5th ECMWF-ESA Machine Learning Workshop

Posters

This page lists all poster files provided to ECMWF for this event.

 
Machine Learning for Cloud Detection in Sentinel-2 Imagery: Enhancing Arctic Visibility to Support Indigenous Sea Ice Navigation
Defne Uras (ALSO Space - UCL Earth Sciences)
 
Interpretable Deep Learning for 3D GNSS Troposphere Tomography: Bridging AI and Physics-Based Atmospheric Models
Saeid Haji-Aghajany (Wrocław University of Environmental and Life Sciences)
 
Developement and implementation of geoML for CO2 monitoring within Agricultural Digital Twins
Asima Khan (University of Leicester)
 
HiResCastNet: A 3D Deep Learning Surrogate Model for Probabilistic Regional High- Resolution Subseasonal Forecast Through Downscaling.
Sofien Resifi (Physical Sciences and Engineering (PSE) at King Abdullah University of Science and Technology)
 
Leveraging machine learning to exploit new land satellite observations for NWP and CO2 monitoring
Patricia de Rosnay (ECMWF)
 
A neural network approach to the ray-tracing in limb scanning observation
Francesco Pio De Cosmo (University of Florence)
 
Advances in Machine Learning–Based Cloud Detection from IASI Observations
Chiara Zugarini (Istituto per le Applicazioni del Calcolo (IAC) - Consiglio Nazionale delle Ricerche (CNR))
 
Opening the Black Box of Ocean Wave Learning
Felipe Minuzzi (Universidade Federal do Rio Grande do Sul)
 
Assessing AI weather models’ tropical cyclone intensity forecasts using autonomous surface vehicle data
Toshiyuki Bandai (NTT)
 
Machine-learning based variational data assimilation for unknown emission source identification in urban environments
Linfeng Li (Imperial College London)
 
Latent Twins Framework for Real-Time Retrieval from Far-Infrared Satellite Observations
Cristina Sgattoni (CNR - IBE)
 
Learning Generic Probabilistic Latent Representations for Multi-Modal Earth Observation Forecasting and Reconstruction
Richard Faucheron (CESBIO / CNES)
 
Predicting the Distance to the AMOC Tipping Point
Francesco Guardamagna (Utrecht University)
 
Hidden Markov Models for Desertification Assessment in Mediterranean Karst Ecosystems
Filippo Gregori (Università di Bologna)
 
Enhancing temporal and vertical resolution of Planetary Boundary Layer satellite temperature and humidity retrievals using in-situ AMDAR observations and Deep Learning approaches
Melina Sol Yabra (NASA Goddard Space Flight Center)
 
Direct observation prediction of clouds capturing kilometer scale processes
Dhamma Kimpara (NSF National Center for Atmospheric Research)
 
Trace4EO: A Provenance Framework for Integrity, Transparency, and Reproducibility in Earth Observation Workflows
Patryk Grzybowski (CloudFerro S.A.)
 
Context selection for stylistically controlled weather forecast text generation
Jasper Wijnands (KNMI)
 
On the effective resolution of AI weather prediction models
Tobias Selz (LMU München)
 
Regional Data-Driven Weather Prediction for the Eastern Alps and Northern Adriatic
Matjaž Puh (University of Nova Gorica, Slovenian Environment Agency)
 
Towards Disentangling Predictive Uncertainty in End-to-End AI Weather Forecasts
Rodrigo Almeida (Fraunhofer HHI)
 
Supporting Weather and Climate Application Development with ML-Friendly Earth Observation Data
Lauren Biermann (EUMETSAT)
 
Spatiotemporal Forecasting via Machine Learning and Data Assimilation: Applications to Pollution and Flood Risk
Fangxin Fang (Imperial College London)
 
Data-Driven Retrieval of Ageostrophic Surface Currents from Satellite Geostrophy and Reanalysis Winds in a Marginal Sea
Amirhossein Barzandeh (Department of Marine Systems, Tallinn University of Technology, Tallinn, 12618, Estonia)
 
A Data-Driven Approach to Modelling a Global Distribution of Ice Nucleating Particles
Gabriella Wallentin (Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT))
 
Towards inverting Spanish NOx emissions with TROPOMI observations and variational autoencoders.
James Petticrew (Barcelona Supercomputing Centre)
 
Advancing Hydrological Data Assimilation Frameworks with Machine Learning
Cagatay Cakan (Aalborg University)
 
Unified Access to DEIMS In-Situ Data via STAC for Scalable Earth Observation Machine Learning
Ignacio Masari (Earth Observation Data Center (EODC) GmbH) , Adrian Di Paolo (Earth Observation Data Center (EODC) GmbH)
 
