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School on Data Assimilation
School on Data Assimilation
from 26 April 2011 to 06 May 2011
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Venue:

The school will be in the AlbaNova main building (Roslagstullsbacken 21) in auditorium FB53 (on Tuesday and Wednesday) and in FA32 on Thursday and Friday. On Saturday morning we will be in the Nordita auditorium; see the photo on the right.

Main topics:

The school consists of teaching lessons during the first week and project work in conjuction with the program on predictability and data assimilation in the second week.
  1. Assimilation of observations. The case of meteorology and oceanography. Inverse problems in general. Bayesian estimation.
  2. The linear case. Best Linear Unbiased Estimation. Simple examples.
  3. Advanced assimilation methods. Variational assimilation. Optimization. Adjoint equations.
  4. Advanced assimilation methods. Kalman Filter. Ensemble Kalman Filter and variants.
  5. Evaluation of assimilation algorithms
  6. The limits of present methods. Future perspectives. Particle filters.

Schedule:

First week:

Lecturers: Olivier Talagrand (OT) and Pavel Sakov (PS)

Tuesday, 26 April

 9:00 Registration

10:00 Lecture 1 by OT: Assimilation of observations. The case of meteorology
      and oceanography. Inverse problems in general. Bayesian estimation.

11:00 short coffee break

11:15 Lecture 2 by OT, continuation of Lecture 1

12:30 lunch

14:00 Lecture 3 by OT: The linear case. Best Linear Unbiased Estimation.
      Simple examples.

15:00 coffee

15:30 Lecture 4 by OT, continuation of Lecture 3

16:30 student presentation

17:30 informal reception  with wine and cheese

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Wednesday, 27 April

 9:00 Lecture 5 by PS: Kalman filter and smoother

10:00 short coffee break

10:15 Lecture 6 by PS, continuation of Lecture 5

11:15 short coffee break

11:30 Lecture 7 by OT: Advanced assimilation methods.
      Variational assimilation. Adjoint equations.

12:30 lunch

14:00 Lecture 8 by OT, continuation of Lecture 7

15:00 coffee

15:30 Lecture 9 by PS: Ensemble Kalman filter (EnKF) and variants.

16:30 short coffee break

16:45 planning of project work

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Thursday, 28 April

 9:00 Lecture 10 by PS, continuation of Lecture 9

10:00 short coffee break

10:15 Lecture 11 by OT: Advanced assimilation methods. Variational assimilation.
      Performances.

11:15 short coffee break

11:30 Lecture 12 by OT, continuation of Lecture 11

12:30 lunch

14:00 Lecture 13 by PS: Ensemble Kalman Smoother (EnKS) and Adaptive EnKF (AEnKF).
      Localization, inflation etc. Iterative methods.

15:00 coffee

15:30 Lecture 14 by PS, continuation of Lecture 13

16:30 short coffee break

16:45 questions regarding project work

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Friday, 29 April

 9:00 Lecture 15 by PS, continuation of Lecture 14

10:00 short coffee break

10:15 Lecture 16 by PS, continuation of Lecture 15

11:15 short coffee break

11:30 Lecture 17 by OT: Evaluation of assimilation algorithms

12:30 lunch

14:00 Lecture 18 by OT, continuation of Lecture 17

15:00 coffee

15:30 start of project work

18:00 common Dinner at AlbaNova

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Saturday, 30 April

 9:00 Lecture 19 by OT: The limits of present methods.
      Future perspectives. Particle filters.

10:00 short coffee break

11:15 Lecture 20 by OT, continuation of Lecture 19

12:30 lunch

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Recommended reading:

In addition to the papers Talagrand.1987.pdf and Talagrand.2010.pdf
available on the link below, we recommend the following reading.

General

Kalnay, E., 2003, Atmospheric modeling, data assimilation and
predictability. Cambridge University Press, Cambridge, UK, 341 pp..

Talagrand, O., 1995: Assimilation of observations, an introduction. J.
Meteor. Soc. Japan, 75, 1B, 191-209 (attached).


Variational assimilation

P. Courtier and O. Talagrand, 1990, Variational assimilation of
meteorological observations with the direct and adjoint shallow-water
equations, Tellus, 42A, 531-549.

O. Talagrand, 2010, Variational Assimilation. in W. A. Lahoz, B. Khattatov
and R. Ménard (editors), Data Assimilation: Making Sense of Observations,
Springer-Verlag GmbH Berlin Heidelberg, Germany, ISBN : 978-3-540-74702-4,
41-67 (attached)


Ensemble Kalman Filter

Geir Evensen: Data assimilation, The Ensemble Kalman Filter, 2nd ed.,
Springer, 2009

The Ensemble Kalman Filter: Theoretical Formulation and Practical
Implementation
Geir Evensen,
Ocean Dynamics, 53, 343-367, 2003.
Available on http://link.springer.de


Particle filters

Particle filtering in geophysical systems Van Leeuwen, P.J., Monthly
Weather Rev. 137, 4089-4114, 2009 (available at the address
http://www.met.reading.ac.uk/~xv901096/research/publications.html)

Link to video recordings

Registration deadline was: 22 March 2011


Dates: from 26 April 2011 09:00 to 06 May 2011 18:00
Location:
Chairs: BRANDENBURG, Axel
Dr. BRANDEFELT, Jenny
Prof. NYCANDER, Jonas
Material: Partie.1.ppt
Partie.1.pdf
Partie.2.ppt
Partie.2.pdf
Partie.3.ppt
Partie.4.ppt
PS-Lecture1
PS-Lecture2
PS-Lecture3
PS-Lecture4
PS-Lecture5
pictures
Didactic material
Partie.3.pdf
Partie.4.pdf
Partie.5.pdf
Partie.6.pdf
L.Smith_Talk
Papers
Poster

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