Articles | Volume 12, issue 3
Geosci. Model Dev., 12, 879–892, 2019
https://doi.org/10.5194/gmd-12-879-2019
Geosci. Model Dev., 12, 879–892, 2019
https://doi.org/10.5194/gmd-12-879-2019
Methods for assessment of models
05 Mar 2019
Methods for assessment of models | 05 Mar 2019

DCMIP2016: the splitting supercell test case

Colin M. Zarzycki et al.

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Cited articles

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Gallus, W. A. and Bresch, J. F.: Comparison of Impacts of WRF Dynamic Core, Physics Package, and Initial Conditions on Warm Season Rainfall Forecasts, Mon. Weather Rev., 134, 2632–2641, https://doi.org/10.1175/MWR3198.1, 2006. a, b
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Guimond, S. R., Reisner, J. M., Marras, S., and Giraldo, F. X.: The Impacts of Dry Dynamic Cores on Asymmetric Hurricane Intensification, J. Atmos. Sci., 73, 4661–4684, https://doi.org/10.1175/JAS-D-16-0055.1, 2016. a, b
Short summary
We summarize the results of the Dynamical Core Model Intercomparison Project's idealized supercell test case. Supercells are storm-scale weather phenomena that are a key target for next-generation, non-hydrostatic weather prediction models. We show that the dynamical cores of most global numerical models converge between approximately 1 and 0.5 km grid spacing for this test, although differences in final solution exist, particularly due to differing grid discretizations and numerical diffusion.