1. A regional model assimilating ARGO, XBT, and altimeter data in the central North Pacific
Bruce Cornuelle, Josh Willis, Dean Roemmich
Scripps Institution of Oceanography,
University of California at San Diego

2. Physical Motivation for QG Assimilation
Gilson et al. [JGR, 2003] eddy fluxes
Eddy/wave propagation

3. Physical Motivation for QG Assimilation
Combination of the observations in time for best resolution
Combination of Surface and interior measurements [Willis et al., JGR, 2003]
Find the limitations (and strengths) of the QG approximation in this region
Predictability

4. Motivation for Model Fitting ('Assimilation')
Test hypothesis: are model physics valid here?
Enforce model physics to enhance process studies
Examine dynamical balances
Enhanced estimates of fluxes
Explore predictability and sensitivity
Only beginning: reality check on model, method

5. Outline Model summary Study region Data Results: model forecasts
Bathymetry
TS relation
Vertical modes
Data
Results: model forecasts
Summary and conclusions
Work remaining

6. QG Model Adapted from Geoff Vallis: CDF experiments
Quasi-geostrophic: streamfunction is model state
Pseudo-spectral (Patterson and Orszag anti-aliasing)
-Plane
Converted to vertical modes; 3 used here
1200 x 1200 km periodic domain
16 harmonics (min scale 80 km)

7. Study Region Fairly smooth bathymetry Domain: 180 – 160E 15N - 30N
Weak mean flow (3 cm or less, except in the south)

8. T-S Relation At depth, most of the spread in the TS
relation is geographical
Points at 500m
depth highlighted

9. Warm, fresh water in northwest
Low Density:
Warm, fresh water in northwest
geostrophic flow
geostrophic flow
High Density:
Cold, Salty water in southeast

10. Vertical Modes QG Equations and Buoyancy frequency
used to calculate vertical modes:
Displacement
Velocity
Buoyancy freq.
calculated from Levitus

11. Vertical Modes Fit to Argo Data
Mean, Min, Max, RMS (s units)
RMS
before & after
before fit
after fit
(fit below 150m only)

12. Data Altimeter data: (days 529-564)
AVISO mapped sea-level anomaly (merged, all-satellites)
1/3o x ~3.5 day resolution.
(days )

13. Data Argo Data During the simulations, float data is concentrated
in the SE part of the domain
(day 522)
Roughly 6 profiles per week
available from float data
(day 522)

14. Data XBT data Not yet incorporated: no salinity info. homogeneous
in time
(day 522)
Dense data at certain times may eventually help with initialization
(day 522)

15. Results Model initialized with 12 days of data:
3 time steps of AVISO mapped SSH
6 Argo profiles
Run for 4 weeks and compared to AVISO mapped SSH

16. Forecasts – 12 day initialization with SSH and Argo
AVISO
forecast
error

17. Forecasts – 12 day initialization with SSH and Argo
AVISO
forecast
Note: largest
errors occur
near the
boundaries
error

18. RMS error in model compared with persistence
Start Day: 557
7 day initialization
12 day initialization

19. RMS error in model compared with persistence
Start Day: 529
7 day initialization
12 day initialization

20. Comparison of Model Forecast With Argo Data
12 Day initialization
with Argo
without Argo
1BC
2BC

21. Comparison of Model Forecast With Argo Data
Reality check:
28 day initialization
with only Argo data
Note: good
agreement in
mode 2 suggests
slow propagation
of mode 2
information

22. Summary and Conclusions
Model forecasts show some skill
Weak nonlinearity: large scale cut-off?
Impact of Argo: small on SSH forecasts
Argo significant for Argo forecasts

23. Summary and Conclusions
Assimilation does not improve forecasts at the moment
Domain limits? Error from the edges
Error bars not adjusted; relative impact of different observations
Smoothness is critical for forecasts
Forecast is good cross-validation (test)

24. To Do Large Domain + Higher Resolution Longer Assimilation runs
Other regions
More Argo data; include HR/XBT data
Along-track SSH data
Include forcing and weak topography
Compare to PE models

25. Pitfalls of Model Fitting (Assimilation)
Observations used to cover up model errors
Model errors aliased into control parameters
Output Instantly obsolete after model is changed
Complicated details: parameters, covariances
Enough free parameters to fit any observation

26. No Mean flow or forcing (Surface flow from Levitus ~ 3 cm or less, except in the south)

27. more QG Model info. Flat topography (Smith-Sandwell has +- 2000m)
No Mean flow or forcing
Viscosity not important (short timescales)