Virtual Event: ECMWF-ESA Workshop on Machine Learning for Earth System Observation and Prediction
from Monday, 5 October 2020 (11:00) to Thursday, 8 October 2020 (15:30)
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Monday, 5 October 202011:00 Welcome and introduction - ECMWF - Andy Brown (ECMWF)Welcome and introduction - ECMWF
- Andy Brown (ECMWF)
11:00 - 11:1511:15 Welcome and introduction - ESA - Pierre-Philippe Mathieu (ESA)Welcome and introduction - ESA- Pierre-Philippe Mathieu (ESA)
11:15 - 11:3011:3011:30 - 13:00Contributions-
11:30 Accelerating and Explaining Earth System Process Models with Machine Learning - David Gagne (National Center for Atmospheric Research)
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12:15 Learning from earth system observations: machine learning or data assimilation? - Alan Geer (ECMWF)
13:00 Lunch breakLunch break13:00 - 14:0014:0014:00 - 15:30Contributions-
14:00 The Rise of AI for EO - Pierre-Philippe Mathieu (ESA)
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14:30 Leveraging Modern AI/ML Techniques in NWP Including Data Fusion/Assimilation - Sid Boukabara (NOAA)
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15:00 Exploring the Frontiers of Deep Learning for Earth System Observation and Prediction - David Hall (NVIDIA)
15:30 Coffee breakCoffee break15:30 - 16:0016:0016:00 - 17:00Contributions-
16:00 On the Interpretation of Neural Networks Trained for Meteorological Applications - Imme Ebert-Uphoff (Colorado State University)
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16:30 Deep Hashing for Scalable Remote Sensing Image Retrieval in Large Archives - Begüm Demir (TU Berlin)
17:0017:00 - 18:30 -
Tuesday, 6 October 202008:5508:55 - 10:30Contributions
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09:00 Using Machine Learning to advance hour-scale heavy rain forecast with high resolution ECMWF Global Model and Local Meso-scale Model Forecasts - Qi Zhong (China Meteorological Administration Training Centre)
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09:30 Artificial Intelligence in ESA Contribution to the United Nations Framework Convention on Climate Change (UNFCCC) : An Overview - Eduardo Pechorro (ESA Climate Office) Amy Campbell (National Oceanography Centre Graduate School)
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10:00 Neural network products in land surface data assimilation - Peter Weston (ECMWF)
10:30 Coffee breakCoffee break10:30 - 11:0011:0011:00 - 13:00Contributions-
11:00 Big Data, Big Computation, and Machine Learning in Numerical Weather Prediction - Takemasa Miyoshi (RIKEN)
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11:30 Artificial Neural Network at the service of Data Assimilation (and vice versa) - Rossella Arcucci (Imperial College London)
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12:00 Using machine learning and data assimilation to learn both dynamics and state - Marc Bocquet (Ecole des Ponts ParisTech)
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12:30 Combining data assimilation and machine learning to emulate hidden dynamics and to infer unresolved scale pametrisation. - Alberto Carrassi (University of Reading and NCEO (UK); University of Utrecht (NL))
13:00 LunchLunch13:00 - 14:0014:0014:00 - 15:30Contributions-
14:00 Data Assimilation and Machine Learning Science at ECMWF - Massimo Bonavita (ECMWF)
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14:30 Joint learning of variational data assimilation models and solvers - Ronan Fablet (IMT Atlantique)
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15:00 Hyperparameter learning in data assimilation systems - Manuel Pulido (Universidad Nacional del Nordeste)
15:30 Coffee breakCoffee break15:30 - 16:0016:0016:00 - 18:00Contributions-
16:00 Bayesian Deep Learning for Data Assimilation - Peter Jan van Leeuwen (Colorado State University)
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16:30 Machine Learning for Applied Weather Prediction - Sue Ellen Haupt (National Center for Atmospheric Research)
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17:00 Deep Unsupervised Learning for Climate Informatics - Claire Monteleoni (University of Colorado)
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17:30 Deep Learning for Post-Processing Ensemble Weather Forecasts - Nikoli Dryden (ETH Zurich)
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Wednesday, 7 October 202009:0009:00 - 10:30Contributions
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09:00 Automatic detection of weather events in high-resolution NWP outputs - Laure Raynaud (Météo-France)
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09:30 Machine learning at ECMWF - Peter Dueben (ECMWF)
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10:00 Probabilistic Deep Learning for Postprocessing Wind Forecasts in Complex Terrain - Daniele Nerini (MeteoSwiss)
10:30 Coffee breakCoffee break10:30 - 11:0011:0011:00 - 13:00Contributions-
11:00 Significance-tested and physically constrained interpretation of a deep-learning model for tornadoes - Ryan Lagerquist (Cooperative Institute for Research in the Atmosphere (CIRA))
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11:30 Neural Networks for Postprocessing Ensemble Weather Forecasts - Sebastian Lerch (Karlsruher Institut für Technologie (KIT))
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12:00 Towards an end-to-end data-driven weather model - Duncan Watson-Parris (University of Oxford)
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12:30 Emulation of gravity wave parameterisation in weather forecasting - Matthew Chantry (University of Oxford)
13:00 Lunch breakLunch break13:00 - 14:0014:0014:00 - 15:30Contributions-
14:00 Physics Guided Machine Learning: A New Framework for Accelerating Scientific Discovery - Vipin Kumar (University of Minnesota)
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14:30 Assessing Machine Learning Approaches for Physical Parameterizations in Atmospheric General Circulation Models - Christiane Jablonowski (University of Michigan)
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15:00 Model optimization with a genetic algorithm - Pieter Houtekamer (Environment and Climate Change Canada)
15:30 Coffee breakCoffee break15:30 - 16:0016:0016:00 - 18:00Contributions-
16:00 Analog Forecasting of Extreme‐Causing Weather Patterns Using Deep Learning - Ashesh Chattopadhyay (Rice University)
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16:30 What If The Easiest Part of the Global Atmospheric System For Machines To Learn Is The Dynamics? - Dale Durran (University of Washington)
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17:00 S2S forecasting using large ensembles of data-driven global weather prediction models - Jonathan Weyn (University of Washington)
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17:30 Description of Working Groups - Massimo Bonavita (ECMWF)
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Thursday, 8 October 202009:0009:00 - 10:30Contributions
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09:00 WG4 (Ensembles, Product Generation) chaired by Laure Raynaud (Météo-France) and Nicolas Longepe (ESA)
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09:00 WG1 (Observations) chaired by Alan Geer (ECMWF) and Bertrand Le Saux (ESA/ESRIN)
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09:00 WG2 (Data Assimilation) chaired by Alberto Carrassi (Univ. of Reading) and Rosella Arcucci (Imperial College)
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09:00 WG3 (Models) chaired by Massimo Bonavita (ECMWF) and Peter Dueben (ECMWF)
10:30 Coffee breakCoffee break10:30 - 11:0011:0011:00 - 12:30Contributions-
11:00 WG1 (Observations) chaired by Alan Geer (ECMWF) and Bertrand Le Saux (ESA/ESRIN)
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11:00 WG2 (Data Assimilation) chaired by Alberto Carrassi (Univ. of Reading) and Rosella Arcucci (Imperial College)
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11:00 WG3 (Models) chaired by Massimo Bonavita (ECMWF) and Peter Dueben (ECMWF)
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11:00 WG4 (Ensembles, Product Generation) chaired by Laure Raynaud (Météo-France) and Nicolas Longepe (ESA)
12:3012:30 - 13:0013:00 Lunch breakLunch break13:00 - 14:0014:0014:00 - 15:30 -