@article{biswas2026weather,
  title = {Weather Jiu-Jitsu: Exploring the Feasibility of Control Paradigms in Weather Foundation Models},
  author = {Prakriti Biswas and Kobi Abayomi and Upmanu Lall},
  year = {2026},
  eprint = {2610.00792},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.00792},
}

@article{li2026stcformer,
  title = {STCFormer: Adaptive Spatio-Temporal Modeling with Dynamic Cluster Transformer for Station-based Weather Forecasting},
  author = {Rongwen Li and Haixin Xie and Mingyang Wang and Hongwu Liu and Kun Fang and Changjian Chen and Zhuo Tang and Kenli Li},
  year = {2026},
  eprint = {2610.00377},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.00377},
}

@article{leung2026butterfly,
  title = {Butterfly Effect Confirmed in Global AI Weather Models: Evidence from Tropical Cyclone Forecasting},
  author = {Jeremy Cheuk-Hin Leung and Daosheng Xu and Weiye Yu and Shaojing Zhang and Xiaodong Zeng and Gaozhen Nie and Jie Feng and Jingchen Pu and Yi Li and Kaijun Ren and Qingcun Zeng and Banglin Zhang},
  year = {2026},
  eprint = {2609.39379},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.39379},
}

@article{park2026proper,
  title = {Proper Scoring Rule-based Diffusion for Probabilistic Weather Forecasting},
  author = {Joonhyeong Park and Giung Nam and Hyungi Lee and Kyunghyun Cho and Byoungwoo Park and Juho Lee},
  year = {2026},
  eprint = {2609.38632},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.38632},
}

@article{mello2026inputfrugal,
  title = {An Input-Frugal Deep Learning Framework for Weather-Driven National Crop-Yield Forecasting: A Case Study of Brazilian Soybean},
  author = {Fernando Dupin da Cunha Mello and Prashant Kumar and Erick G. Sperandio Nascimento},
  year = {2026},
  eprint = {2609.38447},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.38447},
}

@article{pastine2026neural,
  title = {A neural network-based Universal Thermal Climate Index for reliable global thermal-stress classification across extreme weather},
  author = {Bikem Pastine and Milan Klöwer and Tianning Tang and Sarah Wilson Kemsley and Louise Slater},
  year = {2026},
  eprint = {2609.35949},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.35949},
}

@article{nath2026suitable,
  title = {Suitable Measures for the Potential Operational Utility of AI NWP Rainfall Forecasts Over Africa},
  author = {Shruti Nath and Docko Sow and Koomi Toussaint Amoussouvi and Fenwick Cooper and Josiah Kiarie Kimani and John Bagiliko and Florian Pappenberger and Rendani Mbuvha},
  year = {2026},
  eprint = {2609.31775},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.31775},
}

@article{skok2026dataset,
  title = {A dataset of one-dimensional idealized probabilistic fields},
  author = {Gregor Skok and Romain Pic},
  year = {2026},
  eprint = {2609.25720},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.25720},
}

@article{xiao2026fastml,
  title = {FAST-ML: A Hybrid Physics-Machine Learning Framework for Tropical Cyclone Intensity Forecasting},
  author = {Shijie Xiao and Jonathan Lin and Thomas Ehrmann and Ali Sarhadi},
  year = {2026},
  eprint = {2609.25505},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.25505},
}

@article{pic2026spatial,
  title = {Spatial Aggregation of ROC and Precision-Recall Curves},
  author = {Romain Pic and Zhongwei Zhang and Sebastian Engelke and Johanna Ziegel},
  year = {2026},
  eprint = {2609.19517},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.19517},
}

@article{chen2026butterfly,
  title = {Butterfly Effect and the Kinetic Energy Cascade in Probabilistic Machine Learning Weather Prediction Models},
  author = {Jiakai Chen and Joel Oskarsson and Simon Driscoll and Sebastian Schemm},
  year = {2026},
  eprint = {2609.18489},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.18489},
}

@article{elberkennou2026every,
  title = {Every Fixed Metric Has a Blind Spot: A Learned Atmospheric Critic for Scoring Forecast Realism},
  author = {Younes Elberkennou and Dmitri Demler and Thierry Meier and Luca Rispoli and Fanny Lehmann and Joel Oskarsson},
  year = {2026},
  eprint = {2609.18381},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.18381},
}

@article{morsing2026aries,
  title = {Aries: A Proprietary Medium-Range Weather Prediction Model for the Energy Industry},
  author = {Lukas Hedegaard Morsing and Arian Bakhtiarnia and Jonas Lynge Olesen and Tómas Bragi Björnsson Leth and Christian Gøbel Bach},
  year = {2026},
  eprint = {2609.13292},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.13292},
}

@article{dubey2026optimizing,
  title = {Optimizing Geoengineering Interventions Using Differentiable Climate Models},
  author = {Pulkit Dubey and Dorian S. Abbot and Ashesh Chattopadhyay},
  year = {2026},
  eprint = {2609.12528},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.12528},
}

@article{bazlen2026windbench,
  title = {WIND-Bench: A Benchmark Dataset for In-Situ Near-Surface Wind Speed Observations Across the Conterminous United States},
  author = {Kyla Bazlen and Grant Buster and Brandon Benton and Lauren North and Ansley Baring and David D. Turner and Emily Wells and Laura Vimmerstedt},
  year = {2026},
  eprint = {2609.12228},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.12228},
}

@article{adamov2026stochastically,
  title = {Stochastically Perturbed Weights: Ensembles from Deterministic Machine-Learning Weather Models},
  author = {Simon Adamov and Oliver Fuhrer and Reto Knutti and Sebastian Schemm},
  year = {2026},
  eprint = {2609.08412},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.08412},
}

@article{rasp2026weathernext,
  title = {WeatherNext 3: Increasing resolution and performance of global weather models with raw observations},
  author = {Stephan Rasp and Boris Babenko and Dominic Masters and Andrew El-Kadi and Samier Merchant and Guy Shalev and Ilan Price and Fred Zyda and Remi Lam and Sasha Shysheya and Matthew Willson and Stratis Markou and Shreya Agrawal and Suhani Vora and Mohammed Alewi Hassen and Sunny Mak and Tom R. Andersson and Megan Bela and Akib Uddin and Nofar Peled Levi and Ben Gaiarin and Ferran Alet and Aaron Bell and Peter Battaglia and Alvaro Sanchez-Gonzalez},
  year = {2026},
  eprint = {2609.03582},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.03582},
}

@article{schmitt2026improving,
  title = {Improving precipitation forecasts in an AI weather model using observational data},
  author = {Julian F. Schmitt and Bertrand Delorme and Robert C. King and Yashica Patodia and Tapio Schneider and Aditi Sheshadri and Ravi Jain},
  year = {2026},
  eprint = {2609.03210},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.03210},
}

@article{wang2026tcnext,
  title = {TC-Next: Zero-Shot Multimodal Cyclone Forecasting},
  author = {Zhe Wang and Sijie Chen and Yiming Luo and Daehyun Kim and Chien-Yi Chang},
  year = {2026},
  eprint = {2609.02085},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.02085},
}

@article{almeida2026uncertaintyaware,
  title = {Uncertainty-Aware End-to-End AI Weather Forecasting: Disentangling Observation and Model Contributions},
  author = {Rodrigo Almeida and Noelia Otero and Jost Arndt and Simon Baur and Wojciech Samek and Jackie Ma},
  year = {2026},
  eprint = {2608.30795},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.30795},
}

@article{yang2026diffusion,
  title = {Diffusion Distillation for Efficient Weather Ensembles},
  author = {Yiming Yang and Valentin Brekke and James Briant and Serge Guillas},
  year = {2026},
  eprint = {2608.27728},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.27728},
}

@article{singh2026climate,
  title = {Climate Physics Dynamic Matching},
  author = {Gurjeet Sangra Singh and Frantzeska Lavda and Alexandros Kalousis},
  year = {2026},
  eprint = {2608.26907},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.26907},
}

@article{smith2026bridging,
  title = {Bridging short- and medium-range weather forecasting with machine learning},
  author = {Timothy A. Smith and Mariah Pope and Sergey Frolov and Brett Basarab and Daniel Abdi and Paul Madden and Isidora Jankov},
  year = {2026},
  eprint = {2608.26822},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.26822},
}

@article{hassanzadeh2026missing,
  title = {Missing the Butterfly and Predicting the Past: Features or Bugs of Accurate AI Weather Models?},
  author = {Pedram Hassanzadeh and Weidong Li and Y. Qiang Sun and Jiangdi Wang and Alexander Wikner and Justin Finkel and Jonathan Q. Weare},
  year = {2026},
  eprint = {2608.25835},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.25835},
}

@article{singh2026afdbench,
  title = {AFDBench: A Reasoning-First AI Scientist for NationalWeather Service Forecast Discussions},
  author = {Manmeet Singh and Somnath Luitel and Prabhjot Singh and Manraaj Banga and Naveen Sudharsan and Josh Durkee},
  year = {2026},
  eprint = {2608.24954},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.24954},
}

@article{goecke2026aicon,
  title = {AICON: An operational global machine learning weather forecasting model},
  author = {Tobias Goecke and Marek Jacob and Florian Prill and Michael Denhard and Felix Fundel and Jan Keller and Roland Potthast and Hendrik Reich and Britta Seegebrecht and Sven Ulbrich and Arianna Valmassoi and Sabrina Wahl},
  year = {2026},
  eprint = {2608.24651},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.24651},
}

@article{lin2026extremes,
  title = {Extremes on Rewind: Generating 1,000-Member Ensembles Initialized at a Final Condition},
  author = {Jerry Lin and Mu-Ting Chien and Mansi Sakarvadia and Elizabeth A. Barnes},
  year = {2026},
  eprint = {2608.19008},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.19008},
}

@article{zhang2026tianmutc,
  title = {Tianmu-TC: Physics-constraints Generative Artificial Intelligence for Global Tropical Cyclone Forecasting},
  author = {Shiqi Zhang and Pan Mu and Cheng Huang and Hanting Yan and Yuchao Zhu and Jinglin Zhang and Shengyong Chen and Shoujuan Shu and Cong Bai},
  year = {2026},
  eprint = {2608.18500},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.18500},
}

@article{merchant2026how,
  title = {How Do AI Climate Models Respond to Warming Across Climate Zones?},
  author = {Charlotte C. Merchant and Milan Klöwer and Bradley Stanley-Clamp and Maren Höver and Simon L. L. Michel and Edward Groot and Hannah M. Christensen},
  year = {2026},
  eprint = {2608.17986},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.17986},
}

@article{gabler2026do,
  title = {Do AI weather models miss extremes?},
  author = {Marvin Vincent Gabler and Roberto Molinaro and Niall Siegenheim and Henry Martin and Mark Frey and Niels Poulsen and Philipp Seitz and Olivier Lam},
  year = {2026},
  eprint = {2608.09972},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.09972},
}

@article{chen2026veincast,
  title = {VeinCast: Physics-Guided Dynamic Field Graphs with Graph-Conditioned Fusion for Global Medium-Range Weather Forecasting},
  author = {Zhisheng Chen and Jinhan Li and Yuxuan Li and Yuan Gao and Hao Wu and Zheng Lu and Jinlong Du and Kun Wang and Bo An},
  year = {2026},
  eprint = {2608.09286},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.09286},
}

@article{levang2026timestepconditioned,
  title = {Timestep-Conditioned Transformers for Global Weather Forecasting},
  author = {Sam Levang and Fran Bartolic and Ty Dickinson and Chase Dwelle and Paulius Rauba and Viktor Cikojevic},
  year = {2026},
  eprint = {2608.06241},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.06241},
}

@article{carroll2026marscast,
  title = {MarsCast: Transfer Learning of AI Weather Foundation Models to Planetary Atmospheres},
  author = {M. L. Carroll and J. Li and S. D. Guzewich and G. Villanueva and J. A. Caraballo-Vega and M. J. Frost},
  year = {2026},
  eprint = {2608.05054},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.05054},
}

@article{pfreundschuh2026prithviprecip,
  title = {Prithvi-Precip: Integrating Satellite Observations into an Atmospheric AI Foundation Model for Precipitation Forecasting},
  author = {Simon Pfreundschuh and Christian D. Kummerow and Johannes Schmude and Sujit Roy and Rahul Ramachandran and Tsengdar Lee and Valentine Anantharaj and Katherine H. Breen},
  year = {2026},
  eprint = {2608.03959},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.03959},
}

@article{decancq2026weather,
  title = {Weather Emulators at the Frontier of Heat Extremes Predictability},
  author = {Cas Decancq and Thomas Mortier and Jessica Keune and Diego G. Miralles},
  year = {2026},
  eprint = {2607.28220},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.28220},
}

@article{cai2026nipping,
  title = {Nipping the Butterfly Effect in the Bud: Self-Output Fine-Tuning for Autoregressive Weather Prediction},
  author = {Yun-Ye Cai and Hsuan-Tien Lin},
  year = {2026},
  eprint = {2607.21080},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.21080},
}

@article{hover2026spatial,
  title = {Spatial Generalization Tests for Machine Learning-based Weather Models to Assess Physical Consistency},
  author = {Maren Höver and Milan Klöwer and Christian Schroeder de Witt and Hannah M. Christensen},
  year = {2026},
  eprint = {2607.20716},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.20716},
}

@article{singh2026aircastmars,
  title = {Aircast-Mars: A Mars Foundation Model for Global Weather Forecasting with HEALPix-Aware Convolutions},
  author = {Manmeet Singh and Saptarishi Dhanuka and Naveen Sudharsan and Houman Owhadi and Krista M. Soderlund and Alphan Altinok},
  year = {2026},
  eprint = {2607.19370},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.19370},
}

@article{lang2026sensitivity,
  title = {On the sensitivity of machine-learned probabilistic weather forecast models to scale-aware scoring rules},
  author = {Simon Lang and Martin Leutbecher and Sam Hatfield},
  year = {2026},
  eprint = {2607.19161},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.19161},
}

@article{chapman2026hard,
  title = {Hard conservation correctors can hide a degrading model when training autoregressive emulators},
  author = {William E. Chapman and John Schreck and Yingkai Sha},
  year = {2026},
  eprint = {2607.18416},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.18416},
}

@article{piao2026fourier,
  title = {Fourier Geometric Wind Power Forecasting with Numerical Weather Prediction},
  author = {Shiyuan Piao and Fan Zehui and Yang Liu and Hong Cheng and Juepeng Zheng and Jie Zhou and Fugee Tsung},
  year = {2026},
  eprint = {2607.17095},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.17095},
}

@article{yang2026tssm,
  title = {TSSM: Triaxial State Space Model for Global Station Weather Forecasting with Temporal-Variable-Historical Modeling},
  author = {Songru Yang and Zili Liu and Tao Han and Ben Fei and Fenghua Ling and Lei Bai and Chang Liu and Xiangyang Ji and Zhenwei Shi and Zhengxia Zou},
  year = {2026},
  eprint = {2607.13101},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.13101},
}

@article{chen2026robustness,
  title = {Robustness of Deep Learning Models for PV Power Forecasting under NWP Forecast Errors: A Spatiotemporal and Physically Interpretable Analysis},
  author = {Dandan Chen and Yan Zhao and Xuepeng Chen},
  year = {2026},
  eprint = {2607.12954},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.12954},
}

@article{luitel2026evaluating,
  title = {Evaluating the Fidelity of GraphCast AI Forecasts for the Indian Summer Monsoon: A Climatological Assessment Against ERA-5 Reanalysis and IMERG Observations},
  author = {Somnath Luitel and Manmeet Singh and Parthasarathi Mukhopadhyay and Sandeep Juneja and Saptarishi Dhanuka},
  year = {2026},
  eprint = {2607.11905},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.11905},
}

