Precipitation Downscaling Using Foundation Model-Conditioned Diffusion

arXiv:2608.25858 · cs.CV, cs.LG, physics.ao-ph · Submitted 2026-08-26 · Read on arXiv

cs.CV, cs.LG, physics.ao-ph

Submitted: 2026-08-26

Updated: 2026-08-26

Terminology

• Foundation Model — 30× in this paper · explained in 3 episodes
• Diffusion Model — 26× in this paper · explained in 8 episodes
• Diffusion Models — 19× in this paper · explained in 6 episodes
• Accuracy — 15× in this paper · explained in 1 episode
• Calibration — 9× in this paper · explained in 7 episodes
• Fidelity — 9× in this paper · explained in 2 episodes
• Embeddings — 8× in this paper · explained in 2 episodes
• Foundation Models — 7× in this paper · explained in 7 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Fractions Skill Score — 5× in this paper
• Consistency — 4× in this paper · explained in 3 episodes
• Generative Model — 4× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• Radially Averaged Power Spectral Density — 3× in this paper
• Adaptation — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Cross-Attention Mechanism — 2× in this paper · explained in 2 episodes
• European Space Agency — 2× in this paper
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Architectural Adaptation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Conservation Laws — 1× in this paper · explained in 3 episodes
• Continuous Ranked Probability Score — 1× in this paper
• Copernicus Data Store — 1× in this paper
• Data Assimilation — 1× in this paper · explained in 2 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Adversarial Networks (GANs) — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Mode Collapse — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Downscaling weather forecasts from Low- to High-Resolution with Diffusion Models
• Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere
• Denoising Diffusion Probabilistic Models
• Emerging AI-based weather prediction models as downscaling tools
• AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning
• ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
• High-Resolution Image Synthesis with Latent Diffusion Models
• Prithvi WxC: Foundation Model for Weather and Climate
• ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models