68 citations as recorded by crossref.

1. Extending XBAER Algorithm to Aerosol and Cloud Condition L. Mei et al. 10.1109/TGRS.2019.2919910
2. Air Quality over China G. de Leeuw et al. 10.3390/rs13173542
3. AerGOM, an improved algorithm for stratospheric aerosol extinction retrieval from GOMOS observations – Part 2: Intercomparisons C. Robert et al. 10.5194/amt-9-4701-2016
4. Evaluation and comparison of a machine learning cloud identification algorithm for the SLSTR in polar regions C. Poulsen et al. 10.1016/j.rse.2020.111999
5. The role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observations J. Sun et al. 10.5194/amt-12-6319-2019
6. Synergistic angular and spectral estimation of aerosol properties using CHRIS/PROBA-1 and simulated Sentinel-3 data W. Davies & P. North 10.5194/amt-8-1719-2015
7. Global observations of aerosol-cloud-precipitation-climate interactions D. Rosenfeld et al. 10.1002/2013RG000441
8. Retrieval of aerosol optical properties using MERIS observations: Algorithm and some first results L. Mei et al. 10.1016/j.rse.2016.11.015
9. Evaluation and comparison of CMIP6 models and MERRA-2 reanalysis AOD against Satellite observations from 2000 to 2014 over China M. Ali et al. 10.1016/j.gsf.2021.101325
10. Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product N. Docter et al. 10.5194/amt-16-3437-2023
11. A Cloud masking algorithm for the XBAER aerosol retrieval using MERIS data L. Mei et al. 10.1016/j.rse.2016.11.016
12. Development, Production and Evaluation of Aerosol Climate Data Records from European Satellite Observations (Aerosol_cci) T. Popp et al. 10.3390/rs8050421
13. Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations M. Luffarelli et al. 10.3390/atmos13050691
14. Simulating and Evaluating Global Aerosol Distributions With the Online Aerosol‐Coupled CAS‐FGOALS Model H. Wang et al. 10.1029/2019JD032097
15. Aerosol-type retrieval and uncertainty quantification from OMI data A. Kauppi et al. 10.5194/amt-10-4079-2017
16. Systematic Evaluation of Four Satellite AOD Datasets for Estimating PM2.5 Using a Random Forest Approach J. Handschuh et al. 10.3390/rs15082064
17. Estimating PM2.5 surface concentrations from AOD: A combination of SLSTR and MODIS J. Handschuh et al. 10.1016/j.rsase.2022.100716
18. Multiparameter Aerosol Simultaneous Retrieval Combining Satellite Remote Sensing and Atmospheric Simulation Using Space-Time Transformer (STTF) Model Y. Fan et al. 10.1109/TGRS.2025.3538164
19. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
20. Validation of Aerosol Products from AATSR and MERIS/AATSR Synergy Algorithms—Part 1: Global Evaluation Y. Che et al. 10.3390/rs10091414
21. Indirect estimation of absorption properties for fine aerosol particles using AATSR observations: a case study of wildfires in Russia in 2010 E. Rodríguez et al. 10.5194/amt-8-3075-2015
22. Challenges in the atmospheric characterization for the retrieval of spectrally resolved fluorescence and PRI region dynamics from space N. Sabater et al. 10.1016/j.rse.2020.112226
23. HETEAC-Flex: an optimal estimation method for aerosol typing based on lidar-derived intensive optical properties A. Floutsi et al. 10.5194/amt-17-693-2024
24. Spatiotemporal changes in aerosols over Bangladesh using 18 years of MODIS and reanalysis data M. Ali et al. 10.1016/j.jenvman.2022.115097
25. Extended aerosol and surface characterization from S5P/TROPOMI with GRASP algorithm. Part II: Global validation and Intercomparison C. Chen et al. 10.1016/j.rse.2024.114374
26. Extended validation and evaluation of the OLCI–SLSTR SYNERGY aerosol product (SY_2_AOD) on Sentinel-3 L. Sogacheva et al. 10.5194/amt-15-5289-2022
27. Synergy of Satellite‐ and Ground‐Based Aerosol Optical Depth Measurements Using an Ensemble Kalman Filter Approach J. Li et al. 10.1029/2019JD031884
28. A study of the impact of spatial resolution on the estimation of particle matter concentration from the aerosol optical depth retrieved from satellite observations L. Mei et al. 10.1080/01431161.2019.1601279
29. Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012 Y. Che et al. 10.5194/amt-12-4091-2019
30. An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation N. Schutgens et al. 10.5194/acp-20-12431-2020
31. On the added value of satellite AOD for the investigation of ground-level PM2.5 variability J. Handschuh et al. 10.1016/j.atmosenv.2024.120601
32. Effect of Shape and Sizes of Crystal Particles on Angular Distributions of Transmitted Solar Radiation in Two Sensing Geometries: Results of Numerical Simulation T. Zhuravleva 10.1134/S1024856021010127
33. Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street R. Kahn et al. 10.1029/2022RG000796
