134 citations as recorded by crossref.

1. Global aerosol simulations using NICAM.16 on a 14 km grid spacing for a climate study: improved and remaining issues relative to a lower-resolution model D. Goto et al. https://doi.org/10.5194/gmd-13-3731-2020
2. Assessment of Geostationary Satellite Cloud Effective Radius over East China with In Situ Aircraft Measurements Q. Zhang et al. https://doi.org/10.1007/s13351-025-4164-8
3. An evaluation of the liquid cloud droplet effective radius derived from MODIS, airborne remote sensing, and in situ measurements from CAMP2Ex D. Fu et al. https://doi.org/10.5194/acp-22-8259-2022
4. Secondary droplet activation during condensational growth in convective clouds and its detection from satellites A. Efraim et al. https://doi.org/10.1016/j.atmosres.2023.107196
5. Air mass history linked to the development of Arctic mixed-phase clouds R. Murray-Watson & E. Gryspeerdt https://doi.org/10.5194/acp-24-11115-2024
6. Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data D. McCoy et al. https://doi.org/10.5194/acp-18-2035-2018
7. 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
8. Analysis of the Observation Results for Preferentially Oriented Particles in High-Level Clouds According to the EARLINET Lidar Network and MODIS Data A. Skorokhodov & A. Konoshonkin https://doi.org/10.3390/atmos14061018
9. Exploring the Cloud Top Phase Partitioning in Different Cloud Types Using Active and Passive Satellite Sensors O. Bruno et al. https://doi.org/10.1029/2020GL089863
10. Uncertainties in MODIS‐Based Cloud Liquid Water Path Retrievals at High Latitudes Due to Mixed‐Phase Clouds and Cloud Top Height Inhomogeneity S. Khanal & Z. Wang https://doi.org/10.1029/2018JD028558
11. The hemispheric contrast in cloud microphysical properties constrains aerosol forcing I. McCoy et al. https://doi.org/10.1073/pnas.1922502117
12. Stability-dependent increases in liquid water with droplet number in the Arctic R. Murray-Watson & E. Gryspeerdt https://doi.org/10.5194/acp-22-5743-2022
13. Quantifying the dependence of drop spectrum width on cloud drop number concentration for cloud remote sensing M. Lebsock & M. Witte https://doi.org/10.5194/acp-23-14293-2023
14. Robust Susceptibility of Cloud Cover and Radiative Effects to Biases in Retrieved Droplet Concentrations Y. Wang et al. https://doi.org/10.1029/2023JD039145
15. Inferring processes governing cloud transition during mid-latitude marine cold-air outbreaks from satellite J. Zhang et al. https://doi.org/10.5194/acp-26-6015-2026
16. Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations R. Bennartz & J. Rausch https://doi.org/10.5194/acp-17-9815-2017
17. Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning R. Okamura et al. https://doi.org/10.5194/amt-10-4747-2017
18. Polarimetric retrievals of cloud droplet number concentrations K. Sinclair et al. https://doi.org/10.1016/j.rse.2019.04.008
19. Practical Recommendations for Hyperspectral and Thermal Proximal Disease Sensing in Potato and Leek Fields S. Appeltans et al. https://doi.org/10.3390/rs12121939
20. How meteorological conditions influence aerosol-cloud interactions under different pollution regimes J. Zhao et al. https://doi.org/10.5194/acp-25-17701-2025
21. Large simulated radiative effects of smoke in the south-east Atlantic H. Gordon et al. https://doi.org/10.5194/acp-18-15261-2018
22. Phytoplankton Impact on Marine Cloud Microphysical Properties Over the Northeast Atlantic Ocean K. Mansour et al. https://doi.org/10.1029/2021JD036355
23. High sensitivity of simulated fog properties to parameterized aerosol activation in case studies from ParisFog P. Ghosh et al. https://doi.org/10.5194/acp-25-11129-2025
24. Observations of high droplet number concentrations in Southern Ocean boundary layer clouds T. Chubb et al. https://doi.org/10.5194/acp-16-971-2016
25. Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble A. Mikkelsen et al. https://doi.org/10.5194/acp-25-4547-2025
26. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers D. Rosenfeld et al. https://doi.org/10.1073/pnas.1514044113
27. Signatures of aerosol-cloud interactions in GiOcean: a coupled global reanalysis with two-moment cloud microphysics C. Song et al. https://doi.org/10.5194/acp-25-15567-2025
