67 citations as recorded by crossref.

1. Aerosol-induced changes in the vertical structure of precipitation: a perspective of TRMM precipitation radar J. Guo et al. https://doi.org/10.5194/acp-18-13329-2018
2. 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
3. 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
4. Predicting cloud condensation nuclei number concentration based on conventional measurements of aerosol properties in the North China Plain Y. Zhang et al. https://doi.org/10.1016/j.scitotenv.2020.137473
5. Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment R. Wood et al. https://doi.org/10.1175/BAMS-D-13-00180.1
6. Aerosol activation characteristics and prediction at the central European ACTRIS research station of Melpitz, Germany Y. Wang et al. https://doi.org/10.5194/acp-22-15943-2022
7. Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories J. Schmale et al. https://doi.org/10.5194/acp-18-2853-2018
8. Separating aerosol microphysical effects and satellite measurement artifacts of the relationships between warm rain onset height and aerosol optical depth Y. Zhu et al. https://doi.org/10.1002/2015JD023547
9. Assessing Desert Dust Indirect Effects on Cloud Microphysics through a Cloud Nucleation Scheme: A Case Study over the Western Mediterranean K. Tsarpalis et al. https://doi.org/10.3390/rs12213473
10. Aerosol properties and their influences on low warm clouds during the Two-Column Aerosol Project J. Liu & Z. Li https://doi.org/10.5194/acp-19-9515-2019
11. Statistical modelling of roadside and urban background ultrafine and accumulation mode particle number concentrations using generalized additive models L. Gerling et al. https://doi.org/10.1016/j.scitotenv.2019.134570
12. Variations in Cloud Concentration Nuclei Related to Continental Air Pollution Control and Maritime Fuel Regulation over the Northwest Pacific Ocean L. Sun et al. https://doi.org/10.3390/atmos15080972
13. Classifying aerosol type using in situ surface spectral aerosol optical properties L. Schmeisser et al. https://doi.org/10.5194/acp-17-12097-2017
14. 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
15. Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters R. Mamouri & A. Ansmann https://doi.org/10.5194/acp-16-5905-2016
16. Temporary reduction in fine particulate matter due to ‘anthropogenic emissions switch-off’ during COVID-19 lockdown in Indian cities P. Kumar et al. https://doi.org/10.1016/j.scs.2020.102382
17. Global observations of aerosol-cloud-precipitation-climate interactions D. Rosenfeld et al. https://doi.org/10.1002/2013RG000441
18. Influence of biomass aerosol on precipitation over the Central Amazon: an observational study W. Gonçalves et al. https://doi.org/10.5194/acp-15-6789-2015
19. Comparison of aerosol and cloud condensation nuclei between wet and dry seasons in Guangzhou, southern China J. Duan et al. https://doi.org/10.1016/j.scitotenv.2017.06.246
20. CCN activation properties at a tropical hill station in Western Ghats during south-west summer monsoon: Vertical heterogeneity V. Jayachandran et al. https://doi.org/10.1016/j.atmosres.2018.07.018
21. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers D. Rosenfeld et al. https://doi.org/10.1073/pnas.1514044113
22. 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
23. A new method for calculating number concentrations of cloud condensation nuclei based on measurements of a three-wavelength humidified nephelometer system J. Tao et al. https://doi.org/10.5194/amt-11-895-2018
24. 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
25. Investigation of aerosol–cloud interactions under different absorptive aerosol regimes using Atmospheric Radiation Measurement (ARM) southern Great Plains (SGP) ground-based measurements X. Zheng et al. https://doi.org/10.5194/acp-20-3483-2020
26. 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
27. Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment R. Wood et al. https://doi.org/10.1175/BAMS-D-13-00180.1.2016.1.test
28. The short-term variability of aerosols and their impact on cloud properties and radiative effect over the Indo-Gangetic Plain S. Pandey et al. https://doi.org/10.1016/j.apr.2019.12.017
29. Quantifying Long‐Term Seasonal and Regional Impacts of North American Fire Activity on Continental Boundary Layer Aerosols and Cloud Condensation Nuclei T. Logan et al. https://doi.org/10.1029/2020EA001113
30. 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
31. A new technique to retrieve aerosol vertical profiles using micropulse lidar and ground-based aerosol measurements B. Chen et al. https://doi.org/10.5194/amt-18-5841-2025
32. Weekly variability of precipitation induced by anthropogenic aerosols: A case study in Korea in summer 2004 S. Bae et al. https://doi.org/10.1016/j.scitotenv.2015.10.020
33. Effects of anthropogenic aerosols and sea salt aerosols during a summer precipitation event in the Yangtze River Delta P. Han et al. https://doi.org/10.1016/j.atmosres.2022.106584
34. Frontiers in Satellite‐Based Estimates of Cloud‐Mediated Aerosol Forcing D. Rosenfeld et al. https://doi.org/10.1029/2022RG000799
