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Adam J. Clark
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Israel L. Jirak
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Burkely T. Gallo
,
Kent H. Knopfmeier
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Brett Roberts
,
Makenzie Krocak
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Jake Vancil
,
Kimberly A. Hoogewind
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Nathan A. Dahl
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Eric D. Loken
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David Jahn
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David Harrison
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David Imy
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Patrick Burke
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Louis J. Wicker
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Patrick S. Skinner
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Pamela L. Heinselman
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Patrick Marsh
,
Katie A. Wilson
,
Andrew R. Dean
,
Gerald J. Creager
,
Thomas A. Jones
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Jidong Gao
,
Yunheng Wang
,
Montgomery Flora
,
Corey K. Potvin
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Christopher A. Kerr
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Nusrat Yussouf
,
Joshua Martin
,
Jorge Guerra
,
Brian C. Matilla
, and
Thomas J. Galarneau
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Adam J. Clark
,
Israel L. Jirak
,
Burkely T. Gallo
,
Brett Roberts
,
Andrew R. Dean
,
Kent H. Knopfmeier
,
Louis J. Wicker
,
Makenzie Krocak
,
Patrick S. Skinner
,
Pamela L. Heinselman
,
Katie A. Wilson
,
Jake Vancil
,
Kimberly A. Hoogewind
,
Nathan A. Dahl
,
Gerald J. Creager
,
Thomas A. Jones
,
Jidong Gao
,
Yunheng Wang
,
Eric D. Loken
,
Montgomery Flora
,
Christopher A. Kerr
,
Nusrat Yussouf
,
Scott R. Dembek
,
William Miller
,
Joshua Martin
,
Jorge Guerra
,
Brian Matilla
,
David Jahn
,
David Harrison
,
David Imy
, and
Michael C. Coniglio
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Adam J. Clark
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Steven J. Weiss
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John S. Kain
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Israel L. Jirak
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Michael Coniglio
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Christopher J. Melick
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Christopher Siewert
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Ryan A. Sobash
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Patrick T. Marsh
,
Andrew R. Dean
,
Ming Xue
,
Fanyou Kong
,
Kevin W. Thomas
,
Yunheng Wang
,
Keith Brewster
,
Jidong Gao
,
Xuguang Wang
,
Jun Du
,
David R. Novak
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Faye E. Barthold
,
Michael J. Bodner
,
Jason J. Levit
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C. Bruce Entwistle
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Tara L. Jensen
, and
James Correia Jr.

The NOAA Hazardous Weather Testbed (HWT) conducts annual spring forecasting experiments organized by the Storm Prediction Center and National Severe Storms Laboratory to test and evaluate emerging scientific concepts and technologies for improved analysis and prediction of hazardous mesoscale weather. A primary goal is to accelerate the transfer of promising new scientific concepts and tools from research to operations through the use of intensive real-time experimental forecasting and evaluation activities conducted during the spring and early summer convective storm period. The 2010 NOAA/HWT Spring Forecasting Experiment (SE2010), conducted 17 May through 18 June, had a broad focus, with emphases on heavy rainfall and aviation weather, through collaboration with the Hydrometeorological Prediction Center (HPC) and the Aviation Weather Center (AWC), respectively. In addition, using the computing resources of the National Institute for Computational Sciences at the University of Tennessee, the Center for Analysis and Prediction of Storms at the University of Oklahoma provided unprecedented real-time conterminous United States (CONUS) forecasts from a multimodel Storm-Scale Ensemble Forecast (SSEF) system with 4-km grid spacing and 26 members and from a 1-km grid spacing configuration of the Weather Research and Forecasting model. Several other organizations provided additional experimental high-resolution model output. This article summarizes the activities, insights, and preliminary findings from SE2010, emphasizing the use of the SSEF system and the successful collaboration with the HPC and AWC.

A supplement to this article is available online (DOI:10.1175/BAMS-D-11-00040.2)

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Pamela L. Heinselman
,
Patrick C. Burke
,
Louis J. Wicker
,
Adam J. Clark
,
John S. Kain
,
Jidong Gao
,
Nusrat Yussouf
,
Thomas A. Jones
,
Patrick S. Skinner
,
Corey K. Potvin
,
Katie A. Wilson
,
Burkely T. Gallo
,
Montgomery L. Flora
,
Joshua Martin
,
Gerry Creager
,
Kent H. Knopfmeier
,
Yunheng Wang
,
Brian C. Matilla
,
David C. Dowell
,
Edward R. Mansell
,
Brett Roberts
,
Kimberly A. Hoogewind
,
Derek R. Stratman
,
Jorge Guerra
,
Anthony E. Reinhart
,
Christopher A. Kerr
, and
William Miller

Abstract

In 2009, advancements in NWP and computing power inspired a vision to advance hazardous weather warnings from a warn-on-detection to a warn-on-forecast paradigm. This vision would require not only the prediction of individual thunderstorms and their attributes but the likelihood of their occurrence in time and space. During the last decade, the warn-on-forecast research team at the NOAA National Severe Storms Laboratory met this challenge through the research and development of 1) an ensemble of high-resolution convection-allowing models; 2) ensemble- and variational-based assimilation of weather radar, satellite, and conventional observations; and 3) unique postprocessing and verification techniques, culminating in the experimental Warn-on-Forecast System (WoFS). Since 2017, we have directly engaged users in the testing, evaluation, and visualization of this system to ensure that WoFS guidance is usable and useful to operational forecasters at NOAA national centers and local offices responsible for forecasting severe weather, tornadoes, and flash floods across the watch-to-warning continuum. Although an experimental WoFS is now a reality, we close by discussing many of the exciting opportunities remaining, including folding this system into the Unified Forecast System, transitioning WoFS into NWS operations, and pursuing next-decade science goals for further advancing storm-scale prediction.

Significance Statement

The purpose of this research is to develop an experimental prediction system that forecasts the probability for severe weather hazards associated with individual thunderstorms up to 6 h in advance. This capability is important because some people and organizations, like those living in mobile homes, caring for patients in hospitals, or managing large outdoor events, require extended lead time to protect themselves and others from potential severe weather hazards. Our results demonstrate a prediction system that enables forecasters, for the first time, to message probabilistic hazard information associated with individual severe storms between the watch-to-warning time frame within the United States.

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