28. Airborne observations and simulations of three-dimensional radiative interactions between Arctic boundary layer clouds and ice floes M. Schäfer et al. https://doi.org/10.5194/acp-15-8147-2015
29. Climatology of Cloud‐Top Radiative Cooling in Marine Shallow Clouds Y. Zheng et al. https://doi.org/10.1029/2021GL094676
30. The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data E. Gryspeerdt et al. https://doi.org/10.5194/amt-15-3875-2022
31. Subgrid variations of the cloud water and droplet number concentration over the tropical ocean: satellite observations and implications for warm rain simulations in climate models Z. Zhang et al. https://doi.org/10.5194/acp-19-1077-2019
32. Development of aerosol activation in the double-moment Unified Model and evaluation with CLARIFY measurements H. Gordon et al. https://doi.org/10.5194/acp-20-10997-2020
33. Marine liquid cloud geometric thickness retrieved from OCO-2's oxygen A-band spectrometer M. Richardson et al. https://doi.org/10.5194/amt-12-1717-2019
34. Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles J. Vergara-Temprado et al. https://doi.org/10.1073/pnas.1721627115
35. High Sensitivity of Arctic Liquid Clouds to Long‐Range Anthropogenic Aerosol Transport Q. Coopman et al. https://doi.org/10.1002/2017GL075795
36. Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives D. Grosvenor et al. https://doi.org/10.1029/2017RG000593
37. Seasonality biases arise from the interplay of retrieval quality and solar zenith angle effects in passive sensor AOD products S. Smith et al. https://doi.org/10.5194/acp-25-14333-2025
38. Long-term variation of cloud droplet number concentrations from space-based Lidar J. Li et al. https://doi.org/10.1016/j.rse.2018.05.011
39. An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB H. Song et al. https://doi.org/10.1175/JCLI-D-17-0277.1
40. Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations J. Mulcahy et al. https://doi.org/10.5194/gmd-13-6383-2020
41. Cloud geometry from oxygen-A-band observations through an aircraft side window T. Zinner et al. https://doi.org/10.5194/amt-12-1167-2019
42. The Temperature Control of Cloud Adiabatic Fraction and Coverage X. Lu et al. https://doi.org/10.1029/2023GL105831
43. Pristine oceans are a significant source of uncertainty in quantifying global cloud condensation nuclei G. Choudhury et al. https://doi.org/10.5194/acp-25-3841-2025
44. 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
45. Evaluation of Global Climate and Storm-Resolving Model Representations of Mixed-Phase Clouds and Their Hemispheric Contrasts O. Bruno et al. https://doi.org/10.3390/atmos17020156
46. Retrieving the Polar Mixed‐Phase Cloud Liquid Water Path by Combining CALIOP and IIR Measurements T. Luo et al. https://doi.org/10.1002/2017JD027291
47. The Life Cycle of Anvil Clouds and the Top-of-Atmosphere Radiation Balance over the Tropical West Pacific C. Wall et al. https://doi.org/10.1175/JCLI-D-18-0154.1
48. Untangling causality in midlatitude aerosol–cloud adjustments D. McCoy et al. https://doi.org/10.5194/acp-20-4085-2020
49. Identification of Supercooled Cloud Water by FY-4A Satellite and Validation by CALIPSO and Airborne Detection X. Xu et al. https://doi.org/10.3390/rs15010126
50. Coupling aerosols to (cirrus) clouds in the global EMAC-MADE3 aerosol–climate model M. Righi et al. https://doi.org/10.5194/gmd-13-1635-2020
51. What is the Role of Sea Surface Temperature in Modulating Cloud and Precipitation Properties over the Southern Ocean? Y. Huang et al. https://doi.org/10.1175/JCLI-D-15-0768.1
52. Global Estimates of Changes in Shortwave Low‐Cloud Albedo and Fluxes Due to Variations in Cloud Droplet Number Concentration Derived From CERES‐MODIS Satellite Sensors D. Painemal https://doi.org/10.1029/2018GL078880
53. Natural aerosols explain seasonal and spatial patterns of Southern Ocean cloud albedo D. McCoy et al. https://doi.org/10.1126/sciadv.1500157
54. Assessment of Aerosol Optical Depth, Cloud Fraction, and Liquid Water Path in CMIP6 Models Using Satellite Observations J. Liang & J. Griswold https://doi.org/10.3390/rs17142439
55. Validation of MODIS liquid water path for oceanic nonraining warm clouds: Implications on the vertical profile of cloud water content L. Zhou et al. https://doi.org/10.1002/2015JD024499
