Articles | Volume 22, issue 3
https://doi.org/10.5194/acp-22-1773-2022
© 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-22-1773-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Feb 2022
Research article |
| 07 Feb 2022
| 07 Feb 2022
Data assimilation of volcanic aerosol observations using FALL3D+PDAF
Barcelona Supercomputing Center, Barcelona, Spain
Arnau Folch
Geociencias Barcelona (GEO3BCN-CSIC), Barcelona, Spain
Andrew T. Prata
Sub-department of Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK
Federica Pardini
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Pisa, Italy
Giovanni Macedonio
Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Vesuviano, Naples, Italy
Antonio Costa
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, Bologna, Italy
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Short summary
We present a new implementation of an ensemble-based data assimilation method to improve forecasting of volcanic aerosols. This system can be efficiently integrated into operational workflows by exploiting high-performance computing resources. We found a dramatic improvement of forecast quality when satellite retrievals are continuously assimilated. Management of volcanic risk and reduction of aviation impacts can strongly benefit from this research.
We present a new implementation of an ensemble-based data assimilation method to improve...
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