NASA Short-term Prediction Research and Transition (SPoRT) Center graduate student, Sebastian Harkema (UAH) advised by Emily Berndt (ST11), led the development of a publication that objectively tracked cloud features to characterize NASA/NOAA Geostationary Operational Environmental Satellite-16 (GOES-16) Advanced Baseline Imager (ABI) cloud-top imagery leading up to lightning initiation during snowfall (i.e., electrified snowfall/thundersnow), see https://doi.org/10.1175/WAF-D-21-0003.1. As part of his PhD dissertation, this work expands on the results of Alana Cordak’s (UGA) 2019 summer internship hosted by the University of Alabama in Huntsville NASA SPoRT Center.
GOES-16 ABI imagery from ten ABI channels and four multispectral (e.g., red-green-blue – RGB) composites were analyzed to characterize changes in cloud-top phase and ice crystal size changes of tracked cloud features leading up to thundersnow initiation (TSI) identified by the Geostationary Lightning Mapper (GLM). From the ABI 10.3 μm channel, cloud features were associated with a median brightness temperature decrease of 12.2 K one hour prior to TSI indicating the development of the cloud structure prior to initiation. Furthermore, decreases in the reflectance component of the 3.9 μm channel indicated that the tracked cloud features were associated with ice crystal collisions and/or particle settling at cloud top. This provides evidence that non-inductive charging may be playing a role in wintertime cloud electrification.
This study is also one of the first to quantitatively examine the physical meaning of the coloration changes in RGB satellite imagery in environments conducive to lightning initiation. Cloud-tops in the Day Cloud Phase Distinction RGB consistently changed from a cyan to a yellow color prior to TSI. This demonstrates that the tracked cloud features glaciated by transitioning from a water cloud (i.e., cyan) to an ice cloud (i.e., yellow).
Thundersnow flashes were also examined at night using the Nighttime Microphysics RGB and the authors determined that the cloud-top phase and optical thickness information in the imagery should be examined for warm season lightning flashes. The Airmass and Differential Water Vapor RGBs indicated the development of mid-level clouds associated with dry upper-level air masses prior to TSI. Altogether, these RGB composites demonstrate the ability to potentially predict and/or add further understanding to physical processes that can contribute to thundersnow.
The authors also demonstrated similarities between cloud-top characteristics for lightning initiation in warm season convection and cold season convection but on shorter time scales. Therefore, the results within this study can be applied to warm season convection but on a shortened time scale. Understanding the underlying physical processes associated with these cloud-top characteristics inherently increases the fundamental understanding to cloud electrification and enhances our ability to forecast lightning initiation.