Speaker
Angelica Caseri
Description
Around the world, such as in southeastern Brazil, extreme rainfall events cause
several socioeconomic damages. Due to some of its characteristics, as the high
space-time variability, these events are difficult to predict. Methods based on
deep learning can be one of the solutions for this type of issue. These methods
have a high capacity to learning through historical events. This research aims to
develop a model able to generate rainfall nowcasting based on neural networks
using radar data. For study case, fifteen rainfall events were selected in the
region of Campinas (state of São Paulo-Brazil). The results show that the
approach can be a possible solution for nowcasting of extreme rainfall events.
Primary author
Angelica Caseri
Co-author
Leonardo B. L. Santos
(Cemaden)
