@article{mclean2026lightweight,
  title = {Lightweight Probabilistic Downscaling from a Deterministic Base Model},
  author = {Joseph McLean and Tiffany Vlaar and Sigrid Passano Hellan and Linus Ericsson},
  year = {2026},
  eprint = {2609.29383},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.29383},
}

@article{xu2026generative,
  title = {Generative Atmospheric Super-Resolution from Heterogeneous In Situ Observations through Composable Interfaces},
  author = {Yang Xu and Dibyajyoti Chakraborty and Haiwen Guan and Sen Wang and Romit Maulik},
  year = {2026},
  eprint = {2609.29027},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.29027},
}

@article{qian2026evaluating,
  title = {Evaluating Cross-region Generalization for Wavelet-Diffusion Precipitation Downscaling},
  author = {Weikang Qian and Yixin Wen and Chugang Yi and Zhi Li and Lingcheng Li and Haizhao Yang},
  year = {2026},
  eprint = {2609.28749},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.28749},
}

@article{srivastava2026diffusionbased,
  title = {Diffusion-Based Super-Resolution of Adriatic Sea Oceanographic Fields},
  author = {Rajat Srivastava and Muhammad Sarmad and Emanuele Mele and Massimo Cafaro and Marco Pulimeno and Italo Epicoco},
  year = {2026},
  eprint = {2609.22574},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.22574},
}

@article{avireddy2026steering,
  title = {Steering Diffusion Priors with Sparse Observations for High-Resolution Temperature Downscaling},
  author = {Anirudh Avireddy and Manmeet Singh and Shivanshi Singh and Ayush Raj and Saptarishi Dhanuka and Parthasarathi Mukhopadhyay and Sandeep Juneja},
  year = {2026},
  eprint = {2609.09247},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.09247},
}

@article{zhu2026pythonfortran,
  title = {Python-Fortran Hybrid Programming to Fuse AI and Physical Models: Examples of AI-LDA in climate and weather models (Hf2pMDA_v1.0)},
  author = {Xianrui Zhu and Zikuan Lin and Shaoqing Zhang and Zebin Lu and Songhua Wu and Xiangyun Hou and Zhisheng Xiao and Zhicheng Ren and Jiangyu Li and Jing Xu and Yang Gao and Rixu Hao and Xiaolin Yu and Mingkui Li and Guangliang Liu},
  year = {2026},
  eprint = {2608.29532},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.29532},
}

@article{ribeiro2026precipitation,
  title = {Precipitation Downscaling Using Foundation Model-Conditioned Diffusion},
  author = {Victor Nascimento Ribeiro and Jorge Guevara and Jorge Sebastian Moraga and Chris Lucas and Natalie Lord and Andrew Taylor and Edward Lockhart and Will Trojak and Johannes Schmude and Anne Jones},
  year = {2026},
  eprint = {2608.25858},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.25858},
}

@article{sousa2026earth,
  title = {Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling},
  author = {Pedro Sousa and Will Tebbutt and Sadiq Jaffer and Robin Young and Anil Madhavapeddy and Richard E. Turner},
  year = {2026},
  eprint = {2608.12271},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.12271},
}

@article{jadhav2026deep,
  title = {Deep Learning-Based Statistical Downscaling of Sea Surface Temperature Using a Residual Corrective Neural Network},
  author = {Onkar Jadhav and Tim French and Ivica Janekovic and Nicole L. Jones and Matthew Rayson},
  year = {2026},
  eprint = {2608.10022},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.10022},
}

@article{zhang2026temporal,
  title = {Temporal Bridges for Spatial Resolution: Enhancing Climate Data Super-Resolution with Bidirectional Alignment},
  author = {Yichen Zhang and Yixiong Xiao and Congxi Xiao and Jingbo Zhou},
  year = {2026},
  eprint = {2608.05981},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.05981},
}

@article{doshi2026transferable,
  title = {Transferable Dual-Stream Representations for Mesoscale-Preserving Sea Surface Temperature Downscaling},
  author = {Parth Doshi and Priyanka Aravindan and Vaishnav Vaidheeswaran and Md Mahbub Alam and Gabriel Spadon},
  year = {2026},
  eprint = {2608.04230},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.04230},
}

@article{xu2026physicsinformed,
  title = {Physics-Informed Super-Resolution of Atmospheric Data},
  author = {Chang Xu and Gencer Sumbul and Hugo Porta and Manon Béchaz and Sebastian Schemm and Devis Tuia},
  year = {2026},
  eprint = {2607.18877},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.18877},
}

