Abstract
European winter storms are a significant threat to communities, public infrastructure, and private and commercial properties. On seasonal timescales, potential predictability was evidenced in recent state-of-the-art seasonal hindcast suites e.g., the UK Met Office’s GloSea5. Related positive and potentially usable forecast skill for frequency and intensity measures were based on pre-season model initialisation around the beginning of November for the following core winter (DJF) season’s assessment.
This study expands on these findings by analysing extended lead times of seasonal forecast into autumn and late summer before the winter season. Here, in a systematic way, a multi-model ensemble of hindcasts is analysed to evaluate current models’ capability to forecast the seasonal activity for initialisations from September to November. First results indicate potential predictability precursors already from the September initialisations for storm frequencies. These results vary from model to model though. The presentation will discuss differences between models as well as lead times for both, storm frequency and intensity.
This study expands on these findings by analysing extended lead times of seasonal forecast into autumn and late summer before the winter season. Here, in a systematic way, a multi-model ensemble of hindcasts is analysed to evaluate current models’ capability to forecast the seasonal activity for initialisations from September to November. First results indicate potential predictability precursors already from the September initialisations for storm frequencies. These results vary from model to model though. The presentation will discuss differences between models as well as lead times for both, storm frequency and intensity.
Original language | English |
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DOIs | |
Publication status | Published - Apr 2023 |
Event | EGU General Assembly 2023 - Vienna, Austria Duration: 24 Apr 2023 → 28 Apr 2023 |
Conference
Conference | EGU General Assembly 2023 |
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Country/Territory | Austria |
City | Vienna |
Period | 24/04/23 → 28/04/23 |