Extreme Precipitation Nowcasting using Deep Generative Models

Conference Paper (2022)
Author(s)

H. Bi (Student TU Delft)

M.S. Kyryliuk (Student TU Delft)

Z. Wang (Student TU Delft)

C. Meo (TU Delft - Signal Processing Systems)

Y. Wang (TU Delft - Signal Processing Systems)

Ruben Imhoff (Deltares)

R Uijlenhoet (TU Delft - Water Resources)

Justin Dauwels (TU Delft - Signal Processing Systems)

Research Group
Signal Processing Systems
Copyright
© 2022 H. Bi, M.S. Kyryliuk, Z. Wang, C. Meo, Y. Wang, Ruben Imhoff, R. Uijlenhoet, J.H.G. Dauwels
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 H. Bi, M.S. Kyryliuk, Z. Wang, C. Meo, Y. Wang, Ruben Imhoff, R. Uijlenhoet, J.H.G. Dauwels
Research Group
Signal Processing Systems
Pages (from-to)
73
Reuse Rights

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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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