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
Topics
•
•
•
•
Review status and progress
Release of Basic version
NWS Risk reduction
Future work
Basic System Components
NCAR (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
3DVAR MPP Scalability – NCAR IBM-SP
1500
1400
1300
MPP Control Variables+Obs Operators
1200
+MPP Minimization
Wall Clock Time (s)
1100
+Local Background
1000
Perfect Scaling
900
800
700
600
500
400
300
200
100
0
0
4
8
12
16
20
24
28
32
36
40
44
48
52
56
60
64
Number Of Processors
•Test Study: 140x150x41 AFWA 45km “T4 theater” – 25th Jan 2002.
•Background error tuning – Old Its = 98, New = 49 (64PE = 58s).
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-1/2 z )T ( H dx(yo + O1/2 z ) - H dx(yo) )
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-1/2 z )T ( H dx(yo + O1/2 z ) - H dx(yo) )
2
1.8
Total Jb
Error Tuning Factor
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1
2
3
Iteration
4
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-1/2 z )T ( H dx(yo + O1/2 z ) - H dx(yo) )
2
synop u
synop v
1.8
synop t
Error Tuning Factor
1.6
synop p
synop q
1.4
Total Jb
1.2
1
0.8
0.6
0.4
0.2
0
1
2
3
Iteration
4
Basic System Components
NCEP (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.
Basic System Components
AFWA (Completed, Underway, Not started)
• Use of original vertical coordinate for
observations
• Comprehensive performance diagnostics
Basic System Components
FSL (Completed, Underway, Not started)
• Inclusion of Profiler data
• Conversion to i = x, k = 1 at bottom.
Basic System Components
CIMSS (Completed, Underway, Not started)
• Comprehensive documentation
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
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
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
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).
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.)
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.