35. Constraining the Twomey effect from satellite observations: issues and perspectives J. Quaas et al. https://doi.org/10.5194/acp-20-15079-2020
36. Evaluation of aerosol–cloud interactions in E3SM using a Lagrangian framework M. Christensen et al. https://doi.org/10.5194/acp-23-2789-2023
37. An Overview of Dynamic Heterogeneous Oxidations in the Troposphere E. Pillar-Little & M. Guzman https://doi.org/10.3390/environments5090104
38. Vertical profiles of cloud condensation nuclei number concentration and its empirical estimate from aerosol optical properties over the North China Plain R. Zhang et al. https://doi.org/10.5194/acp-22-14879-2022
39. 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
40. Propagation of cloud base to higher levels during Covid-19-Lockdown L. R. et al. https://doi.org/10.1016/j.scitotenv.2020.144299
41. Significant Underestimation in the Optically Based Estimation of the Aerosol First Indirect Effect Induced by the Aerosol Swelling Effect J. Liu & Z. Li https://doi.org/10.1029/2018GL077679
42. A Novel Aerosol Optical Depth Retrieval Method Based on SDAE from Himawari-8/AHI Next-Generation Geostationary Satellite in Hubei Province S. Deng et al. https://doi.org/10.3390/rs17081396
43. Role of aerosols in modulating cloud properties during active–break cycle of Indian summer monsoon A. Bhattacharya et al. https://doi.org/10.1007/s00382-016-3437-4
44. Retrieval of Cloud Condensation Nuclei Number Concentration Profiles From Lidar Extinction and Backscatter Data M. Lv et al. https://doi.org/10.1029/2017JD028102
45. Aerosol properties and their impacts on surface CCN at the ARM Southern Great Plains site during the 2011 Midlatitude Continental Convective Clouds Experiment T. Logan et al. https://doi.org/10.1007/s00376-017-7033-2
46. First surface-based estimation of the aerosol indirect effect over a site in southeastern China J. Liu & Z. Li https://doi.org/10.1007/s00376-017-7106-2
47. Variability of aerosol-cloud interactions induced by different cloud droplet nucleation schemes D. Chang et al. https://doi.org/10.1016/j.atmosres.2020.105367
48. Ten Years of Aerosol Effects on Single-Layer Overcast Clouds over the US Southern Great Plains and the China Loess Plateau H. Yan & T. Wang https://doi.org/10.1155/2020/6719160
49. The relationship between cloud condensation nuclei (CCN) concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellite-based CCN estimates Y. Shinozuka et al. https://doi.org/10.5194/acp-15-7585-2015
50. 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
51. Radiative forcing due to aerosol-cloud interactions for shallow warm clouds over the Northern Indian Ocean H. Kumar & S. Tiwari https://doi.org/10.1016/j.atmosres.2025.108368
52. A correlational study on size differentiated aerosols on monsoonal and pre-monsoonal cloud properties over the Indo Gangetic Basin S. Jose et al. https://doi.org/10.1016/j.atmosres.2021.105796
53. Estimating cloud condensation nuclei number concentrations using aerosol optical properties: role of particle number size distribution and parameterization Y. Shen et al. https://doi.org/10.5194/acp-19-15483-2019
54. Potential impact of aerosols on convective clouds revealed by Himawari-8 observations over different terrain types in eastern China T. Chen et al. https://doi.org/10.5194/acp-21-6199-2021
55. Interpretable ensemble learning unveils main aerosol optical properties in predicting cloud condensation nuclei number concentration N. Wang et al. https://doi.org/10.1038/s41612-025-01181-y
56. Prediction of CCN spectra parameters in the North China Plain using a random forest model M. Liang et al. https://doi.org/10.1016/j.atmosenv.2022.119323
57. 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
58. Limitations of passive remote sensing to constrain global cloud condensation nuclei P. Stier https://doi.org/10.5194/acp-16-6595-2016
59. 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
60. Aerosol physicochemical effects on CCN activation simulated with the chemistry-climate model EMAC D. Chang et al. https://doi.org/10.1016/j.atmosenv.2017.03.036
61. Cloud condensation nuclei phenomenology: predictions based on aerosol chemical and optical properties I. Zabala et al. https://doi.org/10.5194/acp-26-3697-2026
62. Aerosol and monsoon climate interactions over Asia Z. Li et al. https://doi.org/10.1002/2015RG000500
63. Altitude profiles of cloud condensation nuclei characteristics across the Indo-Gangetic Plain prior to the onset of the Indian summer monsoon V. Jayachandran et al. https://doi.org/10.5194/acp-20-561-2020
64. A First Case Study of CCN Concentrations from Spaceborne Lidar Observations A. Georgoulias et al. https://doi.org/10.3390/rs12101557
65. Uncertainty in Predicting CCN Activity of Aged and Primary Aerosols F. Zhang et al. https://doi.org/10.1002/2017JD027058
66. Optical properties and CCN activity of aerosols in a high‐altitude Himalayan environment: Results from RAWEX‐GVAX M. Gogoi et al. https://doi.org/10.1002/2014JD022966
67. Cloud condensation nuclei concentrations derived from the CAMS reanalysis K. Block et al. https://doi.org/10.5194/essd-16-443-2024