@article{lean2026global,
  title = {Global reanalysis from observations alone with machine learning},
  author = {Peter Lean and Ewan Pinnington and Patrick Laloyaux and Mihai Alexe and Eulalie Boucher and Simon Lang and Tomas Kral and Paul Poli and Hans Hersbach and Niels Bormann and Matthew Chantry and Anthony McNally},
  year = {2026},
  eprint = {2607.07879},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.07879},
}

@article{trentini2026integrating,
  title = {Integrating GNSS-Derived Zenith Wet Delay into a Weather Foundation Model Improves Precipitation Forecasting},
  author = {Leonardo Trentini and Fanny Lehmann and Laura Crocetti and Benedikt Soja},
  year = {2026},
  eprint = {2607.05658},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.05658},
}

@article{schloer2026aifssubs,
  title = {AIFS-SUBS: Extending Data-Driven Forecasting to Sub-Seasonal Timescales},
  author = {Jakob Schloer and Steffen Tietsche and Christopher D. Roberts and Lorenzo Zampieri and Simon Lang and Gert Mertes and Gareth Jones and Matthew Chantry and Frederic Vitart},
  year = {2026},
  eprint = {2607.05100},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.05100},
}

@article{erfani2026genealogy,
  title = {On the Genealogy of Machine Learning Weather Prediction},
  author = {Mohammad Hassan Erfani},
  year = {2026},
  eprint = {2607.05045},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.05045},
}

@article{wang2026enhancing,
  title = {Enhancing the Forecasting Capability of Multi-Model Blending Algorithms for Extreme Precipitation via Joint Use of Station and Gridded Observations},
  author = {Yu Wang and Yong Cao and Kan Dai and Yue Shen and Xiaoqing Zeng and Ruixia Zhao},
  year = {2026},
  eprint = {2607.04862},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.04862},
}

@article{wang2026less,
  title = {Less Tokens, Better Forecasts: Sparse Residual Routing for Efficient Weather Prediction},
  author = {Janet Wang and Yunbei Zhang and Lin Zhao and Xi Xiao and Jihun Hamm and Xiao Wang},
  year = {2026},
  eprint = {2607.02829},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.02829},
}

@article{bakketun2026enhancing,
  title = {Enhancing a high resolution data-driven weather prediction model with surface descriptors},
  author = {Åsmund Bakketun and Håvard Homleid Haugen and Jostein Blyverket and Thomas Nils Nipen and Malte Müller},
  year = {2026},
  eprint = {2607.02824},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.02824},
}

@article{pacey2026modelling,
  title = {Modelling convective cell occurrence in proximity to cold fronts using extreme gradient boosting},
  author = {George Pacey and Stephan Pfahl and Lisa Schielicke},
  year = {2026},
  eprint = {2606.26699},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.26699},
}

@article{diaconu2026otter,
  title = {Otter Weather: Skillful and Computationally Efficient Medium-Range Weather Forecasting},
  author = {Cristiana Diaconu and Jonas Scholz and Aliaksandra Shysheya and Stratis Markou and Payel Mukhopadhyay and Miles Cranmer and Richard E. Turner},
  year = {2026},
  eprint = {2606.26421},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.26421},
}

@article{lee2026eventaware,
  title = {Event-Aware Loss Design for Forecasting of Convective Precipitation and Lightning},
  author = {ChangJae Lee and Heecheol Yang and Byeonggwon Kim},
  year = {2026},
  eprint = {2606.25937},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.25937},
}

@article{burghday2026evaluation,
  title = {Evaluation of medium range machine learning models for sub-seasonal prediction},
  author = {Catherine de Burgh-Day and Chen Li and Debra Hudson and Li Shi and Harrison Cook and Robin Wedd and Griffith Young},
  year = {2026},
  eprint = {2606.25417},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.25417},
}

@article{dueben2026machine,
  title = {Machine learning is revolutionizing weather forecasting -- the next step is a change in how we work},
  author = {Peter Dueben and Peter Bauer and Oliver Fuhrer and Nikolay Koldunov and Jørn Kristiansen},
  year = {2026},
  eprint = {2606.25076},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.25076},
}

@article{bhattacharya2026arcomars,
  title = {ARCO-Mars: A Unified Cloud-Optimized Archive of Mars Atmosphere Reanalysis},
  author = {Ananyo Bhattacharya},
  year = {2026},
  eprint = {2606.21701},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.21701},
}

@article{asch2026rigorous,
  title = {Rigorous uncertainty quantification of probabilistic AI weather forecasts with conformal prediction},
  author = {Anna Asch and Raphael Rossellini and Pedram Hassanzadeh and Rebecca Willett},
  year = {2026},
  eprint = {2606.19642},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.19642},
}

@article{pinnington2026aifsdop,
  title = {AIFS-DOP: End-to-End Medium-Range Weather Prediction from Observations Alone with Machine Learning},
  author = {Ewan Pinnington and Peter Lean and Mihai Alexe and Eulalie Boucher and Simon Lang and Patrick Laloyaux and Gert Mertes and Tomas Kral and Patricia de Rosnay and Matthew Chantry and Anthony McNally},
  year = {2026},
  eprint = {2606.19093},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.19093},
}

@article{evans2026hybrid,
  title = {A Hybrid LSTM--Vision Transformer Architecture for Predicting HRRR Forecast Errors},
  author = {David Aaron Evans and Jay C. Rothenberger and Kara J. Sulia and Nick P. Bassill and Chris D. Thorncroft},
  year = {2026},
  eprint = {2606.19026},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.19026},
}

@article{bugaev2026physicsconstrained,
  title = {Physics-Constrained Neural Networks for Improved Short-Term Weather Forecasting: A Case Study over the South Pacific},
  author = {Egor Bugaev and Fedor Buzaev and Dmitry Efremenko and Denis Derkach and Fedor Ratnikov},
  year = {2026},
  eprint = {2606.17659},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.17659},
}

@article{kasteleyn2026physmetricsweather,
  title = {PhysMetrics.Weather: An Evaluation Framework for Physical Consistency in ML Weather Models},
  author = {Emma Kasteleyn and Timo Maier and Axel Lauer and Veronika Eyring and Pierre Gentine and Ana Lucic},
  year = {2026},
  eprint = {2606.10642},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.10642},
}

@article{rowell2026performance,
  title = {Performance Evaluation of GraphCast for Medium-Range Weather Forecasting over Brazil},
  author = {Wolfgang R. Rowell and Lucas S. Kupssinskü},
  year = {2026},
  eprint = {2606.06348},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.06348},
}

@article{minoza2026scalable,
  title = {Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels},
  author = {Jose Marie Antonio Miñoza and Rex Gregor Laylo and Sebastian C. Ibañez},
  year = {2026},
  eprint = {2606.02886},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.02886},
}

@article{dhanuka2026adaweather,
  title = {AdaWeather: Adaptively Mixing Probabilistic Weather Forecasts with Logarithmic Regret},
  author = {Saptarishi Dhanuka and Sarvesh Iyer and Manmeet Singh and Mihir More and Rushil Gupta and Dhruman Gupta and Parthasarathi Mukhopadhyay and Sandeep Juneja},
  year = {2026},
  eprint = {2606.02663},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.02663},
}

@article{baggio2026forecasting,
  title = {Forecasting threshold exceedance of atmospheric variables at a specific location},
  author = {Roberta Baggio and Jean-François Muzy},
  year = {2026},
  eprint = {2605.31079},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.31079},
}

@article{lehmann2026ai,
  title = {Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts},
  author = {Fanny Lehmann and Firat Ozdemir and Yun Cheng and Torsten Hoefler and Sebastian Schemm and Benedikt Soja and Siddhartha Mishra},
  year = {2026},
  eprint = {2605.30184},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.30184},
}

@article{huang2026steering,
  title = {Steering Tropical Cyclones Using Small Perturbations in an AI Weather Model},
  author = {Qin Huang and Moyan Liu and Yeongbin Kwon and Upmanu Lall},
  year = {2026},
  eprint = {2605.29248},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.29248},
}

@article{li2026realbench,
  title = {RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges},
  author = {Ruize Li and Zhibin Wen and Tao Han and Hao Chen and Fenghua Ling and Wei Zhang and Song Guo and Lei Bai},
  year = {2026},
  eprint = {2605.24945},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.24945},
}

@article{craig2026physics,
  title = {The physics of AI weather models},
  author = {George Craig and Tobias Selz and Matthias Beylich and Kirsten I. Tempest},
  year = {2026},
  eprint = {2605.23778},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.23778},
}

@article{peng2026simulation,
  title = {A Simulation Methodology Testbed for Typhoon Sensitivity Analysis: Framework Development and Perturbation-Response Experiments with the Pangu Weather Model},
  author = {Yuehua Peng and Yuchen Zhang and Qin Huang and Chengzhi Ye and Jingsong Yang},
  year = {2026},
  eprint = {2605.21864},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.21864},
}

@article{pidduck2026licensing,
  title = {From Licensing to Open Access: Designing a Sustainable Transition in Operational Weather Data},
  author = {Emma Pidduck and Umberto Modigliani and Victoria L. Bennett and Fabio Venuti and Florian Pappenberger and Florence Rabier},
  year = {2026},
  eprint = {2605.21673},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.21673},
}

@article{marchisio2026qlifcast,
  title = {QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting},
  author = {Alberto Marchisio and Aayan Ebrahim and Nouhaila Innan and Muhammad Kashif and Muhammad Shafique},
  year = {2026},
  eprint = {2605.18333},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.18333},
}

@article{cheon2026beyond,
  title = {Beyond Linear Superposition: Discovering Climate Features in AI Weather Models with KAN-SAE},
  author = {Minjong Cheon},
  year = {2026},
  eprint = {2605.17493},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.17493},
}

@article{ueyama2026guided,
  title = {Guided Diffusion Sampling for Precipitation Forecast Interventions},
  author = {Ayumu Ueyama and Kazuhiko Kawamoto and Hiroshi Kera},
  year = {2026},
  eprint = {2605.14317},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.14317},
}

@article{henn2026aimip,
  title = {AIMIP Phase 1: systematic evaluations of AI weather and climate models},
  author = {Brian Henn and Christopher S. Bretherton and Nikolay Koldunov and Christian Lessig and Maria J. Molina and Troy Arcomano and Oliver Watt-Meyer and Guillaume Couairon and Renu Singh and Robert Brunstein and Yana Hasson and Antonia Jost and Noah Brenowitz and Peter Manshausen and Nathaniel Cresswell-Clay and Dale Durran and Kyle Joseph Chen Hall and Janni Yuval and Dmitrii Kochkov and Stephan Hoyer and Ignacio Lopez-Gomez},
  year = {2026},
  eprint = {2605.06944},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.06944},
}

@article{xu2026tyche,
  title = {Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting},
  author = {Fan Xu and Yuan Gao and Kun Wang and Rui Su and Fenghua Ling and Hao Wu and Wanli Ouyang},
  year = {2026},
  eprint = {2605.06916},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.06916},
}

@article{sarabia2026drops,
  title = {From Drops to Grid: Noise-Aware Spatio-Temporal Neural Process for Rainfall Estimation},
  author = {Rafael Pablos Sarabia and Joachim Nyborg and Morten Birk and Ira Assent},
  year = {2026},
  eprint = {2605.05912},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.05912},
}

@article{edris2026prediction,
  title = {Prediction of Drought and Flash Drought in Africa at the Seasonal-to-Subseasonal Scale using the Community Research Earth Digital Intelligence Twin Framework},
  author = {Stuart Edris and Amy McGovern and Jason Hickey},
  year = {2026},
  eprint = {2605.05255},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.05255},
}

@article{pohle2026uncertainty,
  title = {Uncertainty Quantification in Forecast Comparisons},
  author = {Marc-Oliver Pohle and Tanja Zahn and Sebastian Lerch},
  year = {2026},
  eprint = {2605.03997},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.03997},
}

@article{nai2026cast3,
  title = {Cast3: Translating numerical weather prediction principles into data-driven forecasting},
  author = {Congyi Nai and Baoxiang Pan and Yuan Liang and Xi Chen},
  year = {2026},
  eprint = {2605.01599},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.01599},
}

@article{mcgovern2026extreme,
  title = {Extreme Weather Bench: A framework and benchmark for evaluation of high-impact weather},
  author = {Amy McGovern and Taylor Mandelbaum and Daniel Rothenberg and Nicholas Loveday and Corey Potvin and Montgomery Flora and Linus Magnusson and Eric Gilleland and John Allen},
  year = {2026},
  eprint = {2605.01126},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.01126},
}

@article{ballandies2026calibrating,
  title = {Calibrating Attribution Proxies for Reward Allocation in Participatory Weather Sensing},
  author = {Mark C. Ballandies and Michael T. C. Chiu and Claudio J. Tessone},
  year = {2026},
  eprint = {2604.27944},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.27944},
}

@article{saleem2026pinncast,
  title = {PINN-Cast: Exploring the Role of Continuous-Depth NODE in Transformers and Physics Informed Loss as Soft Physical Constraints in Short-term Weather Forecasting},
  author = {Hira Saleem and Flora Salim and Cormac Purcell},
  year = {2026},
  eprint = {2604.27313},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.27313},
}

@article{hahner2026representing,
  title = {Representing the Surface Ocean in ECMWF's data-driven forecasting system AIFS},
  author = {Sara Hahner and Lorenzo Zampieri and Jean-Raymond Bidlot and Philip Browne and Matthew Chantry and Mariana C. A. Clare and Harrison Cook and Peter Dueben and Rachel Furner and Sarah Keeley and Josh Kousal and Simon Lang and Christian Lessig and Gert Mertes and Kristian Mogensen and Gabriel Moldovan and Charles Pelletier and Florian Pinault and Ana Prieto Nemesio and Baudouin Raoult and Irina Sandu and Mario Santa Cruz and Jakob Schloer and Steffen Tietsche and Hao Zuo},
  year = {2026},
  eprint = {2604.25559},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.25559},
}

@article{polichtchouk2026hybridb,
  title = {Hybrid weather prediction using spectral nudging toward machine-learning forecasts},
  author = {I. Polichtchouk and M. C. A. Clare and M. Chantry and E. Gascón and M. Maier-Gerber and B. Vanniere and S. Lang},
  year = {2026},
  eprint = {2604.22522},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.22522},
}

@article{tempest2026mechanistic,
  title = {Mechanistic Interpretability Tool for AI Weather Models},
  author = {Kirsten I. Tempest and Matthias Beylich and George C. Craig},
  year = {2026},
  eprint = {2604.20467},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.20467},
}

@article{liu2026instabilityaware,
  title = {Instability-Aware Steering of an Extreme Atmospheric River in an AI Weather Foundation Model},
  author = {Moyan Liu and Qin Huang and Upmanu Lall},
  year = {2026},
  eprint = {2604.18906},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.18906},
}

@article{agarwal2026skillful,
  title = {Skillful Global Ocean Emulation and the Role of Correlation-Aware Loss},
  author = {Niraj Agarwal and Timothy A. Smith and Sergey Frolov and Laura C. Slivinski},
  year = {2026},
  eprint = {2604.18727},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.18727},
}

