Topic: Data Assimilation Infrastructure - Software, Frameworks, HPC

Friday, January 20, 2022 from 7-9 UTC

Organisers and Conveners: James Taylor, t.b.a

One of the underlying assumptions underpinning many data assimilation schemes (including variational, Kalman filter, or ensemble-based) is that the background, observational and model errors are Gaussian in distribution. However, this assumption is often false, with errors taking a non-Gaussian distribution. In this session, we invite all contributions to the development of non-Gaussian DA.

Call for abstracts - t.b.a

Presentations:

  • Title t.b.a
    Authors t.b.a

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

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