79 citations as recorded by crossref.

1. MODIS-Derived Arctic Melt Season Fog and Low Stratus over East Greenland Glaciers and the Ice Sheet H. Jiskoot et al. 10.1080/07038992.2019.1635878
2. CALIOP V4 cloud thermodynamic phase assignment and the impact of near-nadir viewing angles M. Avery et al. 10.5194/amt-13-4539-2020
3. The correlation between Arctic sea ice, cloud phase and radiation using A-Train satellites G. Cesana et al. 10.5194/acp-24-7899-2024
4. Supercooled Water Cloud Identification From Geostationary Satellite Thermal Infrared Observations and Its Application in the Sun Glint Region H. Fu et al. 10.1109/TGRS.2024.3458052
5. Cloud Climatologies from Global Climate Models—A Comparison of CMIP5 and CMIP6 Models with Satellite Data A. Lauer et al. 10.1175/JCLI-D-22-0181.1
6. A monthly 1° resolution dataset of daytime cloud fraction over the Arctic during 2000–2020 based on multiple satellite products X. Liu et al. 10.5194/essd-15-3641-2023
7. Bayesian cloud-top phase determination for Meteosat Second Generation J. Mayer et al. 10.5194/amt-17-4015-2024
8. A comparison of Aqua MODIS ice and liquid water cloud physical and optical properties between collection 6 and collection 5.1: Cloud radiative effects B. Yi et al. 10.1002/2016JD025654
9. Observational Constraints on Southern Ocean Cloud-Phase Feedback C. Wall et al. 10.1175/JCLI-D-21-0812.1
10. Assessment and Error Analysis of Terra‐MODIS and MISR Cloud‐Top Heights Through Comparison With ISS‐CATS Lidar A. Mitra et al. 10.1029/2020JD034281
11. Leveraging spatial textures, through machine learning, to identify aerosols and distinct cloud types from multispectral observations W. Marais et al. 10.5194/amt-13-5459-2020
12. Detecting the Phase of Marine Boundary Layer Clouds: Some Implications for Cloud Albedo N. Rampal & R. Davies 10.1029/2022JD037496
13. The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products S. Platnick et al. 10.3390/rs13010002
14. A Comparison of Cloud Microphysical Properties Derived From MODIS and CALIPSO With In Situ Measurements Over the Wintertime Southern Ocean E. Ahn et al. 10.1029/2018JD028535
15. Investigating the development of clouds within marine cold-air outbreaks R. Murray-Watson et al. 10.5194/acp-23-9365-2023
16. On the Temperature Dependence of the Cloud Ice Particle Effective Radius—A Satellite Perspective M. Stengel et al. 10.1029/2022GL102521
17. Gaussian Mixture Model-Based Cloud- Phase Estimation From GEO- KOMPSAT-2A Observations D. Kim & D. Shin 10.1109/TGRS.2024.3383888
18. Under What Conditions Can We Trust Retrieved Cloud Drop Concentrations in Broken Marine Stratocumulus? Y. Zhu et al. 10.1029/2017JD028083
19. Multi-channel Imager Algorithm (MIA): A novel cloud-top phase classification algorithm J. Hu et al. 10.1016/j.atmosres.2021.105767
20. Combining Passive Infrared and Microwave Satellite Observations to Investigate Cloud Microphysical Properties: A Review M. Viggiano et al. 10.3390/rs17020337
21. Spatiotemporal Heterogeneity of Aerosol and Cloud Properties Over the Southeast Atlantic: An Observational Analysis I. Chang et al. 10.1029/2020GL091469
22. Impact of Cloud Condensation Nuclei Reduction on Cloud Characteristics and Solar Radiation during COVID-19 Lockdown 2020 in Moscow J. Shuvalova et al. 10.3390/atmos13101710
23. CERES MODIS Cloud Product Retrievals for Edition 4—Part II: Comparisons to CloudSat and CALIPSO C. Yost et al. 10.1109/TGRS.2020.3015155
24. Detecting Multilayer Clouds From the Geostationary Advanced Himawari Imager Using Machine Learning Techniques Z. Tan et al. 10.1109/TGRS.2021.3087714
25. The Community Cloud retrieval for CLimate (CC4CL) – Part 1: A framework applied to multiple satellite imaging sensors O. Sus et al. 10.5194/amt-11-3373-2018
26. Wintertime In Situ Cloud Microphysical Properties of Mixed‐Phase Clouds Over the Southern Ocean Y. Huang et al. 10.1029/2021JD034832
