Lightning Data Are More Useful Than Previously Thought

Lightning is a spectacular natural phenomenon. It is closely associated with the electrification and discharge of thunderstorms. (Image: via Pixabay)

Lightning is a spectacular natural phenomenon. It is closely associated with the electrification and discharge of thunderstorms. Different types of thunderstorms correspond to different lightning characteristics and charge structures. Their data are proving to be quite useful. But what are the characteristics of lightning in different types of thunderstorms?

To address this question, scientists attempted to depict the lightning activity and charge structure of a supercell over North China using a lightning network, S-band doppler radar, X-band dual-polarization radar, and ground observations. The study was published in Advances in Atmospheric Sciences.

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The lightning strokes light up the night sky with various shapes (Image by WANG Zhichao)
The lightning strokes light up the night sky with various shapes. (Image: via WANG Zhichao)

Lightning characteristics change during supercells

A team from the Institute of Atmospheric Physics (IAP) of the Chinese Academy of Sciences found that the supercell was accompanied by a severe hail fall, while the lightning frequency showed obviously different characteristics before and after the hail fall. The results showed that positive cloud-to-ground (+CG) hits accounted for a high percentage of CG lightning, especially during the hail fall stage.

The charge structure of the thunderstorm converted from an inversion type to a normal tripolar pattern. Based on the retrieval of hydrometeor particles from X-band radar data, the researchers found that graupel, hailstones, and ice crystals were the main charged particles in the convective region, while snow, ice crystals, and graupel were the main charged particles in the stratiform region. Dr. LIU Dongxia, the lead author of the study, said:

In addition, the team suggested that lightning data could improve short-term forecasting, with the study providing a reference for the use of such data in numerical weather models.

Provided by: Li Yuan, Chinese Academy of Sciences [Note: Materials may be edited for content and length.]

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