TY - JOUR
T1 - Time Evolution of Satellite-Based Optical Properties in Lightning Flashes, and its Impact on GLM Flash Detection
AU - Zhang, Daile
AU - Cummins, Kenneth L.
N1 - Funding Information:
We are very grateful for the helpful suggestions and comments provided by William Koshak, Phillip Bitzer, Hugh Christian, Ron Holle, Doug Mach, Scott Rudlosky, Mason Quick, and by Lockheed Martin staff Samantha Edgington and Clemens Tillier. The authors acknowledge NOAA and NASA's Global Hydrology Resource Center (GHRC) for providing GLM and LIS data, respectively. LMA data were graciously provided by Jennifer Wilson, Robert Brown (NASA) and Bill Rison. Co‐author (KLC) gratefully acknowledges access to the NLDN data provided by Vaisala. We also acknowledge the three anonymous reviewers for providing many useful comments. This study is funded by NASA Cooperative Agreement 80MSFC17M0022 and Air Force Contract FA252117P0046. The GLM dataset may be obtained from NOAA through the AWS s3 server at noaa‐goes16.s3.amazonaws.com/index.html#GLM‐L2‐LCFA/ or NOAA Comprehensive Large Array‐data Stewardship System (CLASS) at https://www.bou.class.noaa.gov/saa/products/welcome . The TRMM LIS dataset may be obtained from at https://ghrc.nsstc.nasa.gov/home/ . The NLDN dataset can be obtained by NOAA employees and contractors at https://www.ncei.noaa.gov/data/restricted/national‐lightning‐detection‐network/archive/ . All other users must obtain the NLDN data from the data owner, Vaisala Corporation, through their host web site: https://www.corelogic.com/products/lightning‐verification.aspx or by contacting brooke.pearson@vaisala.com . The LMA data used in this study is available through NASA's GHRC at https://dx.doi.org/10.5067/LMA/DATA101 .
Funding Information:
We are very grateful for the helpful suggestions and comments provided by William Koshak, Phillip Bitzer, Hugh Christian, Ron Holle, Doug Mach, Scott Rudlosky, Mason Quick, and by Lockheed Martin staff Samantha Edgington and Clemens Tillier. The authors acknowledge NOAA and NASA's Global Hydrology Resource Center (GHRC) for providing GLM and LIS data, respectively. LMA data were graciously provided by Jennifer Wilson, Robert Brown (NASA) and Bill Rison. Co-author (KLC) gratefully acknowledges access to the NLDN data provided by Vaisala. We also acknowledge the three anonymous reviewers for providing many useful comments. This study is funded by NASA Cooperative Agreement 80MSFC17M0022 and Air Force Contract FA252117P0046. The GLM dataset may be obtained from NOAA through the AWS s3 server at noaa-goes16.s3.amazonaws.com/index.html#GLM-L2-LCFA/ or NOAA Comprehensive Large Array-data Stewardship System (CLASS) at https://www.bou.class.noaa.gov/saa/products/welcome. The TRMM LIS dataset may be obtained from at https://ghrc.nsstc.nasa.gov/home/. The NLDN dataset can be obtained by NOAA employees and contractors at https://www.ncei.noaa.gov/data/restricted/national-lightning-detection-network/archive/. All other users must obtain the NLDN data from the data owner, Vaisala Corporation, through their host web site: https://www.corelogic.com/products/lightning-verification.aspx or by contacting brooke.pearson@vaisala.com. The LMA data used in this study is available through NASA's GHRC at https://dx.doi.org/10.5067/LMA/DATA101.
Publisher Copyright:
© 2020 The Authors. Journal of Geophysical Research: Atmospheres published by Wiley Periodicals, Inc. on behalf of American Geophysical Union
PY - 2020/3/27
Y1 - 2020/3/27
N2 - The GOES-16 Geostationary Lightning Mapper (GLM) detection efficiency (DE) is studied over a full year (2018/19) in central Florida using the Kennedy Space Center Lightning Mapping Array (KSC LMA). Mean daily flash DE was 73.8%, and detection was highest during nighttime hours. GLM reported 86.5% of the LMA flashes that had coincident cloud-to-ground return strokes reported by the U.S. National Lightning Detection Network. Results also reveal that flash size and duration are critical parameters influencing GLM detection, regardless of the storm type, with 20–40% detection for small and short-duration flashes and greater than 95% detection for very large and long-duration flashes. These findings can be explained by examining the time-evolution of cloud-top optical emissions observed by the Lightning Imaging Sensor (LIS). Statistical simulations based on long-term LIS group area observations indicate that about half of the above-threshold light sources are smaller than a LIS pixel (~ 4 × 4 km) and are smallest during and just after an initial breakdown in IC flashes. This work also demonstrates that for sources smaller than a GLM pixel, the cloud-top energy detection threshold for GLM is double that for LIS despite GLM's lower energy density threshold. Overall, these findings provide a framework for interpreting GLM performance under varying meteorological conditions, and help explain reports of low flash detection efficiency for storms associated with severe weather, as they typically exhibit high flash rates and resulting small and short-duration flashes.
AB - The GOES-16 Geostationary Lightning Mapper (GLM) detection efficiency (DE) is studied over a full year (2018/19) in central Florida using the Kennedy Space Center Lightning Mapping Array (KSC LMA). Mean daily flash DE was 73.8%, and detection was highest during nighttime hours. GLM reported 86.5% of the LMA flashes that had coincident cloud-to-ground return strokes reported by the U.S. National Lightning Detection Network. Results also reveal that flash size and duration are critical parameters influencing GLM detection, regardless of the storm type, with 20–40% detection for small and short-duration flashes and greater than 95% detection for very large and long-duration flashes. These findings can be explained by examining the time-evolution of cloud-top optical emissions observed by the Lightning Imaging Sensor (LIS). Statistical simulations based on long-term LIS group area observations indicate that about half of the above-threshold light sources are smaller than a LIS pixel (~ 4 × 4 km) and are smallest during and just after an initial breakdown in IC flashes. This work also demonstrates that for sources smaller than a GLM pixel, the cloud-top energy detection threshold for GLM is double that for LIS despite GLM's lower energy density threshold. Overall, these findings provide a framework for interpreting GLM performance under varying meteorological conditions, and help explain reports of low flash detection efficiency for storms associated with severe weather, as they typically exhibit high flash rates and resulting small and short-duration flashes.
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U2 - 10.1029/2019JD032024
DO - 10.1029/2019JD032024
M3 - Article
AN - SCOPUS:85082338974
SN - 2169-897X
VL - 125
JO - Journal of Geophysical Research Atmospheres
JF - Journal of Geophysical Research Atmospheres
IS - 6
M1 - e2019JD032024
ER -