Machine-learned cloud classes from satellite data for process-oriented climate model evaluation
Fuente:
arXiv
Saved in:
| Main Authors: | Kaps, A., Lauer, A., Camps-Valls, G., Gentine, P., Gómez-Chova, L., Eyring, V. |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Causally-informed deep learning to improve climate models and projections
by: Iglesias-Suarez, Fernando, et al.
Published: (2023)
by: Iglesias-Suarez, Fernando, et al.
Published: (2023)
Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON
by: Heuer, Helge, et al.
Published: (2023)
by: Heuer, Helge, et al.
Published: (2023)
Data-Driven Equation Discovery of a Cloud Cover Parameterization
by: Grundner, Arthur, et al.
Published: (2023)
by: Grundner, Arthur, et al.
Published: (2023)
Opportunities and challenges of quantum computing for climate modelling
by: Schwabe, Mierk, et al.
Published: (2025)
by: Schwabe, Mierk, et al.
Published: (2025)
Machine learning disentangles bias causes of shortwave cloud radiative effect in a climate model
by: Yang, Hongtao, et al.
Published: (2024)
by: Yang, Hongtao, et al.
Published: (2024)
Reduced Cloud Cover Errors in a Hybrid AI-Climate Model Through Equation Discovery And Automatic Tuning
by: Grundner, Arthur, et al.
Published: (2025)
by: Grundner, Arthur, et al.
Published: (2025)
Representing Subgrid-Scale Cloud Effects in a Radiation Parameterization using Machine Learning: MLe-radiation v1.0
by: Hafner, Katharina, et al.
Published: (2025)
by: Hafner, Katharina, et al.
Published: (2025)
Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties with Deep Learning Multi-Member and Stochastic Parameterizations
by: Behrens, Gunnar, et al.
Published: (2024)
by: Behrens, Gunnar, et al.
Published: (2024)
Physics-Constrained Adaptive Flow Matching for Climate Downscaling
by: Debeire, Kevin, et al.
Published: (2026)
by: Debeire, Kevin, et al.
Published: (2026)
Transferring climate change physical knowledge
by: Immorlano, Francesco, et al.
Published: (2023)
by: Immorlano, Francesco, et al.
Published: (2023)
AIMIP Phase 1: systematic evaluations of AI weather and climate models
by: Henn, Brian, et al.
Published: (2026)
by: Henn, Brian, et al.
Published: (2026)
Quantum Machine Learning for Climate Modelling
by: Schwabe, Mierk, et al.
Published: (2025)
by: Schwabe, Mierk, et al.
Published: (2025)
High-resolution ensemble retrieval of cloud properties for all-day based on geostationary satellite
by: Xiao, Haixia, et al.
Published: (2024)
by: Xiao, Haixia, et al.
Published: (2024)
Evaluating satellite and reanalysis rainfall estimates for climate services in agriculture: a comprehensive methodology
by: Parsons, Danny, et al.
Published: (2025)
by: Parsons, Danny, et al.
Published: (2025)
Physically Consistent Global Atmospheric Data Assimilation with Machine Learning in Latent Space
by: Fan, Hang, et al.
Published: (2025)
by: Fan, Hang, et al.
Published: (2025)
Nonautonomous modelling in Energy Balance Models of climate. Limitations of averaging and climate sensitivity
by: Longo, Iacopo P., et al.
Published: (2025)
by: Longo, Iacopo P., et al.
Published: (2025)
Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model
by: Heuer, Helge, et al.
Published: (2025)
by: Heuer, Helge, et al.
Published: (2025)
When and where higher-resolution climate data improve impact model performance
by: Malle, Johanna T., et al.
Published: (2025)
by: Malle, Johanna T., et al.
Published: (2025)
Interpretable Neural Networks to Predict Momentum Fluxes of Orographic Gravity Waves
by: Haslauer, Elias, et al.
Published: (2026)
by: Haslauer, Elias, et al.
Published: (2026)
Technical Report: Towards Unified Diffusion Models for Multi-Model Climate Emulation at Scale
by: Immorlano, Francesco, et al.
Published: (2025)
by: Immorlano, Francesco, et al.
Published: (2025)
Stress-testing the coupled behavior of hybrid physics-machine learning climate simulations on an unseen, warmer climate
by: Lin, Jerry, et al.
Published: (2024)
by: Lin, Jerry, et al.
Published: (2024)
Power Ensemble Aggregation for Improved Extreme Event AI Prediction
by: Collard, Julien, et al.
