12 citations as recorded by crossref.

1. Quantify the Contribution of Dust and Anthropogenic Sources to Aerosols in North China by Lidar and Validated with CALIPSO Z. Wang et al. 10.3390/rs13091811
2. Modelling the volcanic ash plume from Eyjafjallajökull eruption (May 2010) over Europe: evaluation of the benefit of source term improvements and of the assimilation of aerosol measurements M. Plu et al. 10.5194/nhess-21-3731-2021
3. Added Value of Aerosol Observations of a Future AOS High Spectral Resolution Lidar with Respect to Classic Backscatter Spaceborne Lidar Measurements F. Cornut et al. 10.3390/rs15020506
4. Toward a multivariate formulation of the parametric Kalman filter assimilation: application to a simplified chemical transport model A. Perrot et al. 10.5194/npg-30-139-2023
5. Impact of CALIPSO profile data assimilation on 3-D aerosol improvement in a size-resolved aerosol model H. Ye et al. 10.1016/j.atmosres.2021.105877
6. A Review of Data Assimilation on Aerosol Optical, Radiative, and Climatic Effects Study Y. Cheng et al. 10.1007/s41810-022-00142-9
7. Recent Developments in Satellite Remote Sensing for Air Pollution Surveillance in Support of Sustainable Development Goals D. Stratoulias et al. 10.3390/rs16162932
8. Assimilating spaceborne lidar dust extinction can improve dust forecasts J. Escribano et al. 10.5194/acp-22-535-2022
9. A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model L. El Amraoui et al. 10.3390/rs14081949
10. Scattering and absorbing aerosols in the climate system J. Li et al. 10.1038/s43017-022-00296-7
11. Boundary Conditions for the Parametric Kalman Filter Forecast M. Sabathier et al. 10.1029/2022MS003462
12. Challenges and Opportunities in Lidar Remote Sensing Z. Wang & M. Menenti 10.3389/frsen.2021.641723