The Coastal El Nino Event of 2017 in Ecuador and Peru: A Weather Radar Analysis

The coastal regions of South Ecuador and Peru belong to the areas experiencing the strongest impact of the El Nino Southern Oscillation phenomenon. However, the impact and dynamic development of weather patterns during those events are not well understood, due to the sparse observational networks. In spite of neutral to cold conditions after the decaying 2015/16 El Nino in the central Pacific, the coastal region was hit by torrential rainfall in 2017 causing floods, erosion and landslides with many fatalities and significant damages to infrastructure. A new network of X-band weather radar systems in South Ecuador and North Peru allowed, for the first time, the spatio-temporally high-resolution monitoring of rainfall dynamics, also covering the 2017 event. Here, we compare this episode to the period 2014-2018 to point out the specific atmospheric process dynamics of this event. We found that isolated warming of the Nino 1 and 2 region sea surface temperature was the initial driver of the strong rainfall, but local weather patterns were modified by topography interacting with the synoptic situation. The high resolution radar data, for the first time, allowed to monitor previously unknown local spots of heavy rainfall during ENSO-related extreme events, associated with dynamic flow convergence initiated by low-level thermal breezes. Altogether, the coastal El Nino of 2017, at the same time, caused positive rainfall anomalies in the coastal plain and on the eastern slopes of the Andes, the latter normally associated only with La Nina events. Thus, the 2017 event must be attributed to the La Nina Modoki type.

Automated summary

The coastal regions of South Ecuador and Peru experienced the strongest impact of the El Nino Southern Oscillation phenomenon. However, due to the lack of observation networks, the understanding of the impact and dynamic development of weather patterns during these events is limited. In this study, the high-resolution radar data allowed for the first time the monitoring of previously unknown local spots of heavy rainfall during ENSO-related extreme events.