DOI: 10.1002/2014GL062472
论文题名: Trends in the predictive performance of raw ensemble weather forecasts
作者: Hemri S. ; Scheuerer M. ; Pappenberger F. ; Bogner K. ; Haiden T.
刊名: Geophysical Research Letters
ISSN: 0094-9482
EISSN: 1944-9213
出版年: 2014
卷: 41, 期: 24 起始页码: 9197
结束页码: 9205
语种: 英语
英文关键词: EMOS
; ensemble weather forecasts
; model verification
; statistical postprocessing
Scopus关键词: Atmospheric temperature
; Forecasting
; Wind
; EMOS
; Ensemble model output statistics
; Ensemble weather forecasts
; European centre for medium-range weather forecasts
; Model verification
; Near surface temperature
; Predictive performance
; statistical postprocessing
; Weather forecasting
; ensemble forecasting
; global change
; performance assessment
; reliability analysis
; surface temperature
; weather forecasting
; wind velocity
英文摘要: This study applies statistical postprocessing to ensemble forecasts of near-surface temperature, 24 h precipitation totals, and near-surface wind speed from the global model of the European Centre for Medium-Range Weather Forecasts (ECMWF). The main objective is to evaluate the evolution of the difference in skill between the raw ensemble and the postprocessed forecasts. Reliability and sharpness, and hence skill, of the former is expected to improve over time. Thus, the gain by postprocessing is expected to decrease. Based on ECMWF forecasts from January 2002 to March 2014 and corresponding observations from globally distributed stations, we generate postprocessed forecasts by ensemble model output statistics (EMOS) for each station and variable. Given the higher average skill of the postprocessed forecasts, we analyze the evolution of the difference in skill between raw ensemble and EMOS. This skill gap remains almost constant over time indicating that postprocessing will keep adding skill in the foreseeable future. Key Points Evolution of raw ensemble forecast skillFuture benefits from statistical postprocessingGlobal distribution of forecast skill development ©2014. The Authors. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921769223&doi=10.1002%2f2014GL062472&partnerID=40&md5=4d9d761e8f75848b6e94cb9280758693
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/6746
Appears in Collections: 气候减缓与适应
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作者单位: Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
Recommended Citation:
Hemri S.,Scheuerer M.,Pappenberger F.,et al. Trends in the predictive performance of raw ensemble weather forecasts[J]. Geophysical Research Letters,2014-01-01,41(24).