17 Aug 2022
17 Aug 2022

Effect of extreme El Niño events on the precipitations of Ecuador

Dirk Thielen1, Paolo Ramoni-Perazzi2,3, Mary L. Puche1, Marco Marquez1, José I. Quintero1, Wilmer Rojas1, Alberto Quintero4,5, Guillermo Bianchi6, Irma A. Soto-Werschitz7, and Marco Aurelio Arizapana-Almonacid8 Dirk Thielen et al.
  • 1Laboratory of Landscape Ecology and Climate, Venezuelan Institute for Scientific Research (IVIC), Caracas, 1020A, Venezuela
  • 2Progetto SECOSUD II della Cooperazione Italiana (Sapienza - Eduardo Mondlane), Maputo, Mozambique
  • 3Simulation and Modelling Center (CESIMO), University of Los Andes, Mérida, 5101, Venezuela
  • 4Institute of Biodiversity, Conservation and Natural Resources Management, National Experimental University of Los Llanos “Ezequiel Zamora” (UNELLEZ), Barinas, Venezuela
  • 5Center of Chemical Medicine, Venezuelan Institute for Scientific Research (IVIC), Caracas, 1020A, Venezuela
  • 6Laboratory of Insect Ecology. Department of Biology, University of Los Andes, Mérida, 5101, Venezuela
  • 7Departamento de Ecologia e Conservação, Instituto de Ciências Naturais, Universidade Federal de Lavras, Lavras, 37200-900, Minas Gerais, Brazil
  • 8Research Group on Remote Sensing and Mountain Ecology, School of Engineering and Environmental Management, National Autonomous University of Huanta, Ayacucho, Peru

Abstract. Extreme El Niño events stand out not only for their powerful impacts but also because they are significantly different from other El Niños. In Ecuador, such events are accountable for impacting negatively the economy, infrastructure, and population. Spatial-temporal dynamics of precipitation anomalies from various types of extreme El Niño events are analyzed and compared. Results show that for Eastern Pacific and Coastal El Niño types, most precipitation extremes occur in the first half of the second year of the event. Any significant difference between events becomes more evident at this stage. Spatially, for any event, 50 % of all extreme anomalies occurred at elevations <150 m. Difference between events was significant when considering the altitude when reaching 80 % of all extreme anomalies: EP-EN 97/98 at 500 m, COA-EN 17 at 800 m, and EN 82/83 at 1000 m. Nevertheless, in some sectors of the Andean Cordillera, the ENSO signal could be detected at 3200–3900 m. Distance to coastline and steepness of relief may play determining role. At lowlands, anomalies are most severe in regions where seasonality index is the highest. These results are useful at different decision-making levels for identifying most appropriate practices reducing vulnerability from a potential increase in extreme El Niño frequency and intensity.

Dirk Thielen et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-763', Anonymous Referee #1, 08 Nov 2022
    • AC1: 'Reply on RC1', Paolo Ramoni-Perazzi, 09 Dec 2022
  • RC2: 'Comment on egusphere-2022-763', Anonymous Referee #2, 15 Nov 2022
    • AC2: 'Reply on RC2', Paolo Ramoni-Perazzi, 09 Dec 2022

Dirk Thielen et al.

Dirk Thielen et al.


Total article views: 374 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
260 101 13 374 3 2
  • HTML: 260
  • PDF: 101
  • XML: 13
  • Total: 374
  • BibTeX: 3
  • EndNote: 2
Views and downloads (calculated since 17 Aug 2022)
Cumulative views and downloads (calculated since 17 Aug 2022)

Viewed (geographical distribution)

Total article views: 355 (including HTML, PDF, and XML) Thereof 355 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 02 Feb 2023
Short summary
Extreme El Niño events are significantly different from other El Niños, standing out for their powerful impacts, and are predicted to increase in frequency and intensity. In this regard, we provide valuable and highly strategic information on the similarities and differences between the effects on precipitation from types of extreme El Niño, highlighting spatially and quantitatively, those regions where most extreme precipitation anomalies are most likely to occur in extreme events.