76 citations as recorded by crossref.

1. Aerosols at the poles: an AeroCom Phase II multi-model evaluation M. Sand et al. https://doi.org/10.5194/acp-17-12197-2017
2. Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products T. Toth et al. https://doi.org/10.5194/amt-11-499-2018
3. Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. https://doi.org/10.5194/amt-13-4645-2020
4. Vertical distribution of type-discriminated aerosol concentration from a three-wavelength backscatter spaceborne lidar F. Qayyum et al. https://doi.org/10.1016/j.rse.2026.115399
5. CALIPSO lidar level 3 aerosol profile product: version 3 algorithm design J. Tackett et al. https://doi.org/10.5194/amt-11-4129-2018
6. Constrained Retrievals of Aerosol Optical Properties Using Combined Lidar and Imager Measurements During the FIREX-AQ Campaign N. Midzak et al. https://doi.org/10.3389/frsen.2022.818605
7. Application of high-dimensional fuzzy k-means cluster analysis to CALIOP/CALIPSO version 4.1 cloud–aerosol discrimination S. Zeng et al. https://doi.org/10.5194/amt-12-2261-2019
8. Denoising the space-borne high-spectral-resolution lidar signal with block-matching and 3D filtering Z. Zheng et al. https://doi.org/10.1364/AO.385469
9. Joint multiscale cloud detection algorithm for ground-based lidar W. Xu et al. https://doi.org/10.1364/OE.473727
10. EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product E. Proestakis et al. https://doi.org/10.5194/acp-19-11743-2019
11. Layer detection algorithm for CALIPSO observation based on automatic segmentation with a minimum cost function F. Mao et al. https://doi.org/10.1016/j.jqsrt.2020.107498
12. Characteristics of Atmospheric Aerosols Over the UAE Inferred From CALIPSO and Sun Photometer Aerosol Optical Depth N. Nelli et al. https://doi.org/10.1029/2020EA001360
13. Aerosol indirect effects on the nighttime Arctic Ocean surface from thin, predominantly liquid clouds L. Zamora et al. https://doi.org/10.5194/acp-17-7311-2017
14. Quantifying dust deposition over the Atlantic Ocean E. Proestakis et al. https://doi.org/10.5194/essd-17-4351-2025
15. 基于布料模拟的激光雷达大气垂直层结构识别 屈. Qu Zhichen et al. https://doi.org/10.3788/AOS251044
16. Flood Damage Analysis: First Floor Elevation Uncertainty Resulting from LiDAR-Derived Digital Surface Models J. Bodoque et al. https://doi.org/10.3390/rs8070604
17. Evaluation of aerosol number concentrations from CALIPSO with ATom airborne in situ measurements G. Choudhury et al. https://doi.org/10.5194/acp-22-7143-2022
18. Decadal Aerosol Column-Integrated Lidar Ratio Climatology Over East Asia From Synergistic AD-Net Lidar and Sun/Sky Radiometer Observations M. Kim et al. https://doi.org/10.1109/LGRS.2026.3712279
19. Global vertically resolved aerosol direct radiation effect from three years of CALIOP data using the FORTH radiation transfer model M. Korras-Carraca et al. https://doi.org/10.1016/j.atmosres.2019.03.024
20. The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm M. Kim et al. https://doi.org/10.5194/amt-11-6107-2018
21. New attenuated backscatter profile by removing the CALIOP receiver's transient response X. Lu et al. https://doi.org/10.1016/j.jqsrt.2020.107244
22. Assessment of tropospheric CALIPSO Version 4.2 aerosol types over the ocean using independent CALIPSO–SODA lidar ratios Z. Li et al. https://doi.org/10.5194/amt-15-2745-2022
23. Aerosol-cloud layer detection algorithm of the DQ-1/ACDL F. Mao et al. https://doi.org/10.1016/j.rse.2025.115068
24. Satellite-borne identification and quantification of wildfire smoke emissions in North America via a novel UV-based index Z. Suo et al. https://doi.org/10.1016/j.atmosenv.2025.121069
25. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) airborne field campaign K. Knobelspiesse et al. https://doi.org/10.5194/essd-12-2183-2020
26. Analysis of characteristics and changes in three-dimensional spatial and temporal distribution of aerosol types in Central Asia Y. Gan et al. https://doi.org/10.1016/j.scitotenv.2024.172196
27. All‐Sky Aerosol Direct Radiative Effects at the ARM SGP Site K. Balmes & Q. Fu https://doi.org/10.1029/2021JD034933