@article{mctaggartcowan2026wpmip,
  title = {WP-MIP: An Artificial Intelligence, Hybrid, and Physically Based Model Intercomparison Project for Weather Prediction},
  author = {Ron McTaggart-Cowan and Linus Magnusson and Inna Polichtchouk and Duncan Ackerley and Martin Koehler and Barbara Casati and Jan-Huey Chen and Debra Hudson and Masashi Ujiie and Nurizana Amir Aziz and Massimo Bonavita and Zied Ben Bouallegue and Catherine de Burgh-Day and Stephane Chamberland and Kyounngmi Cho and Caio A. S. Coelho and Rostislav Fadeev and Manuel Fuentes and Jorge L. Garcia Franco and Claude Gilbert and Bruno S. Guimaraes and Chris Harris and Michelle Harrold and Syed Husain and Molly James and Alex Kaltenbaugh and Marta Koch and Paulo Y. Kubota and Eun-Hee Lee and Chen Li and Wei Li and Weiwei Li and Llorenc Lledo and Nicholas Loveday and Chrstian Lussana and Zubiar Maalick and Mohau J. Mateyisi and Amy McGovern and Koos van der Merwe and Joel Miller and Marion Mittermaier and Richard Mladek and Kathryn Newman and Andre L. O. Neves and John Pill and Roland Potthast and Maheswar Pradhan and Subhrajit Rath and David S. Richardson and Leo Separovic and Michelle Simoes Reboita and Gregor Skok and Ankur Srivastava and Mikhail Tolstykh and Zhuo Wang and Beth J. Woodham and Fanglin Yang and Radomir Zaripov and Gan Zhang and Hongyan Zhu},
  year = {2026},
  eprint = {2604.16643},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.16643},
}

@article{zhdanov2026sparse,
  title = {(Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models},
  author = {Maksim Zhdanov and Ana Lucic and Max Welling and Jan-Willem van de Meent},
  year = {2026},
  eprint = {2604.16429},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.16429},
}

@article{cachay2026ucast,
  title = {U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster},
  author = {Salva Rühling Cachay and Duncan Watson-Parris and Rose Yu},
  year = {2026},
  eprint = {2604.09041},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.09041},
}

@article{trinh2026el,
  title = {El Nino Prediction Based on Weather Forecast and Geographical Time-series Data},
  author = {Viet Trinh and Ha-Vy Luu and Quoc-Khiem Nguyen-Pham and Hung Tong and Thanh-Huyen Tran and Hoai-Nam Nguyen Dang},
  year = {2026},
  eprint = {2604.04998},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.04998},
}

@article{harder2026aifscompo,
  title = {AIFS-COMPO: A Global Data-Driven Atmospheric Composition Forecasting System},
  author = {Paula Harder and Johannes Flemming and Mihai Alexe and Gert Mertes and Baudouin Raoult and Matthew Chantry},
  year = {2026},
  eprint = {2604.03300},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.03300},
}

@article{garg2026recipe,
  title = {The Recipe Matters More Than the Kitchen:Mathematical Foundations of the AI Weather Prediction Pipeline},
  author = {Piyush Garg and Diana R. Gergel and Andrew E. Shao and Galen J. Yacalis},
  year = {2026},
  eprint = {2604.01215},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.01215},
}

@article{delefosse2026superresolving,
  title = {Super-Resolving Coarse-Resolution Weather Forecasts With Flow Matching},
  author = {Aymeric Delefosse and Anastase Charantonis and Dominique Béréziat},
  year = {2026},
  eprint = {2604.00897},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.00897},
}

@article{li2026improving,
  title = {Improving Ensemble Forecasts of Abnormally Deflecting Tropical Cyclones with Fused Atmosphere-Ocean-Terrain Data},
  author = {Qixiang Li and Yuan Zhou and Shuwei Huo and Chong Wang and Xiaofeng Li},
  year = {2026},
  eprint = {2603.29200},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.29200},
}

@article{zhang2026tianjian,
  title = {TianJi:An autonomous AI meteorologist for discovering physical mechanisms in atmospheric science},
  author = {Kaikai Zhang and Xiang Wang and Haoluo Zhao and Nan Chen and Mengyang Yu Jing-Jia Luo and Tao Song and Fan Meng},
  year = {2026},
  eprint = {2603.27738},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.27738},
}

@article{feng2026stretchcast,
  title = {StretchCast: Global-Regional AI Weather Forecasting on Stretched Cubed-Sphere Mesh},
  author = {Jin Feng},
  year = {2026},
  eprint = {2603.27288},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.27288},
}

@article{chen2026evaluating,
  title = {Evaluating data-driven background ensembles covariances from Graphcast: a case study for Hurricane Lee (2023)},
  author = {Zhihong Chen and Xuguang Wang},
  year = {2026},
  eprint = {2603.26703},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.26703},
}

@article{pu2026error,
  title = {Error Growth Dynamic and Predictability of Tropical Cyclone in Machine Learning Weather Prediction Model},
  author = {Jingchen Pu and Mu Mu and Jie Feng and Hao Li},
  year = {2026},
  eprint = {2603.26165},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.26165},
}

@article{subramanian2026neural,
  title = {On Neural Scaling Laws for Weather Emulation through Continual Training},
  author = {Shashank Subramanian and Alexander Kiefer and Arnur Nigmetov and Amir Gholami and Dmitriy Morozov and Michael W. Mahoney},
  year = {2026},
  eprint = {2603.25687},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.25687},
}

@article{kuzhamuratov2026marchuk,
  title = {Marchuk: Efficient Global Weather Forecasting from Mid-Range to Sub-Seasonal Scales via Flow Matching},
  author = {Arsen Kuzhamuratov and Mikhail Zhirnov and Andrey Kuznetsov and Ivan Oseledets and Konstantin Sobolev},
  year = {2026},
  eprint = {2603.24428},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.24428},
}

@article{navarro2026assessing,
  title = {Assessing the Robustness of Climate Foundation Models under No-Analog Distribution Shifts},
  author = {Maria Conchita Agana Navarro and Geng Li and Theo Wolf and Maria Perez-Ortiz},
  year = {2026},
  eprint = {2603.23043},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.23043},
}

@article{niu2026enhancing,
  title = {Enhancing AI-Based Tropical Cyclone Track and Intensity Forecasting via Systematic Bias Correction},
  author = {Peisong Niu and Haifan Zhang and Yang Zhao and Tian Zhou and Ziqing Ma and Wenqiang Shen and Junping Zhao and Huiling Yuan and Liang Sun},
  year = {2026},
  eprint = {2603.22314},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.22314},
}

@article{cheon2026sonny,
  title = {Sonny: Breaking the Compute Wall in Medium-Range Weather Forecasting},
  author = {Minjong Cheon},
  year = {2026},
  eprint = {2603.21284},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.21284},
}

@article{baiman2026watch,
  title = {Watch an AI Weather Model Learn (and Unlearn) Tropical Cyclones},
  author = {Rebecca Baiman and Ankur Mahesh and Elizabeth A. Barnes},
  year = {2026},
  eprint = {2603.20541},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.20541},
}

@article{huang2026datadriven,
  title = {Data-driven ensemble prediction of the global ocean},
  author = {Qiusheng Huang and Xiaohui Zhong and Anboyu Guo and Ziyi Peng and Lei Chen and Hao Li},
  year = {2026},
  eprint = {2603.19591},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.19591},
}

@article{han2026machine,
  title = {Machine Learning-Based Prediction of Heat Index in Selected U.S. Cities},
  author = {Yushan Han and Calen Randall},
  year = {2026},
  eprint = {2603.19488},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.19488},
}

@article{ren2026target,
  title = {Target Concept Tuning Improves Extreme Weather Forecasting},
  author = {Shijie Ren and Xinyue Gu and Ziheng Peng and Haifan Zhang and Peisong Niu and Bo Wu and Xiting Wang and Liang Sun and Jirong Wen},
  year = {2026},
  eprint = {2603.19325},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.19325},
}

@article{witt2026splitting,
  title = {Splitting horizontal and vertical polynomial order in a compatible finite element discretisation for numerical weather prediction},
  author = {Daniel Witt and Thomas Bendall and Jemma Shipton},
  year = {2026},
  eprint = {2603.16571},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.16571},
}

@article{xu2026fuxiweather2,
  title = {FuXiWeather2: Learning accurate atmospheric state estimation for operational global weather forecasting},
  author = {Xiaoze Xu and Xiuyu Sun and Songling Zhu and Xiaohui Zhong and Yuanqing Huang and Zijian Zhu and Jun Liu and Hao Li},
  year = {2026},
  eprint = {2603.15358},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.15358},
}

@article{wu2026agcd,
  title = {AGCD: Agent-Guided Cross-Modal Decoding for Weather Forecasting},
  author = {Jing Wu and Yang Liu and Lin Zhang and Junbo Zeng and Jiabin Wang and Zi Ye and Guowen Li and Shilei Cao and Jiashun Cheng and Fang Wang and Meng Jin and Yerong Feng and Hong Cheng and Yutong Lu and Haohuan Fu and Juepeng Zheng},
  year = {2026},
  eprint = {2603.15260},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.15260},
}

@article{niu2026datadriven,
  title = {A Data-Driven Regional Model for Skillful Medium-Range Typhoon Prediction},
  author = {Zeyi Niu and Wei Huang and Sirong Huang and Zhuo Wang and Mu Mu and Mengqi Yang and Xinhai Han and Haofei Sun and Zhaoyang Huo and Bo Qin},
  year = {2026},
  eprint = {2603.15127},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.15127},
}

@article{liu20263dtcr,
  title = {3DTCR: A Physics-Based Generative Framework for Vortex-Following 3D Reconstruction to Improve Tropical Cyclone Intensity Forecasting},
  author = {Jun Liu and Xiaohui Zhong and Kai Zheng and Jiarui Li and Yifei Li and Tao Zhou and Wenxu Qian and Shun Dai and Ruian Tie and Yangyang Zhao and Hao Li},
  year = {2026},
  eprint = {2603.13049},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.13049},
}

@article{wu2026ai,
  title = {From AI Weather Prediction to Infrastructure Resilience: A Correction-Downscaling Framework for Tropical Cyclone Impacts},
  author = {You Wu and Zhenguo Wang and Naiyu Wang},
  year = {2026},
  eprint = {2603.12828},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.12828},
}

@article{aitken2026designing,
  title = {Designing probabilistic AI monsoon forecasts to inform agricultural decision-making},
  author = {Colin Aitken and Rajat Masiwal and Adam Marchakitus and Katherine Kowal and Mayank Gupta and Tyler Yang and Amir Jina and Pedram Hassanzadeh and William R. Boos and Michael Kremer},
  year = {2026},
  eprint = {2603.07893},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.07893},
}

@article{huang2026evaluating,
  title = {Evaluating the Predictability of Selected Weather Extremes with Aurora, an AI Weather Forecast Model},
  author = {Qin Huang and Moyan Liu and Yeongbin Kwon and Upmanu Lall},
  year = {2026},
  eprint = {2603.06516},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.06516},
}

@article{polichtchouk2026hybrida,
  title = {Hybrid ensemble forecasting combining physics-based and machine-learning predictions through spectral nudging},
  author = {Inna Polichtchouk and Simon Lang and Sarah-Jane Lock and Michael Maier-Gerber and Peter Dueben},
  year = {2026},
  eprint = {2603.05570},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.05570},
}

@article{danner2026twostage,
  title = {Two-Stage Photovoltaic Forecasting: Separating Weather Prediction from Plant-Characteristics},
  author = {Philipp Danner and Hermann de Meer},
  year = {2026},
  eprint = {2603.04132},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.04132},
}

@article{tang2026hvrmet,
  title = {HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis},
  author = {Shuo Tang and Jiadong Zhang and Gengxian Zhou and Qizhao Jin and Qinxuan Wang and Yi Hu and Ning Hu and Hongchang Ren and Lingli He and Shiming Xiang and Jingtao Ding and Jian Xu and Jiaolan Fu and Cheng-Lin Liu},
  year = {2026},
  eprint = {2603.01121},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.01121},
}

@article{liu2026physdiff,
  title = {Phys-Diff: A Physics-Inspired Latent Diffusion Model for Tropical Cyclone Forecasting},
  author = {Lei Liu and Xiaoning Yu and Kang Chen and Jiahui Huang and Tengyuan Liu and Hongwei Zhao and Bin Li},
  year = {2026},
  eprint = {2603.00521},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.00521},
}

@article{yu2026scaling,
  title = {Scaling Laws of Global Weather Models},
  author = {Yuejiang Yu and Langwen Huang and Alexandru Calotoiu and Torsten Hoefler},
  year = {2026},
  eprint = {2602.22962},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.22962},
}

@article{li2026synergistic,
  title = {A Synergistic Approach: Dynamics-AI Ensemble in Tropical Cyclone Forecasting},
  author = {Yonghui Li and Wansuo Duan and Hao Li and Wei Han and Han Zhang and Yinuo Li},
  year = {2026},
  eprint = {2602.22533},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.22533},
}

@article{mureravaud2026mediumrange,
  title = {On Using Medium-Range Ensemble Forecasts for Storm Transposition of Synoptic-Scale Systems in Probable Maximum Precipitation Estimation},
  author = {Mathieu Mure-Ravaud},
  year = {2026},
  eprint = {2602.19233},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.19233},
}

@article{gil2026exploring,
  title = {Exploring Novel Data Storage Approaches for Large-Scale Numerical Weather Prediction},
  author = {Nicolau Manubens Gil},
  year = {2026},
  eprint = {2602.17610},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.17610},
}

@article{schmude2026pde,
  title = {PDE foundation models are skillful AI weather emulators for the Martian atmosphere},
  author = {Johannes Schmude and Sujit Roy and Liping Wang and Theodore van Kessel and Levente Klein and Marcus Freitag and Eloisa Bentivegna and Robert Manson-Sawko and Bjorn Lutjens and Manil Maskey and Campbell Watson and Rahul Ramachandran and Juan Bernabe-Moreno},
  year = {2026},
  eprint = {2602.15004},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.15004},
}

@article{wu2026puyunldm,
  title = {PuYun-LDM: A Latent Diffusion Model for High-Resolution Ensemble Weather Forecasts},
  author = {Lianjun Wu and Shengchen Zhu and Yuxuan Liu and Liuyu Kai and Xiaoduan Feng and Duomin Wang and Wenshuo Liu and Jingxuan Zhang and Kelvin Li and Bin Wang},
  year = {2026},
  eprint = {2602.11807},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.11807},
}

@article{chen2026hierarchical,
  title = {Hierarchical Testing of a Hybrid Machine Learning-Physics Global Atmosphere Model},
  author = {Ziming Chen and L. Ruby Leung and Wenyu Zhou and Jian Lu and Sandro W. Lubis and Ye Liu and Chuan-Chieh Chang and Bryce E. Harrop and Ya Wang and Mingshi Yang and Gan Zhang and Yun Qian},
  year = {2026},
  eprint = {2602.11313},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.11313},
}

@article{yan2026uniphy,
  title = {UniPhy: Unifying Riemannian-Clifford Geometry and Biorthogonal Dynamics for Planetary-Scale Continuous Weather Modeling},
  author = {Ruiqing Yan and Haoyu Deng and Yuhang Shao and Xingbo Du and Jingyuan Wang and Zhengyi Yang},
  year = {2026},
  eprint = {2602.09030},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.09030},
}

@article{masiwal2026decisionoriented,
  title = {Decision-oriented benchmarking to transform AI weather forecast access: Application to the Indian monsoon},
  author = {Rajat Masiwal and Colin Aitken and Adam Marchakitus and Mayank Gupta and Katherine Kowal and Hamid A. Pahlavan and Tyler Yang and Y. Qiang Sun and Michael Kremer and Amir Jina and William R. Boos and Pedram Hassanzadeh},
  year = {2026},
  eprint = {2602.03767},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.03767},
}

@article{antonio2026role,
  title = {Role of the ocean for fast atmospheric evolution revealed by machine learning},
  author = {Bobby Antonio and Kristian Strommen and Hannah M. Christensen},
  year = {2026},
  eprint = {2602.01904},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.01904},
}

@article{chen2026emformer,
  title = {EMFormer: Efficient Multi-Scale Transformer for Accumulative Context Weather Forecasting},
  author = {Hao Chen and Tao Han and Jie Zhang and Song Guo and Fenghua Ling and Lei Bai},
  year = {2026},
  eprint = {2602.01194},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.01194},
}

