Articles | Volume 13, issue 3
https://doi.org/10.5194/gmd-13-1431-2020
https://doi.org/10.5194/gmd-13-1431-2020
Model description paper
 | 
24 Mar 2020
Model description paper |  | 24 Mar 2020

FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 1: Model physics and numerics

Arnau Folch, Leonardo Mingari, Natalia Gutierrez, Mauricio Hanzich, Giovanni Macedonio, and Antonio Costa

Related authors

Reconstructing tephra fall deposits via ensemble-based data assimilation techniques
Leonardo Mingari, Antonio Costa, Giovanni Macedonio, and Arnau Folch
Geosci. Model Dev., 16, 3459–3478, https://doi.org/10.5194/gmd-16-3459-2023,https://doi.org/10.5194/gmd-16-3459-2023, 2023
Short summary
Data assimilation of volcanic aerosol observations using FALL3D+PDAF
Leonardo Mingari, Arnau Folch, Andrew T. Prata, Federica Pardini, Giovanni Macedonio, and Antonio Costa
Atmos. Chem. Phys., 22, 1773–1792, https://doi.org/10.5194/acp-22-1773-2022,https://doi.org/10.5194/acp-22-1773-2022, 2022
Short summary
Long-term hazard assessment of explosive eruptions at Jan Mayen (Norway) and implications for air traffic in the North Atlantic
Manuel Titos, Beatriz Martínez Montesinos, Sara Barsotti, Laura Sandri, Arnau Folch, Leonardo Mingari, Giovanni Macedonio, and Antonio Costa
Nat. Hazards Earth Syst. Sci., 22, 139–163, https://doi.org/10.5194/nhess-22-139-2022,https://doi.org/10.5194/nhess-22-139-2022, 2022
Short summary
FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 2: Model validation
Andrew T. Prata, Leonardo Mingari, Arnau Folch, Giovanni Macedonio, and Antonio Costa
Geosci. Model Dev., 14, 409–436, https://doi.org/10.5194/gmd-14-409-2021,https://doi.org/10.5194/gmd-14-409-2021, 2021
Short summary
Volcanic ash forecast using ensemble-based data assimilation: an ensemble transform Kalman filter coupled with the FALL3D-7.2 model (ETKF–FALL3D version 1.0)
Soledad Osores, Juan Ruiz, Arnau Folch, and Estela Collini
Geosci. Model Dev., 13, 1–22, https://doi.org/10.5194/gmd-13-1-2020,https://doi.org/10.5194/gmd-13-1-2020, 2020
Short summary

Related subject area

Atmospheric sciences
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024,https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024,https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024,https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024,https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024,https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary

Cited articles

Aschenbrenner, B. C.: A new method of expressing particle sphericity, J. Sediment. Petrol., 26, 15–31, 1956. a
Bear-Crozier, A., Kartadinata, N., Heriwaseso, A., and Møller Nielsen, O.: Development of python-FALL3D: a modified procedure for modelling volcanic ash dispersal in the Asia-Pacific region, Nat. Hazards, 64, 821–838, 2012. a
Bengtsson, L., Andrae, U., Aspelien, T., Batrak, Y., Calvo, J., de Rooy, W., Gleeson, E., Hansen-Sass, B., Homleid, M., Hortal, M., Ivarsson, K.-I., Lenderink, G., Niemela, S., Nielsen, K., Onvlee, J., Rontu, L., Samuelsson, P., Munoz, D., Subias, A., Tijm, S., Toll, V., Yang, X., and Koltzow, M.: The HARMONIE-AROME Model Configuration in the ALADIN-HIRLAM NWP System, Mon. Weather Rev., 145, 1919–1935, https://doi.org/10.1175/MWR-D-16-0417.1, 2017. a
Biass, S., Scaini, C., Bonadonna, C., Folch, A., Smith, K., and Höskuldsson, A.: A multi-scale risk assessment for tephra fallout and airborne concentration from multiple Icelandic volcanoes – Part 1: Hazard assessment, Nat. Hazards Earth Syst. Sci., 14, 2265–2287, https://doi.org/10.5194/nhess-14-2265-2014, 2014. a
Bonasia, R., Scaini, C., Capra, L., Nathenson, M., Siebe, C., Arana-Salinas, L., and Folch, A.: Long-range hazard assessment of volcanic ash dispersal for a Plinian eruptive scenario at Popocatépetl volcano (Mexico): implications for civil aviation safety, Bull. Volcanol., 76, 789, https://doi.org/10.1007/s00445-013-0789-z, 2013. a
Short summary
This paper presents FALL3D-8.0, the latest version release of an open-source code with a track record of 15+ years and a growing number of users in the volcanological and atmospheric communities. The code, originally conceived for atmospheric dispersal and deposition of tephra particles, has been extended to model other types of particles, aerosols and radionuclides. This paper details the FALL3D-8.0 model physics and the numerical implementation of the code.