Characteristics of Thundersnow Associated with Heavy-Snowfall Observed with Next-Generation Satellite Sensors (117)
Sebastian S. Harkema, University of Alabama in Huntsville / NASA SPoRT, Huntsville, AL
Emily B. Berndt, NASA SPoRT / NASA MSFC
Christopher J. Schultz, NASA SPoRT / NASA MSFC
Geoffrey T. Stano, ENSCO Inc. / NASA SPoRT
Stephanie M. Wingo, NASA Postdoctoral Program
While severe convective weather might be the focus of next-generation satellite sensor data, studies regarding the use of these data for winter weather purposes are sparse. Winter weather is traditionally observed through the use of radar, verified through surface observations and predicted through the use of numerical weather prediction models. Next-generation satellite sensors, such as the Geostationary Lightning Mapper (GLM) on GOES-R series and passive microwave sensors onboard the Global Precipitation Measurement (GPM) constellation satellites provide new capabilities, as discussed below, to gain a better understanding of the processes within mid-latitude cyclones and can simplify the observing, verification, and prediction process. Particularly, forecasting heavy-banded snowfall can benefit from the use of these sensors and subsequent derived products, such as the NESDIS merged Snowfall Rate (merged-SFR), as the bands become a matter of nowcasting rather than predictive in nature. Observed overlap between observations from GLM and merged-SFR indicate the existence of thundersnow and offer valuable insight to the rapidly changing environment in and around areas of heavy snowfall. Alone these measurements provide little information about the vertical structure and microphysical processes with the banded snowfall however, these observations supplemented with GPM products provide unparalleled access to the processes occurring within heavy-banded snowfall. For example, GPM Core Observatory satellite provides the precipitation phase classification (i.e. liquid, mixed phase, ice) within the vertical structure of the banded snowfall. Pairing the GPM data with ground-based radar observations has the potential to increase situation awareness of heavy-banded snow through the ability to view precipitation characteristics throughout a greater depth of the atmosphere. Additionally, the occurrence of lightning in snowstorms indicates the presence of supercooled liquid water a fundamental parameter for ice crystal and aggregate growth, but one that is not measured very well by radar remote sensing. This presentation highlights the synergy of passive microwave, GLM, and ground-based radar observations of a few heavy-banded snowfall cases from the 2017-2018 winter. Results summarize where thundersnow is most likely to occur within banded-snowfall while demonstrating commonalities within the vertical structure and microphysics of the band where thundersnow occurred.