Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. S...

Full description

Saved in:
Bibliographic Details
Published inJournal of operational meteorology Vol. 4; no. 7; p. 92
Main Authors Schultz, Elise V, Schultz, Christopher J, Carey, Lawrence D, Cecil, Daniel J, Bateman, Monte
Format Journal Article
LanguageEnglish
Published United States 28.06.2016
Online AccessGet full text
ISSN2325-6184
2325-6184
DOI10.15191/nwajom.2016.0407

Cover

Abstract This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.
AbstractList This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.
Author Bateman, Monte
Schultz, Elise V
Carey, Lawrence D
Cecil, Daniel J
Schultz, Christopher J
Author_xml – sequence: 1
  givenname: Elise V
  surname: Schultz
  fullname: Schultz, Elise V
  organization: University of Alabama in Huntsville, Huntsville, AL
– sequence: 2
  givenname: Christopher J
  surname: Schultz
  fullname: Schultz, Christopher J
  organization: NASA/MSFC, Huntsville, AL
– sequence: 3
  givenname: Lawrence D
  surname: Carey
  fullname: Carey, Lawrence D
  organization: University of Alabama in Huntsville, Huntsville, AL
– sequence: 4
  givenname: Daniel J
  surname: Cecil
  fullname: Cecil, Daniel J
  organization: NASA/MSFC, Huntsville, AL
– sequence: 5
  givenname: Monte
  surname: Bateman
  fullname: Bateman, Monte
  organization: USRA, Huntsville, AL
BackLink https://www.ncbi.nlm.nih.gov/pubmed/29303164$$D View this record in MEDLINE/PubMed
BookMark eNpNkE1PwkAQhjcGI4j8AC9mj3oo7ke3tEcCWDUlGIFzs93dQrHdbdqtyL-XihpOM3kzz2TmuQYdbbQC4BajIWY4wI96z3emGBKEvSFy0egC9AglzPGw73bO-i4Y1PUOIYSJ73nIvQJdElBEsef2wOe4sabgVkm4tKYq4Kri4iPTG8i1hHarYJRttla3yWtTlHCcb0yV2W0B13UbhovZ0nmHoTK15TYzmleHM2bOy1JV8D6M5g_wrTJfBzjllt-Ay5TntRr81j5YP81Wk2cnWoQvk3HkCMqQdbBgCgdJIFxMR3gUSBmkLk2lZKmPfIIowyTl7Qjjx5cYFkkikBQo9ZhPA0H7gJz2Nrrkhz3P87issuJ4Y4xR_OMxPnmMW49x6_EI3Z2gskkKJf-JP2v0G6HmcYI
CitedBy_id crossref_primary_10_1016_j_atmosres_2022_106164
crossref_primary_10_1016_j_atmosres_2023_106673
crossref_primary_10_1016_j_landusepol_2021_105687
crossref_primary_10_1007_s00703_023_00997_8
crossref_primary_10_1016_j_atmosres_2018_09_018
crossref_primary_10_3390_atmos13020171
crossref_primary_10_1175_WAF_D_17_0025_1
crossref_primary_10_1175_JTECH_D_20_0160_1
crossref_primary_10_1029_2018JD029320
crossref_primary_10_3390_rs12061031
crossref_primary_10_1007_s00445_019_1350_5
crossref_primary_10_1029_2019JD031900
crossref_primary_10_1002_2016JD025142
crossref_primary_10_1002_qj_3897
ContentType Journal Article
DBID NPM
ADTOC
UNPAY
DOI 10.15191/nwajom.2016.0407
DatabaseName PubMed
Unpaywall for CDI: Periodical Content
Unpaywall
DatabaseTitle PubMed
DatabaseTitleList PubMed
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: UNPAY
  name: Unpaywall
  url: https://proxy.k.utb.cz/login?url=https://unpaywall.org/
  sourceTypes: Open Access Repository
DeliveryMethod fulltext_linktorsrc
Discipline Meteorology & Climatology
EISSN 2325-6184
ExternalDocumentID 10.15191/nwajom.2016.0407
29303164
Genre Journal Article
GrantInformation_xml – fundername: Intramural NASA
  grantid: N-999999
GroupedDBID 6KP
ALMA_UNASSIGNED_HOLDINGS
ARCSS
FRP
H13
NPM
ADTOC
UNPAY
ID FETCH-LOGICAL-c350t-1c5e19b9c4137179dd9f43fdd5f808203512fae19b5a93051cbbc0dc0f65839c3
IEDL.DBID UNPAY
ISSN 2325-6184
IngestDate Wed Oct 29 12:20:56 EDT 2025
Sat May 31 02:06:49 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 7
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c350t-1c5e19b9c4137179dd9f43fdd5f808203512fae19b5a93051cbbc0dc0f65839c3
OpenAccessLink https://proxy.k.utb.cz/login?url=https://doi.org/10.15191/nwajom.2016.0407
PMID 29303164
ParticipantIDs unpaywall_primary_10_15191_nwajom_2016_0407
pubmed_primary_29303164
PublicationCentury 2000
PublicationDate 2016-06-28
PublicationDateYYYYMMDD 2016-06-28
PublicationDate_xml – month: 06
  year: 2016
  text: 2016-06-28
  day: 28
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
PublicationTitle Journal of operational meteorology
PublicationTitleAlternate J Operat Meteorol
PublicationYear 2016
SSID ssj0001286604
Score 2.0818264
Snippet This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning...
SourceID unpaywall
pubmed
SourceType Open Access Repository
Index Database
StartPage 92
Title Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data
URI https://www.ncbi.nlm.nih.gov/pubmed/29303164
https://doi.org/10.15191/nwajom.2016.0407
UnpaywallVersion publishedVersion
Volume 4
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ3db9MwEMAt1j5sL3wMBuVjugeEQCilqeM0eaymtRNquopRaXuKLnY8NrKkylKm8ddzl0RVhXgYb7FiK_HZ8v3Odz4L8T5RI-2RZnUI9rXj2UHgBGRHOKFHM0ZhMjSSDzhHc_9k6X09V-dtsmg-C7Ptvye4cL_kd3hd8JFx1-9T89GO6PqKsLsjusv5YnxRXx43pG-RqdJ6Lf_ZbkvD7K7zFd7fYZZtqZLJkyYI67bOQMgRJD_76yrp699_5Wd80F8-FY9boIRxMwOeiUdpvi96EbFwUdZb5vABjrIrAtO69Fz8Gq-rgoqpAY6MvIGqRM0b5oC5AeJByNhg5_0SuKbBBswui_Kq-nEDHCR_CdPT4zPnG0zT4rbx42N5D7NNmwhXq7SEj9NZ9AnqPgKHob4Qy8nx96MTp719wdFSDSrH1Sp1wyTUpObI5guNCa0nrTHKBswNklDBIldRGNKq4eok0QOjB5agRoZaHohOXuTpKwGeRA-tdUcjqQmAVILB0OrAdVFLROP3xMtmbOJVk2IjJgih1cb3euLzZrA2L9luYanHjdRjlnrMUn_9X7XfiD1-5rivYfBWdKpynb4jwqiSQ7EzX0SH7Qz7A1BZzwY
linkProvider Unpaywall
linkToUnpaywall http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ3dT9swEMAtVh62lzHYYGUM3QNCQyilqeM0eawQFCEKaFCJPUUXO-YrJFVIQeyv5y6JqmraA7zFiq3EZ8v3O9_5LMRWrPraI83qEOxrx7PdwAnIjnBCj2aMwrhnJB9wHp36R2Pv-EpdNcmi-SzMvP-e4MLdy57xLucj467foeb9D2LRV4TdLbE4Pj0f_Kkuj-vRt8hUabyW_203p2E-TrMJvjxjms6pksOlOgjrscpAyBEk951pGXf033_yM77pL7-Izw1QwqCeActiIclWRHtELJwX1ZY5bMN-ektgWpW-iqfBtMypmBjgyMgHKAvUvGEOmBkgHoSUDXbeL4E7GmzA9DovbsubB-Ag-WsYnh1cOL9hmOSPtR8fixc4mbUZ4WSSFPBreDLagaqPwGGo38T48OBy_8hpbl9wtFTd0nG1StwwDjWpObL5QmNC60lrjLIBc4MkVLDIVRSGtGq4Oo511-iuJaiRoZaropXlWfJdgCfRQ2vdfl9qAiAVY9CzOnBd1BLR-G2xVo9NNKlTbEQEIbTa-F5b7M4Ga_aS7RaWelRLPWKpRyz19XfV_iE-8TPHffWCDdEqi2nykwijjDebufUKe1vN-g
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Automated+storm+tracking+and+the+lightning+jump+algorithm+using+GOES-R+Geostationary+Lightning+Mapper+%28GLM%29+proxy+data&rft.jtitle=Journal+of+operational+meteorology&rft.date=2016-06-28&rft.issn=2325-6184&rft.eissn=2325-6184&rft_id=info:doi/10.15191%2Fnwajom.2016.0407&rft.externalDocID=10.15191%2Fnwajom.2016.0407
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2325-6184&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2325-6184&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2325-6184&client=summon