Virtual Event: ECMWF-ESA Workshop on Machine Learning for Earth System Observation and Prediction
Posters
This page lists all poster files presented at this event.
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Application of the Long-Short Term Memory neural networks to model bias correction: idealized experiments with the Lorenz-96 model
Arata Amemiya (RIKEN Center for Computational Science)
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Toward an adaptive numerical integration scheme dependent on ML-predicted accuracy
Daniel Ayers (University of Reading)
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Machine learning based pollution anomaly detection using TROPOMI NO2 columns: a COVID-19 case study.
Jerome Barre (ECMWF)
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Comparative study of One-Stage ship detection techniques in SAR images
Filippos Bellos (National and Kapodistrian University of Athens), Theodore Betsas (National Technical University of Athens)
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Emulation of a Full Suite of Atmospheric Physics Parameterizations in NCEP GFS using a Neural Network
Alexei Belochitski (IMSG at NOAA/NWS/NCEP/EMC)
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High-Resolution Radar Echo Prediction with Machine Learning
Matej Choma (Meteopress)
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Improving air pollution forecast with machine learning
Sergey Dyshko (Science and Technology B.V.)
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Using machine learning to correct model error and application to data assimilation with a quasi-geostrophic model
Alban Farchi (CEREA, ENPC)
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DAN - An optimal Data Assimilation framework based on machine learning recurrent Networks
Anthony Fillion (ANITI)
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Simulating precipitation with supervised and generative learning models
Carlos Alberto Gomez Gonzalez (Barcelona Supercomputing Center)
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EO-ALERT: Machine Learning-Based On-Board Satellite Processing for Very-Low Latency Convective Storm Nowcasting
Robert Hinz (DEIMOS Space S.L.U.), Juan Ignacio Bravo (DEIMOS Space S.L.U.)
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Artificial intelligence reconstructs missing climate information
Christopher Kadow (German Climate Computing Center (DKRZ))
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Using Deep Learning to Extract Cyclone Regions of Interest (ROI)
Christina Kumler (CIRES/NOAA/GSL)
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Machine learning surrogate models for oceanic simulations' parameter tuning
Redouane Lguensat (LSCE-IPSL, LOCEAN-IPSL)
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Exploring Bayesian deep learning for weather forecasting with the Lorenz 84 system
Yang Liu (Netherlands eScience Center)
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Bow echo detection in forecasts and radar data with a U-Net
Arnaud MOUNIER (Meteo France)
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Accelerating Climate Model Computation by Neural Networks: A Comparative Study
Maha Mdini (RIKEN)
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Toward an integrated NWP-DA-AI system for precipitation prediction
Shigenori Otsuka (RIKEN)
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Automated NN generation: from the symbolic computation to the design of NN architectures for numerical predictions
Olivier PANNEKOUCKE (INPT-ENM, UMR CNRS CNRM, Météo-France, CERFACS)
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Deep Learning for the Verification of Warm Conveyor Belts in NWP and Climate Models
Julian Quinting (Karlsruhe Institute of Technology)
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Automatic fronts detection using a convolutional neural network.
Lucie ROTTNER (Météo-France)
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NWP Data Integration for Power Grids Risk Assessment Platform
Alla Sapronova
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A Neural Network-Based Observation Operator for Coupled Ocean-Acoustic Variational Data Assimilation
Andrea Storto (Centre for Maritime Research and Experimentation)
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Deriving global absorbing aerosol optical depth from satellite ultra-violet aerosol index: a deep learning approach
Jiyunting Sun (Royal Netherlands Meteorological Institute, R & D Satellite Observations; Delft University of technology, Geoscience & Remote Sensing)
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RRTMGP-NN: Fast and Accurate Predictions of Atmospheric Optical Properties by using Neural Networks
Peter Ukkonen (University of Copenhagen / Danish Meteorological Institute)
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Machine learning parameterization of tropical cyclone boundary layer
Leyi Wang (Nanjing University)
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Mode-decomposition Diagnosis for the Dynamical Processes of Sudden Stratospheric Warming Events
Zheng Wu (ETH Zurich, Switzerland )
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Forecasting short-duration heavy rain based on deep learning
Jie Xiahou
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Quantification of Rain to Improve Scatterometer Wind Speed by a Support Vector Machine Method
Xingou Xu (The Key Laboratory of Microwave Remote Sensing, National Space Science Center, Chinese Academy of Sciences)
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Towards AI-based model-data fusion in precipitation nowcasting
Mingming Zhu (State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences)
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Physics-augmented Deep Learning to Improve Tropical Cyclone Intensity and Size Estimation from Satellite Imagery
Jing-Yi Zhuo (Nanjing University)
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