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- Title
Object-Based Verification of a Prototype Warn-on-Forecast System.
- Authors
Skinner, Patrick S.; Wheatley, Dustan M.; Knopfmeier, Kent H.; Reinhart, Anthony E.; Choate, Jessica J.; Jones, Thomas A.; Creager, Gerald J.; Dowell, David C.; Alexander, Curtis R.; Ladwig, Therese T.; Wicker, Louis J.; Heinselman, Pamela L.; Minnis, Patrick; Palikonda, Rabindra
- Abstract
An object-based verification methodology for the NSSL Experimental Warn-on-Forecast System for ensembles (NEWS-e) has been developed and applied to 32 cases between December 2015 and June 2017. NEWS-e forecast objects of composite reflectivity and 30-min updraft helicity swaths are matched to corresponding reflectivity and rotation track objects in Multi-Radar Multi-Sensor system data on space and time scales typical of a National Weather Service warning. Object matching allows contingency-table-based verification statistics to be used to establish baseline performance metrics for NEWS-e thunderstorm and mesocyclone forecasts. NEWS-e critical success index (CSI) scores of reflectivity (updraft helicity) forecasts decrease from approximately 0.7 (0.4) to 0.4 (0.2) over 3 h of forecast time. CSI scores decrease through the forecast period, indicating that errors do not saturate during the 3-h forecast. Lower verification scores for rotation track forecasts are primarily a result of a high-frequency bias. Comparison of different system configurations used in 2016 and 2017 shows an increase in skill for 2017 reflectivity forecasts, attributable mainly to improvements in the forecast initial conditions. A small decrease in skill in 2017 rotation track forecasts is likely a result of sample differences between 2016 and 2017. Although large case-to-case variation is present, evidence is found that NEWS-e forecast skill improves with increasing object size and intensity.
- Subjects
WEATHER forecasting; OBJECT-oriented databases; CONFIRMATION (Logic); UNITED States. National Weather Service; THUNDERSTORM forecasting
- Publication
Weather & Forecasting, 2018, Vol 33, Issue 5, p1225
- ISSN
0882-8156
- Publication type
Article
- DOI
10.1175/WAF-D-18-0020.1