Subseasonal to Seasonal Climate Forecasts Provide the Backbone of a Near-Real-Time Event Explainer Service

Pandora Hope, Mei Zhao, S. Abhik, Gen Tolhurst, Roseanna C. McKay, Surendra P. Rauniyar, Lynette Bettio, Avijeet Ramchurn, Eun Pa Lim, Acacia S. Pepler, Tim Cowan, Andrew B. Watkins

Research output: Contribution to journalArticleOtherpeer-review

5 Citations (Scopus)


The Australian Bureau of Meteorology (BoM) provides forecasts at daily, multiweek, and seasonal
time scales along with a range of other services.
Customers are keen to be informed about the causes
of extreme weather and climate events to help them
in their planning and decision making. While attribution is often framed in terms of understanding the
role of climate change, it is also useful to understand
the role of climate variability and circulation changes
in causing extreme events (e.g., Mindlin et al. 2020).
The focus of the Event Explainer is to reduce climate
risk by informing decision makers about the causes of
extreme events and, if there are persistent underlying
drivers, the event’s likelihood of recurrence over the
coming season or decade.
This article describes the tools that are being developed at the BoM to explain the causes of extreme
weather and climate events, and how those tools would
add value to existing services. The novel aspect of the
tools is that they will link with the dynamical subseasonal to seasonal (S2S) forecasts currently in operation.
Thus, operational staff are alerted to the upcoming extreme event, and have time to diagnose and quantify
the causes, thereby facilitating earlier and more effective communication with the public and
stakeholders and potentially tailoring the service to users’ needs. Hence there is strong appeal
in using an operational forecast system as the backbone of a real-time attribution system.
Original languageEnglish
Pages (from-to)S7-S13
Number of pages7
JournalBulletin of the American Meteorological Society
Issue number3
Publication statusPublished - 1 Mar 2022
Externally publishedYes

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