@article{bouallegue2026what,
  title = {"What is a realistic forecast?" Assessing data-driven weather forecasts, a journey from verification to falsification},
  author = {Zied Ben Bouallègue},
  year = {2026},
  eprint = {2602.00622},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.00622},
}

@article{zhang2026trackdependent,
  title = {Track-Dependent Links between Tropical Cyclones and Extratropical Predictability in Physical and AI Models},
  author = {Gan Zhang},
  year = {2026},
  eprint = {2601.22540},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.22540},
}

@article{tasim2026physics,
  title = {Physics Informed Reconstruction of Four-Dimensional Atmospheric Wind Fields Using Multi-UAS Swarm Observations in a Synthetic Turbulent Environment},
  author = {Abdullah Tasim and Wei Sun},
  year = {2026},
  eprint = {2601.22111},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.22111},
}

@article{pereira2026learning,
  title = {Learning to Advect: A Neural Semi-Lagrangian Architecture for Weather Forecasting},
  author = {Carlos A. Pereira and Stéphane Gaudreault and Valentin Dallerit and Christopher Subich and Shoyon Panday and Siqi Wei and Sasa Zhang and Siddharth Rout and Eldad Haber and Raymond J. Spiteri and David Millard and Emilia Diaconescu},
  year = {2026},
  eprint = {2601.21151},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.21151},
}

@article{kossaifi2026demystifying,
  title = {Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting},
  author = {Jean Kossaifi and Nikola Kovachki and Morteza Mardani and Daniel Leibovici and Suman Ravuri and Ira Shokar and Edoardo Calvello and Mohammad Shoaib Abbas and Peter Harrington and Ashay Subramaniam and Noah Brenowitz and Boris Bonev and Wonmin Byeon and Karsten Kreis and Dale Durran and Arash Vahdat and Mike Pritchard and Jan Kautz},
  year = {2026},
  eprint = {2601.18111},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.18111},
}

@article{gupta2026healda,
  title = {HealDA: Highlighting the importance of initial errors in end-to-end AI weather forecasts},
  author = {Aayush Gupta and Akshay Subramaniam and Michael S. Pritchard and Karthik Kashinath and Sergey Frolov and Kelsey Lieberman and Christopher Miller and Nicholas Silverman and Noah D. Brenowitz},
  year = {2026},
  eprint = {2601.17636},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.17636},
}

@article{sunil2026trustworthy,
  title = {Toward Trustworthy Short-Range Forecasts with AFNO: From Skill Metrics to Conservation Checks},
  author = {Akshay Sunil and B. Deepthi and Muhammed Rashid},
  year = {2026},
  eprint = {2601.15660},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.15660},
}

@article{li2026searth,
  title = {Searth Transformer: A Transformer Architecture Incorporating Earth's Geospheric Physical Priors for Global Mid-Range Weather Forecasting},
  author = {Tianye Li and Qi Liu and Hao Li and Lei Chen and Wencong Cheng and Fei Zheng and Xiangao Xia and Ya Wang and Gang Huang and Weiwei Wang and Xuan Tong and Ziqing Zu and Yi Fang and Shenming Fu and Jiang Jiang and Haochen Li and Mingxing Li and Jiangjiang Xia},
  year = {2026},
  eprint = {2601.09467},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.09467},
}

@article{fang2026efficient,
  title = {Efficient Parameter Calibration of Numerical Weather Prediction Models via Evolutionary Sequential Transfer Optimization},
  author = {Heping Fang and Peng Yang},
  year = {2026},
  eprint = {2601.08663},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.08663},
}

@article{rajeev2026hybrid,
  title = {Hybrid SARIMA LSTM Model for Local Weather Forecasting: A Residual Learning Approach for Data Driven Meteorological Prediction},
  author = {Shreyas Rajeev and Karthik Mudenahalli Ashoka and Amit Mallappa Tiparaddi},
  year = {2026},
  eprint = {2601.07951},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.07951},
}

@article{christensen2026error,
  title = {Error in ERA5 2m Temperature identified using GraphCast},
  author = {Hannah M. Christensen and Jack Barker and Bobby Antonio and Massimo Bonavita and Mohamed Dahoui and Patricia de Rosnay},
  year = {2026},
  eprint = {2601.04701},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.04701},
}

@article{rauba2026probabilistic,
  title = {Probabilistic Transformers for Joint Modeling of Global Weather Dynamics and Decision-Centric Variables},
  author = {Paulius Rauba and Viktor Cikojevic and Fran Bartolic and Sam Levang and Ty Dickinson and Chase Dwelle},
  year = {2026},
  eprint = {2601.03753},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.03753},
}

@article{cooper2025rainfall,
  title = {Rainfall forecasts in daily use over East Africa improved by machine learning},
  author = {Fenwick C. Cooper and Shruti Nath and Andrew T. T. McRae and Bobby Antonio and Antje Weisheimer and Tim Palmer and Masilin Gudoshava and Nishadh Kalladath and Ahmed Amidhun and Jason Kinyua and Hannah Kimani and David Koros and Zacharia Mwai and Christine Maswi and Benard Chanzu and Samrawit Abebe and Bekalu Tamene and Bekele Kebebe and Asaminew Teshome and Florian Pappenberger and Matthew Chantry and Isaac Obai and Jesse Mason},
  year = {2025},
  eprint = {2512.24525},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.24525},
}

@article{macmillan2025mechanistic,
  title = {Towards mechanistic understanding in a data-driven weather model: internal activations reveal interpretable physical features},
  author = {Theodore MacMillan and Nicholas T. Ouellette},
  year = {2025},
  eprint = {2512.24440},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.24440},
}

@article{schreck2025controllable,
  title = {Controllable Probabilistic Forecasting with Stochastic Decomposition Layers},
  author = {John S. Schreck and William E. Chapman and Charlie Becker and David John Gagne and Dhamma Kimpara and Nihanth Cherukuru and Judith Berner and Kirsten J. Mayer and Negin Sobhani},
  year = {2025},
  eprint = {2512.18815},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.18815},
}

@article{evans2025predicting,
  title = {Predicting Forecast Error for the HRRR Using LSTM Neural Networks: A Comparative Study Using New York and Oklahoma State Mesonets},
  author = {David Aaron Evans and Kara J. Sulia and Nick P. Bassill and Chris D. Thorncroft and Jay C. Rothenberger and Lauriana C. Gaudet},
  year = {2025},
  eprint = {2512.14898},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.14898},
}

@article{raeth2025evaluating,
  title = {Evaluating Weather Forecasts from a Decision Maker's Perspective},
  author = {Kornelius Raeth and Nicole Ludwig},
  year = {2025},
  eprint = {2512.14779},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.14779},
}

@article{takeshima2025bridging,
  title = {Bridging Artificial Intelligence and Data Assimilation: The Data-driven Ensemble Forecasting System ClimaX-LETKF},
  author = {Akira Takeshima and Kenta Shiraishi and Atsushi Okazaki and Tadashi Tsuyuki and Shunji Kotsuki},
  year = {2025},
  eprint = {2512.14444},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.14444},
}

@article{vicensmiquel2025diffusionbased,
  title = {A Diffusion-Based Framework for High-Resolution Precipitation Forecasting over CONUS},
  author = {Marina Vicens-Miquel and Amy McGovern and Aaron J. Hill and Efi Foufoula-Georgiou and Clement Guilloteau and Samuel S. P. Shen},
  year = {2025},
  eprint = {2512.09059},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.09059},
}

@article{chen2025fuxinowcast,
  title = {FuXi-Nowcast: Environment-conditioned deep learning for severe convection nowcasting},
  author = {Lei Chen and Zijian Zhu and Xiaoran Zhuang and Tianyuan Qi and Yuxuan Feng and Xiaohui Zhong and Hao Li},
  year = {2025},
  eprint = {2512.08974},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.08974},
}

@article{arif2025forecasting,
  title = {Forecasting Fails: Unveiling Evasion Attacks in Weather Prediction Models},
  author = {Huzaifa Arif and Pin-Yu Chen and Alex Gittens and James Diffenderfer and Bhavya Kailkhura},
  year = {2025},
  eprint = {2512.08832},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.08832},
}

@article{lizerbram2025robustness,
  title = {Robustness Test for AI Forecasting of Hurricane Florence Using FourCastNetv2 and Random Perturbations of the Initial Condition},
  author = {Adam Lizerbram and Shane Stevenson and Iman Khadir and Matthew Tu and Samuel S. P. Shen},
  year = {2025},
  eprint = {2512.05323},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.05323},
}

@article{peduto2025observationdriven,
  title = {Observation-driven correction of numerical weather prediction for marine winds},
  author = {Matteo Peduto and Qidong Yang and Jonathan Giezendanner and Devis Tuia and Sherrie Wang},
  year = {2025},
  eprint = {2512.03606},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.03606},
}

@article{weng2025climatological,
  title = {Climatological benchmarking of AI-generated tropical cyclones},
  author = {Yanmo Weng and Avantika Gori},
  year = {2025},
  eprint = {2511.21792},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.21792},
}

@article{zhou2025concept,
  title = {Concept drift of simple forecast models as a diagnostic of low-frequency, regime-dependent atmospheric reorganisation},
  author = {Haokun Zhou},
  year = {2025},
  eprint = {2511.19638},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.19638},
}

@article{almeida2025predictive,
  title = {On the Predictive Skill of Artificial Intelligence-based Weather Models for Extreme Events using Uncertainty Quantification},
  author = {Rodrigo Almeida and Noelia Otero and Miguel-Ángel Fernández-Torres and Jackie Ma},
  year = {2025},
  eprint = {2511.17176},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.17176},
}

@article{xiong2025bridging,
  title = {Bridging the Gap Between Bayesian Deep Learning and Ensemble Weather Forecasts},
  author = {Xinlei Xiong and Wenbo Hu and Shuxun Zhou and Kaifeng Bi and Lingxi Xie and Ying Liu and Richang Hong and Qi Tian},
  year = {2025},
  eprint = {2511.14218},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.14218},
}

@article{hedayat2025attentionenhanced,
  title = {Attention-Enhanced Convolutional Autoencoder and Structured Delay Embeddings for Weather Prediction},
  author = {Amirpasha Hedayat and Karthik Duraisamy},
  year = {2025},
  eprint = {2511.12682},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.12682},
}

@article{collard2025power,
  title = {Power Ensemble Aggregation for Improved Extreme Event AI Prediction},
  author = {Julien Collard and Pierre Gentine and Tian Zheng},
  year = {2025},
  eprint = {2511.11170},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.11170},
}

@article{schicker2025beyond,
  title = {Beyond Resolution: Multi-Scale Weather and Climate Data for Alpine Renewable Energy in the Digital Twin Era -- First Evaluations and Recommendations},
  author = {Irene Schicker and Marianne Bügelmayer-Blaschek and Annemarie Lexer and Katharina Baier and Kristofer Hasel and Paolo Gazzaneo},
  year = {2025},
  eprint = {2511.05584},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.05584},
}

@article{germain2025improvement,
  title = {Improvement of a neural network convection scheme by including triggering and evaluation in present and future climates},
  author = {Hugo Germain and Blanka Balogh and Olivier Geoffroy and David Saint-Martin},
  year = {2025},
  eprint = {2511.05074},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.05074},
}

@article{afargangerstman2025do,
  title = {Do AI models predict storm impacts as accurately as physics-based models? A case study of the February 2020 storm series over the North Atlantic},
  author = {Hilla Afargan-Gerstman and Rachel W. -Y. Wu and Alice Ferrini and Daniela I. V. Domeisen},
  year = {2025},
  eprint = {2511.01665},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.01665},
}

@article{rucker2025benchmarking,
  title = {Benchmarking Regional Thermodynamic Trends in an AI emulator, ACE2, and a hybrid model, NeuralGCM},
  author = {Katharine Rucker and Ian Baxter and Pedram Hassanzadeh and Tiffany A. Shaw and Hamid A. Pahlavan},
  year = {2025},
  eprint = {2511.00274},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.00274},
}

@article{liu2025adaptive,
  title = {Adaptive Spatio-Temporal Graphs with Self-Supervised Pretraining for Multi-Horizon Weather Forecasting},
  author = {Yao Liu},
  year = {2025},
  eprint = {2511.00049},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.00049},
}

@article{lancelin2025aiboosted,
  title = {AI-boosted rare event sampling to characterize extreme weather},
  author = {Amaury Lancelin and Alex Wikner and Laurent Dubus and Clément Le Priol and Dorian S. Abbot and Freddy Bouchet and Pedram Hassanzadeh and Jonathan Weare},
  year = {2025},
  eprint = {2510.27066},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.27066},
}

@article{masi2025safe,
  title = {SAFE: A Novel Approach to AI Weather Evaluation through Stratified Assessments of Forecasts over Earth},
  author = {Nick Masi and Randall Balestriero},
  year = {2025},
  eprint = {2510.26099},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.26099},
}

@article{loveday2025evaluating,
  title = {Evaluating Extreme Precipitation Forecasts: A Threshold-Weighted, Spatial Verification Approach for Comparing an AI Weather Prediction Model Against a High-Resolution NWP Model},
  author = {Nicholas Loveday and Tracy Hertneky},
  year = {2025},
  eprint = {2510.25045},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.25045},
}

@article{liu2025revealing,
  title = {Revealing the Potential of Learnable Perturbation Ensemble Forecast Model for Tropical Cyclone Prediction},
  author = {Jun Liu and Tao Zhou and Jiarui Li and Xiaohui Zhong and Peng Zhang and Jie Feng and Lei Chen and Hao Li},
  year = {2025},
  eprint = {2510.23794},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.23794},
}

@article{bailie2025hierarchical,
  title = {Hierarchical Graph Networks for Accurate Weather Forecasting via Lightweight Training},
  author = {Thomas Bailie and S. Karthik Mukkavilli and Varvara Vetrova and Yun Sing Koh},
  year = {2025},
  eprint = {2510.22094},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.22094},
}

@article{xiong2025csupcast,
  title = {CSU-PCAST: A Dual-Branch Transformer Framework for medium-range ensemble Precipitation Forecasting},
  author = {Tianyi Xiong and Haonan Chen and Kelly Mahoney and Jingyin Tang and Tim Smith and Janice Bytheway},
  year = {2025},
  eprint = {2510.20769},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.20769},
}

@article{boucher2025learning,
  title = {Learning Coupled Earth System Dynamics with GraphDOP},
  author = {Eulalie Boucher and Mihai Alexe and Peter Lean and Ewan Pinnington and Simon Lang and Patrick Laloyaux and Lorenzo Zampieri and Patricia de Rosnay and Niels Bormann and Anthony McNally},
  year = {2025},
  eprint = {2510.20416},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.20416},
}

@article{dodson2025signature,
  title = {Signature Kernel Scoring Rule: A Spatio-Temporal Diagnostic for Probabilistic Weather Forecasting},
  author = {Archer Dodson and Ritabrata Dutta},
  year = {2025},
  eprint = {2510.19110},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.19110},
}

@article{sun2025deploying,
  title = {Deploying Atmospheric and Oceanic AI Models on Chinese Hardware and Framework: Migration Strategies, Performance Optimization and Analysis},
  author = {Yuze Sun and Wentao Luo and Yanfei Xiang and Jiancheng Pan and Jiahao Li and Quan Zhang and Xiaomeng Huang},
  year = {2025},
  eprint = {2510.17852},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.17852},
}

@article{chobtham2025leveraging,
  title = {Leveraging Teleconnections with Physics-Informed Graph Attention Networks for Long-Range Extreme Rainfall Forecasting in Thailand},
  author = {Kiattikun Chobtham and Kanoksri Sarinnapakorn and Kritanai Torsri and Prattana Deeprasertkul and Jirawan Kamma},
  year = {2025},
  eprint = {2510.12328},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.12328},
}