Forecasting Cold Winter Temperatures in Finland with the Aila AI Weather Model
Leila Hieta (Finnish Meteorological Institute)
 
Direct AROME Analysis Emulation Using SEVIRI Data
Vincent Chabot (Météo France)
 
Strongly coupled ocean/sea-ice surface data assimilation experiments
Andrea Cipollone (CMCC)
 
3D Radar Echo Motion Estimation Using Deep Learning: A Case Study in Slovakia
Peter Pavlík (Kempelen Institute of Intelligent Technologies)
 
Graph-based data-driven weather prediction over Austria: Assessing Temporal Resolution Trade-Offs
Çağlar Küçük (GeoSphere Austria)
 
Can AI-based weather prediction models simulate the butterfly effect? The role of architecture and implementation.
Tobias Selz (Karlsruhe Institute for Technology (KIT))
 
Towards an aerosol-aware ML-based cloud microphysics parameterization in ICON
Ellen Sarauer
 
From Marine Heatwaves Towards a Framework for Predicting Compound Heatwave-Drought Extremes
Ana Oliveira (CoLAB +ATLANTIC)
 
Climate and Environmental Digital Twins for Human Health: Leveraging Earth Observation for Compound Climate and Air Quality Extremes Early Warning
Ana Oliveira (CoLAB +ATLANTIC)
 
FengYuan: An End-to-End Deep Learning Model for Global Weather Forecasting
Yiheng Shi (The China Meteorological Administration (CMA))
 
Darwin Gödel Machine Agentic AI Framework for Earth System Observation and Prediction Applications
Jakub Juranek (Polish Academy of Sciences)
 
eMONARCH - an AI-driven emulator of the MONARCH CTM (BSC-CNS)
David Mathas (BSC)
 
Probabilistic downscaling of paleoclimate simulations using diffusion models
Trang Nguyen (University of Bern)
 
Relationship between monthly precipitation and mean maximum air temperature at the 850 hPa boundary level in a typical East Mediterranean mountain area
Fadi Karam (Department of Environmental Engineering. Faculty of Agricultural Sciences. Lebanese University)
 
A Latent Twin Architecture for Robust Clear-Sky Retrieval from IASI Acquisitions
Michele Martinazzo (University of Bologna)
 
Machine-Learning Improved Metocean Forecasting for All
Stephan Kistner (DHI A/S)
 
Integrating LiDAR, Satellite Time-Series, and Ecological Features in a Machine Learning Pipeline for Enhanced Forest Carbon Monitoring
Samuele Capobianco (Consultant with the European Commission, Joint Research Centre (JRC); Engineering Ingegneria Informatica SpA Consultant) , Selene Patani (Consultant with the European Commission, Joint Research Centre (JRC))
 
Multi-Modal Generative Video Prediction of All-Sky and MTG Satellite Imagery for Solar Irradiance Nowcasting
Milon Miah (German Aerospace Center)
 
A unified latent-space background-error covariance model for midlatitude and tropical atmospheric data assimilation
Boštjan Melinc (University of Ljubljana)
 
Machine Learning-Based Reconstruction and Projection of Global Land Use at High Resolution
Marina Castaño Ishizaka (BSC)
 
Detecting Wildfires Leveraging Meteosat Third Generation and Machine Learning Techniques
Alessandro Mercatini (Italian Institute for Environmental Protection and Research) , Nazario Tartaglione (Italian Institute for Environmental Protection and Research)
 
Improving nowcasts of convective hazards in Switzerland using deep learning
George Pacey (University of Bern)
 
Quantifying environmental impacts on bias in Arctic TROPOMI methane retrievals using machine learning
Tuomas Häkkilä (Finnish Meteorological Institute)
 
Advancing Hybrid Machine Learning Observation Operators for Sea Ice: Incorporating Scan-Angle Dependency for AMSU-A
Cristina González Flórez (Danish Meteorological Institute)
 
Super-resolution of satellite observations of sea ice thickness using diffusion models and physical modelling.
Fabio Mangini (Nansen Environmental and Remote Sensing Center (NERSC))
 
Continuous Meteorological Field Reconstruction using Neural Transformer Operators
Azhar Gafoor (Indian Institute of Science)
 
Machine learning-based forward operators for visible and near-infrared satellite images
Leonhard Scheck (DWD)
 
Shared-Latent-Space Transformer for Multi-Sensor Harmonization in Earth Observation
Zayd Mahmoud Hamdi
 
LULC Mapping of the Peruvian Andes using EnMAP Hyperspectral Imagery, Machine Learning and High-Performance Computing
Daria-Ioana Radu (University of Cambridge)
 
