11 citations as recorded by crossref.

1. Simultaneous Reconstruction of the Complex Refractive Index and the Particle Size Distribution Function from Lidar Measurements: Testing the Developed Algorithms S. Samoilova https://doi.org/10.1134/S1024856019060137
2. Simultaneous reconstruction of two microphysical aerosol characteristics from the lidar data S. Samoilova et al. https://doi.org/10.1016/j.jqsrt.2018.10.014
3. Separate retrieval of microphysical characteristics in aerosol fractions from laser sensing data S. Samoiliva et al. https://doi.org/10.1016/j.jqsrt.2022.108168
4. Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. https://doi.org/10.1029/2019JD031465
5. Assimilating spaceborne lidar dust extinction can improve dust forecasts J. Escribano et al. https://doi.org/10.5194/acp-22-535-2022
6. Modelling optical properties of atmospheric black carbon aerosols M. Kahnert & F. Kanngießer https://doi.org/10.1016/j.jqsrt.2020.106849
7. Optical properties of water-coated sea salt model particles F. Kanngießer & M. Kahnert https://doi.org/10.1364/OE.437680
8. Aerosol optics model for black carbon applicable to remote sensing, chemical data assimilation, and climate modelling M. Kahnert & F. Kanngießer https://doi.org/10.1364/OE.422523
9. Aerosol-optics model for the backscatter depolarisation ratio of mineral dust particles M. Kahnert et al. https://doi.org/10.1016/j.jqsrt.2020.107177
10. Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie–Raman lidar observations I. Veselovskii et al. https://doi.org/10.5194/amt-11-949-2018
11. Information constraints in variational data assimilation M. Kahnert https://doi.org/10.1002/qj.3347