Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation

• Published in: Journal of Advances in Modeling Earth Systems
• Main Authors: Sein, Dmitry V., Mikolajewicz, Uwe, Gröger, Matthias, Fast, Irina, Cabos, William, Pinto, Joaquim G., Hagemann, Stefan, Semmler, Tido, Izquierdo, Alfredo, Jacob, Daniela
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union 2015
• Subjects: North Atlantic; Sea ice
• Online Access: https://centaur.reading.ac.uk/46853/; https://centaur.reading.ac.uk/46853/1/Sein_et_al-2015-Journal_of_Advances_in_Modeling_Earth_Systems.pdf; https://doi.org/10.1002/2014MS000357

The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller-scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean-regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present-day climate. A global ocean-sea ice-marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e., ocean, atmosphere, terrestrial hydrology, and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale.