Algorithm for Improved QPE over Complex Terrain Using Cloud-to-Ground Lightning Occurrences

Carlos Minjarez-Sosa, Julio Waissman, Christopher Castro, David Adams

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Lightning and deep convective precipitation have long been studied as closely linked variables, the former being viewed as a proxy, or estimator, of the latter. However, to date, no single methodology or algorithm exists for estimating lightning-derived precipitation in a gridded form. This paper, the third in a series, details the specific algorithm where convective rainfall was estimated with cloud-to-ground lightning occurrences from the U.S. National Lightning Detection Network (NLDN), for the North American Monsoon region. Specifically, the authors present the methodology employed in their previous studies to get this estimation, noise test, spatial and temporal neighbors and the algorithm of the Kalman filter for dynamically derived precipitation from lightning.

Original languageEnglish
Article number85
Pages (from-to)85
Issue number2
StatePublished - 19 Feb 2019

Bibliographical note

Publisher Copyright:
© 2019 by the authors.


  • Algorithm
  • Complex terrain
  • Kalman filter
  • Lightning
  • Quantitative Precipitation Estimation


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