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3D-Var analysis system

3D-Var analysis system. W.-S. Wu & , M. Xue # , T. Schlatter @ , R.J. Purser & , M. McAtee % , J. Gao # , D. Devenyi @ , J. Derber * , M. Pondeca * , D. Barker + , S. Benjamin @ , R. Aune $ & General Sciences Corporation/SAIC and NOAA/NCEP/EMC, *NOAA/NCEP/EMC, % AFWA/The Aerospace Corporation,

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3D-Var analysis system

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  1. 3D-Var analysis system W.-S. Wu&, M. Xue#, T. Schlatter@, R.J. Purser&, M. McAtee%, J. Gao#, D. Devenyi@, J. Derber*, M. Pondeca*, D. Barker+, S. Benjamin@, R. Aune$ & General Sciences Corporation/SAIC and NOAA/NCEP/EMC, *NOAA/NCEP/EMC, % AFWA/The Aerospace Corporation, # CAPS/OU, @ NOAA/FSL, + NCAR/MMM, $ NESDIS

  2. Topics • Review status and progress • Release of Basic version • NWS Risk reduction • Future work

  3. Basic System ComponentsNCAR (Completed, Underway, Not started) • External iteration • Ensuring code runs on various machines • Include pseudo-obs for study of background error structures • Convert 3DVAR from B- to A- grid • Bug fixes and code efficiencies • Parallel version • Additional variational diagnostics • WRF Grid I/O

  4. 3DVAR MPP Scalability – NCAR IBM-SP • Test Study: 140x150x41 AFWA 45km “T4 theater” – 25th Jan 2002. • Background error tuning – Old Its = 98, New = 49 (64PE = 58s).

  5. Adaptive Tuning Of Observation/Background Errors • Method follows Dezrosiers and Ivanov (2001): • E(J) = p / 2, E(Jo)= ( p – Tr(HK) ) / 2, E(Jb)= Tr(KH) / 2 • Estimate Tr(KH) = ( O-1/2z )T ( H dx(yo + O1/2z ) - H dx(yo) )

  6. Adaptive Tuning Of Observation/Background Errors • Method follows Dezrosiers and Ivanov (2001): • E(J) = p / 2, E(Jo)= ( p – Tr(HK) ) / 2, E(Jb)= Tr(KH) / 2 • Estimate Tr(KH) = ( O-1/2z )T ( H dx(yo + O1/2z ) - H dx(yo) )

  7. Adaptive Tuning Of Observation/Background Errors • Method follows Dezrosiers and Ivanov (2001): • E(J) = p / 2, E(Jo)= ( p – Tr(HK) ) / 2, E(Jb)= Tr(KH) / 2 • Estimate Tr(KH) = ( O-1/2z )T ( H dx(yo + O1/2z ) - H dx(yo) )

  8. Basic System ComponentsNCEP (Completed, Underway, Not started) • Input of data from BUFR format • Stagger/unstagger grid interface • Bug fixes and code efficiencies • New (optional) background error covariance formulation • Internal 3DVAR changes for WRF mass-core.

  9. Basic System ComponentsAFWA (Completed, Underway, Not started) • Use of original vertical coordinate for observations • Comprehensive performance diagnostics

  10. Basic System ComponentsFSL (Completed, Underway, Not started) • Inclusion of Profiler data • Conversion to i = x, k = 1 at bottom.

  11. Basic System ComponentsCIMSS (Completed, Underway, Not started) • Comprehensive documentation

  12. Major Milestones • Aug. 2002 (Oct. 2001) – Release of Basic version • Simple version with limited data, but basic structure of more advanced versions • June 2003 (Nov. 2002) – Release of Research version • Includes current state-of-the-art in data assimilation • Additional time (> 1 year) necessary to improve results. • 2006 – Release of Advanced version • Includes additional data assimilation science developed under auspices of WRF

  13. Risk Reduction • Modification of Eta analysis system to handle WRF I/O • Risk reduction for operational WRF system • Basis for comparison for research version of WRF

  14. Research version • Situation dependent Background error covariances – NCEP/FSL • Appropriate Balance constraints ( Jc ) - CAPS • MPI/single processor, many machine capable – NCAR/NCEP • Quality control • First Guess at Appropriate Time - NCAR

  15. Research version • Inclusion of additional observations • Radiances over ocean and above surface – NCEP/FSL • Doppler winds and reflectivities – ground based and aircraft – NCAR/CAPS • Scatterometer (NCAR).

  16. Potential advanced version components • Enhanced definition of background errors • Model bias correction • Additional analysis variables • Cloud/Precipitation • Ozone/aerosols/etc. • Land Surface (snow, soil moisture, soil temperature, etc.)

  17. Potential advanced version components • Additional Observations • GPS radio-occultation/ground based • Satellite imagery/new sounders/over land, ice and snow • cloud observations, • land surface observations, • etc.

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