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  • 标题:Predictive skill for atmospheric rivers in the western Iberian Peninsula
  • 本地全文:下载
  • 作者:Ramos, Alexandre M. ; Sousa, Pedro M. ; Dutra, Emanuel
  • 期刊名称:Natural Hazards and Earth System Sciences
  • 电子版ISSN:2195-9269
  • 出版年度:2020
  • 卷号:20
  • 期号:3
  • 页码:877-888
  • DOI:10.5194/nhess-20-877-2020
  • 语种:English
  • 出版社:Copernicus Publications
  • 摘要:A large fraction of extreme precipitation and flood events across western Europe are triggered by atmospheric rivers (ARs). The association between ARs and extreme precipitation days over the Iberian Peninsula has been well documented for western river basins. Since ARs are often associated with high impact weather, it is important tostudy their medium-range predictability. Here we perform such an assessmentusing the ECMWF ensemble forecasts up to 15 d for events where ARs madelandfall in the western Iberian Peninsula during the winters spanning between 2012–2013 and 2015–2016. Vertically integrated horizontal water vapor transport (IVT) and precipitation from the 51 ensemble members of the ECMWF Integrated Forecasting System (IFS) ensemble (ENS) were processed over a domain including western Europe and the contiguous North Atlantic Ocean. Metrics concerning AR location, intensity, and orientation were computed, in order to compare the predictive skill (for different prediction lead times) of IVT and precipitation. We considered several regional boxes over western Iberia, where the presence of ARs is detected in analysis/forecasts, enabling the construction of contingency tables andprobabilistic evaluation for further objective verification of forecastaccuracy. Our results indicate that the ensemble forecasts have skill indetecting upcoming AR events, which can be particularly useful to betterpredict potential hydrometeorological extremes. We also characterized howthe ENS dispersion and confidence curves change with increasing forecastlead times for each sub-domain. The probabilistic evaluation, using receiver operating characteristic (ROC)analysis, shows that for short lead times precipitation forecasts are moreaccurate than IVT forecasts, while for longer lead times this reverses(∼10 d). Furthermore, we show that this reversal occurs for shorter lead times in areas where the AR contribution is more relevant for winter precipitation totals (e.g., northwestern Iberia).
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