Investigating the interactions between data assimilation and post-processing in hydrological ensemble forecasting

JOURNAL OF HYDROLOGY

卷:519

Article

Bourgin, F.¹  Ramos, M. H.¹  Thirel, G.¹  Andreassian, V.¹ 

[1] Irstea, UR HBAN, F-92761 Antony, France

关键词: Hydrological ensemble forecasting;    Data assimilation;    Post-processing;    Ensemble dressing;    Uncertainty propagation;   

DOI  :  10.1016/j.jhydrol.2014.07.054

来源: Elsevier

【 摘 要 】

We investigate how data assimilation and post-processing contribute, either separately or together, to the skill of a hydrological ensemble forecasting system. Based on a large catchment set, we compare four forecasting options: without data assimilation and post-processing, without data assimilation but with post-processing, with data assimilation but without post-processing, and with both data assimilation and post-processing. Our results clearly indicate that both strategies have complementary effects. Data assimilation has mainly a very positive effect on forecast accuracy. Its impact however decreases with increasing lead time. Post-processing, by accounting specifically for hydrological uncertainty, has a very positive and longer lasting effect on forecast reliability. As a consequence, the use of both techniques is recommended in hydrological ensemble forecasting. (C) 2014 Elsevier B.V. All rights reserved.

【 授权许可】

Free