100 citations as recorded by crossref.

1. A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations F. Alexandri et al. https://doi.org/10.5194/amt-17-1739-2024
2. Spatiotemporal characteristics of aerosols and low clouds from MODIS and their implications for marine cloud brightening L. Niu et al. https://doi.org/10.1007/s11430-025-1794-7
3. Assessment of simulated aerosol effective radiative forcings in the terrestrial spectrum I. Heyn et al. https://doi.org/10.1002/2016GL071975
4. Building a cloud in the southeast Atlantic: understanding low-cloud controls based on satellite observations with machine learning J. Fuchs et al. https://doi.org/10.5194/acp-18-16537-2018
5. Opportunistic experiments to constrain aerosol effective radiative forcing M. Christensen et al. https://doi.org/10.5194/acp-22-641-2022
6. Under What Conditions Can We Trust Retrieved Cloud Drop Concentrations in Broken Marine Stratocumulus? Y. Zhu et al. https://doi.org/10.1029/2017JD028083
7. Aerosol-driven droplet concentrations dominate coverage and water of oceanic low-level clouds D. Rosenfeld et al. https://doi.org/10.1126/science.aav0566
8. Satellite Retrieval of Cloud Condensation Nuclei Concentrations in Marine Stratocumulus by Using Clouds as CCN Chambers A. Efraim et al. https://doi.org/10.1029/2020JD032409
9. Treatment of Key Aerosol and Cloud Processes in Earth System Models – Recommendations from the FORCeS Project I. Riipinen et al. https://doi.org/10.16993/tellusb.1883
10. Constraining effects of aerosol-cloud interaction by accounting for coupling between cloud and land surface T. Su et al. https://doi.org/10.1126/sciadv.adl5044
11. Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods H. Jia et al. https://doi.org/10.1038/s41467-021-23888-1
12. CCN Retrievals from Spaceborne Lidar Observations During ACEMED: Sensitivity to Smoke Parameterization A. Georgoulias et al. https://doi.org/10.3390/rs18040586
13. Bounding Global Aerosol Radiative Forcing of Climate Change N. Bellouin et al. https://doi.org/10.1029/2019RG000660
14. Investigating the sign of stratocumulus adjustments to aerosols in the ICON global storm-resolving model E. Fons et al. https://doi.org/10.5194/acp-24-8653-2024
15. Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations D. Painemal et al. https://doi.org/10.5194/acp-20-7167-2020
16. Automated Mapping of Convective Clouds (AMCC) Thermodynamical, Microphysical, and CCN Properties from SNPP/VIIRS Satellite Data Z. Yue et al. https://doi.org/10.1175/JAMC-D-18-0144.1
17. Quantifying cloud adjustments and the radiative forcing due to aerosol–cloud interactions in satellite observations of warm marine clouds A. Douglas & T. L'Ecuyer https://doi.org/10.5194/acp-20-6225-2020
18. How should we aggregate data? Methods accounting for the numerical distributions, with an assessment of aerosol optical depth A. Sayer & K. Knobelspiesse https://doi.org/10.5194/acp-19-15023-2019
19. Is positive correlation between cloud droplet effective radius and aerosol optical depth over land due to retrieval artifacts or real physical processes? H. Jia et al. https://doi.org/10.5194/acp-19-8879-2019
20. Decreasing aerosols increase the European summer diurnal temperature range C. Roesch et al. https://doi.org/10.1038/s41612-025-00922-3
21. Sensitivity of cloud microphysics to aerosol is highly associated with cloud water content: Implications for indirect radiative forcing Y. Wang et al. https://doi.org/10.1016/j.atmosres.2024.107552
22. Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli J. Zhang et al. https://doi.org/10.5194/acp-24-10425-2024
23. Representation Uncertainty in the Earth Sciences C. Bulgin et al. https://doi.org/10.1029/2021EA002129
24. Observational Quantification of Aerosol Invigoration for Deep Convective Cloud Lifecycle Properties Based on Geostationary Satellite Z. Pan et al. https://doi.org/10.1029/2020JD034275
