气候变化领域集成服务门户(CCPortal): Streamflow-based evaluation of climate model sub-selection methods

CCPortal

DOI	10.1007/s10584-020-02854-8
	Streamflow-based evaluation of climate model sub-selection methods
	Kiesel J.; Stanzel P.; Kling H.; Fohrer N.; Jähnig S.C.; Pechlivanidis I.
发表日期	2020
ISSN	0165-0009
英文摘要	The assessment of climate change and its impact relies on the ensemble of models available and/or sub-selected. However, an assessment of the validity of simulated climate change impacts is not straightforward because historical data is commonly used for bias-adjustment, to select ensemble members or to define a baseline against which impacts are compared—and, naturally, there are no observations to evaluate future projections. We hypothesize that historical streamflow observations contain valuable information to investigate practices for the selection of model ensembles. The Danube River at Vienna is used as a case study, with EURO-CORDEX climate simulations driving the COSERO hydrological model. For each selection method, we compare observed to simulated streamflow shift from the reference period (1960–1989) to the evaluation period (1990–2014). Comparison against no selection shows that an informed selection of ensemble members improves the quantification of climate change impacts. However, the selection method matters, with model selection based on hindcasted climate or streamflow alone is misleading, while methods that maintain the diversity and information content of the full ensemble are favorable. Prior to carrying out climate impact assessments, we propose splitting the long-term historical data and using it to test climate model performance, sub-selection methods, and their agreement in reproducing the indicator of interest, which further provide the expectable benchmark of near- and far-future impact assessments. This test is well-suited to be applied in multi-basin experiments to obtain better understanding of uncertainty propagation and more universal recommendations regarding uncertainty reduction in hydrological impact studies. © 2020, The Author(s).
英文关键词	Climate change impact; Climate uncertainty; Ensemble selection; EURO-CORDEX; Hindcast
语种	英语
scopus关键词	Benchmarking; Climate change; Stream flow; Climate change impact; Climate impact assessment; Ensemble of models; Hydrological impacts; Hydrological modeling; Information contents; Uncertainty propagation; Uncertainty reduction; Climate models
来源期刊	Climatic Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/147292
作者单位	Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany; Institute for Natural Resource Conservation, Department of Hydrology and Water Resources Management, Christian-Albrechts-University Kiel, Kiel, Germany; AFRY Austria GmbH, Hydro Consulting, Vienna, Austria; Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
推荐引用方式 GB/T 7714	Kiesel J.,Stanzel P.,Kling H.,et al. Streamflow-based evaluation of climate model sub-selection methods[J],2020.
APA	Kiesel J.,Stanzel P.,Kling H.,Fohrer N.,Jähnig S.C.,&Pechlivanidis I..(2020).Streamflow-based evaluation of climate model sub-selection methods.Climatic Change.
MLA	Kiesel J.,et al."Streamflow-based evaluation of climate model sub-selection methods".Climatic Change (2020).