AbstractWe developed a coupled regional climate system model based on the CCLM regional climate model. Within this model system, using OASIS3-MCT as a coupler, CCLM can be coupled to two land surface models (Community Land Model (CLM) and VEG3D), the NEMO-MED12 regional ocean model for the Mediterranean Sea, two ocean models for the North and Baltic Sea
(NEMO-NORDIC and TRIMNP+CICE) and the earth system model MPI-ESM.
We first present the different model components and the unified OASIS3-MCT interface which handles all couplings in a consistent way, minimizing the model source code modifications and defining the physical and numerical aspects of the couplings. We also address specific coupling issues like the handling of different domains, multiple usage of MCT library and exchange of 3D
fields. We analyse and compare the computational performance of the different couplings based on realcase
simulations over Europe. The usage of the LUCIA tool implemented in OASIS3-MCT enables the quantification of the contributions of the coupled components to the overall coupling cost. These
individual contributions are (1) cost of the model(s) coupled, (2) direct cost of coupling including
horizontal interpolation and communication between the components, (3) load imbalance, (4) cost of different usage of processors by CCLM in coupled and stand alone mode and (5) residual cost including i.a. CCLM additional computations.
Finally a procedure for finding an optimum processor configuration for each of the couplings was developed considering the time to solution, computing cost and parallel efficiency of the simulation. The optimum configurations are presented for sequential, concurrent and mixed (sequential+
concurrent) coupling layouts. The procedure applied can be regarded as independent of the specific coupling layout and coupling details.
We found that the direct cost of coupling, i.e. communications and horizontal interpolation, in
OASIS3-MCT remains below 7% of the CCLM stand-alone cost for all couplings investigated. This is in particular true for the exchange of 450 2D fields between CCLM and MPI-ESM. We identified remaining limitations in the coupling strategies and discuss possible future improvements of the computational efficiency.