56. Weak average liquid-cloud-water response to anthropogenic aerosols V. Toll et al. https://doi.org/10.1038/s41586-019-1423-9
57. A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific A. Correia et al. https://doi.org/10.3390/atmos13010077
58. Geographically coherent patterns of albedo enhancement and suppression associated with aerosol sources and sinks A. Engström et al. https://doi.org/10.3402/tellusb.v67.26442
59. Lagrangian Evolution of the Northeast Pacific Marine Boundary Layer Structure and Cloud during CSET J. Mohrmann et al. https://doi.org/10.1175/MWR-D-19-0053.1
60. Under What Conditions Can We Trust Retrieved Cloud Drop Concentrations in Broken Marine Stratocumulus? Y. Zhu et al. https://doi.org/10.1029/2017JD028083
61. MODIS Cloud Detection Evaluation Using CALIOP over Polluted Eastern China S. Tan et al. https://doi.org/10.3390/atmos10060333
62. Diurnal Evolution of Cloud Water Responses to Aerosols J. Rahu et al. https://doi.org/10.1029/2021JD035091
63. A characterization of clouds over the Great Barrier Reef and the role of local forcing W. Zhao et al. https://doi.org/10.1002/joc.7660
64. Inference of an Optimal Ice Particle Model through Latitudinal Analysis of MISR and MODIS Data Y. Wang et al. https://doi.org/10.3390/rs10121981
65. Improving middle and high latitude cloud liquid water path measurements from MODIS S. Khanal et al. https://doi.org/10.1016/j.atmosres.2020.105033
66. Variability of bulk water vapor content in the marine cloudy boundary layers from microwave and near-infrared imagery L. Millán et al. https://doi.org/10.5194/acp-19-8491-2019
67. Influence of the Subtropical High and Storm Track on Low-Cloud Fraction and Its Seasonality over the South Indian Ocean A. Miyamoto et al. https://doi.org/10.1175/JCLI-D-17-0229.1
68. Identifying Meteorological Controls on Open and Closed Mesoscale Cellular Convection Associated with Marine Cold Air Outbreaks I. McCoy et al. https://doi.org/10.1002/2017JD027031
69. Volcano and Ship Tracks Indicate Excessive Aerosol‐Induced Cloud Water Increases in a Climate Model V. Toll et al. https://doi.org/10.1002/2017GL075280
70. 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
71. The decomposition of cloud–aerosol forcing in the UK Earth System Model (UKESM1) D. Grosvenor & K. Carslaw https://doi.org/10.5194/acp-20-15681-2020
72. Negligible contribution from aerosols to recent trends in Earth’s energy imbalance C. Park & B. Soden https://doi.org/10.1126/sciadv.adv9429
73. Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1 J. Mulcahy et al. https://doi.org/10.1029/2018MS001464
74. 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
75. Re-evaluating winter carbon sink in Southern Ocean by recovering MODIS-Aqua chlorophyll-a product at high solar zenith angles K. Zhang et al. https://doi.org/10.1016/j.isprsjprs.2024.09.033
76. Constraining the aerosol influence on cloud liquid water path E. Gryspeerdt et al. https://doi.org/10.5194/acp-19-5331-2019
77. Aircraft in-situ measurements from SOCRATES constrain the anthropogenic perturbations of cloud droplet number C. Song et al. https://doi.org/10.5194/acp-25-16063-2025
78. The Evaluation of the North Atlantic Climate System in UKESM1 Historical Simulations for CMIP6 J. Robson et al. https://doi.org/10.1029/2020MS002126
79. Liquid Containing Clouds at the North Slope of Alaska Demonstrate Sensitivity to Local Industrial Aerosol Emissions M. Maahn et al. https://doi.org/10.1029/2021GL094307
80. Parameterizing cloud top effective radii from satellite retrieved values, accounting for vertical photon transport: quantification and correction of the resulting bias in droplet concentration and liquid water path retrievals D. Grosvenor et al. https://doi.org/10.5194/amt-11-4273-2018
81. Distinct regional meteorological influences on low-cloud albedo susceptibility over global marine stratocumulus regions J. Zhang & G. Feingold https://doi.org/10.5194/acp-23-1073-2023
82. Global expansion of the sensitive aerosol-limited marine cloud regime under emission reductions X. Han et al. https://doi.org/10.1126/sciadv.aef9665
83. On the relationships among cloud cover, mixed‐phase partitioning, and planetary albedo in GCMs D. McCoy et al. https://doi.org/10.1002/2015MS000589
