Extreme Precipitation Nowcasting using Deep Generative Models

Conference paper (2022)

Authors

H. Bi Student
M.S. Kyryliuk Student
Z. Wang Student
C. Meo Signal Processing Systems - EEMCS
Y. Wang Signal Processing Systems - EEMCS
Ruben Imhoff Deltares
R. Uijlenhoet Water Resources - CEG
J.H.G. Dauwels Signal Processing Systems - EEMCS
Research Group
Signal Processing Systems (EEMCS) (TU Delft)
Copyright: © 2022 H. Bi, M.S. Kyryliuk, Z. Wang, C. Meo, Y. Wang, Ruben Imhoff, R. Uijlenhoet, J.H.G. Dauwels
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Signal Processing Systems

Abstract

Extreme precipitation usually leads to substantial impacts. Floods in the Netherlands, Belgium and Germany in the summer of 2021 have caused loss of lives, destruction of infrastructures, and long-term effect on economics. To avoid such disasters, it is important to develop a reliable and accurate method to predict heavy rain.

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