Name: MAELSTROM dissemination workshop (28 March) and Machine Learning Workshop (29 March - 1 April)
Start: 2022-03-28T08:30:00+01:00
End: 2022-04-01T17:40:00+01:00
Location: Virtual

A Machine Learning Approach to Stochastic Downscaling of Precipitation Forecasts (in session "Session 3: Machine learning for feature detection and user applications")

A machine learning correction model for the warm bias over Arctic sea ice in atmospheric reanalyses (in session "Session 3b: Machine learning for feature detection and user applications")

Accelerating computational fluid dynamics with deep learning (in session "Session 4a: Machine learning tools and high-performance computing")

An Online-Learned Neural Network Chemical Solver for Stable Long-Term Global Simulations of Atmospheric Chemistry (in session "Machine Learning Workshop")

Building Digital Twins of the Earth for NVIDIA’s Earth-2 Initiative (in session "Session 4a: Machine learning tools and high-performance computing")

Causal deep learning for studying the Earth system: soil moisture-precipitation coupling in ERA5 data across Europe (in session "Session 3: Machine learning for feature detection and user applications")

Climate-Invariant, Causally Consistent Neural Networks as Robust Emulators of Subgrid Processes across Climates (in session "Machine Learning Workshop")

ClimateBench: A benchmark dataset for data-driven climate projections (in session "Machine Learning Workshop")

Convergence of HPC and Data Science at the Edinburgh International Data Facility (in session "Session 4: Machine learning tools and high-performance computing")

Convolutional neural networks for skillful global probabilistic prediction of temperature and precipitation on sub-seasonal time-scales (in session "Session 2: Machine learning for forecasts from now-casting to seasonal")

Deep learning augmented numerical weather prediction digital twin experiments for global precipitation forecasting (in session "Session 2b: Machine learning for forecasts from now-casting to seasonal")

Deep Learning for Earth Sciences in the HPC Context (in session "External Science Talks")

Deep Learning for the Verification of Synoptic-scale Processes in NWP and Climate Models (in session "Session 3a: Machine learning for feature detection and user applications")

Deep learning weather prediction: epistemology and new scientific horizons (in session "Session 2b: Machine learning for forecasts from now-casting to seasonal")

Deep-Sea (in session "EuroHPC Partner Project Talks")

Developing an emulator of an Ocean GCM (in session "Machine Learning Workshop")

Discussion with all speakers - moderated by Florian Pinault (in session "Session 4a: Machine learning tools and high-performance computing")

Discussion with all speakers - moderated by Matthew Chantry (in session "Machine Learning Workshop")

Discussion with all speakers - moderated by Mihai Alexe (in session "Session 3b: Machine learning for feature detection and user applications")

Discussion with all speakers - moderated by Peter Dueben (in session "Session 2b: Machine learning for forecasts from now-casting to seasonal")

Discussions between MAELSTROM and the speakers (in session "EuroHPC Partner Project Talks")

Discussions between MAELSTROM and the speakers (in session "External Science Talks")

Ensemble forecast of the Madden Julian Oscillation using a stochastic weather generator based on analogs of Z500 (in session "Session 2a: Machine learning for forecasts from now-casting to seasonal")

Exploring the Use of Machine Learning and Remote Sensing for Traffic Map Generation at Large Scale (in session "Session 4a: Machine learning tools and high-performance computing")

Forecasting Global Weather with Graph Neural Networks (in session "Session 2b: Machine learning for forecasts from now-casting to seasonal")

Generative Adversarial Networks for Extreme Super-Resolution and Downscaling of Wind Fields at Convection-Permitting Scales (in session "Session 3b: Machine learning for feature detection and user applications")

Generative machine learning for extreme climate scenarios (in session "Session 4a: Machine learning tools and high-performance computing")

High-Resolution Solar Power Nowcasting by Deep Learning: How to Extract Features from Historic Time Series, Remote Sensing, and Numeric Weather Prediction Models to achieve Optimized Machine Learning Forecasts (in session "Session 2: Machine learning for forecasts from now-casting to seasonal")

How AI/ML interpenetrate into Weather Forecast: NN emulator for radiation parameterization and Retrieval similar weather condition using satellite images (in session "Machine Learning Workshop")

Identifying Lightning Processes in ERA5 Soundings with Deep Learning (in session "Session 3a: Machine learning for feature detection and user applications")

Identifying relevant large-scale predictors for sub-seasonal precipitation forecast using explainable neural networks (in session "Session 2a: Machine learning for forecasts from now-casting to seasonal")

Improvements of the Adriatic Deep-Learning Sea Level Modeling Network HIDRA (in session "Session 3c: Machine learning for feature detection and user applications")