@article{akami2026superresolution,
  title = {Super-Resolution of Radar/Raingauge-Analyzed Precipitation Using Gaussian Process Regression with a Steering Kernel},
  author = {Shoichi Akami and Tsuyoshi T. Sekiyama and Mizuo Kajino},
  year = {2026},
  eprint = {2607.07290},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.07290},
}

@article{wang2026domainadaptive,
  title = {Domain-Adaptive Climate Downscaling Under Temporal Distribution Shift},
  author = {Shuochen Wang and Nishant Yadav and Auroop R. Ganguly},
  year = {2026},
  eprint = {2607.05645},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.05645},
}

@article{passos2026exploring,
  title = {Exploring Convolutional Neural Processes for Weather Downscaling},
  author = {Francisco Passos},
  year = {2026},
  eprint = {2607.04190},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.04190},
}

@article{rampal2026cordexmlbench,
  title = {CORDEX-ML-Bench: A Benchmark for Data-Driven Regional Climate Downscaling -Experiment Design and Overview},
  author = {Neelesh Rampal and José González-Abad and Henry Addison and Jorge Baño-Medina and Maria Laura Bettolli and Valentina Blasone and Ben Booth and Erika Coppola and Serafina Di Gioia and Joshua Oldham-Dorrington and Antoine Doury and Francois Engelbrecht and Ramón Fuentes-Franco and Peter B. Gibson and Luca Glawion and Caroline Hardy and Mikhail Ivanov and Hugo Kyo Lee and Mikel N. Legasa and Matias Olmo and Andrew Orr and Julius Polz and Martin S. J. Rogers and Maybritt Schillinger and Shivani Sharma and Pedro M. M. Soares and Stefan Sobolowski and Jessica Steinkopf and Wenchang Tang and Jr-Ben Tian and Ricardo Tomé and Ko-Chih Wang and Yi-Chi Wang and Peter A. G. Watson and Tom Wetherell and Martin Widmann and José M. Gutiérrez},
  year = {2026},
  eprint = {2606.29172},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.29172},
}

@article{singh2026temporal,
  title = {Temporal Coverage over Density: Parsimonious Training-Set Design for ML Climate Downscaling},
  author = {Karandeep Singh and Stefan Rahimi and Chad W. Thackeray and Stephen Cropper and Alex Hall},
  year = {2026},
  eprint = {2606.07898},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.07898},
}

@article{wetherell2026flow,
  title = {Flow Matching for Convective-Scale Precipitation Downscaling},
  author = {Tom Wetherell},
  year = {2026},
  eprint = {2606.00281},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.00281},
}

@article{dong2026precipitation,
  title = {Precipitation diffusion downscaling and application to out-of-distribution simulations with and without stratospheric aerosol injection},
  author = {Cameron Dong and James W. Hurrell and Elizabeth A. Barnes},
  year = {2026},
  eprint = {2605.23776},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.23776},
}

@article{wang2026hybrid,
  title = {Hybrid Quantum-Classical Corrective Diffusion Modeling for Meteorological Downscaling},
  author = {Rui Wang and Edoardo Pasetto and Amer Delilbasic and Morris Riedel and Kristel Michielsen and Gabriele Cavallaro},
  year = {2026},
  eprint = {2605.23403},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.23403},
}

@article{wang2026longwang,
  title = {Longwang: Zero-Shot Global Spatiotemporal Precipitation Downscaling with a Latent Generative Prior},
  author = {Yue Wang and Daniele Visioni},
  year = {2026},
  eprint = {2605.17603},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.17603},
}

@article{kutsuna2026generative,
  title = {Generative climate downscaling enables high-resolution compound risk assessment by preserving multivariate dependencies},
  author = {Takuro Kutsuna and Noriko N. Ishizaki and Norihiro Oyama and Hiroaki Yoshida},
  year = {2026},
  eprint = {2605.11531},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.11531},
}

@article{jadhav2026podiff,
  title = {PODiff: Latent Diffusion in Proper Orthogonal Decomposition Space for Scientific Super-Resolution},
  author = {Onkar Jadhav and Tim French and Matthew Rayson and Nicole L. Jones},
  year = {2026},
  eprint = {2605.03399},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.03399},
}

@article{brinkerhoff2026conditional,
  title = {Conditional Flow Matching for Probabilistic Downscaling of Maximum 3-day Snowfall in Alaska},
  author = {Douglas Brinkerhoff and Elizabeth Fischer},
  year = {2026},
  eprint = {2604.25172},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.25172},
}

