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We present a novel global 3-D coronal MHD model called COCONUT, polytropic inits first stage and based on a time-implicit backward Euler scheme. Our modelboosts run-time performance in comparison with contemporary MHD-solvers basedon explicit schemes, which is particularly important when later employed in anoperational setting for space weather forecasting. It is data-driven in thesense that we use synoptic maps as inner boundary input for our potential fieldinitialization as well as an inner boundary condition in the further MHD timeevolution. The coronal model is developed as part of the EUropean HeliosphericFORecasting Information Asset (EUHFORIA) and will replace the currentlyemployed, more simplistic, empirical Wang-Sheeley-Arge (WSA) model. At 21.5 Rswhere the solar wind is already supersonic, it is coupled to EUHFORIA'sheliospheric model. We validate and benchmark our coronal simulation resultswith the explicit-scheme Wind-Predict model and find good agreement foridealized limit cases as well as real magnetograms, while obtaining acomputational time reduction of up to a factor 3 for simple idealized cases,and up to 35 for realistic configurations, and we demonstrate that the timegained increases with the spatial resolution of the input synoptic map. We alsouse observations to constrain the model and show that it recovers relevantfeatures such as the position and shape of the streamers (by comparison witheclipse white-light images), the coronal holes (by comparison with EUV images)and the current sheet (by comparison with WSA model at 0.1 AU).

COCONUT, a novel fast-converging MHD model for solar corona simulations: I. Benchmarking and optimization of polytropic solutions