Oil spill model uncertainty quantification using an atmospheric ensemble

Author:

Kampouris Konstantinos,Vervatis VassiliosORCID,Karagiorgos John,Sofianos Sarantis

Abstract

Abstract. We investigate the impact of atmospheric forcing uncertainties on the prediction of the dispersion of pollutants in the marine environment. Ensemble simulations consisting of 50 members were carried out using the ECMWF ensemble prediction system and the oil spill model MEDSLIK-II in the Aegean Sea. A deterministic control run using the unperturbed wind of the ECMWF high-resolution system served as reference for the oil spill prediction. We considered the oil spill rates and duration to be similar to major accidents of the past (e.g., the Prestige case) and we performed simulations for different seasons and oil spill types. Oil spill performance metrics and indices were introduced in the context of probabilistic hazard assessment. Results suggest that oil spill model uncertainties were sensitive to the atmospheric forcing uncertainties, especially to phase differences in the intensity and direction of the wind among members. An oil spill ensemble prediction system based on model uncertainty of the atmospheric forcing, shows great potential for predicting pathways of oil spill transport alongside a deterministic simulation, increasing the reliability of the model prediction and providing important information for the control and mitigation strategies in the event of an oil spill accident.

Publisher

Copernicus GmbH

Subject

Cell Biology,Developmental Biology,Embryology,Anatomy

Reference44 articles.

1. Al Shami, A., Harik, G., Alameddine, I., Bruschi, D., Garcia, D. A., and El-Fadel, M.: Risk assessment of oil spills along the Mediterranean coast: A sensitivity analysis of the choice of hazard quantification, Sci. Total Environ., 574, 234–245, https://doi.org/10.1016/j.scitotenv.2016.09.064, 2017.

2. Amir-Heidari, P. and Raie, M.: A new stochastic oil spill risk assessment model for Persian Gulf: Development, application and evaluation, Mar. Pollut. Bull., 145, 357–369, https://doi.org/10.1016/j.marpolbul.2019.05.022, 2019.

3. Amir-Heidari, P., Arneborg, L., Lindgren, J. F., Lindhe, A., Rosén, L., Raie, M., Axell, L., and Hassellöv, I.-M.: A state-of-the-art model for spatial and stochastic oil spill risk assessment: A case study of oil spill from a shipwreck, Environ. Int., 126, 309–320, https://doi.org/10.1016/j.envint.2019.02.037, 2019.

4. Buizza, R.: The ECMWF Ensemble Prediction System, in: Predictability of Weather and Climate, vol. 9780521848, edited by: Palmer, T. and Hagedorn, R., 459–488, Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9780511617652.018, 2006.

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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3