@article{hana2026generative,
  title = {Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting},
  author = {Tao Hana and Zhibin Wen and Zhenghao Chen and Fenghua Lin and Junyu Gao and Song Guo and Lei Bai},
  year = {2026},
  eprint = {2604.07928},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.07928},
}

@article{debeire2026physicsconstrained,
  title = {Physics-Constrained Adaptive Flow Matching for Climate Downscaling},
  author = {Kevin Debeire and Aytaç Paçal and Pierre Gentine and Luis Medrano-Navarro and Nils Thuerey and Veronika Eyring},
  year = {2026},
  eprint = {2604.03459},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.03459},
}

@article{brazidec2026downscaling,
  title = {Downscaling weather forecasts from Low- to High-Resolution with Diffusion Models},
  author = {Joffrey Dumont Le Brazidec and Simon Lang and Martin Leutbecher and Baudouin Raoult and Gert Mertes and Florian Pinault and Aristofanis Tsiringakis and Pedro Maciel and Ana Prieto Nemesio and Jan Polster and Cathal O Brien and Matthew Chantry},
  year = {2026},
  eprint = {2604.03303},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.03303},
}

@article{kingston2026ipslaid,
  title = {IPSL-AID: Generative Diffusion Models for Climate Downscaling from Global to Regional Scales},
  author = {Kishanthan Kingston and Olivier Boucher and Freddy Bouchet and Pierre Chapel and Rosemary Eade and Jean-Francois Lamarque and Redouane Lguensat and Kazem Ardaneh},
  year = {2026},
  eprint = {2604.03275},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.03275},
}

@article{shen202630meter,
  title = {30-meter Land Surface Temperature from Landsat via Progressive Self-Training Downscaling},
  author = {Huanfeng Shen and Chan Li and Menghui Jiang and Penghai Wu and Guanhao Zhang and Tian Xie},
  year = {2026},
  eprint = {2603.29478},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.29478},
}

@article{larsson2026climate,
  title = {Climate Downscaling with Stochastic Interpolants (CDSI)},
  author = {Erik Larsson and Ramon Fuentes-Franco and Mikhail Ivanov and Fredrik Lindsten},
  year = {2026},
  eprint = {2603.03838},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.03838},
}

@article{zhang2026physics,
  title = {Physics Encoded Spatial and Temporal Generative Adversarial Network for Tropical Cyclone Image Super-resolution},
  author = {Ruoyi Zhang and Jiawei Yuan and Lujia Ye and Runling Yu and Liling Zhao},
  year = {2026},
  eprint = {2602.17277},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.17277},
}

@article{sharma2026maunetlight,
  title = {MAUNet-Light: A Concise MAUNet Architecture for Bias Correction and Downscaling of Precipitation Estimates},
  author = {Sumanta Chandra Mishra Sharma and Adway Mitra and Auroop Ratan Ganguly},
  year = {2026},
  eprint = {2602.12980},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.12980},
}

@article{molinaro2026universal,
  title = {Universal Diffusion-Based Probabilistic Downscaling},
  author = {Roberto Molinaro and Niall Siegenheim and Henry Martin and Mark Frey and Niels Poulsen and Philipp Seitz and Marvin Vincent Gabler},
  year = {2026},
  eprint = {2602.11893},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.11893},
}

@article{aich2026wind,
  title = {WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling},
  author = {Michael Aich and Andreas Fürst and Florian Sestak and Carlos Ruiz-Gonzalez and Niklas Boers and Johannes Brandstetter},
  year = {2026},
  eprint = {2602.03924},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.03924},
}

@article{dandapanthula2026downscaling,
  title = {Downscaling land surface temperature data using edge detection and block-diagonal Gaussian process regression},
  author = {Sanjit Dandapanthula and Margaret Johnson and Madeleine Pascolini-Campbell and Glynn Hulley and Mikael Kuusela},
  year = {2026},
  eprint = {2602.02813},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.02813},
}

@article{shu2026hybridom,
  title = {HybridOM: Hybrid Physics-Based and Data-Driven Global Ocean Modeling with Efficient Spatial Downscaling},
  author = {Ruiqi Shu and Xiaohui Zhong and Qiusheng Huang and Ruijian Gou and Tianrun Gao and Hao Li and Xiaomeng Huang},
  year = {2026},
  eprint = {2602.00598},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2602.00598},
}

