1. Ensemble simulations and the ocean’s mesoscale
This is the final presentation the summarizes results from the project ”Ensemble forecasting and the ocean’s mesoscale”, sponsored by the Norwegian Research Council under contract no /120.
FoU/Klima seminar series, 17 Februrary 2005 by Arne Melsom

2. Experiments Model: HYCOM v. 2.1.09 Bottom topography:
Vertical resolution: 7 hybrid layers
Horizontal resolution:
Coarse: 0.08°lon x 0.16°lat (9 km)
Fine: °lon x 0.08°lat (4.5 km)
Turbulence model: KPP
Atmospheric forcing: NCEP-RA
Norway UK
North Sea
Skagerak
Bottom topography:
Light gray lines on open boundaries on the map show locations where barotropic inflow (in the west) and outflow (in the north) were specified. Also, a vigorous relaxation toward climatological values for salinity was applied in the southern part of the Kattegat. The model was forced with synoptic (6 hourly) atmospheriv forcing for the period

3. Regional ocean circulation
A sketch of the main ocean currents in the region. NAC is the Norwegian Atlantic Current, NWCC is the Norwegian Coastal Current. Grabbed from the web.

4. The ensemble Climatological forcing Synoptic forcing Ensemble size:
time
Results from January for consequtive years were extracted from the climatologically forced simulation, and used as initial conditions for the 10 year synoptically forced ensemble simulation. Dashed lines indicate the start ( ) and end ( ) of the ensemble simulation period.
Synoptic forcing
Ensemble size:
Coarse resolution: 8 members Fine resolution: 8 members

5. “Baroclinic” sea surface height (January), coarse resolution
Spin up
“Baroclinic” sea surface height (January), coarse resolution
Results from January for the baroclinic sea surface height (bSSH, similar to the dynamic height anomaly). The mean value (black) and the spatial variance (gray) of bSSH for each January snapshots were computed. Results from the spin-up are displayed by thin lines. The 8 open circles correspond to the initialization of the various ensemble members. Thick lines show results for ensemble member no. 3. Initially, there is a trend toward higher values, so the analysis is restricted to the final 5 years, indicated by the full circles. Results in the left and right panels are for the full domain and the “North Sea only” subdomain, respectively (the latter is the unshaded region in the map in the upper left corner).

6. Definitions; ensemble variability
Mean square offset from the daily climatology:
Partitioning (n and s denote grid node and member):
Ensemble variance:
Offset of ensemble mean:
This must be viewed in PowerPoints (animation) mode! eta_tilde(d_n) is the climatology for day no. n (blue line in the figure), eta_hat is the difference between the ensemble mean (red line) and the climatology (blue line) i.e., the deterministic variability due to the prescribed atmospheric forcing, and eta_prime is the difference between one ensemble member (thin black line) and the ensemble mean (red line).
Fraction of non-deterministic variability: t
fnon-det =

7. Are initial fields independent?
fnon-det from subsampled pairs of ensemble members, for baroclinic sea surface height; red circles: consecutive members (1/2, 2/3, …, 7/8) cyan circles: members 1/4, 2/5, …, 5/8 black circles: members 1/6, 2/7, 3/8
coarse resolution
Results for 2 member mini-ensembles. For the full domain, values for ensembles from consequtive years (red circle) appear to be shifted to lower values, suggesting that a memory of more than one year might affect the results. This does not appear to be the case when results for the “North Sea only” domain are analyzed.

8. Variability vs. predictability
Baroclinic sea surface height
variance
fraction of nondeterm. variability
Mean values for the bSSH ensemble variance (eta_prime squared) for the final five years are displayed to the left, the fraction of non-deterministic variability for the bSSH is displayed to the right. Note that in the North Sea, maximum values for the ensemble variance is found in the coastal wave guide. However, this is also a region were the variability due to synoptic wind forcing is very large, so the fraction of non-deterministic variability reaches its maximum values further away from the coast, in the region of the front between the Norwegian Coastal Current and the saltier water masses to the west.

9. Effects of resolution
Fraction of non-deterministic variability, for baroclinic sea surface height (fnon-det)
coarse resolution
fine resolution
The fraction of non-deterministic variability is higher in the fine resolution experiment (when the mesoscale variability is more accurately described), but the spatial pattern is the same (values differ by about a factor of 2).

10. fnon-det(S200m) - fnon-det(S10m)
Depth dependence
Changes in the fraction of non-deterministic variability (fnon-det) with depth, for salinity
fnon-det(S200m) - fnon-det(S10m)
topography (h≥200m)
We expect the fraction of non-deterministic variability to increase with depth, since the (deterministic) wind-induced variability will generally be larger near the surface. This is also generally the case, but near the bottom in regions with large depth gradients, topographical steering may give rise to high degrees of deterministic variability.

11. An outbreak event Late fall of 1996 Layer 2 salinity
October November December
Layer 2 salinity
Late fall of 1996
Salinity 20 km off the coast, from Lillesand to Stavanger, displayed in a Hovmøller diagram. An outbreak event of low salinity wateer masses from the Skagerrak con be identified, starting in early November.

12. An outbreak event (cont’d)
Salinity in layer 2; 23 November 1996 6 8 7 5 1 4 2 3
Results for salinity off the southern tip of Norway, in the aftermath of the outbreak event that was identified on the previous view-graph. Separate frames show results from the various ensemble members (fine resolution experiment). Note the similarity in the mesoscale features.

13. An outbreak event 3 6 1 4 7 2 5 8 23 November 1996 salinity, layer 2
Same as previous view-graph. 2 5 8

14. Ensemble variance of salinity at 10m
early Nov.
Nov./Dec.
late Dec.
Ensemble variance during the outbreak event in 1996 (cfr. previous view-graphs), compared to the same quantity one year later (when no strong outbreak event was identified). The degree of determinism appears to be related to outbreak events.

15. NCC salinity, off western Norway
Salinity in layer 2; 30 October 1998 1 3 5 7
Results that demonstrate how the mesoscale may be represented differently by the various members (relatively high degrees of non-determinism). 2 4 6 8

16. Conclusions
flow instabilities have the largest impact on ensemble variability in frontal regions
the fraction of non-deterministic variability amplitude is scale dependent, the pattern might not be
Skagerrak outbreak events may give rise to “deterministic eddies” off Lista
The first two conclusions were as expected. Regarding the last conclusion, this was not known (and not expected) prior to this study.