Weather radar networks are an excellent tool for quantitative precipitation estimation
(QPE), due to their high resolution in space and time, particularly in remote mountain areas such as
the Tropical Andes. Nevertheless, reduction of the temporal and spatial resolution might severely
reduce the quality of QPE. Thus, the main objective of this study was to analyze the impact of spatial
and temporal resolutions of radar data on the cumulative QPE. For this, data from the world’s highest
X-band weather radar (4450 m a.s.l.), located in the Andes of Ecuador (Paute River basin), and from
a rain gauge network were used. Dierent time resolutions (1, 5, 10, 15, 20, 30, and 60 min) and
spatial resolutions (0.5, 0.25, and 0.1 km) were evaluated. An optical ﬂow method was validated
for 11 rainfall events (with dierent features) and applied to enhance the temporal resolution of
radar data to 1-min intervals. The results show that 1-min temporal resolution images are able to
capture rain event features in detail. The radar–rain gauge correlation decreases considerably when
the time resolution increases (r from 0.69 to 0.31, time resolution from 1 to 60 min). No signiﬁcant
dierence was found in the rain total volume (3%) calculated with the three spatial resolution data.
A spatial resolution of 0.5 km on radar imagery is suitable to quantify rainfall in the AndesMountains.
This study improves knowledge on rainfall spatial distribution in the Ecuadorian Andes, and it will
be the basis for future hydrometeorological studies.