6th Summer School on Theory, Mechanisms and Hierarchical Modelling of Climate Dynamics: Artificial Intelligence and Climate Modelling

A Probabilistic Forecast for Multi-year ENSO Using Bayesian Convolutional Neural Network

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- Baduru_Abstract.jpg

A machine learning method is used to identify sources of long-term ENSO predictability in the ocean (sea surface temperature (SST) and heat content) and the atmosphere (near-surface zonal wind (U10)). Tropical 10m wind sseem to represents an inreresting source of ENSO predictability

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- Colfescu_Abstract.jpg

AI And Regional Climate Downscaling

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AI Physical Routines in Physical Numerical Models

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AI and Hybrid Modelling: Parameter Calibration or Full-AI Modules

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AI and Hybrid Modelling: Parameter Calibration or Full-AI Modules

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AI-Driven reconstruction of oxygen profiles in the North Atlantic Oxygen Minimum Zone

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- Coron_Abstract.jpg

CNN-based forecasting of early winter NAO using sea surface temperature

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- Provenzano_Abstract.jpg

Circulation Regimes and The Signal-to-Noise Paradox in AI Prediction Models

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Climate projections in the Euro-Mediterranean region: atmospheric circulation patterns and temperature and rainfall future changes

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- Olmo_Abstract.jpg

Climate projections in the Euro-Mediterranean region: atmospheric circulation patterns and temperature and rainfall future changes

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Closing

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Convolutional Neural Network (CNN) for Classification and Regression

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Data-Driven Equation Discovery of In-Cloud Vertical Velocity

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- Pechacova_Abstract.jpg

Data-Informed Inversion Model (DIIM): a framework to retrieve marine optical constituents in the BOUSSOLE site using a three-stream irradiance model

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- Soto_L._Abstract.jpg

Deep Learning for Time Series (E.G. RNN, Long-Short Term Memory NN)

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ENSO forecast with AI

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Enhancing Local Climate Zone Classification in Jakarta Using AI: Machine Learning Approach with Landsat 9 and Land Surface Temperature Integration

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- Rezky_Abstract.jpg

Enhancing Regional Precipitation Predictions through Machine Learning using ERA5 and Observational Data

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Enhancing Seasonal Predictions with Machine Learning: A Global Perspective on SST Influence in Early Winter

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- Galvan_Fraile_Abstract.jpg

Exploring windows of opportunity at sub-seasonal time scales for extreme precipitation events: the Valencia DANA case study

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- Perez_Zanon_Abstract.jpg

Fine-Tuning of the Prithvi Foundational Model

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Fine-tuning a global weather model for superior subseasonal forecasting

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- Sansine_Abstract.jpg

From observations to realistic simulations, the mechanisms that develop and prevent convective organization

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- Casallas_Abstract.jpg

Hackathon

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Hackathon

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Hackathon Presentations

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Hackathon Presentations

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Hybrid models at ECMWF, from spectral nudging to online trained model error corrections

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Improving Global Wildfire Simulations Using Machine Learning

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Integrating AI, Ocean Models, and Satellite Observations for Eddy-Resolving Surface Ocean State Estimation

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Internal Variability in Decadal Ensemble Simulations

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Intro to Machine Learning

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- Intro_ML_SMR4067-3.pdf

Introducing PINA

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Introduction To Physics-Informed Neural Networks (PINN)

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Introduction to Atmospheric Modelling

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- Molteni_ICTP_May2025_1.pptx

Introduction to Deep Learning

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- Intro_to_DL.pdf

Introduction to Graph NN (GNN; Difference between Static and Dynamic GNN)

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Introduction to Ocean Modelling

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- OceanModels_evs.pdf

Introduction to Regional Climate Modelling and the Need of AI

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- RCM_and_AI.pdf

Investigating Extreme Precipitation Event Attribution Through Deep-Learning Approaches

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- Corner_Abstract.jpg

Investigating deep convective systems with Machine Learning and causal inference across a hierarchy of datasets

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- Polesello_Abstract.jpg

Lab Activity

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Lab Activity On GNN

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Lab activity

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Lab activity: Comparison Between Traditional Numerical Schemes For Climate Simulations (PINN)

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Lab activity: Comparison Between Traditional Numerical Schemes For Climate Simulations (PINN)

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Lab activity: Simple Deep Learning Model to Have Temperature Forecast from Other Input Fields

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Lab activity: Typical Structure and Input-Output of Climate Data

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Learning the Ocean: Leveraging AI to Improve Ocean Data Assimilation

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- Grande_Abstract.jpg

Linking Research to Action: Exploring the Value of AI-Driven Rainfall Forecasts over the Greater Horn of Africa

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On the application of generative modelling for seasonal climate predictions

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- Palma_Abstract.jpg

Online Poster Session in Breakout Rooms in Zoom

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- Booklet_SMR4067_Post.session_online_.pdf

Open Problem Description for Hackathon, and Creating Groups to Resolve Them

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Opening

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- opening_climate_ai_2025.pptx

Poster session

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- Booklet_SMR4067_Post.sessions_in_person_.pdf

Poster session

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- Booklet_SMR4067_Post.sessions_in_person_.pdf

Reconstruction of the Surface Geostrophic Current in the Mediterranean Sea from Absolute Dynamic Topography Generated by Generative Adversarial Network (Adtgan)

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- Elysee_Abstract.jpg

Retrieving tropical cyclone intensity from climate output: AI approaches and challenges

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- Kieu_Abstract.jpg

Review of State-of-the Art of AI Developments In Weather and Climate Modelling

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Round Table Discussion on Uncertainty Evaluation

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Round Table Discussion: Can AI Models Fully Replace Physical Models for Long-Range Forecasting and Climate Simulations

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Sub-seasonal forecasting with the AIFS

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Testing Leonardo Accounts and Configuration

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Towards Development of Generative AI-based Sub-Seasonal to Seasonal Forecasting System

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Towards a Physics-Informed Neural Network for Ocean Circulation Modelling

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- Gorenstein_Abstract.jpg

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