Oil spill model uncertainty quantification using an atmospheric ensemble

Kampouris, Konstantinos; Vervatis, Vassilios; Karagiorgos, John; Sofianos, Sarantis

doi:https://doi.org/10.5194/os-17-919-2021

Articles | Volume 17, issue 4

https://doi.org/10.5194/os-17-919-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Advances in interdisciplinary studies at multiple scales in...

https://doi.org/10.5194/os-17-919-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 4

Research article

|

15 Jul 2021

Research article |

| 15 Jul 2021

Oil spill model uncertainty quantification using an atmospheric ensemble

Konstantinos Kampouris, Vassilios Vervatis, John Karagiorgos, and Sarantis Sofianos

Data sets

Mediterranean Sea Analysis and Forecast (CMEMS MED-Currents 2016–2019) (Version 1) E. Clementi, J. Pistoia, R. Escudier, D. Delrosso, M. Drudi, A. Grandi, R. Lecci, S. Cretí, S. Ciliberti, G. Coppini, S. Masina, and N. Pinardi https://doi.org/10.25423/CMCC/MEDSEA_ANALYSIS_FORECAST_PHY_006_013_EAS4

Archive Catalogue ECMWF https://apps.ecmwf.int/archive-catalogue/

Bathymetric data set GEBCO https://www.gebco.net/

Coastline data set NOAA https://www.ngdc.noaa.gov/mgg/shorelines/data/gshhg/latest/

Model code and software

MEDSLIK-II MEDSLIK-II Team http://www.medslik-ii.org/

Short summary

The wind is a source of uncertainty in oil spill modeling. We performed oil spill ensemble simulations using an atmospheric ensemble to quantify this uncertainty. We investigate the reliability of oil spill ensemble prediction used as an important forecasting tool to better plan mitigation procedures in the event of an oil spill.