GSTDTAP  > 气候变化
DOI10.1029/2017JD027923
Skill of Subseasonal Forecasts in Europe: Effect of Bias Correction and Downscaling Using Surface Observations
Monhart, S.1,2,3; Spirig, C.2; Bhend, J.2; Bogner, K.1; Schar, C.3; Liniger, M. A.2
2018-08-16
发表期刊JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
ISSN2169-897X
EISSN2169-8996
出版年2018
卷号123期号:15页码:7999-8016
文章类型Article
语种英语
国家Switzerland
英文摘要

Subseasonal predictions bridge the gap between medium-range weather forecasts and seasonal climate predictions. This time horizon is of crucial importance for many planning purposes, including energy production and agriculture. The verification of such predictions is normally done for areal averages of upper-air parameters. Only few studies exist that verify the forecasts for surface parameters with observational stations, although this is crucial for real-world applications, which often require such predictions at specific surface locations. With this study we provide an extensive station-based verification of subseasonal forecasts against 1,637 ground based observational time series across Europe. Twenty years of temperature and precipitation reforecasts of the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System are used to analyze the period of April 1995 to March 2014. A lead time and seasonally dependent bias correction is performed to correct the daily temperature and precipitation forecasts at all stations individually. Two bias correction techniques are compared, a mean debiasing method and a quantile mapping approach. Commonly used skill scores characterizing different aspects of forecast quality are computed for weekly aggregated forecasts with lead times of 5-32days. Overall, promising skill is found for temperature in all seasons except spring. Temperature forecasts tend to show higher skill in Northern Europe and in particular around the Baltic Sea, and in winter. Bias correction is shown to be essential in enhancing the forecast skill in all four weeks for most of the stations and for both variables with QM generally performing better.


Key Points


英文关键词subseasonal predictions bias correction downscaling
领域气候变化
收录类别SCI-E
WOS记录号WOS:000443566900012
WOS关键词ENSEMBLE PREDICTION SYSTEMS ; CLIMATE-CHANGE ; PRECIPITATION FORECASTS ; TEMPERATURE ; ECMWF ; SWITZERLAND ; INDEXES ; VERIFICATION ; REFORECASTS ; CALIBRATION
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/33375
专题气候变化
作者单位1.Swiss Fed Inst Forest Snow & Landscape Res WSL, Mt Hydrol & Mass movements, Birmensdorf, Switzerland;
2.Fed Off Meteorol & Climatol MeteoSwiss, Zurich, Switzerland;
3.Swiss Fed Inst Technol, Inst Atmospher & Climate Sci, Zurich, Switzerland
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GB/T 7714
Monhart, S.,Spirig, C.,Bhend, J.,et al. Skill of Subseasonal Forecasts in Europe: Effect of Bias Correction and Downscaling Using Surface Observations[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2018,123(15):7999-8016.
APA Monhart, S.,Spirig, C.,Bhend, J.,Bogner, K.,Schar, C.,&Liniger, M. A..(2018).Skill of Subseasonal Forecasts in Europe: Effect of Bias Correction and Downscaling Using Surface Observations.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,123(15),7999-8016.
MLA Monhart, S.,et al."Skill of Subseasonal Forecasts in Europe: Effect of Bias Correction and Downscaling Using Surface Observations".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 123.15(2018):7999-8016.
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