气候变化领域集成服务门户(CCPortal): Combining short-range dispersion simulations with fine-scale meteorological ensembles: probabilistic indicators and evaluation during a Kr-85 field campaign

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DOI	10.5194/acp-22-15793-2022
	Combining short-range dispersion simulations with fine-scale meteorological ensembles: probabilistic indicators and evaluation during a Kr-85 field campaign
	El-Ouartassy, Youness; Korsakissok, Irene; Plu, Matthieu; Connan, Olivier; Descamps, Laurent; Raynaud, Laure
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	15793
结束页码	15816
卷号	22 期号:24 页码:24
英文摘要	Numerical atmospheric dispersion models (ADMs) are used for predicting the health and environmental consequences of nuclear accidents in order to anticipate countermeasures necessary to protect the populations. However, these simulations suffer from significant uncertainties, arising in particular from input data: weather conditions and source term. Meteorological ensembles are already used operationally to characterize uncertainties in weather predictions. Combined with dispersion models, these ensembles produce different scenarios of radionuclide dispersion, called members , representative of the variety of possible forecasts. In this study, the fine-scale operational weather ensemble AROME-EPS (Applications of Research to Operations at Mesoscale-Ensemble Prediction System) from Meteo-France is coupled with the Gaussian puff model pX developed by the IRSN (French Institute for Radiation Protection and Nuclear Safety). The source term data are provided at 10 min resolution by the Orano La Hague reprocessing plant (RP) that regularly discharges 85Kr during the spent nuclear fuel reprocessing process. In addition, a continuous measurement campaign of 85Kr air concentration was recently conducted by the Laboratory of Radioecology in Cherbourg (LRC) of the IRSN, within 20 km of the RP in the North-Cotentin peninsula, and is used for model evaluation. This paper presents a probabilistic approach to study the meteorological uncertainties in dispersion simulations at local and medium distances (2-20 km). First, the quality of AROME-EPS forecasts is confirmed by comparison with observations from both Meteo-France and the IRSN. Then, the probabilistic performance of the atmospheric dispersion simulations was evaluated by comparison to the 85Kr measurements carried out during a period of 2 months, using two probabilistic scores: relative operating characteristic (ROC) curves and Peirce skill score (PSS). The sensitivity of dispersion results to the method used for the calculation of atmospheric stability and associated Gaussian dispersion standard deviations is also discussed. A desirable feature for a model used in emergency response is the ability to correctly predict exceedance of a given value (for instance, a dose guide level). When using an ensemble of simulations, the decision threshold is the number of members predicting an event above which this event should be considered probable. In the case of the 16-member dispersion ensemble used here, the optimal decision threshold was found to be 3 members, above which the ensemble better predicts the observed peaks than the deterministic simulation. These results highlight the added value of ensemble forecasts compared to a single deterministic one and their potential interest in the decision process during crisis situations.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000895883800001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273384
作者单位	Centre National de la Recherche Scientifique (CNRS); Meteo France; Universite de Toulouse
推荐引用方式 GB/T 7714	El-Ouartassy, Youness,Korsakissok, Irene,Plu, Matthieu,et al. Combining short-range dispersion simulations with fine-scale meteorological ensembles: probabilistic indicators and evaluation during a Kr-85 field campaign[J],2022,22(24):24.
APA	El-Ouartassy, Youness,Korsakissok, Irene,Plu, Matthieu,Connan, Olivier,Descamps, Laurent,&Raynaud, Laure.(2022).Combining short-range dispersion simulations with fine-scale meteorological ensembles: probabilistic indicators and evaluation during a Kr-85 field campaign.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(24),24.
MLA	El-Ouartassy, Youness,et al."Combining short-range dispersion simulations with fine-scale meteorological ensembles: probabilistic indicators and evaluation during a Kr-85 field campaign".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.24(2022):24.