@article{deng2025adversarial,
  title = {Adversarial Attacks on Downstream Weather Forecasting Models: Application to Tropical Cyclone Trajectory Prediction},
  author = {Yue Deng and Francisco Santos and Pang-Ning Tan and Lifeng Luo},
  year = {2025},
  eprint = {2510.10140},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.10140},
}

@article{tian2025arrow,
  title = {ARROW: An Adaptive Rollout and Routing Method for Global Weather Forecasting},
  author = {Jindong Tian and Yifei Ding and Ronghui Xu and Hao Miao and Chenjuan Guo and Bin Yang},
  year = {2025},
  eprint = {2510.09734},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.09734},
}

@article{srivastava2025controlaugmented,
  title = {Control-Augmented Autoregressive Diffusion for Data Assimilation},
  author = {Prakhar Srivastava and Farrin Marouf Sofian and Francesco Immorlano and Kushagra Pandey and Stephan Mandt},
  year = {2025},
  eprint = {2510.06637},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.06637},
}

@article{baxter2025benchmarking,
  title = {Benchmarking atmospheric circulation variability in an AI emulator, ACE2, and a hybrid model, NeuralGCM},
  author = {Ian Baxter and Hamid Pahlavan and Pedram Hassanzadeh and Katharine Rucker and Tiffany Shaw},
  year = {2025},
  eprint = {2510.04466},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.04466},
}

@article{varambally2025zephyrus,
  title = {Zephyrus: An Agentic Framework for Weather Science},
  author = {Sumanth Varambally and Marshall Fisher and Jas Thakker and Yiwei Chen and Zhirui Xia and Yasaman Jafari and Ruijia Niu and Manas Jain and Veeramakali Vignesh Manivannan and Zachary Novack and Luyu Han and Srikar Eranky and Salva Rühling Cachay and Taylor Berg-Kirkpatrick and Duncan Watson-Parris and Yi-An Ma and Rose Yu},
  year = {2025},
  eprint = {2510.04017},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.04017},
}

@article{yao2025deep,
  title = {Deep learning the sources of MJO predictability: a spectral view of learned features},
  author = {Lin Yao and Da Yang and James P. C. Duncan and Ashesh Chattopadhyay and Pedram Hassanzadeh and Wahid Bhimji and Bin Yu},
  year = {2025},
  eprint = {2510.03582},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.03582},
}

@article{zhang2025equilibrium,
  title = {The Equilibrium Response of Atmospheric Machine-Learning Models to Uniform Sea Surface Temperature Warming},
  author = {Bosong Zhang and Timothy M. Merlis},
  year = {2025},
  eprint = {2510.02415},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.02415},
}

@article{s2025multidata,
  title = {Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting},
  author = {Saranya Ganesh S and Frederick Iat-Hin Tam and Milton S. Gomez and Marie McGraw and Mark DeMaria and Kate Musgrave and Jakob Runge and Tom Beucler},
  year = {2025},
  eprint = {2510.02050},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.02050},
}

@article{stock2025swift,
  title = {Swift: An Autoregressive Consistency Model for Efficient Weather Forecasting},
  author = {Jason Stock and Troy Arcomano and Rao Kotamarthi},
  year = {2025},
  eprint = {2509.25631},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.25631},
}

@article{bodnar2025weather,
  title = {A Weather Foundation Model for the Power Grid},
  author = {Cristian Bodnar and Raphaël Rousseau-Rizzi and Nikhil Shankar and James Merleau and Stylianos Flampouris and Guillem Candille and Slavica Antic and François Miralles and Jayesh K. Gupta},
  year = {2025},
  eprint = {2509.25268},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.25268},
}

@article{huang2025dpsformer,
  title = {DPSformer: A long-tail-aware model for improving heavy rainfall prediction},
  author = {Zenghui Huang and Ting Shu and Zhonglei Wang and Yang Lu and Yan Yan and Wei Zhong and Hanzi Wang},
  year = {2025},
  eprint = {2509.25208},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.25208},
}

@article{lo2025evaluation,
  title = {Evaluation of Machine and Deep Learning Techniques for Cyclone Trajectory Regression and Status Classification by Time Series Data},
  author = {Ethan Zachary Lo and Dan Chie-Tien Lo},
  year = {2025},
  eprint = {2509.24146},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.24146},
}

@article{landsberg2025forecasting,
  title = {Forecasting the Future with Yesterday's Climate: Temperature Bias in AI Weather and Climate Models},
  author = {Jacob B. Landsberg and Elizabeth A. Barnes},
  year = {2025},
  eprint = {2509.22359},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.22359},
}

@article{cao2025taskadaptive,
  title = {Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models},
  author = {Shilei Cao and Hehai Lin and Jiashun Cheng and Yang Liu and Guowen Li and Xuehe Wang and Juepeng Zheng and Haoyuan Liang and Meng Jin and Chengwei Qin and Hong Cheng and Haohuan Fu},
  year = {2025},
  eprint = {2509.22020},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.22020},
}

@article{qu2025accurate,
  title = {Accurate typhoon intensity forecasts using a non-iterative spatiotemporal transformer model},
  author = {Hongyu Qu and Hongxiong Xu and Lin Dong and Chunyi Xiang and Gaozhen Nie},
  year = {2025},
  eprint = {2509.21349},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.21349},
}

@article{zheng2025mesh,
  title = {Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting},
  author = {Zinan Zheng and Yang Liu and Jia Li},
  year = {2025},
  eprint = {2509.20911},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.20911},
}

@article{chen2025s2transformer,
  title = {S$^2$Transformer: Scalable Structured Transformers for Global Station Weather Forecasting},
  author = {Hongyi Chen and Xiucheng Li and Xinyang Chen and Yun Cheng and Jing Li and Kehai Chen and Liqiang Nie},
  year = {2025},
  eprint = {2509.19648},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.19648},
}

@article{holmberg2025graphbased,
  title = {Graph-based Neural Space Weather Forecasting},
  author = {Daniel Holmberg and Ivan Zaitsev and Markku Alho and Ioanna Bouri and Fanni Franssila and Haewon Jeong and Minna Palmroth and Teemu Roos},
  year = {2025},
  eprint = {2509.19605},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.19605},
}

@article{moldovan2025update,
  title = {An update to ECMWF's machine-learned weather forecast model AIFS},
  author = {Gabriel Moldovan and Ewan Pinnington and Ana Prieto Nemesio and Simon Lang and Zied Ben Bouallègue and Jesper Dramsch and Mihai Alexe and Mario Santa Cruz and Sara Hahner and Harrison Cook and Helen Theissen and Mariana Clare and Cathal O'Brien and Jan Polster and Linus Magnusson and Gert Mertes and Florian Pinault and Baudouin Raoult and Patricia de Rosnay and Richard Forbes and Matthew Chantry},
  year = {2025},
  eprint = {2509.18994},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.18994},
}

@article{savary2025trainingfree,
  title = {Training-Free Data Assimilation with GenCast},
  author = {Thomas Savary and François Rozet and Gilles Louppe},
  year = {2025},
  eprint = {2509.18811},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.18811},
}

@article{daub2025technical,
  title = {Technical overview and architecture of the FastNet Machine Learning weather prediction model, version 1.0},
  author = {Eric G. Daub and Tom Dunstan and Thusal Bennett and Matthew Burnand and James Chappell and Alejandro Coca-Castro and Noushin Eftekhari and J. Scott Hosking and Manvendra Janmaijaya and Jon Lillis and David Salvador-Jasin and Nathan Simpson and Oliver T Strickson and Ryan Sze-Yin Chan and Mohamad Elmasri and Lydia Allegranza France and Sam Madge and Aled Owen and James Robinson and Adam A. Scaife and David Walters and Peter Yatsyshin and Theo McCaie and Levan Bokeria and Hannah Brown and Tom Dodds and David Llewellyn-Jones and Sophia Moreton and Tom Potter and Iain Stenson and Louisa van Zeeland and Karina Bett-Williams and Kirstine Ida Dale},
  year = {2025},
  eprint = {2509.17658},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.17658},
}

@article{dunstan2025fastnet,
  title = {FastNet: Improving the physical consistency of machine-learning weather prediction models through loss function design},
  author = {Tom Dunstan and Oliver Strickson and Thusal Bennett and Jack Bowyer and Matthew Burnand and James Chappell and Alejandro Coca-Castro and Kirstine Ida Dale and Eric G. Daub and Noushin Eftekhari and Manvendra Janmaijaya and Jon Lillis and David Salvador-Jasin and Nathan Simpson and Ryan Sze-Yin Chan and Mohamad Elmasri and Lydia Allegranza France and Sam Madge and Levan Bokeria and Hannah Brown and Tom Dodds and Anna-Louise Ellis and David Llewellyn-Jones and Theo McCaie and Sophia Moreton and Tom Potter and James Robinson and Adam A. Scaife and Iain Stenson and David Walters and Karina Bett-Williams and Louisa van Zeeland and Peter Yatsyshin and J. Scott Hosking},
  year = {2025},
  eprint = {2509.17601},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.17601},
}

@article{he2025flowcastode,
  title = {FlowCast-ODE: Continuous Hourly Weather Forecasting with Dynamic Flow Matching and ODE Integration},
  author = {Shuangshuang He and Yuanting Zhang and Hongli Liang and Qingye Meng and Xingyuan Yuan},
  year = {2025},
  eprint = {2509.14775},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.14775},
}

@article{valencia2025dataefficient,
  title = {Data-Efficient Ensemble Weather Forecasting with Diffusion Models},
  author = {Kevin Valencia and Ziyang Liu and Justin Cui},
  year = {2025},
  eprint = {2509.11047},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.11047},
}

@article{baiman2025how,
  title = {How does an AI Weather Model Learn to Forecast Extreme Weather?},
  author = {Rebecca Baiman and Elizabeth A. Barnes and Ankur Mahesh},
  year = {2025},
  eprint = {2509.10639},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.10639},
}

@article{chakraborty2025mowe,
  title = {MoWE : A Mixture of Weather Experts},
  author = {Dibyajyoti Chakraborty and Romit Maulik and Peter Harrington and Dallas Foster and Mohammad Amin Nabian and Sanjay Choudhry},
  year = {2025},
  eprint = {2509.09052},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.09052},
}

@article{antonio2025seasonal,
  title = {Seasonal forecasting using the GenCast probabilistic machine learning model},
  author = {Bobby Antonio and Kristian Strommen and Hannah M. Christensen},
  year = {2025},
  eprint = {2509.06457},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.06457},
}

@article{ganji2025distillation,
  title = {Distillation of CNN Ensemble Results for Enhanced Long-Term Prediction of the ENSO Phenomenon},
  author = {Saghar Ganji and Mohammad Naisipour and Alireza Hassani and Arash Adib},
  year = {2025},
  eprint = {2509.06227},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.06227},
}

@article{gupta2025mausam,
  title = {MAUSAM: An Observations-focused assessment of Global AI Weather Prediction Models During the South Asian Monsoon},
  author = {Aman Gupta and Aditi Sheshadri and Dhruv Suri},
  year = {2025},
  eprint = {2509.01879},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.01879},
}

@article{silva2025exploring,
  title = {Exploring Quantum Machine Learning for Weather Forecasting},
  author = {Maria Heloísa F. da Silva and Gleydson F. de Jesus and Christiano M. S. Nascimento and Valéria L. da Silva and Clebson Cruz},
  year = {2025},
  eprint = {2509.01422},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.01422},
}

@article{ni2025huracan,
  title = {Huracan: A skillful end-to-end data-driven system for ensemble data assimilation and weather prediction},
  author = {Zekun Ni and Jonathan Weyn and Hang Zhang and Yanfei Xiang and Jiang Bian and Weixin Jin and Kit Thambiratnam and Qi Zhang and Haiyu Dong and Hongyu Sun},
  year = {2025},
  eprint = {2508.18486},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.18486},
}

@article{gomez2025global,
  title = {Global Forecasting of Tropical Cyclone Intensity Using Neural Weather Models},
  author = {Milton Gomez and Louis Poulain--Auzeau and Alexis Berne and Tom Beucler},
  year = {2025},
  eprint = {2508.17903},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.17903},
}

@article{niu2025intelligent,
  title = {Intelligent Shanghai Typhoon Model (ISTM): A generative probabilistic emulator for typhoon hybrid modeling},
  author = {Zeyi Niu and Wei Huang and Sirong Huang and Bo Qin and Mengqi Yang and Haofei Sun and Zhaoyang Huo and Haixia Xiao},
  year = {2025},
  eprint = {2508.16851},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.16851},
}

@article{tie2025generative,
  title = {Generative artificial intelligence improves projections of climate extremes},
  author = {Ruian Tie and Xiaohui Zhong and Zhengyu Shi and Hao Li and Bin Chen and Jun Liu and Wu Libo},
  year = {2025},
  eprint = {2508.16396},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.16396},
}

@article{guo2025fuxitc,
  title = {FuXi-TC: A generative framework integrating deep learning and physics-based models for improved tropical cyclone forecasts},
  author = {Shan Guo and Lei Chen and Yangyang Zhao and Yuetan Lin and Zeyi Niu and Xinyan Zhang and Ziyao Sun and Xiaohui Zhong and Hao Li},
  year = {2025},
  eprint = {2508.16168},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.16168},
}

@article{cao2025enhanced,
  title = {Enhanced predictions of the Madden-Julian oscillation using the FuXi-S2S machine learning model: Insights into physical mechanisms},
  author = {Can Cao and Xiaohui Zhong and Lei Chen and Zhiwei Wua and Hao Li},
  year = {2025},
  eprint = {2508.16041},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.16041},
}

@article{zhang2025numerical,
  title = {Numerical models outperform AI weather forecasts of record-breaking extremes},
  author = {Zhongwei Zhang and Erich Fischer and Jakob Zscheischler and Sebastian Engelke},
  year = {2025},
  eprint = {2508.15724},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.15724},
}

@article{roy2025suryabench,
  title = {SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction},
  author = {Sujit Roy and Dinesha V. Hegde and Johannes Schmude and Amy Lin and Vishal Gaur and Rohit Lal and Kshitiz Mandal and Talwinder Singh and Andrés Muñoz-Jaramillo and Kang Yang and Chetraj Pandey and Jinsu Hong and Berkay Aydin and Ryan McGranaghan and Spiridon Kasapis and Vishal Upendran and Shah Bahauddin and Daniel da Silva and Marcus Freitag and Iksha Gurung and Nikolai Pogorelov and Campbell Watson and Manil Maskey and Juan Bernabe-Moreno and Rahul Ramachandran},
  year = {2025},
  eprint = {2508.14107},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.14107},
}

@article{he2025radarqa,
  title = {RadarQA: Multi-modal Quality Analysis of Weather Radar Forecasts},
  author = {Xuming He and Zhiyuan You and Junchao Gong and Couhua Liu and Xiaoyu Yue and Peiqin Zhuang and Wenlong Zhang and Lei Bai},
  year = {2025},
  eprint = {2508.12291},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.12291},
}

@article{lee2025exploring,
  title = {Exploring Multimodal AI Reasoning for Meteorological Forecasting from Skew-T Diagrams},
  author = {ChangJae Lee and Heecheol Yang and Jonghak Choi},
  year = {2025},
  eprint = {2508.12198},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.12198},
}

@article{umar2025decentralized,
  title = {Decentralized Weather Forecasting via Distributed Machine Learning and Blockchain-Based Model Validation},
  author = {Rilwan Umar and Aydin Abadi and Basil Aldali and Benito Vincent and Elliot A. J. Hurley and Hotoon Aljazaeri and Jamie Hedley-Cook and Jamie-Lee Bell and Lambert Uwuigbusun and Mujeeb Ahmed and Shishir Nagaraja and Suleiman Sabo and Weaam Alrbeiqi},
  year = {2025},
  eprint = {2508.09299},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.09299},
}

