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SUMMARY:Training course: Data assimilation
DTSTART:20200224T084500Z
DTEND:20200228T170000Z
DTSTAMP:20260613T062600Z
UID:indico-event-153@events.ecmwf.int
CONTACT:events@ecmwf.int
DESCRIPTION:Overview\n\nThis five-day module focuses on describing data as
 similation methods and general aspects of assimilating observations. Aspec
 ts of the implementation of the assimilation techniques for real-size nume
 rical weather prediction (NWP) systems will also be described.\n\nAs well 
 as lectures there will be discussion and hands-on sessions - please see th
 e draft timetable for more details.\n\nMain topics:\n\n\n	The fundamental 
 data assimilation concepts\n	Optimal Interpolation\, 3D-Var\, 4D-Var and t
 he Kalman filter\n	Ensemble Kalman Filter methods\; Ensemble of Data Assim
 ilations and uncertainty estimation\; Hybrid variational/ensemble based me
 thods\n	Modelling of error covariances\; handling of non-Gaussian errors\n
 	The global observing system\, with emphasis on how to use satellite obser
 vations\n	Bias correction\, quality control and diagnostics\n	Applications
  of data assimilation methods for the land surface\, ocean\, atmospheric c
 omposition and reanalysis\n\n\nRequirements\n\nParticipants should have a 
 good meteorological and mathematical background\, and in particular a good
  understanding of linear algebra. They are expected to be familiar with th
 e contents of standard meteorological and mathematical textbooks.\n\nIf yo
 u are less familiar with data assimilation concepts\, such as Bayes Theore
 m\, you may wish to consider attending the University of Reading Introduct
 ory course\, which runs the week before our course\; for details see the c
 orresponding tab on this page.\n\nIntroductory material not covered by the
  course can be found in our lecture note series.\n\nSome practical experie
 nce in numerical weather prediction is an advantage.\n\nAll lectures will 
 be given in English.\n\nPlease note that no funds are available from ECMWF
  to support participants' attendance at training courses.\n\nA course fee 
 is payable by applicants who do not reside in an ECMWF Member or Co-operat
 ing State.\n\nhttps://events.ecmwf.int/event/153/
IMAGE;VALUE=URI:https://events.ecmwf.int/event/153/logo-3547453490.png
LOCATION:ECMWF
URL:https://events.ecmwf.int/event/153/
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