Evaluation of AMIP-type atmospheric fields as forcing for mediterranean sea and global ocean reanalyses

Oceanic reanalyses are powerful products to reconstruct the historical 3D-state of the ocean and related circulation. At present a challenge is to have oceanic reanalyses covering the whole 20 th century. This study describes the exercise of comparing available datasets to force Mediterranean Sea and global oceanic reanalyses from 1901 to present. In particular, we compared available atmospheric reanalyses with a set of experiments performed with an atmospheric general circulation model where sea surface temperature (SST) and sea-ice concentration are prescribed. These types of experiments have the advantage of covering long time records, at least for the period for which global SST is available, and they can be performed at relatively high horizontal resolutions, a very important requisite for regional oceanic reanalyses. However, they are limited by the intrinsic model biases in representing the mean atmospheric state and its variability. In this study, we show that, within some limits, the atmospheric model performance in representing the basic variables needed for the bulk-formulae to force oceanic data assimilation systems can be comparable to the differences among available atmospheric reanalyses. In the case of the Mediterranean Sea the high horizontal resolution of the set of SST-prescribed experiments combined with their good performance in representing the surface winds in the area made them the most appropriate atmospheric forcing. On the other hand, in the case of the global ocean, atmospheric reanalyses have been proven to be still preferable due to the better representation of spatial and temporal variability of surface winds and radiative fluxes. Because of their intrinsic limitations AMIP experiments cannot provide atmospheric fields alternative to atmospheric reanalyses. Nevertheless, here we show how in the specific case of the Mediterranean Sea, they can be of use, if not preferable, to available atmospheric reanalyses.