84. Sampling Bias From Satellite Retrieval Failures of Cloud Properties and Its Implications for Aerosol‐Cloud Interactions G. Choudhury & T. Goren https://doi.org/10.1029/2025GL115429
85. Exploring Satellite-Derived Relationships between Cloud Droplet Number Concentration and Liquid Water Path Using a Large-Domain Large-Eddy Simulation S. Dipu et al. https://doi.org/10.16993/tellusb.27
86. Weak liquid water path response in ship tracks A. Tippett et al. https://doi.org/10.5194/acp-24-13269-2024
87. MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6 B. Stevens et al. https://doi.org/10.5194/gmd-10-433-2017
88. Observed Southern Ocean Cloud Properties and Shortwave Reflection. Part II: Phase Changes and Low Cloud Feedback* D. McCoy et al. https://doi.org/10.1175/JCLI-D-14-00288.1
89. Considering the Effects of Horizontal Heterogeneities in Satellite-Based Large-Scale Statistics of Cloud Optical Properties T. Várnai & A. Marshak https://doi.org/10.3390/rs16183388
90. A Long-Term Cloud Albedo Data Record Since 1980 from UV Satellite Sensors C. Weaver et al. https://doi.org/10.3390/rs12121982
91. A Comparison of Cloud Microphysical Properties Derived From MODIS and CALIPSO With In Situ Measurements Over the Wintertime Southern Ocean E. Ahn et al. https://doi.org/10.1029/2018JD028535
92. Analysis of geostationary satellite-derived cloud parameters associated with environments with high ice water content A. de Laat et al. https://doi.org/10.5194/amt-10-1359-2017
93. Summer Statistical Models of Cloud Parameters over Western Siberia According to MODIS Data V. Astafurov et al. https://doi.org/10.3103/S1068373921110029
94. Introducing aerosol-cloud interactions in the ECMWF model reveals new constraints on aerosol representation P. Andreozzi et al. https://doi.org/10.5194/acp-26-11309-2026
95. Revealing Bias of Cloud Radiative Effect in WRF Simulation: Bias Quantification and Source Attribution Y. Shan et al. https://doi.org/10.1029/2021JD036319
96. Projecting Stratocumulus Transitions on the Albedo—Cloud Fraction Relationship Reveals Linearity of Albedo to Droplet Concentrations T. Goren et al. https://doi.org/10.1029/2022GL101169
97. The Impacts of Immersion Ice Nucleation Parameterizations on Arctic Mixed-Phase Stratiform Cloud Properties and the Arctic Radiation Budget in GEOS-5 I. Tan & D. Barahona https://doi.org/10.1175/JCLI-D-21-0368.1
98. An Assessment of the Impacts of Cloud Vertical Heterogeneity on Global Ice Cloud Data Records From Passive Satellite Retrievals C. Wang et al. https://doi.org/10.1029/2018JD029681
99. Bias in MODIS cloud drop effective radius for oceanic water clouds as deduced from optical thickness variability across scattering angles L. Liang et al. https://doi.org/10.1002/2015JD023256
100. Natural marine cloud brightening in the Southern Ocean G. Mace et al. https://doi.org/10.5194/acp-23-1677-2023
101. MODIS Retrievals of Cloud Effective Radius in Marine Stratocumulus Exhibit No Significant Bias M. Witte et al. https://doi.org/10.1029/2018GL079325
102. Lightning declines over shipping lanes following regulation of fuel sulfur emissions C. Wright et al. https://doi.org/10.5194/acp-25-2937-2025
103. Aerosol indirect effects on continental low-level clouds over Sweden and Finland M. Sporre et al. https://doi.org/10.5194/acp-14-12167-2014
104. Substantial cooling effect from aerosol-induced increase in tropical marine cloud cover Y. Chen et al. https://doi.org/10.1038/s41561-024-01427-z
105. The relative importance of macrophysical and cloud albedo changes for aerosol-induced radiative effects in closed-cell stratocumulus: insight from the modelling of a case study D. Grosvenor et al. https://doi.org/10.5194/acp-17-5155-2017
106. On the Scattering-Angle Dependence of the Spectral Consistency of Ice Cloud Optical Thickness Retrievals Based on Geostationary Satellite Observations D. Li et al. https://doi.org/10.1109/TGRS.2023.3331970
107. The global aerosol‐cloud first indirect effect estimated using MODIS, MERRA, and AeroCom D. McCoy et al. https://doi.org/10.1002/2016JD026141
108. Potential Link Between Ice Nucleation and Climate Model Spread in Arctic Amplification I. Tan et al. https://doi.org/10.1029/2021GL097373