@article{tang2025meteorpred,
  title = {MeteorPred: A Meteorological Multimodal Large Model and Dataset for Severe Weather Event Prediction},
  author = {Shuo Tang and Jian Xu and Jiadong Zhang and Yi Chen and Qizhao Jin and Lingdong Shen and Chenglin Liu and Shiming Xiang},
  year = {2025},
  eprint = {2508.06859},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.06859},
}

@article{ni2025uniextreme,
  title = {UniExtreme: A Universal Foundation Model for Extreme Weather Forecasting},
  author = {Hang Ni and Weijia Zhang and Hao Liu},
  year = {2025},
  eprint = {2508.01426},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2508.01426},
}

@article{inoue2025cnnbased,
  title = {CNN-based Surface Temperature Forecasts with Ensemble Numerical Weather Prediction},
  author = {Takuya Inoue and Takuya Kawabata},
  year = {2025},
  eprint = {2507.18937},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.18937},
}

@article{kikuchi2025weatheraware,
  title = {Weather-Aware AI Systems versus Route-Optimization AI: A Comprehensive Analysis of AI Applications in Transportation Productivity},
  author = {Tatsuru Kikuchi},
  year = {2025},
  eprint = {2507.17099},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.17099},
}

@article{bonev2025fourcastnet,
  title = {FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale},
  author = {Boris Bonev and Thorsten Kurth and Ankur Mahesh and Mauro Bisson and Jean Kossaifi and Karthik Kashinath and Anima Anandkumar and William D. Collins and Michael S. Pritchard and Alexander Keller},
  year = {2025},
  eprint = {2507.12144},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.12144},
}

@article{cheon2025modernizing,
  title = {Modernizing CNN-based Weather Forecast Model towards Higher Computational Efficiency},
  author = {Minjong Cheon and Eunhan Goo and Su-Hyeon Shin and Muhammad Ahmed and Hyungjun Kim},
  year = {2025},
  eprint = {2507.10893},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.10893},
}

@article{wang2025xichen,
  title = {XiChen: A global weather observation-to-forecast machine learning system via four-dimensional variational gradient-guided flexible assimilation},
  author = {Wuxin Wang and Weicheng Ni and Lilan Huang and Tao Hao and Ben Fei and Shuo Ma and Taikang Yuan and Yanlai Zhao and Kefeng Deng and Xiaoyong Li and Hongze Leng and Boheng Duan and Lei Bai and Weimin Zhang and Junqiang Song and Kaijun Ren},
  year = {2025},
  eprint = {2507.09202},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.09202},
}

@article{jalan2025intraseasonal,
  title = {Intraseasonal Equatorial Kelvin and Rossby Waves in Modern AI-ML Models},
  author = {Shrutee Jalan and Jai Sukhatme},
  year = {2025},
  eprint = {2507.07952},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.07952},
}

@article{kieckhefen2025jigsaw,
  title = {Jigsaw: Training Multi-Billion-Parameter AI Weather Models with Optimized Model Parallelism},
  author = {Deifilia Kieckhefen and Markus Götz and Lars H. Heyen and Achim Streit and Charlotte Debus},
  year = {2025},
  eprint = {2507.05753},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.05753},
}

@article{holmberg2025accurate,
  title = {Accurate Mediterranean Sea forecasting via graph-based deep learning},
  author = {Daniel Holmberg and Emanuela Clementi and Italo Epicoco and Teemu Roos},
  year = {2025},
  eprint = {2506.23900},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.23900},
}

@article{winkler2025arnoldi,
  title = {Arnoldi Singular Vector perturbations for machine learning weather prediction},
  author = {Jens Winkler and Michael Denhard},
  year = {2025},
  eprint = {2506.22450},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.22450},
}

@article{yang2025first,
  title = {The First Compute Arms Race: the Early History of Numerical Weather Prediction},
  author = {Charles Yang},
  year = {2025},
  eprint = {2506.21816},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.21816},
}

@article{cachay2025elucidated,
  title = {Elucidated Rolling Diffusion Models for Probabilistic Forecasting of Complex Dynamics},
  author = {Salva Rühling Cachay and Miika Aittala and Karsten Kreis and Noah Brenowitz and Arash Vahdat and Morteza Mardani and Rose Yu},
  year = {2025},
  eprint = {2506.20024},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.20024},
}

@article{hu2025geometryaware,
  title = {A Geometry-Aware AI Emulator for the Coupled Whole Atmosphere from Earth Surface to the Ionosphere and Thermosphere},
  author = {Jiahui Hu and Wenjun Dong},
  year = {2025},
  eprint = {2506.19340},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.19340},
}

@article{lehmann2025finetuning,
  title = {Finetuning a Weather Foundation Model with Lightweight Decoders for Unseen Physical Processes},
  author = {Fanny Lehmann and Firat Ozdemir and Benedikt Soja and Torsten Hoefler and Siddhartha Mishra and Sebastian Schemm},
  year = {2025},
  eprint = {2506.19088},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.19088},
}

@article{li2025typhoformer,
  title = {TyphoFormer: Language-Augmented Transformer for Accurate Typhoon Track Forecasting},
  author = {Lincan Li and Eren Erman Ozguven and Yue Zhao and Guang Wang and Yiqun Xie and Yushun Dong},
  year = {2025},
  eprint = {2506.17609},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.17609},
}

@article{sudharsan2025utgraphcast,
  title = {UT-GraphCast Hindcast Dataset: A Global AI Forecast Archive from UT Austin for Weather and Climate Applications},
  author = {Naveen Sudharsan and Manmeet Singh and Harsh Kamath and Hassan Dashtian and Clint Dawson and Zong-Liang Yang and Dev Niyogi},
  year = {2025},
  eprint = {2506.17453},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.17453},
}

@article{zambon2025peakweather,
  title = {PeakWeather: MeteoSwiss Weather Station Measurements for Spatiotemporal Deep Learning},
  author = {Daniele Zambon and Michele Cattaneo and Ivan Marisca and Jonas Bhend and Daniele Nerini and Cesare Alippi},
  year = {2025},
  eprint = {2506.13652},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.13652},
}

@article{perkan2025forecast,
  title = {Forecast error diagnostics in neural weather models},
  author = {Uros Perkan and Ziga Zaplotnik and Gregor Skok},
  year = {2025},
  eprint = {2506.11987},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.11987},
}

@article{lang2025multiscale,
  title = {A multi-scale loss formulation for learning a probabilistic model with proper score optimisation},
  author = {Simon Lang and Martin Leutbecher and Pedro Maciel},
  year = {2025},
  eprint = {2506.10868},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.10868},
}

@article{alet2025skillful,
  title = {Skillful joint probabilistic weather forecasting from marginals},
  author = {Ferran Alet and Ilan Price and Andrew El-Kadi and Dominic Masters and Stratis Markou and Tom R. Andersson and Jacklynn Stott and Remi Lam and Matthew Willson and Alvaro Sanchez-Gonzalez and Peter Battaglia},
  year = {2025},
  eprint = {2506.10772},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.10772},
}

@article{cheon2025atmosmj,
  title = {AtmosMJ: Revisiting Gating Mechanism for AI Weather Forecasting Beyond the Year Scale},
  author = {Minjong Cheon},
  year = {2025},
  eprint = {2506.09733},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.09733},
}

@article{zhuang2025ladcast,
  title = {LaDCast: A Latent Diffusion Model for Medium-Range Ensemble Weather Forecasting},
  author = {Yilin Zhuang and Karthik Duraisamy},
  year = {2025},
  eprint = {2506.09193},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.09193},
}

@article{subramaniam2025imposing,
  title = {Imposing the Fundamental Dynamical Constraint of Hydrostatic Balance to Improve Global ML Weather Prediction},
  author = {Akshay Subramaniam and Dale Durran and David Pruitt and Nathaniel Cresswell-Clay and William Yik},
  year = {2025},
  eprint = {2506.08285},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.08285},
}

@article{geng2025fuxiair,
  title = {FuXi-Air: Urban Air Quality Forecasting Based on Emission-Meteorology-Pollutant multimodal Machine Learning},
  author = {Zhixin Geng and Xu Fan and Xiqiao Lu and Yan Zhang and Guangyuan Yu and Cheng Huang and Qian Wang and Yuewu Li and Weichun Ma and Qi Yu and Libo Wu and Hao Li},
  year = {2025},
  eprint = {2506.07616},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.07616},
}

@article{millard2025def,
  title = {DEF: Diffusion-augmented Ensemble Forecasting},
  author = {David Millard and Arielle Carr and Stéphane Gaudreault and Ali Baheri},
  year = {2025},
  eprint = {2506.07324},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.07324},
}

@article{chen2025meteorologicallyinformed,
  title = {Meteorologically-Informed Adaptive Conformal Prediction for Tropical Cyclone Intensity Forecasting},
  author = {Xuepeng Chen and Jing-Jia Luo and Qingqing Li and Fan Meng},
  year = {2025},
  eprint = {2506.06638},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.06638},
}

@article{lee2025improving,
  title = {Improving Post-Processing for Quantitative Precipitation Forecasting Using Deep Learning: Learning Precipitation Physics from High-Resolution Observations},
  author = {ChangJae Lee and Heecheol Yang and Byeonggwon Kim},
  year = {2025},
  eprint = {2506.03842},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.03842},
}

@article{gneiting2025probabilistic,
  title = {Probabilistic measures afford fair comparisons of AIWP and NWP model output},
  author = {Tilmann Gneiting and Tobias Biegert and Kristof Kraus and Eva-Maria Walz and Alexander I. Jordan and Sebastian Lerch},
  year = {2025},
  eprint = {2506.03744},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.03744},
}

@article{huang2025fuxiocean,
  title = {FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution},
  author = {Qiusheng Huang and Yuan Niu and Xiaohui Zhong and Anboyu Guo and Lei Chen and Dianjun Zhang and Xuefeng Zhang and Hao Li},
  year = {2025},
  eprint = {2506.03210},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.03210},
}

@article{akazan2025localized,
  title = {Localized Weather Prediction Using Kolmogorov-Arnold Network-Based Models and Deep RNNs},
  author = {Ange-Clement Akazan and Verlon Roel Mbingui and Gnankan Landry Regis N'guessan and Issa Karambal},
  year = {2025},
  eprint = {2505.22686},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.22686},
}

@article{linander2025pear,
  title = {PEAR: Equal Area Weather Forecasting on the Sphere},
  author = {Hampus Linander and Tage Tykesson and Pietro Rosso and Christoffer Petersson and Daniel Persson and Jan E. Gerken},
  year = {2025},
  eprint = {2505.17720},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.17720},
}

@article{niu2025utilizing,
  title = {Utilizing Strategic Pre-training to Reduce Overfitting: Baguan -- A Pre-trained Weather Forecasting Model},
  author = {Peisong Niu and Ziqing Ma and Tian Zhou and Weiqi Chen and Lefei Shen and Rong Jin and Liang Sun},
  year = {2025},
  eprint = {2505.13873},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.13873},
}

@article{deng2025fable,
  title = {FABLE: A Localized, Targeted Adversarial Attack on Weather Forecasting Models},
  author = {Yue Deng and Asadullah Hill Galib and Xin Lan and Jack Gunn and Pang-Ning Tan and Lifeng Luo},
  year = {2025},
  eprint = {2505.12167},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.12167},
}

@article{hua2025improving,
  title = {Improving Medium Range Severe Weather Prediction through Transformer Post-processing of AI Weather Forecasts},
  author = {Zhanxiang Hua and Ryan Sobash and David John Gagne and Yingkai Sha and Alexandra Anderson-Frey},
  year = {2025},
  eprint = {2505.11750},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.11750},
}

@article{sun2025predicting,
  title = {Predicting Beyond Training Data via Extrapolation versus Translocation: AI Weather Models and Dubai's Unprecedented 2024 Rainfall},
  author = {Y. Qiang Sun and Pedram Hassanzadeh and Tiffany Shaw and Hamid A. Pahlavan},
  year = {2025},
  eprint = {2505.10241},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.10241},
}

@article{wu2025applying,
  title = {Applying the ACE2 Emulator to SST Green's Functions for the E3SMv3 Global Atmosphere Model},
  author = {Elynn Wu and Finn Rebassoo and Pappu Paul and Cristian Proistosescu and Jacqueline Nugent and Daniel McCoy and Peter Caldwell and Christopher S. Bretherton},
  year = {2025},
  eprint = {2505.08742},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.08742},
}

@article{zheng2025physicsassisted,
  title = {Physics-Assisted and Topology-Informed Deep Learning for Weather Prediction},
  author = {Jiaqi Zheng and Qing Ling and Yerong Feng},
  year = {2025},
  eprint = {2505.04918},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.04918},
}

@article{gallusser2025exploring,
  title = {Exploring Design Choices for Autoregressive Deep Learning Climate Models},
  author = {Florian Gallusser and Simon Hentschel and Anna Krause and Andreas Hotho},
  year = {2025},
  eprint = {2505.02506},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.02506},
}

@article{ennis2025turning,
  title = {Turning Up the Heat: Assessing 2-m Temperature Forecast Errors in AI Weather Prediction Models During Heat Waves},
  author = {Kelsey E. Ennis and Elizabeth A. Barnes and Marybeth C. Arcodia and Martin A. Fernandez and Eric D. Maloney},
  year = {2025},
  eprint = {2504.21195},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.21195},
}

@article{niu2025machine,
  title = {Machine Learning (ML)-Physics Fusion Model Outperforms Both Physics-Only and ML-Only Models in Typhoon Predictions},
  author = {Zeyi Niu and Wei Huang and Hao Li and Xuliang Fan and Yuhua Yang and Mengqi Yang and Bo Qin},
  year = {2025},
  eprint = {2504.20852},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.20852},
}

@article{vonich2025atmospheric,
  title = {Atmospheric Predictability Beyond 30 Days with Machine Learning},
  author = {P. Trent Vonich and Gregory J. Hakim},
  year = {2025},
  eprint = {2504.20238},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.20238},
}

@article{cheon2025mjolnir,
  title = {Mjölnir: A Deep Learning Parametrization Framework for Global Lightning Flash Density},
  author = {Minjong Cheon},
  year = {2025},
  eprint = {2504.19822},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.19822},
}

@article{khadir2025democracy,
  title = {Democracy of AI Numerical Weather Models: An Example of Global Forecasting with FourCastNetv2 Made by a University Research Lab Using GPU},
  author = {Iman Khadir and Shane Stevenson and Henry Li and Kyle Krick and Abram Burrows and David Hall and Stan Posey and Samuel S. P. Shen},
  year = {2025},
  eprint = {2504.17028},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.17028},
}

@article{imgrund2025adversarial,
  title = {Adversarial Observations in Weather Forecasting},
  author = {Erik Imgrund and Thorsten Eisenhofer and Konrad Rieck},
  year = {2025},
  eprint = {2504.15942},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.15942},
}

@article{li2025tianquans2s,
  title = {TianQuan-S2S: A Subseasonal-to-Seasonal Global Weather Model via Incorporate Climatology State},
  author = {Guowen Li and Xintong Liu and Yang Liu and Mengxuan Chen and Shilei Cao and Xuehe Wang and Juepeng Zheng and Jinxiao Zhang and Haoyuan Liang and Lixian Zhang and Jiuke Wang and Meng Jin and Hong Cheng and Haohuan Fu},
  year = {2025},
  eprint = {2504.09940},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.09940},
}

