A method of estimating electric fields above electrified clouds from passive microwave observations

Michael Peterson, Chuntao Liu, Douglas Mach, Wiebke Deierling, Christina Kalb

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

A unique dataset of coincident high-altitude passive microwave and electric field observations taken by the NASA ER-2 aircraft is used to assess the feasibility of estimating electric fields above electrified clouds using ubiquitous global and multidecadal satellite products. Once applied to a global dataset, such a product would provide a unique approach for diagnosing and monitoring the current sources of the global electric circuit (GEC). In this study an algorithm has been developed that employs ice scattering signals from 37-and 85-GHz passive microwave observations to characterize the electric fields above clouds overflown by the ER-2 aircraft at nearly 20-km altitude. Electric field estimates produced by this passive microwave algorithm are then compared to electric field observations also taken by the aircraft to assess its potential future utility with satellite datasets. The algorithm is shown to estimate observed electric field strengths over intense convective clouds at least 71% (58%) of the time over land and 43% (40%) of the time over the ocean to within a factor of 2 from 85-GHz (37 GHz) passive microwave observations. Electric fields over weaker clouds can be estimated 58% (41%) of the time over land and 22% (8%) of the time over the ocean from 85-GHz (37 GHz) passive microwave observations. The accuracy of these estimates is limited by systematic errors in the observations along with other factors. Despite these sources of error, the algorithm can produce reasonable estimates of electric fields over carefully selected individual electrified clouds that differ from observations by less than 20 V m-1 for clouds that produce 200-400 V m-1 electric fields at 20 km.

Original languageEnglish
Pages (from-to)1429-1446
Number of pages18
JournalJournal of Atmospheric and Oceanic Technology
Volume32
Issue number8
DOIs
StatePublished - 2015

Keywords

  • Aircraft observations
  • Algorithms
  • Atmospheric electricity
  • Microwave observations

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