Title
Unprecedented rainfall and moisture patterns during el nino 2016 in the eastern pacific and tropical andes: Northern peru and ecuador
Date Issued
01 December 2019
Access level
open access
Resource Type
journal article
Author(s)
Université de Toulouse
Publisher(s)
MDPI AG
Abstract
Using vertically integrated water vapor and its convergence, associated with large-scale and regional atmospheric circulation, we found two patterns of rainfall over the Eastern Pacific (EP) and the tropical Andes-with a focus in Ecuador and northern Peru-during three recent El Nino events: 1983, 1998, and 2016. Although these three events were the strongest El Ninos, the different sources of moisture contribute to different rainfall patterns between El Nino 1983-1998 and 2016. In the region, the spatial pattern of precipitation during El Nino 2016 presents an unprecedented out-of-phase atmospheric response consistent and verified with water vapor transport when compared with El Nino 1983-1998. During El Nino 2016, precipitation in the Andes was enhanced by moist air transported from the Amazon-with an opposite regime compared to the subsidence that dominated in 1983-1998. During the 1983-1998 El Nino, the source of moisture to feed the EP was enhanced by upper-level divergence (300 hPa), which supports moisture influx by middle levels in the EP. In El Nino 2016, this divergent upper-level flow migrated north, followed by the companion moisture. This study illustrates a link between upper-level large-scale circulation and low-level regional mechanisms on the moisture transport in determining different rainfall patterns during El Nino events.
Volume
10
Issue
12
Language
English
OCDE Knowledge area
Meteorología y ciencias atmosféricas Ciencias de la Tierra, Ciencias ambientales
Scopus EID
2-s2.0-85079739826
Source
Atmosphere
ISSN of the container
20734433
Source funding
Ministerio de Educación del Perú
Sponsor(s)
This research was funded by the Peruvian Ministry of Education under the MINEDU-PRONABEC scholarship. The authors would like to thank the Peruvian NationalWeather (SENAMHI) for providing the observed dataset.
Sources of information: Directorio de Producción Científica Scopus