Copertina

Investigating the Robustness of Extreme Precipitation Super-Resolution Across Climates

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Largeau, Louise, Beucler, Tom, Leutwyler, David, Mariethoz, Gregoire, Chavez-Demoulin, Valerie, Koch, Erwan
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Atmospheric and Oceanic Physics Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Next-Generation Earth System Models: Towards Reliable Hybrid Models for Weather and Climate Applications
di: Beucler, Tom, et al.
Pubblicazione: (2023)

Improving Predictions of Convective Storm Wind Gusts through Statistical Post-Processing of Neural Weather Models
di: Leclerc, Antoine, et al.
Pubblicazione: (2025)

SwAIther-Precip: Lead-Time-Aware Bias Correction Enables Kilometer-Scale Downscaling of Global AI Precipitation Forecasts over Switzerland
di: Assouline, Dan, et al.
Pubblicazione: (2026)

Lessons Learned: Reproducibility, Replicability, and When to Stop
di: Gomez, Milton S., et al.
Pubblicazione: (2024)

Lightning-Fast Convective Outlooks: Predicting Severe Convective Environments with Global AI-based Weather Models
di: Feldmann, Monika, et al.
Pubblicazione: (2024)

Identifying Three-Dimensional Radiative Patterns Associated with Early Tropical Cyclone Intensification
di: Tam, Frederick Iat-Hin, et al.
Pubblicazione: (2024)

Flow Matching for Convective-Scale Precipitation Downscaling
di: Wetherell, Tom
Pubblicazione: (2026)

Data-Driven Integration Kernels for Interpretable Nonlocal Operator Learning
di: Ferretti, Savannah L., et al.
Pubblicazione: (2026)

Super Resolution On Global Weather Forecasts
di: Zhang, Lawrence, et al.
Pubblicazione: (2024)

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

Selection of CMIP6 Models for Regional Precipitation Projection and Climate Change Assessment in the Jhelum and Chenab River Basins
di: Jamal, Saad Ahmed, et al.
Pubblicazione: (2026)

Navigating the Noise: Bringing Clarity to ML Parameterization Design with O(100) Ensembles
di: Lin, Jerry, et al.
Pubblicazione: (2023)

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

Climate-Invariant Machine Learning
di: Beucler, Tom, et al.
Pubblicazione: (2021)

CASCADE: Cross-scale Advective Super-resolution with Climate Assimilation and Downscaling Evolution
di: Kovalenko, Alexander
Pubblicazione: (2026)

PODiff: Latent Diffusion in Proper Orthogonal Decomposition Space for Scientific Super-Resolution
di: Jadhav, Onkar, et al.
Pubblicazione: (2026)

Interpretable AI-Driven Discovery of Terrain-Precipitation Relationships for Enhanced Climate Insights
di: Xu, Hao, et al.
Pubblicazione: (2023)

From Winter Storm Thermodynamics to Wind Gust Extremes: Discovering Interpretable Equations from Data
di: Tam, Frederick Iat-Hin, et al.
Pubblicazione: (2025)

Distilling Machine Learning's Added Value: Pareto Fronts in Atmospheric Applications
di: Beucler, Tom, et al.
Pubblicazione: (2024)

Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data and Application to Ukraine
di: Benton, Brandon N., et al.
Pubblicazione: (2024)

Physics-Informed Lightweight Machine Learning for Aviation Visibility Nowcasting Across Multiple Climatic Regimes
di: Castillo, Marcelo Cerda
Pubblicazione: (2025)

Crowdsourcing the Frontier: Advancing Hybrid Physics-ML Climate Simulation via a $50,000 Kaggle Competition
di: Lin, Jerry, et al.
Pubblicazione: (2025)

Calibrated Conformal Prediction Intervals for Microphysical Process Rates
di: Simm, Miriam, et al.
Pubblicazione: (2026)

Guided Diffusion Sampling for Precipitation Forecast Interventions
di: Ueyama, Ayumu, et al.
Pubblicazione: (2026)

MMWSTM-ADRAN+: A Novel Hybrid Deep Learning Architecture for Enhanced Climate Time Series Forecasting and Extreme Event Prediction
di: Ahmed, Shaheen Mohammed Saleh, et al.
Pubblicazione: (2025)

AirCast-SR: A Foundation Model for Kilometer-Scale Atmospheric Super-Resolution via Latent Consistency Diffusion
di: Luitel, Somnath, et al.
Pubblicazione: (2026)

Oya: Deep Learning for Accurate Global Precipitation Estimation
di: Brempong, Emmanuel Asiedu, et al.
Pubblicazione: (2025)

Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model
di: Heuer, Helge, et al.
Pubblicazione: (2025)

Reduced Cloud Cover Errors in a Hybrid AI-Climate Model Through Equation Discovery And Automatic Tuning
di: Grundner, Arthur, et al.
Pubblicazione: (2025)

Leadsee-Precip: A Deep Learning Diagnostic Model for Precipitation
di: Ji, Weiwen, et al.
Pubblicazione: (2024)

Beyond Resolution: Multi-Scale Weather and Climate Data for Alpine Renewable Energy in the Digital Twin Era -- First Evaluations and Recommendations
di: Schicker, Irene, et al.
Pubblicazione: (2025)

Towards Location-Specific Precipitation Projections Using Deep Neural Networks
di: Kumar, Bipin, et al.
Pubblicazione: (2025)

A Likelihood-Based Generative Approach for Spatially Consistent Precipitation Downscaling
di: González-Abad, Jose
Pubblicazione: (2024)

STAA: Spatio-Temporal Alignment Attention for Short-Term Precipitation Forecasting
di: Chen, Min, et al.
Pubblicazione: (2024)

ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation
di: Yu, Sungduk, et al.
Pubblicazione: (2023)

Longwang: Zero-Shot Global Spatiotemporal Precipitation Downscaling with a Latent Generative Prior
di: Wang, Yue, et al.
Pubblicazione: (2026)

Hard-Constrained Deep Learning for Climate Downscaling
di: Harder, Paula, et al.
Pubblicazione: (2022)

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

CSU-PCAST: A Dual-Branch Transformer Framework for medium-range ensemble Precipitation Forecasting
di: Xiong, Tianyi, et al.
Pubblicazione: (2025)

Data-Driven Equation Discovery of a Cloud Cover Parameterization
di: Grundner, Arthur, et al.
Pubblicazione: (2023)