@article{tie2026zeroshot,
  title = {Zero-Shot Statistical Downscaling via Diffusion Posterior Sampling},
  author = {Ruian Tie and Wenbo Xiong and Zhengyu Shi and Xinyu Su and Chenyu jiang and Libo Wu and Hao Li},
  year = {2026},
  eprint = {2601.21760},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2601.21760},
}

@article{wardleikis2025intercomparison,
  title = {An intercomparison of generative machine learning methods for downscaling precipitation at fine spatial scales},
  author = {Bryn Ward-Leikis and Neelesh Rampal and Yun Sing Koh and Peter B. Gibson and Hong-Yang Liu and Vassili Kitsios and Tristan Meyers and Jeff Adie and Yang Juntao and Steven C. Sherwood},
  year = {2025},
  eprint = {2512.13987},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.13987},
}

@article{sipila2025timeaware,
  title = {Time-aware UNet and super-resolution deep residual networks for spatial downscaling},
  author = {Mika Sipilä and Sabrina Maggio and Sandra De Iaco and Klaus Nordhausen and Monica Palma and Sara Taskinen},
  year = {2025},
  eprint = {2512.13753},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.13753},
}

@article{lutjens2025meltwaterbench,
  title = {MeltwaterBench: Deep learning for spatiotemporal downscaling of surface meltwater},
  author = {Björn Lütjens and Patrick Alexander and Raf Antwerpen and Til Widmann and Guido Cervone and Marco Tedesco},
  year = {2025},
  eprint = {2512.12142},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.12142},
}

@article{effenberger2025bridging,
  title = {Bridging CORDEX and CMIP6: Machine Learning Downscaling for Wind and Solar Energy Droughts in Central Europe},
  author = {Nina Effenberger and Maxim Samarin and Maybritt Schillinger and Reto Knutti},
  year = {2025},
  eprint = {2512.07429},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.07429},
}

@article{sun2025china,
  title = {China Regional 3km Downscaling Based on Residual Corrective Diffusion Model},
  author = {Honglu Sun and Hao Jing and Zhixiang Dai and Sa Xiao and Wei Xue and Jian Sun and Qifeng Lu},
  year = {2025},
  eprint = {2512.05377},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.05377},
}

@article{xiang2025spatiotemporal,
  title = {Spatiotemporal Satellite Image Downscaling with Transfer Encoders and Autoregressive Generative Models},
  author = {Yang Xiang and Jingwen Zhong and Yige Yan and Petros Koutrakis and Eric Garshick and Meredith Franklin},
  year = {2025},
  eprint = {2512.05139},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.05139},
}

@article{harder2025global,
  title = {On Global Applicability and Location Transferability of Generative Deep Learning Models for Precipitation Downscaling},
  author = {Paula Harder and Christian Lessig and Matthew Chantry and Francis Pelletier and David Rolnick},
  year = {2025},
  eprint = {2512.01400},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2512.01400},
}

@article{fanelli2025superresolution,
  title = {Super-resolution of satellite-derived SST data via Generative Adversarial Networks},
  author = {Claudia Fanelli and Tiany Li and Luca Biferale and Bruno Buongiorno Nardelli and Daniele Ciani and Andrea Pisano and Michele Buzzicotti},
  year = {2025},
  eprint = {2511.22610},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.22610},
}

@article{silva2025multiresolution,
  title = {A multiresolution weather dataset for the Southwestern South Atlantic (2017-2018)},
  author = {Luan C. V. Silva and Lívia Sancho and Mauricio S. Silva and Elisa Passos and Larissa F. R. Jacinto and Rebeca S. Lyra and Nilton O. Moraes and Carina S. Bock and Douglas M. Nehme and Raquel Toste and Jacques Honigbaum and Rodrigo S. Luna and Carlos H. Beisl and Patricia M. Silva and Adriano O. Vasconcelos and Rian C. Ferreira and Cédric Eneau and Fernando A. Rochinha and Luiz P. F. Assad and Alvaro L. G. A. Coutinho and Laura Bahiense and Alexandre G. Evsukoff},
  year = {2025},
  eprint = {2511.18704},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.18704},
}

@article{luong2025climate,
  title = {Climate Downscaling of Tropical Cyclone Intensity using Deep Learning},
  author = {Minh-Khanh Luong and Chanh Kieu},
  year = {2025},
  eprint = {2511.05392},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2511.05392},
}

