mlsanityData to 7 Oct 2026

Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification

arXiv 2304.12891 ↗First posted 25 Apr 2023physics.ao-ph cs.LG eess.IVcited by 53

On the map: Diffusion models → Flow matching, time series and science

Abstract (arXiv)

Diffusion models have been widely adopted in image generation, producing higher-quality and more diverse samples than generative adversarial networks (GANs). We introduce a latent diffusion model (LDM) for precipitation nowcasting - short-term forecasting based on the latest observational data. The LDM is more stable and requires less computation to train than GANs, albeit with more computationally expensive generation. We benchmark it against the GAN-based Deep Generative Models of Rainfall (DGMR) and a statistical model, PySTEPS. The LDM produces more accurate precipitation predictions, while the comparisons are more mixed when predicting whether the precipitation exceeds predefined thresholds. The clearest advantage of the LDM is that it generates more diverse predictions than DGMR or PySTEPS. Rank distribution tests indicate that the distribution of samples from the LDM accurately reflects the uncertainty of the predictions. Thus, LDMs are promising for any applications where uncertainty quantification is important, such as weather and climate.

Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 27 of its 54 references that are in the map. First posted on arXiv 25 Apr 2023.

Builds on

27 of 54 references.

References · 27

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2020Denoising Diffusion Implicit Modelscited by 9,655
  6. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  7. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  8. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  9. 2022Generative Adversarial Networkscited by 5,603
  10. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  11. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  12. 2015Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcastingcited by 1,428
15 more
  1. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  2. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,036
  3. 2022FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operatorscited by 748
  4. 2022Pseudo Numerical Methods for Diffusion Models on Manifoldscited by 695
  5. 2018Which Training Methods for GANs do actually Converge?cited by 672
  6. 2021SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Modelscited by 415
  7. 2021Skillful Precipitation Nowcasting using Deep Generative Models of Radarcited by 308
  8. 2019Seeing What a GAN Cannot Generatecited by 148
  9. 2020Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Networkcited by 68
  10. 2022A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecastscited by 64
  11. 2019Machine Learning for Precipitation Nowcasting from Radar Imagescited by 56
  12. 2022Increasing the accuracy and resolution of precipitation forecasts using deep generative modelscited by 35
  13. 2022Machine learning emulation of a local-scale UK climate modelcited by 20
  14. 2022Thunderstorm nowcasting with deep learning: a multi-hazard data fusion modelcited by 7
  15. 2022Seamless lightning nowcasting with recurrent-convolutional deep learningcited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 9; 2024: 17; 2025: 14; 2026: 13.

53 papers.

Sort:

By area:

  1. 2023Residual Corrective Diffusion Modeling for Km-scale Atmospheric Downscalingcited by 103
  2. 2023PreDiff: Precipitation Nowcasting with Latent Diffusion Modelscited by 96
  3. 2024A Survey on Diffusion Models for Time Series and Spatio-Temporal Datacited by 66
  4. 2023DiffCast: A Unified Framework via Residual Diffusion for Precipitation Nowcastingcited by 57
  5. 2023Foundation Models for Weather and Climate Data Understanding: A Comprehensive Surveycited by 32
  6. 2024Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modelingcited by 32
  7. 2024Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectivescited by 27
  8. 2023Conformal Contextual Robust Optimizationcited by 25
  9. 2023Precipitation nowcasting with generative diffusion modelscited by 22
  10. 2023Precipitation Downscaling with Spatiotemporal Video Diffusioncited by 16
  11. 2024Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcastingcited by 16
  12. 2024DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models with 3D Diffusion Modelscited by 15
38 more
  1. 2025Deep Learning and Foundation Models for Weather Prediction: A Surveycited by 15
  2. 2024Validating Deep Learning Weather Forecast Models on Recent High-Impact Extreme Eventscited by 14
  3. 2024Deep learning for precipitation nowcasting: A survey from the perspective of time series forecastingcited by 14
  4. 2024Can AI be enabled to dynamical downscaling? A Latent Diffusion Model to mimic km-scale COSMO5.0CLM9 simulationscited by 14
  5. 2023Forecasting Tropical Cyclones with Cascaded Diffusion Modelscited by 10
  6. 2025A Probabilistic Approach to Wildfire Spread Prediction Using a Denoising Diffusion Surrogate Modelcited by 10
  7. 2023Deterministic Guidance Diffusion Model for Probabilistic Weather Forecastingcited by 9
  8. 2024DiffObs: Generative Diffusion for Global Forecasting of Satellite Observationscited by 9
  9. 2025ClimateLLM: Efficient Weather Forecasting via Frequency-Aware Large Language Modelscited by 9
  10. 2024GPTCast: a weather language model for precipitation nowcastingcited by 8
  11. 2024CaFA: Global Weather Forecasting with Factorized Attention on Spherecited by 6
  12. 2025LaDCast: A Latent Diffusion Model for Medium-Range Ensemble Weather Forecastingcited by 6
  13. 2025FlowCast: Advancing Precipitation Nowcasting with Conditional Flow Matchingcited by 6
  14. 2024CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty Quantificationcited by 5
  15. 2024Towards diffusion models for large-scale sea-ice modellingcited by 4
  16. 2024VegeDiff: Latent Diffusion Model for Geospatial Vegetation Forecastingcited by 4
  17. 2024Modulated Adaptive Fourier Neural Operators for Temporal Interpolation of Weather Forecastscited by 4
  18. 2024DuoCast: Duo-Probabilistic Diffusion for Precipitation Nowcastingcited by 4
  19. 2025Improving Tropical Cyclone Forecasting With Video Diffusion Modelscited by 3
  20. 2025RainPro-8: An Efficient Deep Learning Model to Estimate Rainfall Probabilities Over 8 Hourscited by 2
  21. 2025Guided Unconditional and Conditional Generative Models for Super-Resolution and Inference of Quasi-Geostrophic Turbulencecited by 2
  22. 2026PODiff: Latent Diffusion in Proper Orthogonal Decomposition Space for Scientific Super-Resolutioncited by 2
  23. 2026Probabilistic Precipitation Nowcasting with Rectified Flow Transformerscited by 2
  24. 2026Pointwise is Pointless? A Multimodal Ablation Study for Precipitation Nowcasting with Graph Neural Networkscited by 2
  25. 2025Controlling Ensemble Variance in Diffusion Models: An Application for Reanalyses Downscalingcited by 1
  26. 2025A PDE-Informed Latent Diffusion Model for 2-m Temperature Downscalingcited by 1
  27. 2025STLDM: Spatio-Temporal Latent Diffusion Model for Precipitation Nowcastingcited by 1
  28. 2026PixelFlowCast: Latent-Free Precipitation Nowcasting via Pixel Mean Flowscited by 1
  29. 2026SwAIther-Precip: Lead-Time-Aware Bias Correction Enables Kilometer-Scale Downscaling of Global AI Precipitation Forecasts over Switzerlandcited by 1
  30. 2026Patch-PODiff-ViT: Structured Latent Diffusion with Patchwise POD for Super-Resolution and Uncertainty Quantificationcited by 1
  31. 2024Multi-Source Temporal Attention Network for Precipitation Nowcastingcited by 0
  32. 2025CNCast: Leveraging 3D Swin Transformer and DiT for Enhanced Regional Weather Forecastingcited by 0
  33. 2025Physical Scales Matter: The Role of Receptive Fields and Advection in Satellite-Based Thunderstorm Nowcasting with Convolutional Neural Networkscited by 0
  34. 2025Km-scale dynamical downscaling through conformalized latent diffusion modelscited by 0
  35. 2026CASCADE: Cross-scale Advective Super-resolution with Climate Assimilation and Downscaling Evolutioncited by 0
  36. 2026Physics-Informed Diffusion Model for Generating Synthetic Extreme Rare Weather Events Datacited by 0
  37. 2026Generative climate downscaling enables high-resolution compound risk assessment by preserving multivariate dependenciescited by 0
  38. 2026Beyond MSE: Improving Precipitation Nowcasting with Multi-Quantile Regressioncited by 0

50 most cited of 53 All 53 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2024RNDiff: Rainfall nowcasting with Condition Diffusion Model
  2. 2026NowcastDiT: Diffusion Transformers are Effective Precipitation Nowcasters
  3. 2024PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling
  4. 2024Extreme Precipitation Nowcasting using Multi-Task Latent Diffusion Models
  5. 2026Regional Climate Model Emulation with Diffusion Approaches: What is the Added Value of Generative Machine Learning?
  6. 2026SimCast-S2S: A Computationally Efficient Diffusion Model for Subseasonal Precipitation Forecasting
  7. 2024Diffusion-Based Joint Temperature and Precipitation Emulation of Earth System Models
  8. 2024Precipitation Nowcasting Using Diffusion Transformer with Causal Attention