34. Aerosol composition retrieval from a combination of three different spaceborne instruments: information content analysis U. Stöffelmair et al. 10.5194/amt-18-2005-2025
35. Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products M. Haarig et al. 10.5194/amt-16-5953-2023
36. Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring C. Chen et al. 10.5194/essd-12-3573-2020
37. Earth system data cubes unravel global multivariate dynamics M. Mahecha et al. 10.5194/esd-11-201-2020
38. HETEAC: The Aerosol Classification Model for EarthCARE U. Wandinger et al. 10.1051/epjconf/201611901004
39. Evaluation of seven European aerosol optical depth retrieval algorithms for climate analysis G. de Leeuw et al. 10.1016/j.rse.2013.04.023
40. A consistent aerosol optical depth (AOD) dataset over mainland China by integration of several AOD products H. Xu et al. 10.1016/j.atmosenv.2015.05.023
41. The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 A. Sinyuk et al. 10.5194/amt-13-3375-2020
42. Calibrating low-cost sensors using MERRA-2 reconstructed PM2.5 mass concentration as a proxy V. Malyan et al. 10.1016/j.apr.2023.102027
43. A new generation aerosol optical depth dataset based on AVHRR data over China from 1981 to 2000 Y. Che et al. 10.1016/j.rse.2025.114899
44. Atmospheric aerosol measurements from the ATSR-SLSTR series of dual-view satellite instruments 1995–2022 K. Pearson et al. 10.1038/s41597-025-04694-6
45. Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns G. de Leeuw et al. 10.5194/acp-18-1573-2018
46. Intercomparison in spatial distributions and temporal trends derived from multi-source satellite aerosol products J. Wei et al. 10.5194/acp-19-7183-2019
47. An improved meteorological variables-based aerosol optical depth estimation method by combining a physical mechanism model with a two-stage model F. Li et al. 10.1016/j.chemosphere.2024.142820
48. Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. 10.1080/10643389.2019.1665944
49. A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing A. Sayer et al. 10.5194/amt-13-373-2020
50. Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm A. Sinyuk et al. 10.5194/amt-15-4135-2022
51. Benchmarking of essential climate variables: Gamma index theory and results for surface albedo and aerosol optical depth F. Cappucci & N. Gobron 10.1016/j.rse.2017.06.004
52. Light-absorbing aerosol properties retrieved from the sunphotometer observation over the Yangtze River Delta, China J. Wang et al. 10.1364/AO.57.000992
53. Post-processing to remove residual clouds from aerosol optical depth retrieved using the Advanced Along Track Scanning Radiometer L. Sogacheva et al. 10.5194/amt-10-491-2017
54. Systematic Propagation of AVHRR AOD Uncertainties—A Case Study to Demonstrate the FIDUCEO Approach T. Popp & J. Mittaz 10.3390/rs14040875
55. Determination of land surface reflectance using the AATSR dual-view capability L. Sogacheva et al. 10.5194/amt-8-891-2015
56. APOLLO_NG – a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels L. Klüser et al. 10.5194/amt-8-4155-2015
57. The ADV/ASV AATSR aerosol retrieval algorithm: current status and presentation of a full-mission AOD dataset P. Kolmonen et al. 10.1080/17538947.2015.1111450
58. Satellite Climate Data Records: Development, Applications, and Societal Benefits W. Yang et al. 10.3390/rs8040331
59. Aerosol remote sensing in polar regions C. Tomasi et al. 10.1016/j.earscirev.2014.11.001
60. Smoke aerosol properties and ageing effects for northern temperate and boreal regions derived from AERONET source and age attribution T. Nikonovas et al. 10.5194/acp-15-7929-2015
61. Summertime Aerosol Radiative Effects and Their Dependence on Temperature over the Southeastern USA T. Mielonen et al. 10.3390/atmos9050180
62. Himawari-8 Aerosol Optical Depth (AOD) Retrieval Using a Deep Neural Network Trained Using AERONET Observations L. She et al. 10.3390/rs12244125
63. XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation L. Mei et al. 10.5194/acp-18-2511-2018
64. Global aerosol modeling with MADE3 (v3.0) in EMAC (based on v2.53): model description and evaluation J. Kaiser et al. 10.5194/gmd-12-541-2019
65. Known and unknown unknowns: uncertainty estimation in satellite remote sensing A. Povey & R. Grainger 10.5194/amt-8-4699-2015
66. HETEAC – the Hybrid End-To-End Aerosol Classification model for EarthCARE U. Wandinger et al. 10.5194/amt-16-2485-2023
67. Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China Y. Che et al. 10.5194/acp-16-9655-2016
68. Retrieval and validation of aerosol optical depth using GF-1 WFV cameras data X. Wang et al. 10.1016/j.asr.2019.10.023