WGAN-GP-Based Conditional GAN (cGAN) With Extreme Critic for Precipitation Downscaling in a Key Agricultural Region of the Northeastern U.S.

WGAN-GP-Based Conditional GAN (cGAN) With Extreme Critic for Precipitation Downscaling in a Key Agricultural Region of the Northeastern U.S.

This study develops a conditional Generative Adversarial Network with a multi-head Critic (cGAN_ext), under a Wasserstein GAN with gradient penalty (WGAN-GP) framework, to downscale coarse-resolution meteorological data into high-resolution precipitation fields. The model’s U-Net Generato...

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Bibliographic Details
Main Authors: Jangho Lee, Sun Young Park
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Precipitation
radar
multi-radar multi-sensor
generative adversarial network (GAN)
conditional GAN
Wasserstein GAN
Online Access:https://ieeexplore.ieee.org/document/10918718/
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https://ieeexplore.ieee.org/document/10918718/

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