SRNDiff: Short-term Rainfall Nowcasting with Condition Diffusion Model

arXiv:2402.13737v1 Announce Type: new
Abstract: Diffusion models are widely used in image generation because they can generate high-quality and realistic samples. This is in contrast to generative adversarial networks (GANs) and variational autoencoders (VAEs), which have some limitations in terms of image quality.We introduce the diffusion model to the precipitation forecasting task and propose a short-term precipitation nowcasting with condition diffusion model based on historical observational data, which is referred to as SRNDiff. By incorporating an additional conditional decoder module …

abstract adversarial arxiv autoencoders contrast cs.cv diffusion diffusion model diffusion models forecasting gans generate generative generative adversarial networks image image generation limitations networks nowcasting precipitation quality rainfall samples terms type variational autoencoders