What do sequential patterns say about the "el Niño" phenomenon?

Oscar Díaz-Barriga, Miguel Nunez-Del-Prado, Hugo Alatrista-Salas

Research output: Contribution to journalArticle in a journalpeer-review


El Niño phenomenon starts with an increase in the temperature of the sea surface in the equatorial zone of the Pacific Ocean. This increase is characterized by the arrival of a superficial mass of warm waters into the sea, which generates anomalous climate changes on land. These unusual events can be floods, droughts, intense rains, which endanger the urban population and infrastructure of cities. To be able to launch early warnings of possible catastrophic events in populated areas, it is necessary to know how and within how long the change in sea temperature impacts on continental characteristics. The present work describes a computational process based on techniques of extraction and visualization of sequential patterns to capture temporal variations of the variables describing the El Niño phenomenon. Results show the existence of correlations between the sea surface temperature and the flow of the rivers of the coast. These correlations can be used as monitoring tools for early warning releases.
Original languageEnglish
Article number8932343
Pages (from-to)1335-1341
Number of pages7
JournalIEEE Latin America Transactions
Issue number8
StatePublished - 1 Aug 2019
Externally publishedYes

Bibliographical note

Funding Information: Posteriormente, Kalra et al. [5] utilizaron Support Vector Machines (SVM) con el objetivo de mejorar los pronósticos de caudales en las cuencas de los ríos Gunnison y San Juan. Para ello se usa la información de los índices oceánicos-atmosféricos promedio anuales que consisten en: la Oscilación Decadal del Pacífico (ODP), la Oscilación del Atlántico Norte (OAN), la Oscilación Multidecadal del Atlántico (OMA), El Niño - Oscilación del Sur (ENSO) y la temperatura de la superficie del mar (TSM) para la región de Hondo en el período de 1906-2006.


  • Data mining
  • El Niño phenomenon
  • Pattern visualization
  • Sequential pattern mining


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