A low-cost identification method for sting jets in gridded data

A sting jet (SJ) is a descending airstream that can develop in connection with Shapiro-Keyser-type cyclones, bringing high winds to the surface. While winds in extratropical cyclones are often associated with the warm or cold jet (WJ and CJ, respectively), cold-frontal convection or cold-sector winds, SJs are less common but –if occurring– often cause the highest gusts and considerable damage.

In 2022, we introduced RAMEFI (RAndom-forest-based MEsoscale wind Feature Identification), the first objective and flexible identification tool for high-wind features within cyclones, using a probabilistic random forest based on eight surface parameters. However, due to their similar surface characteristics, it is challenging to distinguish the SJ from the CJ in surface parameters alone, such that the two features have been combined in RAMEFI so far. Nevertheless, the origin and potential for damage differ. While the SJ is a descending air stream originating within the cloud head, the CJ stays at low levels throughout its lifetime. With the descent, the SJ brings high momentum from mid-levels down to the top of the boundary layer or even to the surface. ... mehrThis commonly creates higher wind gusts, and thus a separate detection is desirable.

In this work, we introduce an extension of RAMEFI to identify potential SJs, focusing on output from high-resolution numerical weather prediction models. This way we want to create a suitable alternative to the data-intensive and computationally expensive computation of Lagrangian trajectories, the most established SJ identification method. Our approach is based on a simple detection of a coherent three-dimensional region of high winds. We further use relative humidity to ensure the proximity to the cloud head following previous literature and gust speeds to connect the region to actual surface impact.

Results using model simulations of 20 SJ and non-SJ storms and the deterministic forecast from the German weather service (ICON-EU) over a period of three winters show promise, with a high hit and low false alarm rate when compared to Lagrangian trajectories. This allows tests with other models and resolutions, computation of climatologies and operational use including an application to ensemble forecasts.