@article{rosu2025pdeinformed,
  title = {A PDE-Informed Latent Diffusion Model for 2-m Temperature Downscaling},
  author = {Paul Rosu and Muchang Bahng and Erick Jiang and Rico Zhu and Vahid Tarokh},
  year = {2025},
  eprint = {2510.23866},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.23866},
}

@article{redondo2025sparse,
  title = {Sparse Local Implicit Image Function for sub-km Weather Downscaling},
  author = {Yago del Valle Inclan Redondo and Enrique Arriaga-Varela and Dmitry Lyamzin and Pablo Cervantes and Tiago Ramalho},
  year = {2025},
  eprint = {2510.20228},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.20228},
}

@article{saccardi2025assessing,
  title = {Assessing the Geographic Generalization and Physical Consistency of Generative Models for Climate Downscaling},
  author = {Carlo Saccardi and Maximilian Pierzyna and Haitz Sáez de Ocáriz Borde and Simone Monaco and Cristian Meo and Pietro Liò and Rudolf Saathof and Geethu Joseph and Justin Dauwels},
  year = {2025},
  eprint = {2510.13722},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.13722},
}

@article{yasuda2025probabilistic,
  title = {Probabilistic Super-Resolution for Urban Micrometeorology via a Schrödinger Bridge},
  author = {Yuki Yasuda and Ryo Onishi},
  year = {2025},
  eprint = {2510.12148},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.12148},
}

@article{le2025deep,
  title = {Deep Learning Reconstruction of Tropical Cyclogenesis in the Western North Pacific from Climate Reanalysis Dataset},
  author = {Duc-Trong Le and Tran-Binh Dang and Anh-Duc Hoang Gia and Duc-Hai Nguyen and Minh-Hoa Tien and Xuan-Truong Ngo and Quang-Trung Luu and Quang-Lap Luu and Tai-Hung Nguyen and Thanh T. N. Nguyen and Chanh Kieu},
  year = {2025},
  eprint = {2510.06118},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.06118},
}

@article{ma2025diffusionbased,
  title = {Diffusion-Based, Data-Assimilation-Enabled Super-Resolution of Hub-height Winds},
  author = {Xiaolong Ma and Xu Dong and Ashley Tarrant and Lei Yang and Rao Kotamarthi and Jiali Wang and Feng Yan and Rajkumar Kettimuthu},
  year = {2025},
  eprint = {2510.03364},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2510.03364},
}

@article{schillinger2025enscale,
  title = {EnScale: Temporally-consistent multivariate generative downscaling via proper scoring rules},
  author = {Maybritt Schillinger and Maxim Samarin and Xinwei Shen and Reto Knutti and Nicolai Meinshausen},
  year = {2025},
  eprint = {2509.26258},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.26258},
}

@article{liu2025cera,
  title = {CERA: A Framework for Improved Generalization of Machine Learning Models to Changed Climates},
  author = {Shuchang Liu and Paul A. O'Gorman},
  year = {2025},
  eprint = {2509.00010},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2509.00010},
}

@article{bochow2025physicsconstrained,
  title = {Physics-constrained generative machine learning-based high-resolution downscaling of Greenland's surface mass balance and surface temperature},
  author = {Nils Bochow and Philipp Hess and Alexander Robinson},
  year = {2025},
  eprint = {2507.22485},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.22485},
}

@article{elkabid2025multiscale,
  title = {Multiscale Neural PDE Surrogates for Prediction and Downscaling: Application to Ocean Currents},
  author = {Abdessamad El-Kabid and Loubna Benabbou and Redouane Lguensat and Alex Hernández-García},
  year = {2025},
  eprint = {2507.18067},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.18067},
}

@article{shiraishi2025wasserstein,
  title = {Wasserstein GAN-Based Precipitation Downscaling with Optimal Transport for Enhancing Perceptual Realism},
  author = {Kenta Shiraishi and Yuka Muto and Atsushi Okazaki and Shunji Kotsuki},
  year = {2025},
  eprint = {2507.17798},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.17798},
}

@article{rampal2025downscaling,
  title = {Downscaling with AI reveals the large role of internal variability in fine-scale projections of climate extremes},
  author = {Neelesh Rampal and Peter B. Gibson and Steven C. Sherwood and Laura E. Queen and Hamish Lewis and Gab Abramowitz},
  year = {2025},
  eprint = {2507.06527},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.06527},
}