27. Southern Ocean cloud and shortwave radiation biases in a nudged climate model simulation: does the model ever get it right? S. Fiddes et al. 10.5194/acp-22-14603-2022
28. 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 10.1029/2018JD028558
29. Evaluation of the MODIS Collection 6 multilayer cloud detection algorithm through comparisons with CloudSat Cloud Profiling Radar and CALIPSO CALIOP products B. Marchant et al. 10.5194/amt-13-3263-2020
30. Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC) K. Meyer et al. 10.5194/amt-9-1785-2016
31. VIIRS Edition 1 Cloud Properties for CERES, Part 2: Evaluation with CALIPSO C. Yost et al. 10.3390/rs15051349
32. An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path T. Greenwald et al. 10.1002/2017JD027638
33. The Role of Thermodynamic Phase Shifts in Cloud Optical Depth Variations With Temperature I. Tan et al. 10.1029/2018GL081590
34. Broadband and filter radiometers at Ross Island, Antarctica: detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation K. Scarci et al. 10.5194/acp-24-6681-2024
35. From trees to rain: enhancement of cloud glaciation and precipitation by pollen J. Kretzschmar et al. 10.1088/1748-9326/ad747a
36. What is the Role of Sea Surface Temperature in Modulating Cloud and Precipitation Properties over the Southern Ocean? Y. Huang et al. 10.1175/JCLI-D-15-0768.1
37. Comparison of Cloud Properties from Himawari-8 and FengYun-4A Geostationary Satellite Radiometers with MODIS Cloud Retrievals R. Lai et al. 10.3390/rs11141703
38. Effect of Aerosols, Tropospheric NO2 and Clouds on Surface Solar Radiation over the Eastern Mediterranean (Greece) G. Alexandri et al. 10.3390/rs13132587
39. Empirical algorithm for detecting coccolithophore blooms through satellite observation in the Barents Sea S. He et al. 10.1016/j.rse.2021.112886
40. Updated observations of clouds by MODIS for global model assessment R. Pincus et al. 10.5194/essd-15-2483-2023
41. Investigation on the spatiotemporal and vertical structure of ice cloud and aerosol parameters from multi-source satellite datasets (2007–2021) over the Tarim Basin, China H. Pan et al. 10.1016/j.jastp.2024.106185
42. Constraining Clouds and Convective Parameterizations in a Climate Model Using Paleoclimate Data R. Ramos et al. 10.1029/2021MS002893
43. Effect of volcanic emissions on clouds during the 2008 and 2018 Kilauea degassing events K. Breen et al. 10.5194/acp-21-7749-2021
44. Evaluating the consistency and continuity of pixel-scale cloud property data records from Aqua and SNPP (Suomi National Polar-orbiting Partnership) Q. Yue et al. 10.5194/amt-15-2099-2022
45. Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives D. Grosvenor et al. 10.1029/2017RG000593
46. Construction of Nighttime Cloud Layer Height and Classification of Cloud Types S. Chen et al. 10.3390/rs12040668
47. Temperature‐Independent Cloud Phase Retrieval From Shortwave‐Infrared Measurement of GCOM‐C/SGLI With Comparison to CALIPSO T. Nagao & K. Suzuki 10.1029/2021EA001912
48. Variability of bulk water vapor content in the marine cloudy boundary layers from microwave and near-infrared imagery L. Millán et al. 10.5194/acp-19-8491-2019
49. Cloud phase characteristics over Southeast Asia from A-Train satellite observations Y. Hong & L. Di Girolamo 10.5194/acp-20-8267-2020
50. Satellites See the World’s Atmosphere S. Ackerman et al. 10.1175/AMSMONOGRAPHS-D-18-0009.1
51. Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project M. Stengel et al. 10.5194/essd-9-881-2017
52. Air mass history linked to the development of Arctic mixed-phase clouds R. Murray-Watson & E. Gryspeerdt 10.5194/acp-24-11115-2024
53. Spatio‐temporal variability of warm rain events over southern West Africa from geostationary satellite observations for climate monitoring and model evaluation M. Young et al. 10.1002/qj.3372