25. Aerosol measurements by SPEXone on the NASA PACE mission: expected retrieval capabilities O. Hasekamp et al. https://doi.org/10.1016/j.jqsrt.2019.02.006
26. Impact of isolated atmospheric aging processes on the cloud condensation nuclei activation of soot particles F. Friebel et al. https://doi.org/10.5194/acp-19-15545-2019
27. Studying the Aerosol Effect on Deep Convective Clouds over the Global Oceans by Applying Machine Learning Techniques on Long-Term Satellite Observation X. Zhao et al. https://doi.org/10.3390/rs16132487
28. Negligible contribution from aerosols to recent trends in Earth’s energy imbalance C. Park & B. Soden https://doi.org/10.1126/sciadv.adv9429
29. Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation M. Bonazzola et al. https://doi.org/10.5194/gmd-16-1359-2023
30. Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks H. Andersen et al. https://doi.org/10.5194/acp-17-9535-2017
31. Analyzing Sensitive Aerosol Regimes and Active Geolocations of Aerosol Effects on Deep Convective Clouds over the Global Oceans by Using Long-Term Operational Satellite Observations X. Zhao & M. Foster https://doi.org/10.3390/cli10110167
32. Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic E. Lenhardt et al. https://doi.org/10.5194/amt-16-2037-2023
33. Climatology Perspective of Sensitive Regimes and Active Regions of Aerosol Indirect Effect for Cirrus Clouds over the Global Oceans X. Zhao et al. https://doi.org/10.3390/rs12050823
34. Emission Reductions Significantly Reduce the Hemispheric Contrast in Cloud Droplet Number Concentration in Recent Two Decades Y. Cao et al. https://doi.org/10.1029/2022JD037417
35. Quantifying variations in shortwave aerosol–cloud–radiation interactions using local meteorology and cloud state constraints A. Douglas & T. L'Ecuyer https://doi.org/10.5194/acp-19-6251-2019
36. A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations P. Patel et al. https://doi.org/10.5194/acp-24-2861-2024
37. Dust suppresses aerosol first indirect effects in marine warm clouds over the North Atlantic Ocean S. Pandey et al. https://doi.org/10.1038/s43247-026-03693-8
38. Aerosol-induced modification of organised convection and top-of-atmosphere radiation N. Nishant et al. https://doi.org/10.1038/s41612-019-0089-1
39. Developing a climatological simplification of aerosols to enter the cloud microphysics of a global climate model U. Proske et al. https://doi.org/10.5194/acp-24-5907-2024
40. Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 2: Controls on the ice crystal number concentration E. Gryspeerdt et al. https://doi.org/10.5194/acp-18-14351-2018
41. A First Case Study of CCN Concentrations from Spaceborne Lidar Observations A. Georgoulias et al. https://doi.org/10.3390/rs12101557
42. Assessment of CALIOP-Derived CCN Concentrations by In Situ Surface Measurements G. Choudhury & M. Tesche https://doi.org/10.3390/rs14143342
43. Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals A. Varble et al. https://doi.org/10.5194/acp-23-13523-2023
44. Spatial Heterogeneity of Aerosol Effect on Liquid Cloud Microphysical Properties in the Warm Season Over Tibetan Plateau P. Zhao et al. https://doi.org/10.1029/2022JD037738
45. Retrieval and validation of cloud condensation nuclei from satellite and airborne measurements over the Indian Monsoon region A. Aravindhavel et al. https://doi.org/10.1016/j.atmosres.2023.106802
46. Relationship between cloud condensation nuclei (CCN) concentration and aerosol optical depth in the Arctic region S. Ahn et al. https://doi.org/10.1016/j.atmosenv.2021.118748
47. A Case Study in Low Aerosol Number Concentrations Over the Eastern North Atlantic: Implications for Pristine Conditions in the Remote Marine Boundary Layer S. Pennypacker & R. Wood https://doi.org/10.1002/2017JD027493
48. Opposite Aerosol Index‐Cloud Droplet Effective Radius Correlations Over Major Industrial Regions and Their Adjacent Oceans X. Ma et al. https://doi.org/10.1029/2018GL077562