@article{harder2025rainshift,
  title = {RainShift: A Benchmark for Precipitation Downscaling Across Geographies},
  author = {Paula Harder and Luca Schmidt and Francis Pelletier and Nicole Ludwig and Matthew Chantry and Christian Lessig and Alex Hernandez-Garcia and David Rolnick},
  year = {2025},
  eprint = {2507.04930},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.04930},
}

@article{babu2025guided,
  title = {Guided Unconditional and Conditional Generative Models for Super-Resolution and Inference of Quasi-Geostrophic Turbulence},
  author = {Anantha Narayanan Suresh Babu and Akhil Sadam and Pierre F. J. Lermusiaux},
  year = {2025},
  eprint = {2507.00719},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2507.00719},
}

@article{chakraborty2025multimodal,
  title = {Multimodal Atmospheric Super-Resolution With Deep Generative Models},
  author = {Dibyajyoti Chakraborty and Haiwen Guan and Jason Stock and Troy Arcomano and Guido Cervone and Romit Maulik},
  year = {2025},
  eprint = {2506.22780},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.22780},
}

@article{merizzi2025vision,
  title = {Vision Transformers for Multi-Variable Climate Downscaling: Emulating Regional Climate Models with a Shared Encoder and Multi-Decoder Architecture},
  author = {Fabio Merizzi and Harilaos Loukos},
  year = {2025},
  eprint = {2506.22447},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.22447},
}

@article{curran2025generate,
  title = {Generate the Forest before the Trees -- A Hierarchical Diffusion model for Climate Downscaling},
  author = {Declan J. Curran and Sanaa Hobeichi and Hira Saleem and Hao Xue and Flora D. Salim},
  year = {2025},
  eprint = {2506.19391},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.19391},
}

@article{tu2025mods,
  title = {MODS: Multi-source Observations Conditional Diffusion Model for Meteorological State Downscaling},
  author = {Siwei Tu and Jingyi Xu and Weidong Yang and Lei Bai and Ben Fei},
  year = {2025},
  eprint = {2506.14798},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2506.14798},
}

@article{luo2025physicsguided,
  title = {Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting},
  author = {Yingtao Luo and Shikai Fang and Binqing Wu and Qingsong Wen and Liang Sun},
  year = {2025},
  eprint = {2505.14555},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.14555},
}

@article{wang2025orbit2,
  title = {ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling},
  author = {Xiao Wang and Jong-Youl Choi and Takuya Kurihaya and Isaac Lyngaas and Hong-Jun Yoon and Xi Xiao and David Pugmire and Ming Fan and Nasik M. Nafi and Aristeidis Tsaris and Ashwin M. Aji and Maliha Hossain and Mohamed Wahib and Dali Wang and Peter Thornton and Prasanna Balaprakash and Moetasim Ashfaq and Dan Lu},
  year = {2025},
  eprint = {2505.04802},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.04802},
}

@article{wang2025supporting,
  title = {Supporting renewable energy planning and operation with data-driven high-resolution ensemble weather forecast},
  author = {Jingnan Wang and Jie Chao and Shangshang Yang and Kaijun Ren and Kefeng Deng and Xi Chen and Yaxin Liu and Hanqiuzi Wen and Ziniu Xiao and Lifeng Zhang and Xiaodong Wang and Jiping Guan and Baoxiang Pan},
  year = {2025},
  eprint = {2505.04396},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2505.04396},
}

@article{yasuda2025zeroshot,
  title = {Zero-Shot Super-Resolution from Unstructured Data Using a Transformer-Based Neural Operator for Urban Micrometeorology},
  author = {Yuki Yasuda and Ryo Onishi},
  year = {2025},
  eprint = {2504.21361},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.21361},
}

@article{yu2025rainy,
  title = {Rainy: Unlocking Satellite Calibration for Deep Learning in Precipitation},
  author = {Zhenyu Yu and Hanqing Chen and Mohd Yamani Idna Idris and Pei Wang},
  year = {2025},
  eprint = {2504.10776},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.10776},
}

@article{kieu2025nwpbased,
  title = {NWP-based deep learning for tropical cyclone intensity prediction},
  author = {Chanh Kieu and Khanh Luong and Tri Nguyen},
  year = {2025},
  eprint = {2504.09143},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2504.09143},
}

@article{iotti2025rainscalegan,
  title = {RainScaleGAN: a Conditional Generative Adversarial Network for Rainfall Downscaling},
  author = {Marcello Iotti and Paolo Davini and Jost von Hardenberg and Giuseppe Zappa},
  year = {2025},
  eprint = {2503.13316},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2503.13316},
}

