Verification of Quasi-Linear Convective Systems Predicted by the Warn-on-Forecast System (WoFS)

Abstract

Abstract Quasi-linear convective systems (QLCSs) can produce multiple hazards (e.g., straight-line winds, flash flooding, and mesovortex tornadoes) that pose a significant threat to life and property, and are often difficult to accurately forecast. The NSSL Warn-on-Forecast System (WoFS) is a convection-allowing ensemble system developed to provide short-term, probabilistic forecasting guidance for severe convective events. Examination of WoFS’s capability to predict QLCSs has yet to be systematically assessed across a large number of cases for 0–6-h forecast times. In this study, the quality of WoFS QLCS forecasts for 50 QLCS days occurring between 2017 and 2020 is evaluated using object-based verification techniques. First, a storm mode identification and classification algorithm is tuned to identify high-reflectivity, linear convective structures. The algorithm is used to identify convective line objects in WoFS forecasts and Multi-Radar Multi-Sensor system (MRMS) gridded observations. WoFS QLCS objects are matched with MRMS observed objects to generate bulk verification statistics. Results suggest WoFS’s QLCS forecasts are skillful with the 3- and 6-h forecasts having similar probability of detection and false alarm ratio values near 0.59 and 0.34, respectively. The WoFS objects are larger, more intense, and less eccentric than those in MRMS. A novel centerline analysis is performed to evaluate orientation, length, and tortuosity (i.e., curvature) differences, and spatial displacements between observed and predicted convective lines. While no systematic propagation biases are found, WoFS typically has centerlines that are more tortuous and displaced to the northwest of MRMS centerlines, suggesting WoFS may be overforecasting the intensity of the QLCS’s rear-inflow jet and northern bookend vortex. Significance Statement Quasi-linear convective systems (QLCSs), also known as squall lines, can be very destructive to life and property as they produce multiple hazards such as hail, severe straight-line winds, flash flooding, and tornadoes that typically form quickly and may be difficult to observe on radar. These storms can occur year-round and have the propensity to develop overnight or into the early morning hours, potentially catching the public off-guard. An ensemble prediction system called the Warn-on-Forecast System (WoFS), created by the National Severe Storms Laboratory, has shown promise in accurately forecasting a variety of severe weather events. This research evaluates the quality of the WoFS’s QLCS forecasts. Results show WoFS can accurately predict these systems for forecast times out to 6 h.