Topic: Machine Learning for Data Assimilation

Friday, December 3, 2021 from 15-17 UTC

Organizers and Conveners: Nora Schenk, Marc Bocquet, Manuel Pulido, Lars Nerger

Link to Session Recordings (RIKEN homepage)

Program/Abstracts (PDF Download)

Presentations:

• VAE as a Stochastic Multidimensional Extension to Gaussian Anamorphosis
  Daisuke Hotta
• State, Global and Local Parameter Estimation using Local Ensemble Kalman Filters: Applications to Online Machine Learning of Chaotic Dynamics
  Quentin Malartic, Alban Farchi, Marc Bocquet
• Machine Learning Techniques to Construct Patched Analog Ensembles for Data Assimilation
  Lucia Minah Yang, Ian Grooms, Zofia Stanley
• Deep Learning for Retrieving Terrestrial Water Storage (TWS) from Spaceborne Gravity Observations and Satellite Altimetry
  Maria Aufschlager, Christopher Irrgang, Jan Saynisch-Wagner, Robert Dill, Eva Boergens, Maik Thomas
• Forecast Uncertainty for Data Assimilation using Neural Networks
  Maximiliano A. Sacco, Yicun Zhen, Pierre Tandeo, Manuel Pulido, Juan Ruiz

Time Zones:
15 – 17 UTC
Europe:           03 – 05 pm GMT (London)     | 04 – 06 pm CET (Berlin)
Asia/Australia: 11 – 01 am CST (Shanghai)  | 00 – 02 am JST (Tokyo)      | 02 – 04 am AEDT (Sydney)
Americas:        07 – 09 am PST (San Fran.) | 08 – 10 am MST (Denver)   | 10 – 12 am EST (New York)

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