|Variability of shelf-seas hydrodynamic models: lessons from the NOMADS2 Project|Delhez, E.J.M.; Damm, P.; de Goede, E.; de Kok, J.M.; Dumas, F.; Gerritsen, H.; Jones, J.E.; Ozer, J.; Pohlmann, T.; Rasch, P.S.; Skogen, M.; Proctor, R. (2004). Variability of shelf-seas hydrodynamic models: lessons from the NOMADS2 Project. J. Mar. Syst. 45(1-2): 39-53. dx.doi.org/10.1016/j.jmarsys.2003.09.003
In: Journal of Marine Systems. Elsevier: Tokyo; Oxford; New York; Amsterdam. ISSN 0924-7963, more
hydrodynamic models; NOMADS2; north sea
|Authors|| || Top |
- Delhez, E.J.M., more
- Damm, P.
- de Goede, E.
- de Kok, J.M.
- Dumas, F.
- Gerritsen, H., more
- Jones, J.E.
- Ozer, J., more
- Pohlmann, T.
- Rasch, P.S.
- Skogen, M.
- Proctor, R.
Model simulations at the seasonal time scale are often lacking in any real assessment of the associated error bounds. We use here the results of nine three-dimensional hydrodynamic models covering (at least) the Southern and Central North Sea to investigate the range of model variability and model errors. The models are run as they are, i.e. with their usual grid, model domain, equation formulation and numerical details, but in a consistent framework-bathymetry, boundary and initial conditions, meteorological forcing functions interpolated from a common data set-.
While the responses of the models are clearly qualitatively similar, large quantitative differences do occur. These differences are often of the same order of magnitude as both the ensemble mean and the sensitivity of the individual results to critical parameters.
The direct comparison of the results with measurements from the North Sea Project provides a quantification of the model errors for the salinity and temperature distributions. Using the cost function approach, it is shown that the mean errors (for all the models and all seasons) reach about 70% of the natural variability for the temperature and 90% for the salinity. These errors are larger in summer, when a stratification develops over the Central and Northern North Sea, than in winter.
No single model parameter (spatial resolution, turbulence closure scheme, model domain, etc.) can explain the different behaviours of the models.