Journal of Geophysical Research: Atmospheres

Geostationary infrared methods for detecting lightning-producing cumulonimbus clouds

Authors

  • Retha Matthee,

    Corresponding author
    1. National Space Science and Technology Center, Atmospheric Science Department, University of Alabama in Huntsville, Huntsville, Alabama, USA
    • Corresponding author: R. Matthee, National Space Science and Technology Center, Atmospheric Science Department, University of Alabama in Huntsville 320 Sparkman Dr., Huntsville, AL 35805-1912, USA. (matthee@nsstc.uah.edu)

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  • John R. Mecikalski

    1. National Space Science and Technology Center, Atmospheric Science Department, University of Alabama in Huntsville, Huntsville, Alabama, USA
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Abstract

[1] This study documents the behavior of cloud top infrared (IR) fields known to describe physical processes associated with growing convective clouds, for 30 nonlightning and 33 cloud-to-ground (CG) lightning-producing convective storms. The goal is to define “critical” threshold values for up to 10 IR fields that delineate lightning from nonlightning convective storms. Meteosat Second Generation and United Kingdom Meteorological Office very low frequency arrival time difference satellite and lightning data, respectively, were used in this study. These were collected during the National Aeronautics and Space Administration (NASA) African Monsoon Multidisciplinary Analyses (NAMMA) field campaign in August–September 2006 in Equatorial Africa. The main conclusions show that eight of 10 IR fields that describe updraft strength, cloud depth, and glaciation (or ice at cloud top) are significantly different between the nonlightning and lightning-producing convective clouds. The lack of notch overlap in “box and whiskers” plots confirms a 95% confidence that the two data sets are different. Nonlightning-producing clouds are far less vertically developed and possess >50% weaker updrafts (as estimated from satellite trends), as well as little to no evidence of ice or glaciation at cloud top. Results from this study therefore can be used to nowcast and identify with high confidence convective clouds that are producing or are going to produce CG lightning using Meteosat data, assuming appropriate tracking of growing cumulus clouds is performed.

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