TY - JOUR
T1 - Climatological analyses of LMA data with an open-source lightning flash-clustering algorithm
AU - Fuchs, Brody R.
AU - Bruning, Eric C.
AU - Rutledge, Steven A.
AU - Carey, Lawrence D.
AU - Krehbiel, Paul R.
AU - Rison, William
N1 - Publisher Copyright:
© 2016. American Geophysical Union. All Rights Reserved.
PY - 2016
Y1 - 2016
N2 - Approximately 63 million lightning flashes have been identified and analyzed from multiple years of Washington, D. C., northern Alabama, and northeast Colorado lightning mapping array (LMA) data using an open-source flash-clustering algorithm. LMA networks detect radiation produced by lightning breakdown processes, allowing for high-resolution mapping of lightning flashes. Similar to other existing clustering algorithms, the algorithm described herein groups lightning-produced radiation sources by space and time to estimate total flash counts and information about each detected flash. Various flash characteristics and their sensitivity to detection efficiency are investigated to elucidate biases in the algorithm, detail detection efficiencies of various LMAs, and guide future improvements. Furthermore, flash density values in each region are compared to corresponding satellite estimates. While total flash density values produced by the algorithm in Washington, D. C. (~20 flashes km-2 yr-1), and Alabama (~35 flashes km-2 yr-1) are within 50% of satellite estimates, LMA-based estimates are approximately a factor of 3 larger (50 flashes km-2 yr-1) than satellite estimates in northeast Colorado. Accordingly, estimates of the ratio of in-cloud to cloud-to-ground flashes near the LMA network (~20) are approximately a factor of 3 larger than satellite estimates in Colorado. These large differences between estimates may be related to the distinct environment conducive to intense convection, low-altitude flashes, and unique charge structures in northeast Colorado.
AB - Approximately 63 million lightning flashes have been identified and analyzed from multiple years of Washington, D. C., northern Alabama, and northeast Colorado lightning mapping array (LMA) data using an open-source flash-clustering algorithm. LMA networks detect radiation produced by lightning breakdown processes, allowing for high-resolution mapping of lightning flashes. Similar to other existing clustering algorithms, the algorithm described herein groups lightning-produced radiation sources by space and time to estimate total flash counts and information about each detected flash. Various flash characteristics and their sensitivity to detection efficiency are investigated to elucidate biases in the algorithm, detail detection efficiencies of various LMAs, and guide future improvements. Furthermore, flash density values in each region are compared to corresponding satellite estimates. While total flash density values produced by the algorithm in Washington, D. C. (~20 flashes km-2 yr-1), and Alabama (~35 flashes km-2 yr-1) are within 50% of satellite estimates, LMA-based estimates are approximately a factor of 3 larger (50 flashes km-2 yr-1) than satellite estimates in northeast Colorado. Accordingly, estimates of the ratio of in-cloud to cloud-to-ground flashes near the LMA network (~20) are approximately a factor of 3 larger than satellite estimates in Colorado. These large differences between estimates may be related to the distinct environment conducive to intense convection, low-altitude flashes, and unique charge structures in northeast Colorado.
UR - http://www.scopus.com/inward/record.url?scp=84979783259&partnerID=8YFLogxK
U2 - 10.1002/2015JD024663
DO - 10.1002/2015JD024663
M3 - Article
AN - SCOPUS:84979783259
SN - 0148-0227
VL - 121
SP - 8625
EP - 8648
JO - Journal of Geophysical Research
JF - Journal of Geophysical Research
IS - 14
ER -