Instantaneous Detection of High-risk Lightning with Pinpoint Accuracy

The Challenge

Lightning is the primary cause of large bushfires in Australia, with fires started by lightning accounting for more than 90% of the area burned during the Black Summer 2019-20 Bushfires. Out of potentially many thousands of lightning strikes from thunderstorms, only a small fraction of strikes are capable of starting a fire. Quickly and accurately detecting these lightning ignitions is essential for rapid fire containment and suppression, to prevent subsequent loss. However, currently there is no system in Australia that can reliably provide this critical information.

The Solution

This project will utilise novel lightning detectors capable of measuring the attributes of High Risk Lightning (HRL), including long continuing currents and charge transfer, that lead to heating. Fire agencies can then efficiently target this small proportion of HRL strikes. In addition, the smart detectors are able to map lightning in 3D, leading to superior detection efficiency and location accuracy, thereby facilitating both a quicker and more efficient inspection of high risk ground strikes.

This outcome is accomplished using a machine learning algorithm to analyse electric field waveforms from the lightning detector, to identify the presence of long-continuing current. This unique characterisation of lightning strikes is combined with information about weather and fuel attributes derived from satellite and airborne sensors, to enable a more thorough characterisation of the conditions under which lightning ignitions occur. An historical analysis of lightning-initiated bushfires, conducted in tandem with the HRL project, will facilitate rapid parameterisation of the risk factors for lightning ignition, without waiting many years to achieve results.

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