Articles | Volume 22, issue 21
https://doi.org/10.5194/acp-22-13967-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-13967-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation and bias correction of probabilistic volcanic ash forecasts
NOAA Air Resources Laboratory, College Park, MD, USA
Tianfeng Chai
NOAA Air Resources Laboratory, College Park, MD, USA
Cooperative Institute for Satellite and Earth System Studies (CISESS), University of Maryland, College Park, MD, USA
Binyu Wang
NOAA National Centers for Environmental Prediction, Environmental Modeling Center, College Park, MD, USA
IM Systems Group, Rockville, MD, USA
Allison Ring
Department of Atmospheric and Ocean Science, University of Maryland, College Park, MD, USA
Barbara Stunder
NOAA Air Resources Laboratory, College Park, MD, USA
Christopher P. Loughner
NOAA Air Resources Laboratory, College Park, MD, USA
Michael Pavolonis
NOAA National Environmental Satellite, Data and Information Service (NESDIS), Madison, WI, USA
Justin Sieglaff
University of Wisconsin-Madison, Cooperative Institute for Meteorological Satellite Studies (UW/CIMSS), Madison, WI, USA
Viewed
Total article views: 2,336 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 11 May 2022)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,883 | 399 | 54 | 2,336 | 69 | 68 |
- HTML: 1,883
- PDF: 399
- XML: 54
- Total: 2,336
- BibTeX: 69
- EndNote: 68
Total article views: 1,892 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 02 Nov 2022)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,541 | 308 | 43 | 1,892 | 59 | 62 |
- HTML: 1,541
- PDF: 308
- XML: 43
- Total: 1,892
- BibTeX: 59
- EndNote: 62
Total article views: 444 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 11 May 2022)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
342 | 91 | 11 | 444 | 10 | 6 |
- HTML: 342
- PDF: 91
- XML: 11
- Total: 444
- BibTeX: 10
- EndNote: 6
Viewed (geographical distribution)
Total article views: 2,336 (including HTML, PDF, and XML)
Thereof 2,281 with geography defined
and 55 with unknown origin.
Total article views: 1,892 (including HTML, PDF, and XML)
Thereof 1,886 with geography defined
and 6 with unknown origin.
Total article views: 444 (including HTML, PDF, and XML)
Thereof 395 with geography defined
and 49 with unknown origin.
Country | # | Views | % |
---|
Country | # | Views | % |
---|
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Cited
10 citations as recorded by crossref.
- Improving communication between volcano observatories and volcanic ash advisory centres in Europe—outcomes from a first workshop C. Witham et al. 10.1007/s00445-024-01775-z
- Using synthetic case studies to explore the spread and calibration of ensemble atmospheric dispersion forecasts A. Jones et al. 10.5194/acp-23-12477-2023
- Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17) A. Brodtkorb et al. 10.5194/gmd-17-1957-2024
- Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs T. Chai et al. 10.5194/acp-23-12907-2023
- Observing ocean ecosystem responses to volcanic ash K. Bisson et al. 10.1016/j.rse.2023.113749
- Inverse modeling of 137Cs during Chernobyl 2020 wildfires without the first guess O. Tichý et al. 10.1016/j.apr.2025.102419
- How dependent are quantitative volcanic ash concentration and along‐flight dosage forecasts to model structural choices? L. James et al. 10.1002/met.70003
- An investigation of changes to commercial aircraft flight paths during volcanic eruptions J. Delbrel et al. 10.1186/s13617-025-00150-7
- Reducing dependence of modeled resuspended volcanic ash on meteorological grid resolution A. Crawford et al. 10.3389/feart.2025.1511847
- Toward Next‐Generation Lava Flow Forecasting: Development of a Fast, Physics‐Based Lava Propagation Model D. Hyman et al. 10.1029/2022JB024998
9 citations as recorded by crossref.
- Improving communication between volcano observatories and volcanic ash advisory centres in Europe—outcomes from a first workshop C. Witham et al. 10.1007/s00445-024-01775-z
- Using synthetic case studies to explore the spread and calibration of ensemble atmospheric dispersion forecasts A. Jones et al. 10.5194/acp-23-12477-2023
- Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17) A. Brodtkorb et al. 10.5194/gmd-17-1957-2024
- Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs T. Chai et al. 10.5194/acp-23-12907-2023
- Observing ocean ecosystem responses to volcanic ash K. Bisson et al. 10.1016/j.rse.2023.113749
- Inverse modeling of 137Cs during Chernobyl 2020 wildfires without the first guess O. Tichý et al. 10.1016/j.apr.2025.102419
- How dependent are quantitative volcanic ash concentration and along‐flight dosage forecasts to model structural choices? L. James et al. 10.1002/met.70003
- An investigation of changes to commercial aircraft flight paths during volcanic eruptions J. Delbrel et al. 10.1186/s13617-025-00150-7
- Reducing dependence of modeled resuspended volcanic ash on meteorological grid resolution A. Crawford et al. 10.3389/feart.2025.1511847
1 citations as recorded by crossref.
Latest update: 12 Jul 2025
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.
This study describes the development of a workflow which produces probabilistic and quantitative...
Altmetrics
Final-revised paper
Preprint