109. In situ and satellite-based estimates of cloud properties and aerosol–cloud interactions over the southeast Atlantic Ocean S. Gupta et al. https://doi.org/10.5194/acp-22-12923-2022
110. A Cloud Vertical Structure Optimization Algorithm Combining FY-4A and DSCOVR Satellite Data Z. Zheng et al. https://doi.org/10.3390/rs17142484
111. Analyzing the Thermodynamic Phase Partitioning of Mixed Phase Clouds Over the Southern Ocean Using Passive Satellite Observations Q. Coopman et al. https://doi.org/10.1029/2021GL093225
112. Supercooled Water Cloud Identification From Geostationary Satellite Thermal Infrared Observations and Its Application in the Sun Glint Region H. Fu et al. https://doi.org/10.1109/TGRS.2024.3458052
113. Strong Dependence of Atmospheric Feedbacks on Mixed‐Phase Microphysics and Aerosol‐Cloud Interactions in HadGEM3 A. Bodas‐Salcedo et al. https://doi.org/10.1029/2019MS001688
114. Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland M. Sporre et al. https://doi.org/10.5194/amt-9-3193-2016
115. Assessment of aerosol–cloud–radiation correlations in satellite observations, climate models and reanalysis F. Bender et al. https://doi.org/10.1007/s00382-018-4384-z
116. Observed Southern Ocean Cloud Properties and Shortwave Reflection. Part I: Calculation of SW Flux from Observed Cloud Properties* D. McCoy et al. https://doi.org/10.1175/JCLI-D-14-00287.1
117. Validation of MODIS and AHI Observed Water Cloud Properties Using Surface Radiation Data P. KHATRI et al. https://doi.org/10.2151/jmsj.2018-036
118. Aerosol midlatitude cyclone indirect effects in observations and high-resolution simulations D. McCoy et al. https://doi.org/10.5194/acp-18-5821-2018
119. An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path T. Greenwald et al. https://doi.org/10.1002/2017JD027638
120. Daytime variation in the aerosol indirect effect for warm marine boundary layer clouds in the eastern North Atlantic S. Qiu et al. https://doi.org/10.5194/acp-24-2913-2024
121. Investigating the development of clouds within marine cold-air outbreaks R. Murray-Watson et al. https://doi.org/10.5194/acp-23-9365-2023
122. Satellite derived product benchmarking and empirical model development for estimating photosynthetically active radiation at high latitudes S. Zainali et al. https://doi.org/10.1016/j.agrformet.2025.111014
123. The sensitivity of Southern Ocean aerosols and cloud microphysics to sea spray and sulfate aerosol production in the HadGEM3-GA7.1 chemistry–climate model L. Revell et al. https://doi.org/10.5194/acp-19-15447-2019
124. Deconvolution of boundary layer depth and aerosol constraints on cloud water path in subtropical stratocumulus decks A. Possner et al. https://doi.org/10.5194/acp-20-3609-2020
125. Large Contribution of Supercooled Liquid Clouds to the Solar Radiation Budget of the Southern Ocean A. Bodas-Salcedo et al. https://doi.org/10.1175/JCLI-D-15-0564.1
126. The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models H. Song et al. https://doi.org/10.5194/gmd-11-3147-2018
127. Retrieval of cloud properties from thermal infrared radiometry using convolutional neural network Q. Wang et al. https://doi.org/10.1016/j.rse.2022.113079
128. A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations R. Schulte et al. https://doi.org/10.5194/amt-17-3583-2024
129. Instantaneous Linkages between Clouds and Large-Scale Meteorology over the Southern Ocean in Observations and a Climate Model C. Wall et al. https://doi.org/10.1175/JCLI-D-17-0156.1
130. Cloud-Base Height Retrieval from MODIS Satellite Data Based on Self-Organizing Neural Networks A. Skorokhodov et al. https://doi.org/10.1134/S1024856023060209
131. Observational Constraints on Southern Ocean Cloud-Phase Feedback C. Wall et al. https://doi.org/10.1175/JCLI-D-21-0812.1
132. Albedo susceptibility of northeastern Pacific stratocumulus: the role of covarying meteorological conditions J. Zhang et al. https://doi.org/10.5194/acp-22-861-2022
133. Satellite retrieval of cloud base height and geometric thickness of low-level cloud based on CALIPSO X. Lu et al. https://doi.org/10.5194/acp-21-11979-2021
134. Spatial Aggregation of Satellite Observations Leads to an Overestimation of the Radiative Forcing due to Aerosol‐Cloud Interactions T. Goren et al. https://doi.org/10.1029/2023GL105282