Data Assimilation Education Foru

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					 Data Assimilation Education Forum
Part I: Overview of Data Assimilation
  Identifying Current and Future Shortfalls in
          Data Assimilation Education




                             January 21, 2008

                             presented by
                           Michele Rienecker
                                 Head
                     NASA/GSFC/Global Modeling and
                           Assimilation Office
            Thank you to…..
•   Eugenia Kalnay, UMD
•   Robert Miller, OSU
•   Carl Wunsch, MIT
•   Keith Haines, U. Reading
•   Nancy Nichols, U. Reading
                  The Problem

• Lack of qualified personnel in data assimilation
  (state estimation, inverse methods) for large
  systems
• Lack of qualified personnel with interest and
  experience in radiative transfer
•    Lack of programming and computing skills for
    high end computers
                   University Experience - 1
•   UMD: a very successful data assimilation educational program -
        Chaos-Weather Project
         •   Interdisciplinary: Mathematicians, Physicists, Atmospheric and Oceanic scientists
         •   Started in 2001, 12 completed PhD’s, about 10 underway.
         •   2 graduate courses on data assimilation taught on a regular basis
         •   Introductory course attracts some of the best students in Atmospheric Sciences and Applied
             Math (~ 8-10 students/ year)
         •   ~1/2 take the follow-on, advanced course
         •   It has been essential to develop a collection of simple models and methods for data assimilation
             that the students can learn from and work with.


•   Developing the infrastructure (including computational resources) for
    development and testing of methods is essential.
•   Need access to an operational system

• 2007 JCSDA summer workshop - ~ 60 applicants - lecturers
  from UMD, JCSDA, NCEP, GMAO, NRL, and other universities.
               University Experience - 2

•   OSU: Andrew Bennett’s summer school is now taught as a regular
    course, but # of eligible students is pretty small
• Problem: understanding DA requires a level of mathematical
  sophistication that most students simply do not have
• Solution: incorporate more mathematical concepts into graduate
  courses from the beginning, including problems of high
  complexity
• Problem: students are averse to this!
                University Experience - 3
•   MIT: “Inference from Data and Models” - ~50% of students not
    meteorology or oceanography
•   Much of what is now done in NWP centers and in large university
    projects involves the application of these ideas to real systems to get
    real results --- a numerical engineering problem
•   A growing interest in the methods by the Engineering Schools
•   Headed toward a situation in which data assimilation-like methods will
    become part of the standard engineering curriculum
•   The students involved have to learn enough about how we do things to
    make it work, but none of them seems interested in extending the
    methods
•   A growing tendency to run big numerical models as black boxes, and to
    download vast data sets from the web that they then regard as 'truth'.
    We need to produce a new generation that is adept in both using models
    and data, has a realistic sense of what both are good for, and retains a
    healthy skepticism about what was assumed and done.
                             U. Reading Experience
•   Data assimilation program promoted through Mathematics and
    Meteorology Depts
•   Strong offering of PhD projects - PhD students are supported by
    grants from the UK Research Councils.
•   NERC and EPSRC PhD CASE awards - in co-operation with industry and
    scientific research agencies. The project is agreed between the
    university and the industry and must be scientifically competitive to win
    the award. The project has both industrial and academic supervisors
    and the student is funded to spend some part of the time getting work
    experience in the industry. This is attractive to good students and is an
    excellent way to gain interest in the subject!
•   At least 16 students funded by this arrangement working on topics in
    data assimilation with support from the Met Office.

     NERC: Natural Environment Research Council
     EPSRC: Engineering and Physical Sciences Research Council
     CASE: Co-operative Awards in Science and Engineering [Cooperating organization provides at least 1/3 of required funding]
            U. Reading Experience (ctd)
• NERC funded Centre of Excellence in Data Assimilation (DARC) -
  a distributed research centre specifically in Data Assimilation
  with the Directorate centred at Reading:
       ・University of Reading
       ・University of Oxford
       ・University of Cambridge
       ・Rutherford Appleton Laboratory
       ・University of Leeds, and
       ・Edinburgh University.

• DARC Post-Doctoral Fellows at Reading help to supervise PhD
  students, and also collaborate with the MetOffice and ECMWF
  on projects on data assimilation.
• This creates a critical mass doing research in the area -
  provides a strong research environment for students.
           U. Reading Experience (ctd)
• One of the DARC’s main objectives is to provide training in data
  assimilation - lecturing and tutorial teaching in summer schools,
  NATO ASI meetings, and and similar training courses, by giving
  seminars at other institutions, …..

• A web-page dedicated to providing tutorial examples and
  computer programs that can be used freely by other groups for
  training. This is a popular website and is used internationally. We
  get around 100 hits per month on this site.


• http://darc.nerc.ac.uk
                         What we need

•   Ph.D. level scientists with good grounding in data assimilation methods
    and experience with large models and/or expertise relevant to satellite
    data (radiative transfer)
•   Scientists who can advance our science, not just apply existing systems
    as a black box to a science problem
•   Scientists who have some experience with (or exposure to) large,
    complex systems and models and don’t require extensive OJT
•   Scientists who can program in modern Fortran on high end computing
    architectures
                           Summary
• Challenge: Need to entice students to be interested in
  assimilation development, not just in using an existing system
• Challenge: Need to excite students to work in this discipline
  after graduation
• Need to have a partnership with Math depts to ensure that
  students have a strong background in stats, analysis, and PDEs
• Need to reach out to engineering schools - appropriate
  curriculum and new graduates
• Universities consortium ? - going it alone is not as effective
• Summer schools not effective by themselves
                      Summary (ctd)

• Need to involve “industry” in partnership with the university -
  don’t just leave it to the university - requires an investment
  from the operational centers
• Partnership with operational centers is best way to provide
  experience with systems of relevant complexity and with
  relevant computational infrastructure

				
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