28. Spatiotemporal distribution characteristics of aerosols over the South China Sea based an improved spaceborne-Lidar aerosol identification algorithm H. Yang et al. https://doi.org/10.1364/OE.573891
29. Atmospheric Dust as an Air Quality Hazard to the World Population E. Proestakis et al. https://doi.org/10.3390/rs18142403
30. All-sky direct aerosol radiative effects estimated from integrated A-Train satellite measurements M. Kacenelenbogen et al. https://doi.org/10.5194/acp-25-15875-2025
31. Three-dimensional dust aerosol distribution and extinction climatology over northern Africa simulated with the ALADIN numerical prediction model from 2006 to 2010 M. Mokhtari et al. https://doi.org/10.5194/acp-15-9063-2015
32. Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations P. Ma et al. https://doi.org/10.1038/s41467-018-05028-4
33. Australian wildfires cause the largest stratospheric warming since Pinatubo and extends the lifetime of the Antarctic ozone hole L. Damany-Pearce et al. https://doi.org/10.1038/s41598-022-15794-3
34. Airborne HSRL-2 measurements of elevated aerosol depolarization associated with non-spherical sea salt R. Ferrare et al. https://doi.org/10.3389/frsen.2023.1143944
35. On the representativeness of the ground-based lidar observations for satellite calibration/validation – the example of the archipelago of Cabo Verde A. Floutsi et al. https://doi.org/10.5194/amt-19-1901-2026
36. Characterization of dust aerosols from ALADIN and CALIOP measurements R. Song et al. https://doi.org/10.5194/amt-17-2521-2024
37. Estimation of nighttime aerosol optical depths using the ground-based microwave radiometer G. Liu et al. https://doi.org/10.5194/amt-18-6705-2025
38. Identifying Aerosol Subtypes from CALIPSO Lidar Profiles Using Deep Machine Learning S. Zeng et al. https://doi.org/10.3390/atmos12010010
39. Mapping 532 nm lidar ratios for CALIPSO-classified marine aerosols using MODIS AOD constrained retrievals and GOCART model simulations T. Toth et al. https://doi.org/10.5194/amt-18-6765-2025
40. Determination of dust storm height using weak beam photons from ICESat-2 and relating with vertical wind profile G. Dandabathula et al. https://doi.org/10.1016/j.atmosenv.2025.121276
41. Quantifying the low bias of CALIPSO's column aerosol optical depth due to undetected aerosol layers M. Kim et al. https://doi.org/10.1002/2016JD025797
42. Vertical distribution of aerosols and clouds over north-eastern South Asia: Aerosol-cloud interactions P. Dahutia et al. https://doi.org/10.1016/j.atmosenv.2019.116882
43. Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product A. Feofilov et al. https://doi.org/10.5194/amt-16-3363-2023
44. Nine-year spatial and temporal evolution of desert dust aerosols over South and East Asia as revealed by CALIOP E. Proestakis et al. https://doi.org/10.5194/acp-18-1337-2018
45. Study on Vertically Distributed Aerosol Optical Characteristics over Saudi Arabia Using CALIPSO Satellite Data Z. Zhang et al. https://doi.org/10.3390/app12020603
46. Observations of the spectral dependence of linear particle depolarization ratio of aerosols using NASA Langley airborne High Spectral Resolution Lidar S. Burton et al. https://doi.org/10.5194/acp-15-13453-2015
47. Enhancements to the caliop aerosol subtyping and lidar ratio selection algorithms for level II version 4 A. Omar et al. https://doi.org/10.1051/epjconf/201817602006
48. Statistics of Smoke Sphericity and Optical Properties Using Spaceborne Lidar Measurements N. Midzak et al. https://doi.org/10.3390/rs17030409
49. High-Resolution Detection of Stratospheric Aerosols in CALIPSO Atmospheric Lidar Data Facilitated by the CALIOP-Density-Dimension Algorithm U. Herzfeld et al. https://doi.org/10.1109/TGRS.2025.3569546
50. Relationship between low-cloud presence and the amount of overlying aerosols C. Chung et al. https://doi.org/10.5194/acp-16-5781-2016
51. Particulate matter concentrations derived from airborne high spectral resolution lidar measurements using machine learning regression R. Ferrare et al. https://doi.org/10.5194/amt-18-7735-2025
