Automated trigger procedure for operational attribution

The need and interest in operational detection and attribution services is growing. To increase the operational efficiency of relevant and rapid attribution studies, an efficient method for the first step in the process - triggering and selection of extreme events for potential study, is required. It can also be beneficial to ensure that the triggering process is as objective as possible in order to reduce risks of selection bias and ensure any operational service is fully traceable regarding decisions made when initiating a study.

The “Heat wave magnitude index daily (HWMId)” of Russo et al. 2015 is adapted for the purpose of triggering heat, cold and wet extremes on a daily basis. Using a clustering algorithm, events are automatically ranked per type across a 2-week period, covering recent and upcoming days, according to an index accounting for their intensity, duration and area. This index, together with related metrics such as DEI, EFI and RX3day, is displayed regionally and globally in the “Hazard Monitoring Tool” - a user interface for operational use.

The outcome of the method’s application to heat extremes will be demonstrated and compared to HWMId for well known extreme events and other events of interest. The adaptation of the method for cold and wet extremes will also be presented, along with several other diagnostic tools that can aid the selection of the most suitable extreme events for a rapid attribution study. As this is work in progress, we look forward to discussions on the challenges as well as the promising results of this method.