1. Anton Eliassen, Lars Petter Røed and Øyvind Sætra
Numerical Ocean Weather Prediction at the Norwegian Meteorological Institute: Safeguarding life, property and the environment at sea
Anton Eliassen, Lars Petter Røed and Øyvind Sætra
Presented at the opening of the Mohn-Sverdrup Center, Bergen Oct. 20, 2004

2. The met.no mandate Provide: Broadcast: Services for military purposes:
Financed by the Norwegian Government to safeguard life, property and the environment at land and sea.
Provide:
general weather forecasts,
climate information,
warnings of severe weather to the general public and
forecasts for search and rescue operations
Broadcast:
Using Norwegian Broadcasting Company (public radio/TV),
Using Internet and
other generally available distribution channels
Services for military purposes:
In case of a war, the met.no services are transferred to military command

3. But safety at sea is more than meteorology ….
stand-by emergency services
”Prestige”
Oil drift and combatment
Search and rescue

4. ... more than meteorology ….
monitoring and forecasting of the transport and dispersion of nutrients, algae, fish larvae, contaminants
UTC
Diatome concentrations
Chlorophyll concentrations

5. ... more than meteorology ….
safeguarding life and property regarding:
Ship traffic
Offshore operations
Military operations
Fisheries
Recreation, leisure yachting

6. This requires timely predictions
Surface conditions:
Waves
Water level
Ice drift
Ice concentration
Ice thickness
Profiles with depth of
Temperature
Salinity
Currents
Current and salinity at 10m depth
Wave spectrum

7. met.no’s NOWP system Atmosphere Ice Ocean circulation Waves Drift Oil
OSI-SAF conc.
Atmosphere
OSI-SAF SST
Ice
ECMWF
MI-IM
Concentration Thickness Drift
Ocean circulation
HIRLAM
Wind Temperature Pressure Clouds
Precipitation Humidity Wind stress Heat flux
MICOM
HYCOM
MI-POM
Water level Temperature Salinity
Current Turbulence incl tides
Typical suite of operational forecast models, with emergency drift models embedded.
Note the variety of models giving the same type of information – typical weather forecasting procedure.
Drift forecast service must give access to all and default to the presumed best.
NWP models are the backbone of the system.
HIRLAM run in-house, main model for forcing ocean models .
ECMWF data used for forcing HIRLAM and for direct forcing of ocean models
Ocean circ.: MI-POM is the current operational code, HYCOM being implemented as alternative / potential replacement.
Waves: WAM
Ice model is 2-way coupled to MI-POM, run on basin-scale model of Arctic.
Ecosystem: module developed by IMR in Bergen
All the greenish boxes are models run routinely, 1-2 times daily, with forecasts out to as much as 10 days.
There are also two stand-by models shown in reddish:
Drift: actually 2 models, one for ships and one for small floating objects.
Oil: 3D with novel bottom blowout module.
All 3 application models are cooperative efforts: DnV, USCG, IMR
The various arrows show how the forcing fields are delivered between the models.
In addition, there is river forcing, which has become increasingly important with the advent of ecosystem modeling.
This is a limited amount of data assimilation in the current system.
Waves
Drift
Oil
Ecosys.
MI-WAM
Dir. spectrum Sign. Wave height Mean period & dir. Peak period & dir.
Ship/Leeway
Trajectory Probability Drag charact.
OD3D
Dispersion Drift (3D) Weathering DeepBlow
IMR / MI
Nutrients Oxygen Sedimentation Flag. & diatom
Rivers
Volume flux Nutrient loads
Altimeter Hs

8. Forecast samples
Hs 20 Oct UTC
SSH 20 Oct UTC

9. Forecast samples
SST UTC
SSC and SSS UTC

10. How good are the predictions?
Validation of Arctic20 against SST from satellite imagery (OSI-SAF)
OSI-SAF: SST 168 hr composite UTC
Arctic20: SST UTC

11. How good are the predictions?
Validation of SST in terms of the mean RMS error (oC)
Mean score Jul-Sep 2004

12. SAR Search and Rescue: Leeway model
Split search area due to bimodal leeway (split is exaggerated for illustration)
Individual trajectory
Initial cloud shows uncertainty in Last Known Position (LKP)

13. Leeway bimodality
Experiments produce two stable drift directions, left and right of downwind, for same type of object.
NB! Jibing not important.
In practice, we cannot know which side will be “selected” by the object.
 leeway model must produce both trajectories

14. POMS: Pilot Ocean Monitoring System

16. OSI-SAF SST Lista Sep. 28, 2000 01:15 UTC NORWAY DENMARK
Note eddies along southern tip of Norway
Note also filament north of Denmark
DENMARK

17. Snapshot of surface currents
Sep. 28, 2000
00 UTC
Kristiansand
Lista ● ●
Norwegian Meteorological Institute has today a forecasting system for the Skagerrak area employing MI-POM. MI_POM is met.no’s version of the Princeton Ocean Model, which I am sure most of you know. Anyway, this is a 3-D numerical ocean model with sigma coordinates in the vertical and it is based on primitive equations.
●This is a part of the model domain, in our model with 4km mesh size. This model is nested within a much larger model domain with 20 km mesh size. We use Hirlam data as atmospheric forcing and produce 60 hours prognosis.
Here, we have picked a day with high mesoscale variability, more specific the 28’th of Setpthember The arrows show here the surface current. As you can see, this is a day with a lot of mesoscale activity. Note especially the eddies around the Lista area. ●
Reference point

18. Seksjon oseanografi