@article{kim2025examplebased,
  title = {Example-Based Concept Analysis Framework for Deep Weather Forecast Models},
  author = {Soyeon Kim and Junho Choi and Subeen Lee and Jaesik Choi},
  year = {2025},
  eprint = {2504.00831},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.00831},
}

@article{kim2025explainable,
  title = {Explainable AI-Based Interface System for Weather Forecasting Model},
  author = {Soyeon Kim and Junho Choi and Yeji Choi and Subeen Lee and Artyom Stitsyuk and Minkyoung Park and Seongyeop Jeong and Youhyun Baek and Jaesik Choi},
  year = {2025},
  eprint = {2504.00795},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.00795},
}

@article{pujol2025improving,
  title = {Improving prediction of heavy rainfall in the Mediterranean with Neural Networks using both observation and Numerical Weather Prediction data},
  author = {Killian Pujol and Roberta Baggio and Dominique Lambert and Jean-François Muzy and Jean-Baptiste Filippi and Florian Pantillon},
  year = {2025},
  eprint = {2503.24216},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.24216},
}

@article{sakhuja2025quantumassisted,
  title = {Quantum-Assisted Machine Learning Models for Enhanced Weather Prediction},
  author = {Saiyam Sakhuja and Shivanshu Siyanwal and Abhishek Tiwari and Britant and Savita Kashyap},
  year = {2025},
  eprint = {2503.23408},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.23408},
}

@article{du2025weathermesh3,
  title = {WeatherMesh-3: Fast and accurate operational global weather forecasting},
  author = {Haoxing Du and Lyna Kim and Joan Creus-Costa and Jack Michaels and Anuj Shetty and Todd Hutchinson and Christopher Riedel and John Dean},
  year = {2025},
  eprint = {2503.22235},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.22235},
}

@article{huang2025fuxirtm,
  title = {FuXi-RTM: A Physics-Guided Prediction Framework with Radiative Transfer Modeling},
  author = {Qiusheng Huang and Xiaohui Zhong and Xu Fan and Lei Chen and Hao Li},
  year = {2025},
  eprint = {2503.19940},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.19940},
}

@article{hirabayashi2025datadriven,
  title = {Data-driven Mesoscale Weather Forecasting Combining Swin-Unet and Diffusion Models},
  author = {Yuta Hirabayashi and Daisuke Matsuoka},
  year = {2025},
  eprint = {2503.19354},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.19354},
}

@article{baggio2025local,
  title = {Local wind speed forecasting at short time horizons based on Numerical Weather Prediction and observations from surrounding stations},
  author = {Roberta Baggio and Killian Pujol and Florian Pantillon and Dominique Lambert and Jean-Baptiste Filippi and Jean-François Muzy},
  year = {2025},
  eprint = {2503.18797},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.18797},
}

@article{kumar2025locationspecific,
  title = {Towards Location-Specific Precipitation Projections Using Deep Neural Networks},
  author = {Bipin Kumar and Bhvisy Kumar Yadav and Soumypdeep Mukhopadhyay and Rakshit Rohan and Bhupendra Bahadur Singh and Rajib Chattopadhyay and Nagraju Chilukoti and Atul Kumar Sahai},
  year = {2025},
  eprint = {2503.14095},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.14095},
}

@article{choudhury2025development,
  title = {Development of a Data-driven weather forecasting system over India with Pangu-Weather architecture and IMDAA reanalysis Data},
  author = {Animesh Choudhury and Jagabandhu Panda},
  year = {2025},
  eprint = {2503.12956},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.12956},
}

@article{rout2025probabilistic,
  title = {Probabilistic Forecasting for Dynamical Systems with Missing or Imperfect Data},
  author = {Siddharth Rout and Eldad Haber and Stéphane Gaudreault},
  year = {2025},
  eprint = {2503.12273},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.12273},
}

@article{fernandez2025predicting,
  title = {Predicting Tropical Cyclone Track Forecast Errors using a Probabilistic Neural Network},
  author = {M. A. Fernandez and Elizabeth A. Barnes and Randal J. Barnes and Mark DeMaria and Marie McGraw and Galina Chirokova and Lixin Lu},
  year = {2025},
  eprint = {2503.09840},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.09840},
}

@article{meng2025physicsinformed,
  title = {Physics-Informed Residual Neural Ordinary Differential Equations for Enhanced Tropical Cyclone Intensity Forecasting},
  author = {Fan Meng},
  year = {2025},
  eprint = {2503.06436},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.06436},
}

@article{dinenis2025weaklyconstrained,
  title = {Weakly-Constrained 4D Var for Downscaling with Uncertainty using Data-Driven Surrogate Models},
  author = {Philip Dinenis and Vishwas Rao and Mihai Anitescu},
  year = {2025},
  eprint = {2503.02665},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.02665},
}

@article{niu2025mlphysical,
  title = {ML-Physical Fusion Models Are Accelerating the Paradigm Shift in Operational Typhoon Forecasting},
  author = {Zeyi Niu},
  year = {2025},
  eprint = {2503.00424},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.00424},
}

@article{sha2025investigating,
  title = {Investigating the use of terrain-following coordinates in AI-driven precipitation forecasts},
  author = {Yingkai Sha and John S. Schreck and William Chapman and David John Gagne},
  year = {2025},
  eprint = {2503.00332},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.00332},
}

@article{herrera2025spatiotemporal,
  title = {Spatiotemporal Forecasting in Climate Data Using EOFs and Machine Learning Models: A Case Study in Chile},
  author = {Mauricio Herrera and Francisca Kleisinger and Andrés Wilsón},
  year = {2025},
  eprint = {2502.17495},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2502.17495},
}

@article{xu2025ai,
  title = {AI Models Still Lag Behind Traditional Numerical Models in Predicting Sudden-Turning Typhoons},
  author = {Daosheng Xu and Zebin Lu and Jeremy Cheuk-Hin Leung and Dingchi Zhao and Yi Li and Yang Shi and Bin Chen and Gaozhen Nie and Naigeng Wu and Xiangjun Tian and Yi Yang and Shaoqing Zhang and Banglin Zhang},
  year = {2025},
  eprint = {2502.16036},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2502.16036},
}

@article{li2025climatellm,
  title = {ClimateLLM: Efficient Weather Forecasting via Frequency-Aware Large Language Models},
  author = {Shixuan Li and Wei Yang and Peiyu Zhang and Xiongye Xiao and Defu Cao and Yuehan Qin and Xiaole Zhang and Yue Zhao and Paul Bogdan},
  year = {2025},
  eprint = {2502.11059},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2502.11059},
}

@article{chen2025learning,
  title = {Learning low-dimensional representations of ensemble forecast fields using autoencoder-based methods},
  author = {Jieyu Chen and Kevin Höhlein and Sebastian Lerch},
  year = {2025},
  eprint = {2502.04409},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2502.04409},
}

@article{fan2025physically,
  title = {Physically Consistent Global Atmospheric Data Assimilation with Machine Learning in Latent Space},
  author = {Hang Fan and Lei Bai and Ben Fei and Yi Xiao and Kun Chen and Yubao Liu and Yongquan Qu and Fenghua Ling and Pierre Gentine},
  year = {2025},
  eprint = {2502.02884},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2502.02884},
}

@article{sudharsan2025enhancing,
  title = {Enhancing Near Real Time AI-NWP Hurricane Forecasts: Improving Explainability and Performance Through Physics-Based Models and Land Surface Feedback},
  author = {Naveen Sudharsan and Manmeet Singh and Sasanka Talukdar and Shyama Mohanty and Harsh Kamath and Krishna K. Osuri and Hassan Dashtian and Michael Young and Zong-Liang Yang and Clint Dawson and L. Ruby Leung and Sundararaman Gopalakrishnan and Avichal Mehra and Vijay Tallapragada and Dev Niyogi},
  year = {2025},
  eprint = {2502.01797},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2502.01797},
}

@article{subich2025fixing,
  title = {Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function},
  author = {Christopher Subich and Syed Zahid Husain and Leo Separovic and Jing Yang},
  year = {2025},
  eprint = {2501.19374},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.19374},
}

@article{ren2025improving,
  title = {Improving Tropical Cyclone Forecasting With Video Diffusion Models},
  author = {Zhibo Ren and Pritthijit Nath and Pancham Shukla},
  year = {2025},
  eprint = {2501.16003},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.16003},
}

@article{sen2025qgaphensemble,
  title = {QGAPHEnsemble : Combining Hybrid QLSTM Network Ensemble via Adaptive Weighting for Short Term Weather Forecasting},
  author = {Anuvab Sen and Udayon Sen and Mayukhi Paul and Apurba Prasad Padhy and Sujith Sai and Aakash Mallik and Chhandak Mallick},
  year = {2025},
  eprint = {2501.10866},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.10866},
}

@article{shi2025deep,
  title = {Deep Learning and Foundation Models for Weather Prediction: A Survey},
  author = {Jimeng Shi and Azam Shirali and Bowen Jin and Sizhe Zhou and Wei Hu and Rahuul Rangaraj and Shaowen Wang and Jiawei Han and Zhaonan Wang and Upmanu Lall and Yanzhao Wu and Leonardo Bobadilla and Giri Narasimhan},
  year = {2025},
  eprint = {2501.06907},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.06907},
}

@article{sha2025improving,
  title = {Improving AI weather prediction models using global mass and energy conservation schemes},
  author = {Yingkai Sha and John S. Schreck and William Chapman and David John Gagne},
  year = {2025},
  eprint = {2501.05648},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.05648},
}

@article{zhao2024omghd,
  title = {OMG-HD: A High-Resolution AI Weather Model for End-to-End Forecasts from Observations},
  author = {Pengcheng Zhao and Jiang Bian and Zekun Ni and Weixin Jin and Jonathan Weyn and Zuliang Fang and Siqi Xiang and Haiyu Dong and Bin Zhang and Hongyu Sun and Kit Thambiratnam and Qi Zhang},
  year = {2024},
  eprint = {2412.18239},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.18239},
}

@article{slivinski2024assimilating,
  title = {Assimilating Observed Surface Pressure into ML Weather Prediction Models},
  author = {Laura C. Slivinski and Jeffrey S. Whitaker and Sergey Frolov and Timothy A. Smith and Niraj Agarwal},
  year = {2024},
  eprint = {2412.18016},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.18016},
}

@article{lang2024aifscrps,
  title = {AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score},
  author = {Simon Lang and Mihai Alexe and Mariana C. A. Clare and Christopher Roberts and Rilwan Adewoyin and Zied Ben Bouallègue and Matthew Chantry and Jesper Dramsch and Peter D. Dueben and Sara Hahner and Pedro Maciel and Ana Prieto-Nemesio and Cathal O'Brien and Florian Pinault and Jan Polster and Baudouin Raoult and Steffen Tietsche and Martin Leutbecher},
  year = {2024},
  eprint = {2412.15832},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.15832},
}

@article{alexe2024graphdop,
  title = {GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations},
  author = {Mihai Alexe and Eulalie Boucher and Peter Lean and Ewan Pinnington and Patrick Laloyaux and Anthony McNally and Simon Lang and Matthew Chantry and Chris Burrows and Marcin Chrust and Florian Pinault and Ethel Villeneuve and Niels Bormann and Sean Healy},
  year = {2024},
  eprint = {2412.15687},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.15687},
}

@article{couairon2024archesweather,
  title = {ArchesWeather & ArchesWeatherGen: a deterministic and generative model for efficient ML weather forecasting},
  author = {Guillaume Couairon and Renu Singh and Anastase Charantonis and Christian Lessig and Claire Monteleoni},
  year = {2024},
  eprint = {2412.12971},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.12971},
}

@article{mukhin2024metastability,
  title = {Metastability, atmospheric midlatitude circulation regimes and large-scale teleconnection: a data-driven approach},
  author = {Dmitry Mukhin and Roman Samoilov and Abdel Hannachi},
  year = {2024},
  eprint = {2412.06933},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.06933},
}

@article{tian2024jacobianenforced,
  title = {Jacobian-Enforced Neural Networks (JENN) for Improved Data Assimilation Consistency in Dynamical Models},
  author = {Xiaoxu Tian},
  year = {2024},
  eprint = {2412.01013},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.01013},
}

@article{skok2024smoothing,
  title = {Smoothing and spatial verification of global fields},
  author = {Gregor Skok and Katarina Kosovelj},
  year = {2024},
  eprint = {2412.00936},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.00936},
}

@article{tian2024exploring,
  title = {Exploring the Use of Machine Learning Weather Models in Data Assimilation},
  author = {Xiaoxu Tian and Daniel Holdaway and Daryl Kleist},
  year = {2024},
  eprint = {2411.14677},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.14677},
}

@article{ji2024leadseeprecip,
  title = {Leadsee-Precip: A Deep Learning Diagnostic Model for Precipitation},
  author = {Weiwen Ji and Jin Feng and Yueqi Liu and Yulu Qiu and Hua Gao},
  year = {2024},
  eprint = {2411.12640},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.12640},
}

@article{ling2024fengwuw2s,
  title = {FengWu-W2S: A deep learning model for seamless weather-to-subseasonal forecast of global atmosphere},
  author = {Fenghua Ling and Kang Chen and Jiye Wu and Tao Han and Jing-Jia Luo and Wanli Ouyang and Lei Bai},
  year = {2024},
  eprint = {2411.10191},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.10191},
}

@article{kudo2024deepmedcast,
  title = {DeepMedcast: A Deep Learning Method for Generating Intermediate Weather Forecasts among Multiple NWP Models},
  author = {Atsushi Kudo},
  year = {2024},
  eprint = {2411.10010},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.10010},
}

@article{schreck2024community,
  title = {Community Research Earth Digital Intelligence Twin (CREDIT)},
  author = {John Schreck and Yingkai Sha and William Chapman and Dhamma Kimpara and Judith Berner and Seth McGinnis and Arnold Kazadi and Negin Sobhani and Ben Kirk and David John Gagne},
  year = {2024},
  eprint = {2411.07814},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.07814},
}

@article{zhao2024weathergfm,
  title = {WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning},
  author = {Xiangyu Zhao and Zhiwang Zhou and Wenlong Zhang and Yihao Liu and Xiangyu Chen and Junchao Gong and Hao Chen and Ben Fei and Shiqi Chen and Wanli Ouyang and Xiao-Ming Wu and Lei Bai},
  year = {2024},
  eprint = {2411.05420},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.05420},
}

@article{choi2024advancing,
  title = {Advancing Meteorological Forecasting: AI-based Approach to Synoptic Weather Map Analysis},
  author = {Yo-Hwan Choi and Seon-Yu Kang and Minjong Cheon},
  year = {2024},
  eprint = {2411.05384},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.05384},
}

@article{leinonen2024modulated,
  title = {Modulated Adaptive Fourier Neural Operators for Temporal Interpolation of Weather Forecasts},
  author = {Jussi Leinonen and Boris Bonev and Thorsten Kurth and Yair Cohen},
  year = {2024},
  eprint = {2410.18904},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.18904},
}

@article{sun2024ai,
  title = {Can AI weather models predict out-of-distribution gray swan tropical cyclones?},
  author = {Y. Qiang Sun and Pedram Hassanzadeh and Mohsen Zand and Ashesh Chattopadhyay and Jonathan Weare and Dorian S. Abbot},
  year = {2024},
  eprint = {2410.14932},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.14932},
}

@article{kalita2024datadriven,
  title = {Data-driven rainfall prediction at a regional scale: a case study with Ghana},
  author = {Indrajit Kalita and Lucia Vilallonga and Yves Atchade},
  year = {2024},
  eprint = {2410.14062},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.14062},
}

@article{huang2024tcpdiffusion,
  title = {TCP-Diffusion: A Multi-modal Diffusion Model for Global Tropical Cyclone Precipitation Forecasting with Change Awareness},
  author = {Cheng Huang and Pan Mu and Cong Bai and Peter AG Watson},
  year = {2024},
  eprint = {2410.13175},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.13175},
}

