Collaborative Efforts between the United States and United Kingdom to Advance Prediction of High-Impact Weather

Kain, John S. ; Willington, Steve ; Clark, Adam J. ; Weiss, Steven J. ; Weeks, Mark ; Jirak, Israel L. ; Coniglio, Michael C. ; Roberts, Nigel M. ; Karstens, Christopher D. ; Wilkinson, Jonathan M. ; Knopfmeier, Kent H. ; Lean, Humphrey W. ; Ellam, Laura ; Hanley, Kirsty ; North, Rachel ; Suri, Dan

Année de publication
2017

In recent years, a growing partnership has emerged between the Met Office and the designated U.S. national centers for expertise in severe weather research and forecasting, that is, the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory (NSSL) and the NOAA Storm Prediction Center (SPC). The driving force behind this partnership is a compelling set of mutual interests related to predicting and understanding high-impact weather and using high-resolution numerical weather prediction models as foundational tools to explore these interests.The forum for this collaborative activity is the NOAA Hazardous Weather Testbed, where annual Spring Forecasting Experiments (SFEs) are conducted by NSSL and SPC. For the last decade, NSSL and SPC have used these experiments to find ways that high-resolution models can help achieve greater success in the prediction of tornadoes, large hail, and damaging winds. Beginning in 2012, the Met Office became a contributing partner in annual SFEs, bringing complementary expertise in the use of convection-allowing models, derived in their case from a parallel decadelong effort to use these models to advance prediction of flash floods associated with heavy thunderstorms.The collaboration between NSSL, SPC, and the Met Office has been enthusiastic and productive, driven by strong mutual interests at a grassroots level and generous institutional support from the parent government agencies. In this article, a historical background is provided, motivations for collaborative activities are emphasized, and preliminary results are highlighted.

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