49. Estimation of Cloud Condensation Nuclei (CCN) using a neural network retrieval algorithm—A synthetic study for SPEXone on the NASA PACE mission N. Hannadige et al. https://doi.org/10.1016/j.jqsrt.2026.109853
50. Reconciling observed and predicted droplet concentration at the Indian summer monsoon cloud base M. Varghese & T. Prabhakaran https://doi.org/10.1016/j.scitotenv.2025.179077
51. Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors H. Dadashazar et al. https://doi.org/10.5194/acp-21-10499-2021
52. Machine Learning Approach to Investigating the Relative Importance of Meteorological and Aerosol-Related Parameters in Determining Cloud Microphysical Properties F. Bender et al. https://doi.org/10.16993/tellusb.1868
53. POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites Y. He et al. https://doi.org/10.5194/amt-16-1951-2023
54. Retrieved XCO2 Accuracy Improvement by Reducing Aerosol-Induced Bias for China’s Future High-Precision Greenhouse Gases Monitoring Satellite Mission J. Ke et al. https://doi.org/10.3390/atmos13091384
55. Sensitivities of cloud radiative effects to large-scale meteorology and aerosols from global observations H. Andersen et al. https://doi.org/10.5194/acp-23-10775-2023
56. SPEX airborne spectropolarimeter calibration and performance J. Smit et al. https://doi.org/10.1364/AO.58.005695
57. Strategizing emission cuts in China to mitigate short-term warming from clean air policies Y. Zhu et al. https://doi.org/10.1038/s41467-026-72190-5
58. Constraining the instantaneous aerosol influence on cloud albedo E. Gryspeerdt et al. https://doi.org/10.1073/pnas.1617765114
59. Distinct impacts on precipitation by aerosol radiative effect over three different megacity regions of eastern China Y. Sun & C. Zhao https://doi.org/10.5194/acp-21-16555-2021
60. Aerosol effective radius governs the relationship between cloud condensation nuclei (CCN) concentration and aerosol backscatter E. Lenhardt et al. https://doi.org/10.5194/acp-25-13747-2025
61. Characterizing the Relative Importance Assigned to Physical Variables by Climate Scientists when Assessing Atmospheric Climate Model Fidelity S. Burrows et al. https://doi.org/10.1007/s00376-018-7300-x
62. Aerosol optical depth disaggregation: toward global aerosol vertical profiles S. Bouabid et al. https://doi.org/10.1017/eds.2024.15
63. Bibliometric Analysis of Aerosol-Radiation Research from 1999 to 2023 S. Wang & B. Yi https://doi.org/10.3390/atmos15101189
64. The Global Atmosphere‐aerosol Model ICON‐A‐HAM2.3–Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness M. Salzmann et al. https://doi.org/10.1029/2021MS002699
65. Variability in the correlation between satellite-derived liquid cloud droplet effective radius and aerosol index over the northern Pacific Ocean S. Tan et al. https://doi.org/10.1080/16000889.2017.1391656
66. The importance of mixed-phase and ice clouds for climate sensitivity in the global aerosol–climate model ECHAM6-HAM2 U. Lohmann & D. Neubauer https://doi.org/10.5194/acp-18-8807-2018
67. A machine learning paradigm for necessary observations to reduce uncertainties in aerosol climate forcing J. Redemann & L. Gao https://doi.org/10.1038/s41467-024-52747-y
68. Advancing the quantification of aerosol-cloud interactions with the CALIPSO-CloudSat-Aqua/MODIS record Z. Li et al. https://doi.org/10.5194/acp-26-7705-2026
69. Weather specific evaluation of satellite retrieved aerosol optical depth over drylands of the Southwest United States H. Dhaliwal & S. Pal https://doi.org/10.1016/j.atmosres.2026.108932
70. Passive remote sensing of aerosol layer height using near‐UV multiangle polarization measurements L. Wu et al. https://doi.org/10.1002/2016GL069848
71. Dissipating the correlation smokescreen: causal decomposition of the radiative effects of biomass burning aerosols over the South-East Atlantic E. Fons et al. https://doi.org/10.1017/eds.2026.10049
72. Unveiling aerosol–cloud interactions – Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data D. Neubauer et al. https://doi.org/10.5194/acp-17-13165-2017