Published: (2025)
by: Collard, Julien, et al.
Published: (2025)
Advancing global sea ice prediction capabilities using a fully-coupled climate model with integrated machine learning
by: Gregory, William, et al.
Published: (2025)
by: Gregory, William, et al.
Published: (2025)
Improvement of a neural network convection scheme by including triggering and evaluation in present and future climates
by: Germain, Hugo, et al.
Published: (2025)
by: Germain, Hugo, et al.
Published: (2025)
On idealized models of turbulent condensation in clouds
by: Abade, G. C.
Published: (2025)
by: Abade, G. C.
Published: (2025)
Contributions of greenhouse gases and solar activity to global climate change from CMIP6 models simulations
by: Mokhov, Igor I., et al.
Published: (2024)
by: Mokhov, Igor I., et al.
Published: (2024)
Quantifying urban and landfill methane emissions in the United States using TROPOMI satellite data
by: Wang, Xiaolin, et al.
Published: (2025)
by: Wang, Xiaolin, et al.
Published: (2025)
Tropical temperature distributions over a wide range of climates: theory and idealized simulations
by: Duffield, Joshua A. M., et al.
Published: (2025)
by: Duffield, Joshua A. M., et al.
Published: (2025)
Blending machine learning and physics-based approaches for weather and climate: a typology
by: Shipway, Benjamin J, et al.
Published: (2026)
by: Shipway, Benjamin J, et al.
Published: (2026)
Snow cover over the Iberian mountains in km-scale global climate simulations: evaluation and projected changes
by: García-Maroto, Diego, et al.
Published: (2025)
by: García-Maroto, Diego, et al.
Published: (2025)
Skilful global seasonal predictions from a machine learning weather model trained on reanalysis data
by: Kent, Chris, et al.
Published: (2025)
by: Kent, Chris, et al.
Published: (2025)
On the importance of learning non-local dynamics for stable data-driven climate modeling: A 1D gravity wave-QBO testbed
by: Pahlavan, Hamid A., et al.
Published: (2024)
by: Pahlavan, Hamid A., et al.
Published: (2024)
Regional impacts poorly constrained by climate sensitivity
by: Swaminathan, Ranjini, et al.
Published: (2024)
by: Swaminathan, Ranjini, et al.
Published: (2024)
Relationship of temperature changes in the mesopause region with the climate changes at the surface from observations in 1960-2024
by: Mokhov, I. I., et al.
Published: (2024)
by: Mokhov, I. I., et al.
Published: (2024)
Quantum Neural Networks for Cloud Cover Parameterizations in Climate Models
by: Pastori, Lorenzo, et al.
Published: (2025)
by: Pastori, Lorenzo, et al.
Published: (2025)
Evaluating local climate in global storm-resolving models with the Köppen-Geiger classification
by: van Heerwaarden, Chiel C., et al.
Published: (2026)
by: van Heerwaarden, Chiel C., et al.
Published: (2026)
Hybrid physics-data-driven modeling for sea ice thermodynamics and transfer learning
by: De Cillis, Giovanni, et al.
Published: (2026)
by: De Cillis, Giovanni, et al.
Published: (2026)
Ice clouds as nonlinear oscillators
by: Bergner, Hannah, et al.
Published: (2025)
by: Bergner, Hannah, et al.
Published: (2025)
The role of the surface evapotranspiration in regional climate modelling: Evaluation and near-term future changes
by: Ojeda, Matilde García-Valdecasas, et al.
Published: (2024)
by: Ojeda, Matilde García-Valdecasas, et al.
Published: (2024)
Assessing the climate benefits of afforestation: processes, methods, and frameworks
by: Dsouza, Kevin Bradley, et al.
Published: (2024)
by: Dsouza, Kevin Bradley, et al.
Published: (2024)
Similar Items
-
Causally-informed deep learning to improve climate models and projections
by: Iglesias-Suarez, Fernando, et al.
Published: (2023) -
Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON
by: Heuer, Helge, et al.
Published: (2023) -
Data-Driven Equation Discovery of a Cloud Cover Parameterization
by: Grundner, Arthur, et al.
Published: (2023) -
Opportunities and challenges of quantum computing for climate modelling
by: Schwabe, Mierk, et al.
Published: (2025) -
Machine learning disentangles bias causes of shortwave cloud radiative effect in a climate model
by: Yang, Hongtao, et al.
Published: (2024)