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NOAA Hazardous Weather Testbed posts preliminary results from experiment
The NOAA Hazardous Weather Testbed (HWT) recently posted preliminary results from their 2007 Spring Experiment. The results will improve severe-weather forecasts, target areas for further research, and will become important contributions to the scientific literature.
The annual Spring Experiment operates on the premise that numerical modelers can learn to incorporate more operational relevance in their research efforts if they work closely with forecasters in an experimental forecasting exercise. And, operational forecasters can make more skillful interpretations of numerical model output if they work with numerical modelers in an experimental forecasting exercise.
Results: Participants found newly developed forecasting systems and products were quite effective at forecasting storm structures, predicting low probability/high impact storm activities and identifying areas favorable for severe thunderstorms.
Payoffs: The production and implementation of a storm-scale ensemble of model forecasts into the forecast process was successful. Also, Storm Prediction Center forecasters are becoming skillful users of storm-scale models and severe-weather forecasters nationwide are becoming acquainted with and encouraged by storm-scale ensembles.
Background: The 2007 Spring Experiment, hosted by NOAA’s Hazardous Weather Testbed and conducted from April through June 2007 in Norman, Okla., drew strength from the participation of a broad spectrum of individuals, including a total of 63 research scientists, forecasters, university faculty, graduate students, and administrators from government agencies, academia, and the private sector. The participants focused on identified characteristic behaviors and specific strengths/weaknesses of the different model configurations and provided focused feedback to model developers on the performance of the experimental models during severe thunderstorm episodes. They also evaluated the operational utility of several experimental versions of models, including an ensemble of model predictions during severe weather episodes
Significance: Targets improving the precision and utility of severe storm forecasts and warnings to protect the public.