@article{duan2024testing,
  title = {Testing NeuralGCM's capability to simulate future heatwaves based on the 2021 Pacific Northwest heatwave event},
  author = {Shiheng Duan and Jishi Zhang and Céline Bonfils and Giuliana Pallotta},
  year = {2024},
  eprint = {2410.09120},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.09120},
}

@article{liu2024compressing,
  title = {Compressing high-resolution data through latent representation encoding for downscaling large-scale AI weather forecast model},
  author = {Qian Liu and Bing Gong and Xiaoran Zhuang and Xiaohui Zhong and Zhiming Kang and Hao Li},
  year = {2024},
  eprint = {2410.09109},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.09109},
}

@article{siddiqui2024exploring,
  title = {Exploring the design space of deep-learning-based weather forecasting systems},
  author = {Shoaib Ahmed Siddiqui and Jean Kossaifi and Boris Bonev and Christopher Choy and Jan Kautz and David Krueger and Kamyar Azizzadenesheli},
  year = {2024},
  eprint = {2410.07472},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.07472},
}

@article{andrae2024continuous,
  title = {Continuous Ensemble Weather Forecasting with Diffusion models},
  author = {Martin Andrae and Tomas Landelius and Joel Oskarsson and Fredrik Lindsten},
  year = {2024},
  eprint = {2410.05431},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.05431},
}

@article{cheng2024yantian,
  title = {YanTian: An Application Platform for AI Global Weather Forecasting Models},
  author = {Wencong Cheng and Jiangjiang Xia and Chang Qu and Zhigang Wang and Xinyi Zeng and Fang Huang and Tianye Li},
  year = {2024},
  eprint = {2410.04539},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.04539},
}

@article{kieu2024predictability,
  title = {Predictability of Global AI Weather Models},
  author = {Chanh Kieu},
  year = {2024},
  eprint = {2410.03266},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.03266},
}

@article{ran2024hrextreme,
  title = {HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting},
  author = {Nian Ran and Peng Xiao and Yue Wang and Wesley Shi and Jianxin Lin and Qi Meng and Richard Allmendinger},
  year = {2024},
  eprint = {2409.18885},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.18885},
}

@article{rackow2024robustness,
  title = {Robustness of AI-based weather forecasts in a changing climate},
  author = {Thomas Rackow and Nikolay Koldunov and Christian Lessig and Irina Sandu and Mihai Alexe and Matthew Chantry and Mariana Clare and Jesper Dramsch and Florian Pappenberger and Xabier Pedruzo-Bagazgoitia and Steffen Tietsche and Thomas Jung},
  year = {2024},
  eprint = {2409.18529},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.18529},
}

@article{gong2024weatherformer,
  title = {WeatherFormer: Empowering Global Numerical Weather Forecasting with Space-Time Transformer},
  author = {Junchao Gong and Tao Han and Kang Chen and Lei Bai},
  year = {2024},
  eprint = {2409.16321},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.16321},
}

@article{banomedina2024harnessing,
  title = {Harnessing AI data-driven global weather models for climate attribution: An analysis of the 2017 Oroville Dam extreme atmospheric river},
  author = {Jorge Baño-Medina and Agniv Sengupta and Allison Michaelis and Luca Delle Monache and Julie Kalansky and Duncan Watson-Parris},
  year = {2024},
  eprint = {2409.11605},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.11605},
}

@article{zhang2024super,
  title = {Super Resolution On Global Weather Forecasts},
  author = {Lawrence Zhang and Adam Yang and Rodz Andrie Amor and Bryan Zhang and Dhruv Rao},
  year = {2024},
  eprint = {2409.11502},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.11502},
}

@article{li2024weather,
  title = {Weather Prediction Using CNN-LSTM for Time Series Analysis: A Case Study on Delhi Temperature Data},
  author = {Bangyu Li and Yang Qian},
  year = {2024},
  eprint = {2409.09414},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.09414},
}

@article{jin2024weatherreal,
  title = {WeatherReal: A Benchmark Based on In-Situ Observations for Evaluating Weather Models},
  author = {Weixin Jin and Jonathan Weyn and Pengcheng Zhao and Siqi Xiang and Jiang Bian and Zuliang Fang and Haiyu Dong and Hongyu Sun and Kit Thambiratnam and Qi Zhang},
  year = {2024},
  eprint = {2409.09371},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.09371},
}

@article{zhong2024fuxi20,
  title = {FuXi-2.0: Advancing machine learning weather forecasting model for practical applications},
  author = {Xiaohui Zhong and Lei Chen and Xu Fan and Wenxu Qian and Jun Liu and Hao Li},
  year = {2024},
  eprint = {2409.07188},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.07188},
}

@article{demaria2024evaluation,
  title = {Evaluation of Tropical Cyclone Track and Intensity Forecasts from Artificial Intelligence Weather Prediction (AIWP) Models},
  author = {Mark DeMaria and James L. Franklin and Galina Chirokova and Jacob Radford and Robert DeMaria and Kate D. Musgrave and Imme Ebert-Uphoff},
  year = {2024},
  eprint = {2409.06735},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.06735},
}

@article{millard2024deep,
  title = {Deep Learning for Koopman Operator Estimation in Idealized Atmospheric Dynamics},
  author = {David Millard and Arielle Carr and Stéphane Gaudreault},
  year = {2024},
  eprint = {2409.06522},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.06522},
}

@article{shi2024codicast,
  title = {CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty Quantification},
  author = {Jimeng Shi and Bowen Jin and Jiawei Han and Sundararaman Gopalakrishnan and Giri Narasimhan},
  year = {2024},
  eprint = {2409.05975},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.05975},
}

@article{zhu2024puyun,
  title = {PuYun: Medium-Range Global Weather Forecasting Using Large Kernel Attention Convolutional Networks},
  author = {Shengchen Zhu and Yiming Chen and Peiying Yu and Xiang Qu and Yuxiao Zhou and Yiming Ma and Zhizhan Zhao and Yukai Liu and Hao Mi and Bin Wang},
  year = {2024},
  eprint = {2409.02123},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.02123},
}

@article{monaco2024uncertaintyaware,
  title = {Uncertainty-aware segmentation for rainfall prediction post processing},
  author = {Simone Monaco and Luca Monaco and Daniele Apiletti},
  year = {2024},
  eprint = {2408.16792},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.16792},
}

@article{subich2024efficient,
  title = {Efficient fine-tuning of 37-level GraphCast with the Canadian global deterministic analysis},
  author = {Christopher Subich},
  year = {2024},
  eprint = {2408.14587},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.14587},
}

@article{niu2024improving,
  title = {Improving Typhoon Predictions by Integrating Data-Driven Machine Learning Models with Physics Models Based on the Spectral Nudging and Data Assimilation},
  author = {Zeyi Niu and Wei Huang and Lei Zhang and Lin Deng and Haibo Wang and Yuhua Yang and Dongliang Wang and Hong Li},
  year = {2024},
  eprint = {2408.12630},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.12630},
}

@article{wang2024benchmarking,
  title = {Benchmarking AI-based data assimilation to advance data-driven global weather forecasting},
  author = {Wuxin Wang and Weicheng Ni and Ben Fei and Tao Han and Lilan Huang and Taikang Yuan and Xiaoyong Li and Lei Bai and Boheng Duan and Kaijun Ren},
  year = {2024},
  eprint = {2408.11438},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.11438},
}

@article{benson2024atmospheric,
  title = {Atmospheric Transport Modeling of CO$_2$ with Neural Networks},
  author = {Vitus Benson and Ana Bastos and Christian Reimers and Alexander J. Winkler and Fanny Yang and Markus Reichstein},
  year = {2024},
  eprint = {2408.11032},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.11032},
}

@article{gopakumar2024uncertainty,
  title = {Uncertainty Quantification of Surrogate Models using Conformal Prediction},
  author = {Vignesh Gopakumar and Ander Gray and Joel Oskarsson and Lorenzo Zanisi and Daniel Giles and Matt J. Kusner and Stanislas Pamela and Marc Peter Deisenroth},
  year = {2024},
  eprint = {2408.09881},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.09881},
}

@article{sun2024fuxi,
  title = {FuXi Weather: A data-to-forecast machine learning system for global weather},
  author = {Xiuyu Sun and Xiaohui Zhong and Xiaoze Xu and Yuanqing Huang and Hao Li and J. David Neelin and Deliang Chen and Jie Feng and Wei Han and Libo Wu and Yuan Qi},
  year = {2024},
  eprint = {2408.05472},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.05472},
}

@article{lutjens2024impact,
  title = {The impact of internal variability on benchmarking deep learning climate emulators},
  author = {Björn Lütjens and Raffaele Ferrari and Duncan Watson-Parris and Noelle Selin},
  year = {2024},
  eprint = {2408.05288},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.05288},
}

@article{mahesh2024hugeb,
  title = {Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators},
  author = {Ankur Mahesh and William Collins and Boris Bonev and Noah Brenowitz and Yair Cohen and Joshua Elms and Peter Harrington and Karthik Kashinath and Thorsten Kurth and Joshua North and Travis OBrien and Michael Pritchard and David Pruitt and Mark Risser and Shashank Subramanian and Jared Willard},
  year = {2024},
  eprint = {2408.03100},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.03100},
}

@article{mahesh2024hugea,
  title = {Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators},
  author = {Ankur Mahesh and William Collins and Boris Bonev and Noah Brenowitz and Yair Cohen and Peter Harrington and Karthik Kashinath and Thorsten Kurth and Joshua North and Travis OBrien and Michael Pritchard and David Pruitt and Mark Risser and Shashank Subramanian and Jared Willard},
  year = {2024},
  eprint = {2408.01581},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.01581},
}

@article{chen2024spatial,
  title = {Spatial Temporal Approach for High-Resolution Gridded Wind Forecasting across Southwest Western Australia},
  author = {Fuling Chen and Kevin Vinsen and Arthur Filoche},
  year = {2024},
  eprint = {2407.20283},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.20283},
}

@article{li2024efficiently,
  title = {Efficiently improving key weather variables forecasting by performing the guided iterative prediction in latent space},
  author = {Shuangliang Li and Siwei Li},
  year = {2024},
  eprint = {2407.19187},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.19187},
}

@article{kotsuki2024ensemble,
  title = {Ensemble data assimilation to diagnose AI-based weather prediction model: A case with ClimaX version 0.3.1},
  author = {Shunji Kotsuki and Kenta Shiraishi and Atsushi Okazaki},
  year = {2024},
  eprint = {2407.17781},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.17781},
}

@article{wesselkamp2024advances,
  title = {Advances in Land Surface Model-based Forecasting: A comparative study of LSTM, Gradient Boosting, and Feedforward Neural Network Models as prognostic state emulators},
  author = {Marieke Wesselkamp and Matthew Chantry and Ewan Pinnington and Margarita Choulga and Souhail Boussetta and Maria Kalweit and Joschka Boedecker and Carsten F. Dormann and Florian Pappenberger and Gianpaolo Balsamo},
  year = {2024},
  eprint = {2407.16463},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.16463},
}

@article{mcnally2024data,
  title = {Data driven weather forecasts trained and initialised directly from observations},
  author = {Anthony McNally and Christian Lessig and Peter Lean and Eulalie Boucher and Mihai Alexe and Ewan Pinnington and Matthew Chantry and Simon Lang and Chris Burrows and Marcin Chrust and Florian Pinault and Ethel Villeneuve and Niels Bormann and Sean Healy},
  year = {2024},
  eprint = {2407.15586},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.15586},
}

@article{karlbauer2024comparing,
  title = {Comparing and Contrasting DLWP Backbones on Navier-Stokes and Atmospheric Dynamics},
  author = {Matthias Karlbauer and Danielle C. Maddix and Abdul Fatir Ansari and Boran Han and Gaurav Gupta and Yuyang Wang and Andrew Stuart and Michael W. Mahoney},
  year = {2024},
  eprint = {2407.14129},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.14129},
}

@article{yin2024scalable,
  title = {A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics},
  author = {Junqi Yin and Siming Liang and Siyan Liu and Feng Bao and Hristo G. Chipilski and Dan Lu and Guannan Zhang},
  year = {2024},
  eprint = {2407.12168},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.12168},
}

@article{vandal2024global,
  title = {Global atmospheric data assimilation with multi-modal masked autoencoders},
  author = {Thomas J. Vandal and Kate Duffy and Daniel McDuff and Yoni Nachmany and Chris Hartshorn},
  year = {2024},
  eprint = {2407.11696},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.11696},
}

@article{mirowski2024neural,
  title = {Neural Compression of Atmospheric States},
  author = {Piotr Mirowski and David Warde-Farley and Mihaela Rosca and Matthew Koichi Grimes and Yana Hasson and Hyunjik Kim and Mélanie Rey and Simon Osindero and Suman Ravuri and Shakir Mohamed},
  year = {2024},
  eprint = {2407.11666},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.11666},
}

@article{husain2024leveraging,
  title = {Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging},
  author = {Syed Zahid Husain and Leo Separovic and Jean-François Caron and Rabah Aider and Mark Buehner and Stéphane Chamberland and Ervig Lapalme and Ron McTaggart-Cowan and Christopher Subich and Paul A. Vaillancourt and Jing Yang and Ayrton Zadra},
  year = {2024},
  eprint = {2407.06100},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.06100},
}

@article{price2023gencast,
  title = {GenCast: Diffusion-based ensemble forecasting for medium-range weather},
  author = {Ilan Price and Alvaro Sanchez-Gonzalez and Ferran Alet and Tom R. Andersson and Andrew El-Kadi and Dominic Masters and Timo Ewalds and Jacklynn Stott and Shakir Mohamed and Peter Battaglia and Remi Lam and Matthew Willson},
  year = {2023},
  eprint = {2312.15796},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2312.15796},
}

@article{xiao2023fengwu4dvar,
  title = {FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation},
  author = {Yi Xiao and Lei Bai and Wei Xue and Kang Chen and Tao Han and Wanli Ouyang},
  year = {2023},
  eprint = {2312.12455},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2312.12455},
}

@article{lam2022graphcast,
  title = {GraphCast: Learning skillful medium-range global weather forecasting},
  author = {Remi Lam and Alvaro Sanchez-Gonzalez and Matthew Willson and Peter Wirnsberger and Meire Fortunato and Ferran Alet and Suman Ravuri and Timo Ewalds and Zach Eaton-Rosen and Weihua Hu and Alexander Merose and Stephan Hoyer and George Holland and Oriol Vinyals and Jacklynn Stott and Alexander Pritzel and Shakir Mohamed and Peter Battaglia},
  year = {2022},
  eprint = {2212.12794},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2212.12794},
}

@article{bi2022panguweather,
  title = {Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast},
  author = {Kaifeng Bi and Lingxi Xie and Hengheng Zhang and Xin Chen and Xiaotao Gu and Qi Tian},
  year = {2022},
  eprint = {2211.02556},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2211.02556},
}

@article{hu2022swinvrnn,
  title = {SwinVRNN: A Data-Driven Ensemble Forecasting Model via Learned Distribution Perturbation},
  author = {Yuan Hu and Lei Chen and Zhibin Wang and Hao Li},
  year = {2022},
  eprint = {2205.13158},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2205.13158},
}

@article{pathak2022fourcastnet,
  title = {FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators},
  author = {Jaideep Pathak and Shashank Subramanian and Peter Harrington and Sanjeev Raja and Ashesh Chattopadhyay and Morteza Mardani and Thorsten Kurth and David Hall and Zongyi Li and Kamyar Azizzadenesheli and Pedram Hassanzadeh and Karthik Kashinath and Animashree Anandkumar},
  year = {2022},
  eprint = {2202.11214},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2202.11214},
}