Linking Lightning Activity to Upper-Cloud Radar Signatures Using EarthCARE CPR and MTG-LI Satellite Observations

Lightning initiation occurs in turbulent mixed-phase regions of cloud where efficient charge separation takes place. However, direct observational evidence linking cloud dynamics, microphysics, and electrical activity remains limited. To address this observational gap, we examine storm overpasses in which the Meteosat Third-Generation Lightning Imager (MTG-LI) detected lightning activity while the EarthCARE satellite simultaneously sampled the same storms using its 94 GHz Doppler Cloud Profiling Radar (CPR). Due to significant radar signal attenuation and multiple scattering in the intense convective cores, our analysis focuses on upper-cloud regions, where CPR reflectivity and Doppler velocity measurements remain more robust and interpretable.

LI measurements are first matched spatio-temporally to EarthCARE CPR tracks to allow direct intercomparison, and then clustered into storm objects using a three-dimensional (latitude–longitude–time) DBSCAN clustering algorithm. For the matched storms, we analyze several key variables: (i) vertical profiles of radar reflectivity, (ii) estimates of ice water content, (iii) Doppler velocity profiles including metrics such as standard deviation to quantify along- and across-track velocity variability, and (iv) concurrent lightning activity metrics derived from MTG-LI detections.

In the presented work, we show the comparison of these variables to reveal potential links between radar-derived cloud microphysical properties, Doppler velocity signatures, and observed lightning activity. However, interpreting Doppler velocities in deep convective clouds poses substantial challenges due to EarthCARE CPR’s narrow Nyquist velocity range, which frequently leads to aliasing of measured signals. Nevertheless, observed variability in Doppler velocities can serve as a strong indicator of convective updrafts and downdrafts. The combined analysis of CPR and MTG-LI observations can therefore bring advancements in several pathways: improve the interpretation of EarthCARE Doppler velocity data, provide deeper insights into storm electrification processes, and potentially support more accurate parameterizations of electrified convection.