@article{hess2026climtipgml,
  title = {ClimTip-GML: A global bias-corrected and downscaled dataset for assessing impacts of climate tipping events},
  author = {Philipp Hess and Sebastian Bathiany and Lucas Ferreira Correa and Laura C. Jackson and Casey R. Patrizio and Niklas Boers},
  year = {2026},
  eprint = {2609.23149},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.23149},
}

@article{lakatos2026statistical,
  title = {Statistical versus machine learning-based spatial interpolation of post-processed ensemble weather forecasts},
  author = {Mária Lakatos},
  year = {2026},
  eprint = {2609.07512},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.07512},
}

@article{sun2026pcsdiff,
  title = {PCSDiff: Diffusion-Based Bias Correction and Super Resolution Toward Practical Operational Medium-Term Precipitation Forecast},
  author = {Yuze Sun and Shiyi Wang and Jiancheng Pan and Die Wang and Andreas F. Prein and Wentao Luo and Linhan Jiang and Jie Wu and Quan Zhang and Xiaomeng Huang},
  year = {2026},
  eprint = {2609.06942},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.06942},
}

@article{sawadekar2026differentiable,
  title = {A Differentiable Framework for Global Circulation Model Precipitation Bias Correction},
  author = {Kamlesh Sawadekar and Seth McGinnis and Peijun Li and Kathryn Lawson and Chaopeng Shen},
  year = {2026},
  eprint = {2604.23045},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.23045},
}

@article{iwase2026improvements,
  title = {Improvements to the post-processing of weather forecasts using machine learning and feature selection},
  author = {Kazuma Iwase and Tomoyuki Takenawa},
  year = {2026},
  eprint = {2604.19340},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.19340},
}

@article{tran2026mpmoe,
  title = {MP-MoE: Matrix Profile-Guided Mixture of Experts for Precipitation Forecasting},
  author = {Huyen Ngoc Tran and Dung Trung Tran and Hong Nguyen and Xuan Vu Phan and Nam-Phong Nguyen},
  year = {2026},
  eprint = {2603.25046},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.25046},
}

@article{nadera2026hurrigan,
  title = {HURRI-GAN: A Novel Approach for Hurricane Bias-Correction Beyond Gauge Stations using Generative Adversarial Networks},
  author = {Noujoud Nadera and Hadi Majed and Stefanos Giaremis and Rola El Osta and Clint Dawson and Carola Kaiser and Hartmut Kaiser},
  year = {2026},
  eprint = {2603.06649},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.06649},
}

@article{roberts2026ensemblesizedependence,
  title = {Ensemble-size-dependence of deep-learning post-processing methods that minimize an (un)fair score: motivating examples and a proof-of-concept solution},
  author = {Christopher David Roberts},
  year = {2026},
  eprint = {2602.15830},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.15830},
}

@article{bruninx2026probabilistic,
  title = {Probabilistic Wind Power Forecasting with Tree-Based Machine Learning and Weather Ensembles},
  author = {Max Bruninx and Diederik van Binsbergen and Timothy Verstraeten and Ann Nowé and Jan Helsen},
  year = {2026},
  eprint = {2602.13010},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.13010},
}

@article{landry2026stipp,
  title = {STIPP: Space-time in situ postprocessing over the French Alps using proper scoring rules},
  author = {David Landry and Isabelle Gouttevin and Hugo Merizen and Claire Monteleoni and Anastase Charantonis},
  year = {2026},
  eprint = {2601.02882},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.02882},
}

@article{dirkson2025we,
  title = {Are we misdiagnosing ensemble forecast reliability? On the insufficiency of Spread-Error and rank-based reliability metrics},
  author = {Arlan Dirkson and Mark Buehner},
  year = {2025},
  eprint = {2512.02160},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.02160},
}

@article{flos2025cobase,
  title = {COBASE: A new copula-based shuffling method for ensemble weather forecast postprocessing},
  author = {Maurits Flos and Bastien François and Irene Schicker and Kirien Whan and Elisa Perrone},
  year = {2025},
  eprint = {2510.25610},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.25610},
}