Assessing and Exploiting the Joint Information Content of Multiple Solar Channels Using Distributional Regression Networks
Stefano Franzoni (Ludwig Maximilians Universität)
 
Democratizing Weather Forecasting in Least Developed Countries through AI-Based Weather Prediction: Insights from a Pilot Project in Malawi
Dina Abdel-Fattah (Norwegian Meteorological Institute)
 
Evaluation of ML emulators for covariance propagation in realistic DA workflows
Simon Toedtli (NSF NCAR)
 
DestinE Platform: Accelerating Climate Innovation Through Machine Learning and Advanced Digital Twin Services
Matteo Cortese (Serco Italy)
 
MLCast Community: An Open-Source Framework for Machine Learning-Based Weather Nowcasting
Gabriele Franch (Fondazione Bruno Kessler)
 
Improving Sea Level Height warnings in Venice with hybrid sub-seasonal forecasts
Antonello Squintu (CMCC Foundation)
 
Hyperparameter-Tuned Machine Learning Models for Predicting Sea-Level Anomalies in the Venice Lagoon
Mehri Hashemi Devin (CMCC Foundation - Euro- Mediterranean Center on Climate Change)
 
High-Resolution Urban Temperature Downscaling Using Machine Learning and ICON+TERRA_URB Outputs
Tanguy Houget (DIATI - Politecnico di Torino / LMFA - Ecole Centrale de Lyon)
 
Deep learning for high-resolution climate projections: a Latent Diffusion Model emulating dynamical downscaling of precipitation and temperature
Elena Tomasi (Fondazione Bruno Kessler)
 
How well can ML-based models predict hot spell duration in Europe?
Duncan Pappert (University of Bern)
 
Feature selection for global data-driven seasonal forecasts of heatwaves
Fabio Merizzi (University of Bologna)
 
Sentinel-4 Capabilities for Volcanic Emission Monitoring and ML-Enhanced Retrievals
Giovanni Salvatore di Bella (University of Catania)
 
Advancing Actionable Seasonal Forecasts with Deep Learning: A Post-Processing Comparison in the Blue Nile Basin
Rebecca Wiegels (IMKIFU, Campus Alpin, KIT)
 
Bris: A high-resolution data-driven weather model for public weather forecasting
Magnus Sikora Ingstad (Norwegian Meteorological Institute)
 
Non-linear Machine Learning for Cloud Controlling Factor Analysis
Lina Rennstich (KIT)
 
MAR.ia: a diffusion-based emulator for high-resolution climate downscaling over Belgium
Elise Faulx (Uliege) , Sacha Peters (Uliège)
 
RACCOONN: Retrievals of Atmospheric Conditions Computed using Observations and Optimized Neural Networks
Benoit Tremblay (Environment and Climate Change Canada)
 
Schools on the Frontline: A Spatial Assessment of Children’s Exposure to Climate Extremes
Diego Santos (ESA)
 
Towards ensemble data assimilation of satellite radiances in Machine Learning Limited Area Models
Marcello Grenzi (University of Bologna)
 
Assimilation of sea surface temperature in the Mediterranean Sea using ML-based operators
Daniele Bigoni (CMCC Foundation, Italy)
 
Out-of-Distribution Skill of AI Weather Prediction Models in the Past, Present and Future
Mozhgan Amiramjadi (Karlsruhe Institute of Technology)
 
AI-Driven Mapping of Buildings, Roads, and Hydrography for Rural Electrification in Togo
Franco Fernandez Lopez (Murmuration SAS)
 
Deep learning based solar nowcasting system combining satellite observations and NWP data
Soma Oláh (HungaroMet Hungarian Meteorological Service)
 
Characterizing cloud spatial structures and their transitions to extreme precipitation over the Alps through self-supervised learning
Daniele Corradini (University of Cologne)
 
Reconstructing the Seasonal Cycle of Upper-Ocean Biogeochemical Profiles in the Norwegian Sea with BGC Argo–Informed Machine Learning
Fabio Mangini (Nansen Environmental and Remote Sensing Center (NERSC))
 
EnsAI: An Emulator for Atmospheric Chemical Ensembles
Michael Sitwell (Environment and Climate Change Canada)
 
Understanding Changes in Tropical Wetlands with Remote Sensing, Machine Learning and Land Surface Modeling
Pantula Chandana (University of Leicester - National Centre for Earth Observation)
 
Destination Earth Data Lake Capabilities for AI/ML Developments: Bringing Data, Services and Infrastructure Together
Oriol Hinojo Comellas (EUMETSAT)