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Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/40877
Title: Influence of ENSO on droughts and vegetation in a high mountain equatorial climate basin
Authors: Tonon Ordoñez, Maria Dolores
Pacheco Nivelo, Jheimy
Solera, Abel
Aviles Añazco, Alex Manuel
metadata.dc.ucuenca.correspondencia: Aviles Añazco, Alex Manuel, alex.aviles@ucuenca.edu.ec
Keywords: Equatorial andean basin
ENSO
NDVI
SPEI
Wavelet coherence
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 1. Ciencias Naturales y Exactas
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 1.5.9 Meteorología y Ciencias Atmosféricas
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 1.5 Ciencias de la Tierra y el Ambiente
metadata.dc.ucuenca.areaconocimientounescoamplio: 05 - Ciencias Físicas, Ciencias Naturales, Matemáticas y Estadísticas
metadata.dc.ucuenca.areaconocimientounescodetallado: 0521 - Ciencias Ambientales
metadata.dc.ucuenca.areaconocimientounescoespecifico: 052 - Medio Ambiente
Issue Date: 2022
metadata.dc.ucuenca.volumen: Volumen 13, número 12
metadata.dc.source: Atmosphere
metadata.dc.identifier.doi: 10.3390/atmos13122123
metadata.dc.type: ARTÍCULO
Abstract: 
Several studies have assessed droughts and vegetation considering climatic factors, particularly El Niño-Southern Oscillation (ENSO) at different latitudes. However, there are knowledge gaps in the tropical Andes, a region with high spatiotemporal climatic variability. This research analyzed the relationships between droughts, vegetation, and ENSO from 2001–2015. Meteorological drought was analyzed using the Standardized Precipitation Evapotranspiration Index (SPEI) for 1, 3 and 6 months. Normalized Difference Vegetation Index (NDVI) was used to evaluate vegetation, and ENSO indexes were used as climate drivers. The Wavelet coherence method was used to establish time-frequency relationships. This approach was applied in the Machángara river sub-basin in the Southern Ecuadorian Andes. The results showed significant negative correlations during 2009–2013 between the SPEI and NDVI, with the SPEI6 lagging by nine months and a return period of 1.5 years. ENSO–SPEI presented the highest negative correlations during 2009–2014 and a return period of three years, with ENSO leading the relationship for around fourteen months. ENSO-NDVI showed the highest positive correlations during 2004–2008 and a return period of one year, with the ENSO indexes continually delayed by approximately one month. These results could be a benchmark for developing advanced studies for climate hazards.
URI: http://dspace.ucuenca.edu.ec/handle/123456789/40877
https://www.scopus.com/record/display.uri?eid=2-s2.0-85144818006&doi=10.3390%2fatmos13122123&origin=inward&txGid=014744720f2ee7f53600ae3e96dca3c0
metadata.dc.ucuenca.urifuente: https://www.mdpi.com/
ISSN: 2073-4433
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