@article{zeng2025review,
  title = {A Review of Neural Networks in Precipitation Prediction},
  author = {Yugong Zeng and Jiayuan Wang and Jonathan Wu},
  year = {2025},
  eprint = {2510.22855},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.22855},
}

@article{lakatos2025compositeloss,
  title = {A Composite-Loss Graph Neural Network for the Multivariate Post-Processing of Ensemble Weather Forecasts},
  author = {Mária Lakatos},
  year = {2025},
  eprint = {2509.02784},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.02784},
}

@article{zhou2025how,
  title = {How to systematically develop an effective AI-based bias correction model?},
  author = {Xiao Zhou and Yuze Sun and Jie Wu and Xiaomeng Huang},
  year = {2025},
  eprint = {2504.15322},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.15322},
}

@article{trotta2025statistical,
  title = {Statistical post-processing yields accurate probabilistic forecasts from Artificial Intelligence weather models},
  author = {Belinda Trotta and Robert Johnson and Catherine de Burgh-Day and Debra Hudson and Esteban Abellan and James Canvin and Andrew Kelly and Daniel Mentiplay and Benjamin Owen and Jennifer Whelan},
  year = {2025},
  eprint = {2504.12672},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.12672},
}

@article{bulte2025graph,
  title = {Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall},
  author = {Christopher Bülte and Sohir Maskey and Philipp Scholl and Jonas von Berg and Gitta Kutyniok},
  year = {2025},
  eprint = {2504.05471},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.05471},
}

@article{landry2025generating,
  title = {Generating ensembles of spatially-coherent in-situ forecasts using flow matching},
  author = {David Landry and Claire Monteleoni and Anastase Charantonis},
  year = {2025},
  eprint = {2504.03463},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.03463},
}

@article{leclerc2025improving,
  title = {Improving Predictions of Convective Storm Wind Gusts through Statistical Post-Processing of Neural Weather Models},
  author = {Antoine Leclerc and Erwan Koch and Monika Feldmann and Daniele Nerini and Tom Beucler},
  year = {2025},
  eprint = {2504.00128},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.00128},
}

@article{poecke2024selfattentive,
  title = {Self-attentive Transformer for Fast and Accurate Postprocessing of Temperature and Wind Speed Forecasts},
  author = {Aaron Van Poecke and Tobias Sebastian Finn and Ruoke Meng and Joris Van den Bergh and Geert Smet and Jonathan Demaeyer and Piet Termonia and Hossein Tabari and Peter Hellinckx},
  year = {2024},
  eprint = {2412.13957},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.13957},
}

@article{nai2024boosting,
  title = {Boosting weather forecast via generative superensemble},
  author = {Congyi Nai and Xi Chen and Shangshang Yang and Yuan Liang and Ziniu Xiao and Baoxiang Pan},
  year = {2024},
  eprint = {2412.08377},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.08377},
}

@article{lee2024selfsupervised,
  title = {Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation},
  author = {Junha Lee and Sojung An and Sujeong You and Namik Cho},
  year = {2024},
  eprint = {2412.05825},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.05825},
}

@article{satheesh2024machine,
  title = {Machine learning models for daily rainfall forecasting in Northern Tropical Africa using tropical wave predictors},
  author = {Athul Rasheeda Satheesh and Peter Knippertz and Andreas H. Fink},
  year = {2024},
  eprint = {2408.16349},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.16349},
}

@article{feik2024graph,
  title = {Graph Neural Networks and Spatial Information Learning for Post-Processing Ensemble Weather Forecasts},
  author = {Moritz Feik and Sebastian Lerch and Jan Stühmer},
  year = {2024},
  eprint = {2407.11050},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.11050},
}

@article{sha2024improving,
  title = {Improving ensemble extreme precipitation forecasts using generative artificial intelligence},
  author = {Yingkai Sha and Ryan A. Sobash and David John Gagne},
  year = {2024},
  eprint = {2407.04882},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.04882},
}