerosols contribute significantly to the total AOD, whereas during pre-cyclonic conditions, the main contributors are natural (sea-salt) aerosols. The coarse-mode particles are more dominant during cyclonic and post-cyclonic conditions than pre-cyclonic ones. Furthermore, our observations indicate that the atmospheric boundary layer (ABL) height increases by ∼0.1–0.6 km along the cyclone track during cyclonic conditions compared to pre-cyclonic conditions. While AOD from the free troposphere (FT) contributes more to the total AOD, contributions from ABL increase, while those from the FT decrease during cyclonic and post-cyclonic conditions.

Theoretical derivation of aerosol lidar ratio using Mie theory for CALIOP-CALIPSO and OPAC aerosol models

Abstract. The extinction-to-backscattering ratio, popularly known as lidar (light detection and ranging) ratio of atmospheric aerosols is an important optical property, which is essential to retrieve the extinction profiles of atmospheric aerosols. Lidar satellite observations can provide the global coverage of atmospheric aerosols along with their vertical extent. NASA's Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is the only space-based platform available, so far, that provides the vertical profiles of extinction due to atmospheric aerosols. A physics-based theoretical approach is presented in the present paper that estimates lidar ratio values for CALIPSO aerosol models, which can be used as inputs to determine the extinction profiles of aerosols using CALIPSO data. The developed methodology was also qualified by comparing it with the lidar ratio values derived using AERONET (AErosol RObotic NETwork) datasets. Lidar ratio values for CALIPSO aerosol models were estimated in the range of 38.72 to 85.98 sr at 532 nm, whereas at 1064 nm lidar ratio varied between 20.11 to 71.11 sr depending upon the aerosol type and their size distributions. Aerosols are compositions of various particles; thus, the presence of water vapour in the atmosphere can affect the optical properties of the aerosols. Thus, the effect of relative humidity on lidar ratio was studied using Optical Properties of Aerosols and Clouds (OPAC) aerosol models, which are the standard aerosol models against the cluster-classified AERONET and CALIPSO aerosol models. Water-soluble particles contribute substantially in clean continental, clean marine, tropical marine and desert aerosol models and are hygroscopic in nature. Hygroscopic sulfate particles dominate the Antarctic aerosols during summertime. In the presence of relative humidity between 0 %–80 %, the lidar ratio values were observed to decrease from 53.59 to 47.13, from 53.66 to 47.15, from 53.70 to 47.16, and from 55.32 to 48.78 sr at 532 nm for clean continental, clean marine, tropical marine, and desert aerosols, respectively, whereas lidar ratio gradually increased from 47.13 to 51, from 47.15 to 51, from 47.16 to 51, and from 48.78 to 51.68 sr, respectively, for these aerosol models when relative humidity was between 80 %–99 %, due to constituent hygroscopic particles. In the case of Antarctic aerosols, the lidar ratio was observed to increase from 57.73 to 97.64 sr due to hygroscopic sulfate particles that backscattered heavily in the presence of water vapour at 532 nm. The soot particles dominate the polluted continental and polluted marine particles, causing an increase in lidar ratio over its corresponding clean counterpart. Similar results were observed at 1064 nm for OPAC aerosol models.

Assessment of aerosol optical and physical properties and implications for radiative effects over the semiarid region of Indo‐Gangetic Basin

This study assesses the physical and optical properties and estimated the radiative forcing of aerosol at Agra over the Indo‐Gangetic Basin (IGB) during July 2016–December 2019 using black carbon (BC) mass concentration (AE‐33 aethalometer), data sets from satellite and model simulations. The optical properties of aerosol and radiative forcing have been measured by the Optical and Physical Properties of Aerosols and Clouds (OPAC) and Santa Barbara Discrete Ordinate Radiative Transfer Atmospheric Radiative Transfer (SBDART) model. The high BC mass concentration has been observed in November and lowest in August. An adverse meteorological condition due to a combination of temperature and low wind speed results in poor dispersion in the wintertime is a common factor for high concentration level pollutants over Agra. The diurnal and temporal cycle of BC mass concentration exhibits a high concentration at nighttime due to the lower atmospheric boundary layer. The seasonal variation of absorption coefficient (βabs) and Absorption Angstrom Exponent (AAE) is found to be higher during post‐monsoon and lowest in monsoon season. This suggests that black carbon concentration over Agra is mainly generated from crop burning, waste burning, automobile exhaust and long‐range transport from Punjab and Haryana as the present site is downwind. OPAC‐derived aerosol optical depth (AOD), single‐scattering albedo (SSA), Angstrom Exponent (AE) and asymmetry parameter (AsyP) were estimated to be 0.57 ± 0.07, 0.78 ± 0.16, 0.99 ± 0.21 and 0.81 ± 0.15, respectively. AOD and AE from the OPAC and the moderate resolution imaging spectroradiometer (MODIS) have shown the consistent relationship. The mean radiative forcing is 18.3 ± 2.1 W m−2 at the top of the atmosphere while, at the surface, net radiative forcing is −42.4 ± 7.2 and 59.1 ± 6.5 W m−2 at the atmosphere during the study period. Vertical profiles were estimated using the observations from Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the change in heating rate from the SBDART model over Agra.