We report on efforts to couple, validate, and apply a dynamic Greenland Ice Sheet (GIS) component within DOE’s Energy Exascale Earth System Model (E3SM). The ice sheet model component of E3SM is the MPAS Albany Land Ice (MALI) model, which allows for HPC-performant, 3d and depth-integrated higher-order ice dynamics solvers on unstructured, variable resolution meshes. Ice sheet initial conditions are optimized to provide a good match to both historical observations of velocity and geometry and observed mass-loss transients. Within the E3SM Land Model (ELM), a new 16-layer snowpack model has been added and validated to enable the accurate simulation of snow and firn compaction necessary for calculating ice sheet surface mass balance (SMB). Within E3SM, new software support has been added to enable partially- and fully-coupled standard resolution model configurations that include an active, dynamic GIS component with variable 3-30km or 1-10km resolution. Climate forcing from the atmosphere occurs through snowpack evolution in the land model, with SMB passed to the ice sheet model. Forcing from the ocean model occurs by the extrapolation of proximal ocean temperatures, which drive parameterizations of ice front melt and/or iceberg calving in MALI. Freshwater fluxes from ice front melt, icebergs, and surface melt are passed back through the coupler to E3SM’s ocean and runoff components. The computational costs of coupled configurations with an active 1-10km resolution GIS are 6k core hours per simulated year with a throughput of 6 simulated years per day (1685 AMD Epyc processors). Here, we report on partially-coupled historical simulations (1990s to early 2020s) forced by ERA5 reanalysis. We use the Land Ice Verification and Validation toolkit (LIVVkit) to validate the ice sheet surface climate and whole-ice-sheet and basin-scale mass change. We also report on initial fully-coupled simulations over the same historical time period, which are being used to identify and improve coupled-model biases, eventually allowing for coupled future simulations under a range of SSP forcings.