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SUMMARY:Training course: Data assimilation
DTSTART:20230522T080000Z
DTEND:20230526T145000Z
DTSTAMP:20260722T233000Z
UID:indico-event-333@events.ecmwf.int
CONTACT:events@ecmwf.int
DESCRIPTION:This five-day course focuses on describing data assimilation m
 ethods and general aspects of assimilating observations. Aspects of the im
 plementation of the assimilation techniques for real-size numerical weathe
 r prediction (NWP) systems will also be described.As well as lectures ther
 e will be discussion and hands-on sessions. Main topicsThe fundamental da
 ta assimilation conceptsOptimal Interpolation\, 3D-Var\, 4D-Var and the Ka
 lman filterEnsemble Kalman Filter methods\; Ensemble of Data Assimilations
  and uncertainty estimation\; Hybrid variational/ensemble based methodsMod
 elling of error covariances\; handling of non-Gaussian errorsThe global ob
 serving system\, with emphasis on how to use satellite observationsBias co
 rrection\, quality control and diagnosticsApplications of data assimilatio
 n methods for the land surface\, ocean\, atmospheric composition and reana
 lysisRequirementsParticipants should have a good meteorological and mathem
 atical background\, and in particular a good understanding of linear algeb
 ra. They are expected to be familiar with the contents of standard meteoro
 logical and mathematical textbooks.Introductory material not covered by th
 e course can be found in our lecture note series.Some practical experience
  in numerical weather prediction is an advantage.All lectures will be give
 n in English.N.B. Please note the UK National Centre for Earth Observation
  (NCEO) and the University of Reading will also run a data assimilation tr
 aining course from 9- 12 May 2023. This free course will take place in the
  University of Reading\, just down the road from where the ECMWF trainings
  will be held. For more information\, please visit https://research.readin
 g.ac.uk/met-darc/training/training-courses/darc-nceo-da-2023/  \n\nhttps
 ://events.ecmwf.int/event/333/
IMAGE;VALUE=URI:https://events.ecmwf.int/event/333/logo-3547453490.png
LOCATION:ECMWF
URL:https://events.ecmwf.int/event/333/
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