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Related Experiment Video

Updated: Dec 20, 2025

Method for Recording Broadband High Resolution Emission Spectra of Laboratory Lightning Arcs
07:51

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Removing solar artifacts from Geostationary Lightning Mapper data to document lightning extremes.

Michael Peterson1

  • 1ISR-2, Los Alamos National Laboratory, Los Alamos, New Mexico, United States.

Journal of Applied Remote Sensing
|May 23, 2020
PubMed
Summary
This summary is machine-generated.

We evaluated filters to remove solar artifacts from Geostationary Lightning Mapper (GLM) data, revealing extreme lightning events. Solar contamination is significant, impacting lightning rate calculations.

Keywords:
GOES-16Geostationary Lightning Mapperlightningsolar artifactsthunderstorms

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Area of Science:

  • Atmospheric Science
  • Geophysics
  • Remote Sensing

Background:

  • The Geostationary Lightning Mapper (GLM) provides crucial data on lightning activity.
  • Solar artifacts can contaminate GLM data, affecting lightning event and group rate calculations.
  • Understanding and mitigating solar contamination is essential for accurate lightning analysis.

Purpose of the Study:

  • To compare the performance of three distinct filters for identifying solar artifacts in GLM data.
  • To quantify the severity of solar contamination in GLM measurements.
  • To accurately compute the frequency of extreme lightning events in the Americas.

Main Methods:

  • Performance evaluation of three solar artifact identification filters with varying complexity.
  • Application of selected filters to document GLM solar contamination levels.
  • Analysis of GLM data to compute extreme lightning frequencies after artifact removal.

Main Results:

  • Solar artifacts occur frequently in GLM data, averaging approximately one every 8 minutes.
  • Solar contamination can account for up to 40% of recorded events during specific daytime periods.
  • A frequency-domain filter identified a 50-60 Hz anthropogenic carrier wave in some lightning and solar events.
  • Removal of solar artifacts revealed that extreme lightning flashes (500+ km, 10+ s) are rare, occurring a few times annually.
  • Exceptional lightning events are linked to predisposed storm conditions rather than random occurrences.

Conclusions:

  • The developed filters effectively identify and mitigate solar artifacts in GLM data.
  • Accurate characterization of extreme lightning requires diligent removal of solar contamination.
  • GLM data, when properly processed, can reveal insights into the dynamics of severe thunderstorms and extreme lightning.