Global climate models as forcing for regional ocean modeling: a sensitivity study in the Iberian Basin (Eastern North Atlantic)
Cordeiro Pires A., Nolasco A., Roch A., Ramos A.M., Duber J.
Climate Dynamics, DOI:10.1007/s00382-014-2151-3
This work evaluates the performance of several global climate models (GCMs) as forcing of a regional ocean model configuration centered in the Iberian Basin. The study is divided in two parts. First, the output of nine GCMs is analyzed based on the fields needed to force the ocean model (Regional Ocean Modelling System—ROMS). GCMs differ greatly between them and their performance depends on the field. In the second part, the two GCMs with the worst performances in both extremes of the ensemble are used as forcing for two ROMS simulations, with the purpose of assessing the range of uncertainty comprised in this set of GCMs. Two other ROMS runs are setup: one climatologically forced control run, and one forced with the average of all the nine GCMs—the ensemble mean. Results show that the tendency of overestimation/underestimation of the forcings is reflected in the modeled hydrography, both at the surface and deeper layers down to 500 m. Nevertheless, in terms of circulation, all four runs reproduce the Azores Current, as well as the coastal transition zone seasonality (winter poleward flow and summer upwelling-associated equatorward flow). The CGCMs output performance as forcing depends on the forcing variable: one performs well for one or more variables, but badly for others, and which field is well or badly reproduced varies for each CGCM. Therefore, there is not a single CGCM having the best forcing for all variables. Hence, our results indicate that the most adequate approach consists of using the ensemble mean as forcing rather than using an individual model. This is supported by the general low overall (i.e. for all forcing variables) errors of the ensemble mean regarding the control climatological dataset, and the good comparison of the ensemble-forced ROMS run with the control run.