TY - JOUR
T1 - Distinctive Signals in 1-min Observations of Overshooting Tops and Lightning Activity in a Severe Supercell Thunderstorm
AU - Borque, Paloma
AU - Vidal, Luciano
AU - Rugna, Martín
AU - Lang, Timothy J.
AU - Nicora, María Gabriela
AU - Nesbitt, Stephen W.
N1 - Funding Information:
This research was supported by the National Science Foundation through Grant AGS-1661719. Additional funding for this study was provided by the U.S. Department of Energy Office of Science Biological and Environmental Research as part of the Atmospheric System Research Program. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RLO1830. RELAMPAGO was funded in Argentina by the SMN and the Province of Córdoba, and in the USA by the NSF, NASA, and NOAA. CACTI was a U.S. DOE-ARM funded project. Funding for the RELAMPAGO LMA came from the NOAA GOES-R Program, with additional support from the NASA Lightning Imaging Sensor (LIS) project. The authors thank three anonymous reviewers for their helpful comments and suggestions that helped improve the manuscript, Steven Goodman for his support in providing MDS over the RELAMPAGO-CACTI area, and Earth Networks for providing the lightning data (https://www.earthnetworks.com/why-us/networks/lightning/), which can be obtained by contacting Steve Prinzivalli (sprinzivalli@earthnetworks.com).
Funding Information:
This research was supported by the National Science Foundation through Grant AGS‐1661719. Additional funding for this study was provided by the U.S. Department of Energy Office of Science Biological and Environmental Research as part of the Atmospheric System Research Program. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy under Contract DE‐AC05‐76RLO1830. RELAMPAGO was funded in Argentina by the SMN and the Province of Córdoba, and in the USA by the NSF, NASA, and NOAA. CACTI was a U.S. DOE‐ARM funded project. Funding for the RELAMPAGO LMA came from the NOAA GOES‐R Program, with additional support from the NASA Lightning Imaging Sensor (LIS) project. The authors thank three anonymous reviewers for their helpful comments and suggestions that helped improve the manuscript, Steven Goodman for his support in providing MDS over the RELAMPAGO‐CACTI area, and Earth Networks for providing the lightning data ( https://www.earthnetworks.com/why-us/networks/lightning/ ), which can be obtained by contacting Steve Prinzivalli (sprinzivalli@earthnetworks.com).
Publisher Copyright:
©2020. American Geophysical Union. All Rights Reserved.
PY - 2020/10/27
Y1 - 2020/10/27
N2 - This work examines a severe weather event that took place over central Argentina on 11 December 2018. The evolution of the storm from its initiation, rapid organization into a supercell, and eventual decay was analyzed with high-temporal resolution observations. This work provides insight into the spatio-temporal co-evolution of storm kinematics (updraft area and lifespan), cloud-top cooling rates, and lightning production that led to severe weather. The analyzed storm presented two convective periods with associated severe weather. An overall decrease in cloud-top local minima IR brightness temperature (MinIR) and lightning jump (LJ) preceded both periods. LJs provided the highest lead time to the occurrence of severe weather, with the ground-based lightning networks providing the maximum warning time of around 30 min. Lightning flash counts from the Geostationary Lightning Mapper (GLM) were underestimated when compared to detections from ground-based lightning networks. Among the possible reasons for GLM's lower detection efficiency were an optically dense medium located above lightning sources and the occurrence of flashes smaller than GLM's footprint. The minimum MinIR provided the shorter warning time to severe weather occurrence. However, the secondary minima in MinIR that preceded the absolute minima improved this warning time by more than 10 min. Trends in MinIR for time scales shorter than 6 min revealed shorter cycles of fast cooling and warming, which provided information about the lifecycle of updrafts within the storm. The advantages of using observations with high-temporal resolution to analyze the evolution and intensity of convective storms are discussed.
AB - This work examines a severe weather event that took place over central Argentina on 11 December 2018. The evolution of the storm from its initiation, rapid organization into a supercell, and eventual decay was analyzed with high-temporal resolution observations. This work provides insight into the spatio-temporal co-evolution of storm kinematics (updraft area and lifespan), cloud-top cooling rates, and lightning production that led to severe weather. The analyzed storm presented two convective periods with associated severe weather. An overall decrease in cloud-top local minima IR brightness temperature (MinIR) and lightning jump (LJ) preceded both periods. LJs provided the highest lead time to the occurrence of severe weather, with the ground-based lightning networks providing the maximum warning time of around 30 min. Lightning flash counts from the Geostationary Lightning Mapper (GLM) were underestimated when compared to detections from ground-based lightning networks. Among the possible reasons for GLM's lower detection efficiency were an optically dense medium located above lightning sources and the occurrence of flashes smaller than GLM's footprint. The minimum MinIR provided the shorter warning time to severe weather occurrence. However, the secondary minima in MinIR that preceded the absolute minima improved this warning time by more than 10 min. Trends in MinIR for time scales shorter than 6 min revealed shorter cycles of fast cooling and warming, which provided information about the lifecycle of updrafts within the storm. The advantages of using observations with high-temporal resolution to analyze the evolution and intensity of convective storms are discussed.
KW - aerosol transport
KW - atmospheric modeling
KW - large eddy simulation (LES)
KW - random walk
KW - sea spray generation
KW - upscaled modeling
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UR - http://www.scopus.com/inward/citedby.url?scp=85094165201&partnerID=8YFLogxK
U2 - 10.1029/2020JD032856
DO - 10.1029/2020JD032856
M3 - Article
AN - SCOPUS:85094165201
VL - 125
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
SN - 2169-897X
IS - 20
M1 - e2020JD032856
ER -