Articles | Volume 22, issue 21
https://doi.org/10.5194/acp-22-13967-2022
https://doi.org/10.5194/acp-22-13967-2022
Research article
 | 
02 Nov 2022
Research article |  | 02 Nov 2022

Evaluation and bias correction of probabilistic volcanic ash forecasts

Alice Crawford, Tianfeng Chai, Binyu Wang, Allison Ring, Barbara Stunder, Christopher P. Loughner, Michael Pavolonis, and Justin Sieglaff

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Cited articles

Barnes, L. R., Schultz, D. M., Gruntfest, E. C., Hayden, M. H., and Benight, C.: Corrigendum: False Alarm Rate or False Alarm Ratio?, Weather Forecast., 24, 1452–1453, https://doi.org/10.1175/2009WAF2222300.1, 2009. a, b, c
Beckett, F. M., Witham, C. S., Leadbetter, S. J., Crocker, R., Webster, H. N., Hort, M. C., Jones, A. R., Devenish, B. J., and Thomson, D. J.: Atmospheric Dispersion Modelling at the London VAAC: A Review of Developments since the 2010 Eyjafjallajokull Volcano Ash Cloud, Atmosphere, 11, 352, https://doi.org/10.3390/atmos11040352, 2020. a
Belitz, K. and Stackelberg, P. E.: Evaluation of six methods for correcting bias in estimates from ensemble tree machine learning regression models, Environ. Modell. Softw., 139, 105006, https://doi.org/10.1016/j.envsoft.2021.105006, 2021. a
Cai, Z., Griessbach, S., and Hoffmann, L.: Improved estimation of volcanic SO2 injections from satellite retrievals and Lagrangian transport simulations: the 2019 Raikoke eruption, Atmos. Chem. Phys., 22, 6787–6809, https://doi.org/10.5194/acp-22-6787-2022, 2022. a, b
Chai, T., Crawford, A., Stunder, B., Pavolonis, M. J., Draxler, R., and Stein, A.: Improving volcanic ash predictions with the HYSPLIT dispersion model by assimilating MODIS satellite retrievals, Atmos. Chem. Phys., 17, 2865–2879, https://doi.org/10.5194/acp-17-2865-2017, 2017. a, b, c
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Short summary
This study describes the development of a workflow which produces probabilistic and quantitative forecasts of volcanic ash in the atmosphere. The workflow includes methods of incorporating satellite observations of the ash cloud into a modeling framework as well as verification statistics that can be used to guide further model development and provide information for risk-based approaches to flight planning.
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