This study examined 34 lightning flashes within four separate thundersnow events derived from lightning mapping arrays (LMAs) in northern Alabama, central Oklahoma, and Washington DC. The goals were to characterize the in‐cloud component of each lightning flash, as well as the correspondence between the LMA observations and lightning data taken from national lightning networks like the National Lightning Detection Network (NLDN). Individual flashes were examined in detail to highlight several observations within the data set. The study results demonstrated that the structures of these flashes were primarily normal polarity. The mean area encompassed by this set of flashes is 375 km2, with a maximum flash extent of 2,300 km2, a minimum of 3 km2, and a median of 128 km2. An average of 2.29 NLDN flashes were recorded per LMA‐derived lightning flash. A maximum of 11 NLDN flashes were recorded in association with a single LMA‐derived flash on 10 January 2011. Additionally, seven of the 34 flashes in the study contain zero NLDN‐identified flashes. Eleven of the 34 flashes initiated from tall human‐made objects (e.g., communication towers). In at least six lightning flashes, the NLDN detected a return stroke from the cloud back to the tower and not the initial upward leader. This study also discusses lightning's interaction with the human‐built environment and provides an example of lightning within heavy snowfall observed by Geostationary Operational Environmental Satellite‐16's Geostationary Lightning Mapper.
This study examines characteristics of lightning in snowfall events (i.e., thundersnow, TSSN) from the perspective of the Geostationary Lightning Mapper (GLM) and the National Environmental Satellite Data and Information Service (NESDIS) merged Snowfall Rate (mSFR) product. A thundersnow detection algorithm (TDA) was derived from the GLM and mSFR that resulted in a probability of detection (POD) of 66.7% when compared to the aviation routine weather report (METAR) reports of TSSN. However, using the TDA an additional 2175 lightning flashes within detected snowfall were identified that were not observed by the METAR reports, indicating that TSSN has been under reported in previous literature. TSSN flashes observed by GLM have mean flash areas, durations, and total optical energy outputs of 754 km2, 402 ms, and 1342 fJ, which are between the 50th and 99th percentile values for all flashes within the GLM field of view. A comparison with data from the National Lightning Detection Network (NLDN) indicated that the NLDN had at least one cloud or ground flash detection in 1709 of the 2214 flashes observed by GLM in snowfall. An average of 5.85 NLDN flashes was assigned to a single GLM flash when the NLDN flash data were constrained by the GLM flash duration and spatial footprint. Statistically significant (p < 0.01) differences in flash area and flash energy were found between flashes that were observed by the NLDN and those that were not. Additionally, when GLM was combined with the NLDN, at least 11.1% of flashes involved a tall human-made object like an antenna or wind turbine.
Lightning is commonly used to indicate the presence of heavy snowfall potential in winter cyclones because there is a common microphysical environment that enhances both dendritic growth of ice crystals (IC) and cloud electrification (e.g.
Detection of hazardous dust events in nighttime satellite imagery is limited as dust is difficult to distinguish from the cooling ground. A physically-based approach to developing a machine learning model with satellite imagery inputs correctly labels 85% of dust pixels. Application of the machine learning model to a dust event enhances identification of dust, distinguishing the boundaries of the plume.
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