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Intra-event extreme rainfall characterization in the tropical Andes: a high-resolution weather radar approach

delete2026-07-23
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OA
AI
G
GU Gabriela Urgilés *
R
Rolando Célleri
D
Daniela Ballari
J
Jörg Bendix
J
Johanna Orellana‐Alvear
DOI:10.3389/frsen.2026.1793996delete
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Abstract

Abstract

En 中文
IntroductionHydrological hazards; such as floods and landslides are frequently driven by extreme rainfall events (ERE). Thus; understanding the spatio-temporal patterns and intra-event behavior of these events is important for identifying vulnerable regions; improving early warning systems; and enhancing water management.MethodsThis study aimed to analyze the spatio-temporal intra-event characteristics of ERE; using high-resolution (5min) weather radar data focusing on their internal structure and spatial distribution. The study was conducted in the headwaters of the Paute basin (2; 200–4; 400 m a.s.l.) in southern Ecuador. Based on three ERE classes; four intra-event rainfall features were analyzed: area; maximum rainfall; cohesion; and the locations of rainfall hotspots.ResultsThese features revealed different rainfall patterns for the three distinct rainfall classes. Class 1 is characterized by the highest rainfall peaks; concentrated between 12:00 and 19:00 (afternoon). Class 3 shows the lowest rainfall peaks. Class 2 shows the least cohesive rainfall core and a mixed behavior in features. Regarding the locations of rainfall hotspots; classes 1 and 2 show hotspots located at the catchment outlets and at the urban (City of Cuenca) areas of the sub-catchments (around 2; 500 m a.s.l); while those in class 3 are found at headwaters (above 3; 500 m a.s.l).DiscussionIdentifying these rainfall characteristics and hotspot location provides a better understanding of extreme rainfall behavior in the tropical Andes; which enhances knowledge of hydrological processes; and improves flood forecasting.
Keywords:
tropical Andes
hotspots
spatio-temporal characteristics
extreme rainfall
weather radar

Journal

F
Frontiers in Remote Sensing
IF:
3.7
Papers:
560
Citations:
993

Organization

L
laboratory for climatology and remote sensing
Scholars:
2
Papers: 1
Citations: 0
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