54. Characterizing Vertical Stratification of the Cloud Thermodynamic Phase With a Combined Use of CALIPSO Lidar and MODIS SWIR Measurements T. Nagao & K. Suzuki 10.1029/2022JD036826
55. Improved Retrieval of Cloud Liquid Water from CloudSat and MODIS J. Leinonen et al. 10.1175/JAMC-D-16-0077.1
56. Sensitivity of Multispectral Imager Liquid Water Cloud Microphysical Retrievals to the Index of Refraction S. Platnick et al. 10.3390/rs12244165
57. How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties J. Mayer et al. 10.5194/amt-17-5161-2024
58. Determining AHI Cloud-Top Phase and Intercomparisons With MODIS Products Over North Pacific X. Zhuge et al. 10.1109/TGRS.2020.2990955
59. Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS collections 5.1 and 6 over global oceans J. Rausch et al. 10.5194/amt-10-2105-2017
60. Evaluation of AIRS Cloud Phase Classification over the Arctic Ocean against Combined CloudSat–CALIPSO Observations C. Peterson et al. 10.1175/JAMC-D-20-0016.1
61. Tropopause Laminar Cirrus and Its Role in the Lower Stratosphere Total Water Budget T. Wang et al. 10.1029/2018JD029845
62. Derivation of Shortwave Radiometric Adjustments for SNPP and NOAA-20 VIIRS for the NASA MODIS-VIIRS Continuity Cloud Products K. Meyer et al. 10.3390/rs12244096
63. A comparison of Aqua MODIS ice and liquid water cloud physical and optical properties between collection 6 and collection 5.1: Pixel‐to‐pixel comparisons B. Yi et al. 10.1002/2016JD025586
64. Long‐Term Observations of Upper‐Tropospheric Cloud Ice From the MLS T. Wang et al. 10.1029/2020JD034058
65. Cloud Detection and Classification Algorithms for Himawari-8 Imager Measurements Based on Deep Learning W. Li et al. 10.1109/TGRS.2022.3153129
66. Cloud Phase Classification Based on the Submillimeter and Microwave Radiometer Synergistic Observations P. Dong et al. 10.1109/LGRS.2024.3450872
67. A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations C. Wang et al. 10.5194/amt-13-2257-2020
68. Comparison of the Novel Probabilistic Self-Optimizing Vectorized Earth Observation Retrieval Classifier with Common Machine Learning Algorithms J. Musial & J. Bojanowski 10.3390/rs14020378
69. Diurnal spatial distributions of aerosol optical and cloud micro-macrophysics properties in Africa based on MODIS observations D. Ntwali & H. Chen 10.1016/j.atmosenv.2018.03.054
70. The Impact of PM2.5 on the Growth Curves of Children's Obesity Indexes: A Prospective Cohort Study J. Tong et al. 10.3389/fpubh.2022.843622
71. Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, as well as their application in aerosol–cloud interactions G. Saponaro et al. 10.5194/acp-20-1607-2020
72. A Machine Learning-Based Multiple Cloud Vertical Structure Parameter Prediction Algorithm Only Using OCO-2 Oxygen A-Band Measurements Y. Lei et al. 10.3390/rs15123142
73. Identification of Supercooled Cloud Water by FY-4A Satellite and Validation by CALIPSO and Airborne Detection X. Xu et al. 10.3390/rs15010126
74. Obtaining Cloud Base Height and Phase From Thermal Infrared Radiometry Using a Deep Learning Algorithm Q. Wang et al. 10.1109/TGRS.2023.3317532
75. Retrieval of radiative and microphysical properties of clouds from multispectral infrared measurements H. Iwabuchi et al. 10.1186/s40645-016-0108-3
76. Relations between marine biogeochemical indices and cloud properties over the Arabian Sea V. Rao et al. 10.1007/s12040-021-01638-7
77. Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 2. Retrieval evaluation C. Wang et al. 10.1002/2015JD024528
78. The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua S. Platnick et al. 10.1109/TGRS.2016.2610522
79. Shortwave direct radiative effects of above-cloud aerosols over global oceans derived from 8 years of CALIOP and MODIS observations Z. Zhang et al. 10.5194/acp-16-2877-2016