52. CALIPSO-based aerosol extinction profile estimation from MODIS and MERRA-2 data using a hybrid model of Transformer and CNN Y. Zhen et al. https://doi.org/10.1016/j.scitotenv.2024.176423
53. Aerosol Retrievals from CALIPSO Lidar Ocean Surface Returns S. Venkata & J. Reagan https://doi.org/10.3390/rs8121006
54. Three-dimensional evolution of Saharan dust transport towards Europe based on a 9-year EARLINET-optimized CALIPSO dataset E. Marinou et al. https://doi.org/10.5194/acp-17-5893-2017
55. 地基Mie散射激光雷达反演的研究进展与挑战 毛. Mao Feiyue et al. https://doi.org/10.3788/AOS222188
56. Saharan dust long-range transport across the Atlantic studied by an airborne Doppler wind lidar and the MACC model F. Chouza et al. https://doi.org/10.5194/acp-16-11581-2016
57. Progress and Challenges in Quantifying Wildfire Smoke Emissions, Their Properties, Transport, and Atmospheric Impacts I. Sokolik et al. https://doi.org/10.1029/2018JD029878
58. How much of the global aerosol optical depth is found in the boundary layer and free troposphere? Q. Bourgeois et al. https://doi.org/10.5194/acp-18-7709-2018
59. Adaptive iterative optimization inversion method for plume extinction coefficient of Mie-scattering lidar Y. Ma et al. https://doi.org/10.1364/OE.577392
60. Persistent EarthCARE underflight studies of the ITCZ and organized convection (PERCUSION): contribution to EarthCARE validation S. Groß et al. https://doi.org/10.5194/amt-19-3933-2026
61. Comparison of V4 and V3 CALIOP (L3) aerosol products: A global perspective V. Sreekanth & P. Kulkarni https://doi.org/10.1016/j.rsase.2020.100412
62. Extinction and optical depth retrievals for CALIPSO's Version 4 data release S. Young et al. https://doi.org/10.5194/amt-11-5701-2018
63. Comparisons between the distributions of dust and combustion aerosols in MERRA-2, FLEXPART, and CALIPSO and implications for deposition freezing over wintertime Siberia L. Zamora et al. https://doi.org/10.5194/acp-22-12269-2022
64. Modeling of aerosol induced snow albedo feedbacks over the Himalayas and its implications on regional climate K. Usha et al. https://doi.org/10.1007/s00382-020-05222-5
65. Perception and sensing for autonomous vehicles under adverse weather conditions: A survey Y. Zhang et al. https://doi.org/10.1016/j.isprsjprs.2022.12.021
66. Vertical Distribution of the Aerosol Mass Concentration in East Asia Using CALIPSO Data S. Li et al. https://doi.org/10.1109/JSTARS.2025.3538572
67. Detection of pollution outflow from Mexico City using CALIPSO lidar measurements J. Kar et al. https://doi.org/10.1016/j.rse.2015.08.009
68. Novel aerosol extinction coefficients and lidar ratios over the ocean from CALIPSO–CloudSat: evaluation and global statistics D. Painemal et al. https://doi.org/10.5194/amt-12-2201-2019
69. Dust Lidar Ratios Retrieved from the CALIOP Measurements Using the MODIS AOD as a Constraint M. Kim et al. https://doi.org/10.3390/rs12020251
70. The Diurnal Variation of the Aerosol Optical Depth at the ARM SGP Site K. Balmes et al. https://doi.org/10.1029/2021EA001852
71. An automatic observation-based aerosol typing method for EARLINET N. Papagiannopoulos et al. https://doi.org/10.5194/acp-18-15879-2018
72. An Overview of Aerosol Properties in Clear and Cloudy Sky Based on CALIPSO Observations Y. Hong & L. Di Girolamo https://doi.org/10.1029/2022EA002287
73. Two-dimensional mineral dust radiative effect calculations from CALIPSO observations over Europe M. Granados-Muñoz et al. https://doi.org/10.5194/acp-19-13157-2019
74. Multi‐Year Seasonal Trends in Sea Ice, Chlorophyll Concentration, and Marine Aerosol Optical Depth in the Bellingshausen Sea S. Dasarathy et al. https://doi.org/10.1029/2021JD034737
75. Dust and smoke layers over the Atlantic Ocean weaken the underlying low-level cloud-top radiative cooling through different pathways S. Pandey & A. Adebiyi https://doi.org/10.1038/s43247-026-03183-x
76. A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure dust E. Proestakis et al. https://doi.org/10.5194/amt-17-3625-2024