Improving medium-range ensemble forecasts with transformers (in session "Session 2b: Machine learning for forecasts from now-casting to seasonal")

Improving rare events predictions by oversampling tabular data with a mix of categorical and continuous variables by generative adversarial networks (in session "Session 4: Machine learning tools and high-performance computing")

Improving sub-seasonal forecasts by correcting missing teleconnections using ANN-based post-processing (in session "Session 2: Machine learning for forecasts from now-casting to seasonal")

Improving the prediction of the Madden-Julian Oscillation of the ECMWF model by post-processing (in session "Session 2a: Machine learning for forecasts from now-casting to seasonal")

Improving the radiative scheme with machine learning on an heterogeneous cluster (in session "Session 4: Machine learning tools and high-performance computing")

Interpretable Deep Learning for Probabilistic MJO Prediction (in session "Session 2: Machine learning for forecasts from now-casting to seasonal")

Introduction (in session "MAELSTROM Workshop")

Latent space, feature space and the global domain – how ozone research can benefit from explainable machine learning (in session "Session 3b: Machine learning for feature detection and user applications")

Learning from Noisy Class Labels for Earth Observation (in session "Session 3b: Machine learning for feature detection and user applications")

Machine learning for gravity waves in a climate model (in session "Machine Learning Workshop")

ML-based fire hazard model trained on thermal infrared satellite data (in session "Session 3a: Machine learning for feature detection and user applications")

Neural network emulation of precipitation and condensation processes in FV3GFS (in session "Machine Learning Workshop")

Neural-network parameterization of subgrid momentum transport learned from a high-resolution simulation (in session "Machine Learning Workshop")

Opportunistic mixture model for post-processing S2S temperature and precipitation forecasts using convolutional neural networks (in session "Session 2b: Machine learning for forecasts from now-casting to seasonal")

Pangeo: An Open Source Ecosystem for Data-Intensive Science (in session "External Science Talks")

Photographic Visualization of Weather Forecasts with Generative Adversarial Networks (in session "Session 3a: Machine learning for feature detection and user applications")

Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling (in session "Session 4: Machine learning tools and high-performance computing")

Physics-Informed Learning of Aerosol Microphysics (in session "Machine Learning Workshop")

Possibility for further discussions between the working groups (in session "External Science Talks")

Possibility for general discussion (in session "MAELSTROM Workshop")

Poster session (in session "Machine Learning Workshop")

Rainfall scenarios from AROME-EPS forecasts using autoencoder and climatological patterns (in session "Session 3: Machine learning for feature detection and user applications")

Red-Sea (in session "EuroHPC Partner Project Talks")

Spatially coherent postprocessing of cloud cover and precipitation forecasts using generative adversarial networks (in session "Session 3c: Machine learning for feature detection and user applications")

Spatio-temporal Forecasting of Meteorological Visibility over Northwest of Morocco using Long short-term memory (LSTM) network. (in session "Session 3c: Machine learning for feature detection and user applications")

Sub-Seasonal Probabilistic Precipitation Forecasting using Extreme Learning Machine (in session "Session 2a: Machine learning for forecasts from now-casting to seasonal")

The European Destination Earth project and its potential for boosting machine learning (in session "Session 4: Machine learning tools and high-performance computing")

Time-Consistent Downscaling of Atmospheric Fields with Generative Adversarial Networks (in session "External Science Talks")

TimeX (in session "EuroHPC Partner Project Talks")

Towards physics-based machine learning for land surface modeling: The case of land-atmosphere interactions (in session "Machine Learning Workshop")

Tropical Extreme Weather Event Management and Climate Adaptation via Supervised Computer Vision-based Algorithms (in session "Session 4a: Machine learning tools and high-performance computing")

Use of Machine learning for the detection and classification of observation anomalies (in session "Session 4a: Machine learning tools and high-performance computing")

Utilizing self-learning capability of a deep neural network and continuous monitoring of geostationary satellite to understand clouds structure and organization. (in session "Session 3: Machine learning for feature detection and user applications")

Welcome and introduction (in session "Machine Learning Workshop")

Why and how to learn end-to-end subgrid closures for atmosphere and ocean models? (in session "Machine Learning Workshop")

WP1 Summary on Applications and Data Sets (in session "MAELSTROM Workshop")

WP2 Summary on Software Tools (in session "MAELSTROM Workshop")

WP3 Summary on Hardware Benchmarks (in session "MAELSTROM Workshop")

MAELSTROM dissemination workshop (28 March) and Machine Learning Workshop (29 March - 1 April)

Material Package

#MLWS2022