Abstract. Adequate Earth system simulations require interactions between the atmosphere, the ocean, and the ice sheets. To this end, numerical solvers that compute the evolution of the different Earth system components are coupled. There are frameworks and libraries for coupling that handle the complex tasks of coordinating solver execution, communicating between processes, and mapping between different meshes. This allows solvers to be developed independently without compromises on numerical methods or technology. Code reuse is improved, both over large, monolithic software systems that reimplement each coupled model as well as over ad-hoc coupling scripts. In this work, we use the preCICE coupling library to couple the Ice-sheet and Sea-level System Model (ISSM) with the subglacial hydrology model CUAS-MPI. An adapter for each model is required to pass meshes and coupled variables between the model and preCICE. We focus mainly on the technical aspects (design, development, and use of the adapters, choice of coupling library, and large-scale performance analysis), using a synthetic setup to verify functionality and correctness. The adapters we developed are generic and reusable for use cases other than ice-hydrology coupling. Computational performance for the coupled system is measured on a high-performance computing cluster. We find that coupling with preCICE has low computational overhead and does not negatively impact scaling. A comparison between unidirectional and bidirectional coupling for the synthetic ice sheet shows that the coupling captures the anticipated feedback mechanisms between the two systems. The coupled simulations are numerically stable, despite the nonlinearities in the physical system. The generic coupling library preCICE is well suited for our use case and has advantages as well as disadvantages over Earth System Model-specific libraries. The new framework and code enable studies of the subglacial hydrological systems of ice sheets, as well as coupling ISSM or CUAS-MPI with other codes, such as in global Earth System Models or process models.
Abele et al. (Mon,) studied this question.