9 citations as recorded by crossref.

1. Evaluating the Wegener–Bergeron–Findeisen process in ICON in large-eddy mode with in situ observations from the CLOUDLAB project N. Omanovic et al. https://doi.org/10.5194/acp-24-6825-2024
2. Impact of Holuhraun volcano aerosols on clouds in cloud-system-resolving simulations M. Haghighatnasab et al. https://doi.org/10.5194/acp-22-8457-2022
3. Open Water in Sea Ice Causes High Bias in Polar Low‐Level Clouds in GFDL CM4 X. Li et al. https://doi.org/10.1029/2023GL106322
4. The impact of the mesh size and microphysics scheme on the representation of mid-level clouds in the ICON model in hilly and complex terrain N. Omanovic et al. https://doi.org/10.5194/acp-24-14145-2024
5. Seasonal Cycle of Idealized Polar Clouds: Large Eddy Simulations Driven by a GCM X. Zhang et al. https://doi.org/10.1029/2021MS002671
6. Evaluation of CanESM Cloudiness, Cloud Type and Cloud Radiative Forcing Climatologies Using the CALIPSO-GOCCP and CERES Datasets F. Boudala et al. https://doi.org/10.3390/rs14153668
7. Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic J. Kretzschmar et al. https://doi.org/10.5194/acp-20-13145-2020
8. The climate response to increased cloud liquid water over the Arctic in CESM1: a sensitivity study of Wegener–Bergeron–Findeisen process Y. Huang et al. https://doi.org/10.1007/s00382-021-05648-5
9. Quasi-Lagrangian observations of cloud transitions during the initial phase of marine cold air outbreaks in the Arctic – Part 1: Temporal and spatial evolution A. Weber et al. https://doi.org/10.5194/acp-26-3521-2026