@article{tu2025satellite,
  title = {Satellite Observations Guided Diffusion Model for Accurate Meteorological States at Arbitrary Resolution},
  author = {Siwei Tu and Ben Fei and Weidong Yang and Fenghua Ling and Hao Chen and Zili Liu and Kun Chen and Hang Fan and Wanli Ouyang and Lei Bai},
  year = {2025},
  eprint = {2502.07814},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2502.07814},
}

@article{merizzi2025controlling,
  title = {Controlling Ensemble Variance in Diffusion Models: An Application for Reanalyses Downscaling},
  author = {Fabio Merizzi and Davide Evangelista and Harilaos Loukos},
  year = {2025},
  eprint = {2501.14822},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.14822},
}

@article{liu2025kolmogorov,
  title = {Kolmogorov Arnold Neural Interpolator for Downscaling and Correcting Meteorological Fields from In-Situ Observations},
  author = {Zili Liu and Hao Chen and Lei Bai and Wenyuan Li and Zhengxia Zou and Zhenwei Shi},
  year = {2025},
  eprint = {2501.14404},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.14404},
}

@article{dai2025precipdiff,
  title = {PrecipDiff: Leveraging image diffusion models to enhance satellite-based precipitation observations},
  author = {Ting-Yu Dai and Hayato Ushijima-Mwesigwa},
  year = {2025},
  eprint = {2501.07447},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.07447},
}

@article{lupinjimenez2025simultaneous,
  title = {Simultaneous emulation and downscaling with physically-consistent deep learning-based regional ocean emulators},
  author = {Leonard Lupin-Jimenez and Moein Darman and Subhashis Hazarika and Tianning Wu and Michael Gray and Ruyoing He and Anthony Wong and Ashesh Chattopadhyay},
  year = {2025},
  eprint = {2501.05058},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2501.05058},
}

@article{radhakrishnan2024continuous,
  title = {Continuous latent representations for modeling precipitation with deep learning},
  author = {Gokul Radhakrishnan and Rahul Sundar and Nishant Parashar and Antoine Blanchard and Daiwei Wang and Boyko Dodov},
  year = {2024},
  eprint = {2412.14620},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.14620},
}

@article{lyu2024downscaling,
  title = {Downscaling Precipitation with Bias-informed Conditional Diffusion Model},
  author = {Ran Lyu and Linhan Wang and Yanshen Sun and Hedanqiu Bai and Chang-Tien Lu},
  year = {2024},
  eprint = {2412.14539},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.14539},
}

@article{dong2024quantifying,
  title = {Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model},
  author = {Xiaochong Dong and Jun Dan and Yingyun Sun and Yang Liu and Xuemin Zhang and Shengwei Mei},
  year = {2024},
  eprint = {2412.11399},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.11399},
}

@article{fernandezgodino2024staged,
  title = {A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport},
  author = {M. Giselle Fernández-Godino and Wai Tong Chung and Akshay A. Gowardhan and Matthias Ihme and Qingkai Kong and Donald D. Lucas and Stephen C. Myers},
  year = {2024},
  eprint = {2412.10945},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.10945},
}

@article{guevara2024enhancing,
  title = {Enhancing operational wind downscaling capabilities over Canada: Application of a Conditional Wasserstein GAN methodology},
  author = {Jorge Guevara and Victor Nascimento and Johannes Schmude and Daniel Salles and Simon Corbeil-Létourneau and Madalina Surcel and Dominique Brunet},
  year = {2024},
  eprint = {2412.06958},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2412.06958},
}

@article{glawion2024global,
  title = {Global spatio-temporal downscaling of ERA5 precipitation through generative AI},
  author = {Luca Glawion and Julius Polz and Harald Kunstmann and Benjamin Fersch and Christian Chwala},
  year = {2024},
  eprint = {2411.16098},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.16098},
}

@article{curran2024resolutionagnostic,
  title = {Resolution-Agnostic Transformer-based Climate Downscaling},
  author = {Declan Curran and Hira Saleem and Sanaa Hobeichi and Flora Salim},
  year = {2024},
  eprint = {2411.14774},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2411.14774},
}

@article{perez2024transformer,
  title = {Transformer based super-resolution downscaling for regional reanalysis: Full domain vs tiling approaches},
  author = {Antonio Pérez and Mario Santa Cruz and Daniel San Martín and José Manuel Gutiérrez},
  year = {2024},
  eprint = {2410.12728},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.12728},
}

