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Development of a prototype real-time sting-jet precursor tool for forecasters

Gray, S. L. ORCID: https://orcid.org/0000-0001-8658-362X, Martinez-Alvarado, O. ORCID: https://orcid.org/0000-0002-5285-0379, Ackerley, D. and Suri, D. (2020) Development of a prototype real-time sting-jet precursor tool for forecasters. Weather. ISSN 1477-8696

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To link to this item DOI: 10.1002/wea.3889

Abstract/Summary

Damaging surface winds in some European storms have been attributed to descending mesoscale airstreams termed sting jets. The development of a prototype real-time tool that Met Office forecasters can use to identify favourable conditions for sting jet occurrence in extratropical cyclones is presented. The motivation is to improve national severe weather warnings. We have previously developed a convective-instability-based tool to identify sting-jet precursors for research purposes and applied it to storms in reanalyses and climate models with insufficient spatial resolution to represent sting jets. Here we describe the challenges of applying this research-derived diagnostic to output from an operational forecast system and demonstrate its usefulness for a recent winter storm. Through close collaboration with the researchers and forecasters from the Met Office, the diagnostic has been adapted to work on output from the Met Office’s operational global ensemble forecasts as it becomes available. Since autumn 2019, forecasters have been able to view graphical output informing them whether storms impacting the UK and Europe (up to seven days in the future) have the precursor. The tool has already proven useful in informing guidance for severe weather warnings, including those issued by the Met Office's impact-based National Severe Weather Warning Service that goes out to seven days ahead and is the primary hazardous weather warning service for the public and emergency responders.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:94616
Publisher:Wiley

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