73. Strong Precipitation Suppression by Aerosols in Marine Low Clouds C. Fan et al. https://doi.org/10.1029/2019GL086207
74. Observational constraints suggest a smaller effective radiative forcing from aerosol–cloud interactions C. Park et al. https://doi.org/10.5194/acp-25-7299-2025
75. Constraining Uncertainty in Aerosol Direct Forcing D. Watson‐Parris et al. https://doi.org/10.1029/2020GL087141
76. Evidence of cloud sensitivity to above-cloud CCN as a function of environmental stability in the Southeast Atlantic based on remote sensing observations E. Lenhardt et al. https://doi.org/10.5194/acp-26-11709-2026
77. 基于MODIS观测的全球气溶胶与低云时空特征及其对<?A3B2 pi6?>海洋云增亮的启示 莉. 牛 et al. https://doi.org/10.1360/SSTe-2025-0229
78. A robust aerosol impact on clouds along the subtropical to tropical transition N. Yeheskel et al. https://doi.org/10.5194/acp-26-8765-2026
79. A New Cloud Water Path Retrieval Method Based on Geostationary Satellite Infrared Measurements G. Tana et al. https://doi.org/10.1109/TGRS.2025.3526262
80. Optimal choice of proxy for cloud condensation nuclei reduces uncertainty in aerosol-cloud-climate forcing H. Jia et al. https://doi.org/10.1126/sciadv.aea4828
81. Opinion: A critical evaluation of the evidence for aerosol invigoration of deep convection A. Varble et al. https://doi.org/10.5194/acp-23-13791-2023
82. Constraining the Twomey effect from satellite observations: issues and perspectives J. Quaas et al. https://doi.org/10.5194/acp-20-15079-2020
83. Addressing the difficulties in quantifying droplet number response to aerosol from satellite observations H. Jia et al. https://doi.org/10.5194/acp-22-7353-2022
84. Cloud condensation nuclei concentrations derived from the CAMS reanalysis K. Block et al. https://doi.org/10.5194/essd-16-443-2024
85. Surprising similarities in model and observational aerosol radiative forcing estimates E. Gryspeerdt et al. https://doi.org/10.5194/acp-20-613-2020
86. Decomposing the effective radiative forcing of anthropogenic aerosols based on CMIP6 Earth system models A. Kalisoras et al. https://doi.org/10.5194/acp-24-7837-2024
87. The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing, and climate sensitivity D. Neubauer et al. https://doi.org/10.5194/gmd-12-3609-2019
88. Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations P. Ma et al. https://doi.org/10.1038/s41467-018-05028-4
89. Nonlinearity of the cloud response postpones climate penalty of mitigating air pollution in polluted regions H. Jia & J. Quaas https://doi.org/10.1038/s41558-023-01775-5
90. Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street R. Kahn et al. https://doi.org/10.1029/2022RG000796
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92. Observing short-timescale cloud development to constrain aerosol–cloud interactions E. Gryspeerdt et al. https://doi.org/10.5194/acp-22-11727-2022
93. Validation of satellite-retrieved CCN based on a cruise campaign over the polluted Northwestern Pacific ocean Y. Wang et al. https://doi.org/10.1016/j.atmosres.2021.105722
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96. The importance of comprehensive parameter sampling and multiple observations for robust constraint of aerosol radiative forcing J. Johnson et al. https://doi.org/10.5194/acp-18-13031-2018
97. Effects of auxiliary atmospheric state parameters on the aerosol optical properties retrieval errors of high-spectral-resolution lidar Y. Zhang et al. https://doi.org/10.1364/AO.57.002627
98. Estimating cloud condensation nuclei concentrations from CALIPSO lidar measurements G. Choudhury & M. Tesche https://doi.org/10.5194/amt-15-639-2022
99. Impact of Saharan dust on North Atlantic marine stratocumulus clouds: importance of the semidirect effect A. Amiri-Farahani et al. https://doi.org/10.5194/acp-17-6305-2017
100. Potential Modulation of Aerosol on Precipitation Efficiency in Southwest China P. Zhao et al. https://doi.org/10.3390/rs16081445