@article{giroux2024interpolationfree,
  title = {Interpolation-Free Deep Learning for Meteorological Downscaling on Unaligned Grids Across Multiple Domains with Application to Wind Power},
  author = {Jean-Sébastien Giroux and Simon-Philippe Breton and Julie Carreau},
  year = {2024},
  eprint = {2410.03945},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.03945},
}

@article{lopezgomez2024dynamicalgenerative,
  title = {Dynamical-generative downscaling of climate model ensembles},
  author = {Ignacio Lopez-Gomez and Zhong Yi Wan and Leonardo Zepeda-Núñez and Tapio Schneider and John Anderson and Fei Sha},
  year = {2024},
  eprint = {2410.01776},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.01776},
}

@article{liu2024downscalingb,
  title = {Downscaling Extreme Precipitation with Wasserstein Regularized Diffusion},
  author = {Yuhao Liu and James Doss-Gollin and Qiushi Dai and Ashok Veeraraghavan and Guha Balakrishnan},
  year = {2024},
  eprint = {2410.00381},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.00381},
}

@article{dai2024mocolsk,
  title = {MoCoLSK: Modality Conditioned High-Resolution Downscaling for Land Surface Temperature},
  author = {Qun Dai and Chunyang Yuan and Yimian Dai and Yuxuan Li and Xiang Li and Kang Ni and Jianhui Xu and Xiangbo Shu and Jian Yang},
  year = {2024},
  eprint = {2409.19835},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.19835},
}

@article{qayyum2024implicit,
  title = {Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data},
  author = {Alif Bin Abdul Qayyum and Xihaier Luo and Nathan M. Urban and Xiaoning Qian and Byung-Jun Yoon},
  year = {2024},
  eprint = {2409.17367},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.17367},
}

@article{rampal2024extrapolation,
  title = {On the Extrapolation of Generative Adversarial Networks for downscaling precipitation extremes in warmer climates},
  author = {Neelesh Rampal and Peter B. Gibson and Steven Sherwood and Gab Abramowitz},
  year = {2024},
  eprint = {2409.13934},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.13934},
}

@article{chajaei2024machine,
  title = {Machine Learning Framework for High-Resolution Air Temperature Downscaling Using LiDAR-Derived Urban Morphological Features},
  author = {Fatemeh Chajaei and Hossein Bagheri},
  year = {2024},
  eprint = {2409.02120},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2409.02120},
}

@article{liu2024downscalinga,
  title = {Downscaling Neural Network for Coastal Simulations},
  author = {Zhi-Song Liu and Markus Büttner and Matthew Scarborough and Eirik Valseth and Vadym Aizinger and Bernhard Kainz and Andreas Rupp},
  year = {2024},
  eprint = {2408.16553},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.16553},
}

@article{han2024generative,
  title = {Generative Diffusion Model-based Downscaling of Observed Sea Surface Height over Kuroshio Extension since 2000},
  author = {Qiuchang Han and Xingliang Jiang and Yang Zhao and Xudong Wang and Zhijin Li and Renhe Zhang},
  year = {2024},
  eprint = {2408.12632},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.12632},
}

@article{saha2024rapida,
  title = {Rapid Statistical-Physical Adversarial Downscaling Reveals Bangladesh's Rising Rainfall Risk in a Warming Climate},
  author = {Anamitra Saha and Sai Ravela},
  year = {2024},
  eprint = {2408.11790},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.11790},
}

@article{liu2024mambads,
  title = {MambaDS: Near-Surface Meteorological Field Downscaling with Topography Constrained Selective State Space Modeling},
  author = {Zili Liu and Hao Chen and Lei Bai and Wenyuan Li and Wanli Ouyang and Zhengxia Zou and Zhenwei Shi},
  year = {2024},
  eprint = {2408.10854},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2408.10854},
}

@article{benton2024super,
  title = {Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data and Application to Ukraine},
  author = {Brandon N. Benton and Grant Buster and Pavlo Pinchuk and Andrew Glaws and Ryan N. King and Galen Maclaurin and Ilya Chernyakhovskiy},
  year = {2024},
  eprint = {2407.19086},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.19086},
}

@article{prasad2024evaluating,
  title = {Evaluating the transferability potential of deep learning models for climate downscaling},
  author = {Ayush Prasad and Paula Harder and Qidong Yang and Prasanna Sattegeri and Daniela Szwarcman and Campbell Watson and David Rolnick},
  year = {2024},
  eprint = {2407.12517},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2407.12517},
}