Predictive skill for atmospheric rivers in the western Iberian Peninsula

• Published in: Natural Hazards and Earth System Sciences
• Main Authors: Ramos, Alexandre M., Sousa, Pedro M., Dutra, Emanuel, Trigo, Ricardo M.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2020
• Subjects: article; Verlagsveröffentlichung; Western River; North Atlantic
• Online Access: https://doi.org/10.5194/nhess-20-877-2020; https://noa.gwlb.de/receive/cop_mods_00051056; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00050713/nhess-20-877-2020.pdf; https://nhess.copernicus.org/articles/20/877/2020/nhess-20-877-2020.pdf

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 to study their medium-range predictability. Here we perform such an assessment using the ECMWF ensemble forecasts up to 15 d for events where ARs made landfall 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 and probabilistic evaluation for further objective verification of forecast accuracy. Our results indicate that the ensemble forecasts have skill in detecting upcoming AR events, which can be particularly useful to better predict potential hydrometeorological extremes. We also characterized how the ENS dispersion and confidence curves change with increasing forecast lead times for each sub-domain. The probabilistic evaluation, using receiver operating characteristic (ROC) analysis, shows that for short lead times precipitation forecasts are more accurate 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).