:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Deng, Zijun, Orozco, Rafael, Gahlot, Abhinav Prakash, Herrmann, Felix J.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Atmospheric and Oceanic Physics
Online Access:	https://arxiv.org/abs/2501.18761
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Explainable Comparison of Feature-Based and Deep Learning Models for TROPOMI Methane Plume Screening
by: Kurchaba, Solomiia, et al.
Published: (2026)

A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulation
by: Schmidt, Jonathan, et al.
Published: (2024)

Calibrating Geophysical Predictions under Constrained Probabilistic Distributions
by: Hou, Zhewen, et al.
Published: (2025)

A Practical Probabilistic Benchmark for AI Weather Models
by: Brenowitz, Noah D., et al.
Published: (2024)

Predicting Tropical Cyclone Track Forecast Errors using a Probabilistic Neural Network
by: Fernandez, M. A., et al.
Published: (2025)

Diffusion-LAM: Probabilistic Limited Area Weather Forecasting with Diffusion
by: Larsson, Erik, et al.
Published: (2025)

Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction
by: Guan, Hannah, et al.
Published: (2026)

Probabilistic Super-Resolution for Urban Micrometeorology via a Schrödinger Bridge
by: Yasuda, Yuki, et al.
Published: (2025)

Probabilistic Emulation of the Community Radiative Transfer Model Using Machine Learning
by: Howard, Lucas, et al.
Published: (2025)

Njord: A Probabilistic Graph Neural Network for Ensemble Ocean Forecasting
by: Holmberg, Daniel, et al.
Published: (2026)

Bayesian Optimisation for Active Monitoring of Air Pollution
by: Hellan, Sigrid Passano, et al.
Published: (2022)

AODDiff: Probabilistic Reconstruction of Aerosol Optical Depth via Diffusion-based Bayesian Inference
by: Fan, Linhao, et al.
Published: (2025)

Prototype-Based Methods in Explainable AI and Emerging Opportunities in the Geosciences
by: Narayanan, Anushka, et al.
Published: (2024)

Data-Driven Probabilistic Air-Sea Flux Parameterization
by: Wu, Jiarong, et al.
Published: (2025)

Interpretable Cross-Sphere Multiscale Deep Learning Predicts ENSO Skilfully Beyond 2 Years
by: Hao, Rixu, et al.
Published: (2025)

Probabilistic measures afford fair comparisons of AIWP and NWP model output
by: Gneiting, Tilmann, et al.
Published: (2025)

Contributions of El Niño Southern Oscillation (ENSO) Diversity to Low-Frequency Changes in ENSO Variance
by: Schlör, Jakob, et al.
Published: (2023)

Physics Guided Machine Learning Methods for Hydrology
by: Khandelwal, Ankush, et al.
Published: (2020)

Diffusion Model-based Probabilistic Downscaling for 180-year East Asian Climate Reconstruction
by: Ling, Fenghua, et al.
Published: (2024)

Reconstructing Global Daily CO2 Emissions via Machine Learning
by: Li, Tao, et al.
Published: (2024)

Physically Constrained Generative Adversarial Networks for Improving Precipitation Fields from Earth System Models
by: Hess, Philipp, et al.
Published: (2022)

Improving Model Chain Approaches for Probabilistic Solar Energy Forecasting through Post-processing and Machine Learning
by: Horat, Nina, et al.
Published: (2024)

Conditional Flow Matching for Probabilistic Downscaling of Maximum 3-day Snowfall in Alaska
by: Brinkerhoff, Douglas, et al.
Published: (2026)

Diffusion-Based Joint Temperature and Precipitation Emulation of Earth System Models
by: Christensen, Katie, et al.
Published: (2024)

Are Deep Learning Methods Suitable for Downscaling Global Climate Projections? An Intercomparison for Temperature and Precipitation over Spain
by: González-Abad, Jose, et al.
Published: (2024)

mloz: A Highly Efficient Machine Learning-Based Ozone Parameterization for Climate Sensitivity Simulations
by: Ma, Yiling, et al.
Published: (2025)

Elucidated Rolling Diffusion Models for Probabilistic Forecasting of Complex Dynamics
by: Cachay, Salva Rühling, et al.
Published: (2025)

Probabilistic Emulation of a Global Climate Model with Spherical DYffusion
by: Cachay, Salva Rühling, et al.
Published: (2024)

An Operational Deep Learning System for Satellite-Based High-Resolution Global Nowcasting
by: Agrawal, Shreya, et al.
Published: (2025)

Probabilistic bias adjustment of seasonal predictions of Arctic Sea Ice Concentration
by: Gooya, Parsa, et al.
Published: (2025)

Supporting renewable energy planning and operation with data-driven high-resolution ensemble weather forecast
by: Wang, Jingnan, et al.
Published: (2025)

Learning effective Sargassum transport dynamics from limited drifter observations
by: Beron-VEra, F. J., et al.
Published: (2026)

Controllable Probabilistic Forecasting with Stochastic Decomposition Layers
by: Schreck, John S., et al.
Published: (2025)

U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster
by: Cachay, Salva Rühling, et al.
Published: (2026)

Enforcing Equity in Neural Climate Emulators
by: Yik, William, et al.
Published: (2024)

Prototype-based Explainable Neural Networks with Channel-specific Reasoning for Geospatial Learning Tasks
by: Narayanan, Anushka, et al.
Published: (2026)

S$^2$Transformer: Scalable Structured Transformers for Global Station Weather Forecasting
by: Chen, Hongyi, et al.
Published: (2025)

Skillful Subseasonal-to-Seasonal Forecasting of Extreme Events with a Multi-Sphere Coupled Probabilistic Model
by: Mu, Bin, et al.
Published: (2025)

Atmospheric Predictability Beyond 30 Days with Machine Learning
by: Vonich, P. Trent, et al.
Published: (2025)

ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses
by: Watt-Meyer, Oliver, et al.
Published: (2024)