Breaking New Ground in Severe Weather Prediction: The 2015 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment Journal Article uri icon



  • Abstract; Led by NOAA’s Storm Prediction Center and National Severe Storms Laboratory, annual spring forecasting experiments (SFEs) in the Hazardous Weather Testbed test and evaluate cutting-edge technologies and concepts for improving severe weather prediction through intensive real-time forecasting and evaluation activities. Experimental forecast guidance is provided through collaborations with several U.S. government and academic institutions, as well as the Met Office. The purpose of this article is to summarize activities, insights, and preliminary findings from recent SFEs, emphasizing SFE 2015. Several innovative aspects of recent experiments are discussed, including the 1) use of convection-allowing model (CAM) ensembles with advanced ensemble data assimilation, 2) generation of severe weather outlooks valid at time periods shorter than those issued operationally (e.g., 1–4 h), 3) use of CAMs to issue outlooks beyond the day 1 period, 4) increased interaction through software allowing participants to create individual severe weather outlooks, and 5) tests of newly developed storm-attribute-based diagnostics for predicting tornadoes and hail size. Additionally, plans for future experiments will be discussed, including the creation of a Community Leveraged Unified Ensemble (CLUE) system, which will test various strategies for CAM ensemble design using carefully designed sets of ensemble members contributed by different agencies to drive evidence-based decision-making for near-future operational systems.

publication date

  • August 1, 2017

has restriction

  • hybrid

Date in CU Experts

  • May 25, 2022 6:35 AM

Full Author List

  • Gallo BT; Clark AJ; Jirak I; Kain JS; Weiss SJ; Coniglio M; Knopfmeier K; Correia J; Melick CJ; Karstens CD

author count

  • 23

Other Profiles

International Standard Serial Number (ISSN)

  • 0882-8156

Electronic International Standard Serial Number (EISSN)

  • 1520-0434

Additional Document Info

start page

  • 1541

end page

  • 1568


  • 32


  • 4