The reduction continuous rank probability score for evaluating discharge forecasts from hydrological ensemble prediction systems

被引:17
作者
Trinh, B. N. [1 ]
Thielen-del Pozo, J. [1 ]
Thirel, G. [1 ,2 ]
机构
[1] Commiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21020 Ispra, Italy
[2] IRSTEA, F-92761 Antony, France
来源
ATMOSPHERIC SCIENCE LETTERS | 2013年 / 14卷 / 02期
关键词
flood forecasting; skill scores; discharge; probabilistic forecasting; ensemble prediction system; FLOOD ALERT SYSTEM; SKILL; VERIFICATION; IMPACT;
D O I
10.1002/asl2.417
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Ensemble prediction system (EPS) meteorological forecasts are increasingly being used as input to hydrological models in order to extend flood-warning lead-times and to improve forecasts and the knowledge of their uncertainty. Probabilistic skill scores classically used in meteorology are usually also utilized for assessing the quality of hydrological ensemble forecasts. However, the different river discharge magnitudes can make difficult the interpretation and comparisons of these scores, as it is for the continuous rank probability score (CRPS). In this letter, a novel 'Reduction' CRPS (RCRPS), which takes into account the different river discharge magnitudes, is proposed, and its usefulness is exhibited. Copyright. (C) 2013 Royal Meteorological Society
引用
收藏
页码:61 / 65
页数:5
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