14 citations as recorded by crossref.

1. Refining an ensemble of volcanic ash forecasts using satellite retrievals: Raikoke 2019 A. Capponi et al. https://doi.org/10.5194/acp-22-6115-2022
2. Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits S. Osman et al. https://doi.org/10.3390/atmos11060567
3. 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. https://doi.org/10.5194/nhess-21-3731-2021
4. Assessment of the volcanic hazard of Mt. Paektu explosion to international air traffic using South Korean airspace S. Kim et al. https://doi.org/10.1007/s11069-018-3562-y
5. Anthropogenic heat flux: advisable spatial resolutions when input data are scarce A. Gabey et al. https://doi.org/10.1007/s00704-018-2367-y
6. Evaluation and bias correction of probabilistic volcanic ash forecasts A. Crawford et al. https://doi.org/10.5194/acp-22-13967-2022
7. Inverse transport modeling of volcanic sulfur dioxide emissions using large-scale simulations Y. Heng et al. https://doi.org/10.5194/gmd-9-1627-2016
8. Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers D. Piontek et al. https://doi.org/10.3390/rs15051247
9. Use of radar rainfall to model deposition of radionuclides S. Leadbetter https://doi.org/10.1016/j.atmosenv.2019.04.056
10. The 2019 Raikoke volcanic eruption – Part 1: Dispersion model simulations and satellite retrievals of volcanic sulfur dioxide J. de Leeuw et al. https://doi.org/10.5194/acp-21-10851-2021
11. Characterizing the Atmospheric Conditions Leading to Large Error Growth in Volcanic Ash Cloud Forecasts H. Dacre & N. Harvey https://doi.org/10.1175/JAMC-D-17-0298.1
12. Evaluating the assimilation of S5P/TROPOMI near real-time SO2 columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption A. Inness et al. https://doi.org/10.5194/gmd-15-971-2022
13. The Use of Gaussian Mixture Models with Atmospheric Lagrangian Particle Dispersion Models for Density Estimation and Feature Identification A. Crawford https://doi.org/10.3390/atmos11121369
14. An ensemble of state-of-the-art ash dispersion models: towards probabilistic forecasts to increase the resilience of air traffic against volcanic eruptions M. Plu et al. https://doi.org/10.5194/nhess-21-2973-2021