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contributor authorBitzer, Phillip M.
contributor authorBurchfield, Jeffrey C.
contributor authorChristian, Hugh J.
date accessioned2017-06-09T17:26:10Z
date available2017-06-09T17:26:10Z
date copyright2016/03/01
date issued2016
identifier issn0739-0572
identifier otherams-85225.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4228649
description abstractistorically, researchers explore the effectiveness of one lightning detection system with respect to another system; that is, the probability that system A detects a discharge given that system B detected the same discharge is estimated. Since no system detects all lightning, a more rigorous comparison should include the reverse process?that is, the probability that system B detects a discharge given that system A detected it. Further, the comparison should use the fundamental physical process detected by each system. Of particular interest is the comparison of ground-based radio frequency detectors with space-based optical detectors. Understanding these relationships is critical as the availability and use of lightning data, both ground based and space based, increases. As an example, this study uses Bayesian techniques to compare the effectiveness of the Earth Networks Total Lightning Network (ENTLN), a ground-based wideband network, and the Lightning Imaging Sensor (LIS), a space-based optical detector. This comparison is completed by matching LIS groups and ENTLN pulses, each of which correspond to stroke-type discharges. The comparison covers the period from 2009 to 2013 over several spatial domains. In 2013 LIS detected 52.0% of the discharges ENTLN reported within the LIS field of view globally and 53.2% near North America. Conversely, ENTLN detected 5.9% of the pulses detected by LIS globally and 26.9% near North America in 2013. Using these results in the Bayesian-based methodology outlined, the study finds that LIS detected 80.1% of discharges near North America in 2013, while ENTLN detected 40.1%.
publisherAmerican Meteorological Society
titleA Bayesian Approach to Assess the Performance of Lightning Detection Systems
typeJournal Paper
journal volume33
journal issue3
journal titleJournal of Atmospheric and Oceanic Technology
identifier doi10.1175/JTECH-D-15-0032.1
journal fristpage563
journal lastpage578
treeJournal of Atmospheric and Oceanic Technology:;2016:;volume( 033 ):;issue: 003
contenttypeFulltext


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