DOI: 10.5194/hess-22-6591-2018
论文题名: On the skill of raw and post-processed ensemble seasonal meteorological forecasts in Denmark
作者: Lucatero D. ; Madsen H. ; Refsgaard J.C. ; Kidmose J. ; Jensen K.H.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2018
卷: 22, 期: 12 起始页码: 6591
结束页码: 6609
语种: 英语
Scopus关键词: Climatology
; Ensemble prediction
; European centre for medium-range weather forecasts
; Multiplicative factors
; Reference evapotranspiration
; Seasonal forecasting
; Seasonal forecasts
; Spatiotemporal variability
; Statistical consistencies
; Weather forecasting
英文摘要: This study analyzes the quality of the raw and post-processed seasonal forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) System 4. The focus is given to Denmark, located in a region where seasonal forecasting is of special difficulty. The extent to which there are improvements after post-processing is investigated. We make use of two techniques, namely linear scaling or delta change (LS) and quantile mapping (QM), to daily bias correct seasonal ensemble predictions of hydrologically relevant variables such as precipitation, temperature and reference evapotranspiration (ET0). Qualities of importance in this study are the reduction of bias and the improvement in accuracy and sharpness over ensemble climatology. Statistical consistency and its improvement is also examined. Raw forecasts exhibit biases in the mean that have a spatiotemporal variability more pronounced for precipitation and temperature. This variability is more stable for ET0 with a consistent positive bias. Accuracy is higher than ensemble climatology for some months at the first month lead time only and, in general, ECMWF System 4 forecasts tend to be sharper. ET0 also exhibits an underdispersion issue, i.e., forecasts are narrower than their true uncertainty level. After correction, reductions in the mean are seen. This, however, is not enough to ensure an overall higher level of skill in terms of accuracy, although modest improvements are seen for temperature and ET0, mainly at the first month lead time. QM is better suited to improve statistical consistency of forecasts that exhibit dispersion issues, i.e., when forecasts are consistently overconfident. Furthermore, it also enhances the accuracy of the monthly number of dry days to a higher extent than LS. Caution is advised when applying a multiplicative factor to bias correct variables such as precipitation. It may overestimate the ability that LS has in improving sharpness when a positive bias in the mean exists. © Author(s) 2018. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/163099
Appears in Collections: 气候变化与战略
There are no files associated with this item.
作者单位: Lucatero, D., Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark; Madsen, H., DHI, Hørsholm, Denmark; Refsgaard, J.C., Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark; Kidmose, J., Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark; Jensen, K.H., Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Recommended Citation:
Lucatero D.,Madsen H.,Refsgaard J.C.,et al. On the skill of raw and post-processed ensemble seasonal meteorological forecasts in Denmark[J]. Hydrology and Earth System Sciences,2018-01-01,22(12)