An Efficient Ice Sheet/Earth System Model Spin‐up Procedure for CESM2‐CISM2: Description, Evaluation, and Broader Applicability

Abstract

Spinning up a highly complex, coupled Earth system model (ESM) is a time consuming and computationally demanding exercise. For models with interactive ice sheet components, this becomes a major challenge, as ice sheets are sensitive to bidirectional feedback processes and equilibrate over glacial timescales of up to many millennia. This work describes and demonstrates a computationally tractable, iterative procedure for spinning up a contemporary, highly complex ESM that includes an interactive ice sheet component. The procedure alternates between a computationally expensive coupled configuration and a computationally cheaper configuration where the atmospheric component is replaced by a data model. By periodically regenerating atmospheric forcing consistent with the coupled system, the data atmosphere remains adequately constrained to ensure that the broader model state evolves realistically. The applicability of the method is demonstrated by spinning up the preindustrial climate in the Community Earth System Model Version 2 (CESM2), coupled to the Community Ice Sheet Model Version 2 (CISM2) over Greenland. The equilibrium climate state is similar to the control climate from a coupled simulation with a prescribed Greenland ice sheet, indicating that the iterative procedure is consistent with a traditional spin‐up approach without interactive ice sheets. These results suggest that the iterative method presented here provides a faster and computationally cheaper method for spinning up a highly complex ESM, with or without interactive ice sheet components. The method described here has been used to develop the climate/ice sheet initial conditions for transient, ice sheet‐enabled simulations with CESM2‐CISM2 in the Coupled Model Intercomparison Project Phase 6 (CMIP6).

Accelerated Greenland Ice Sheet Mass Loss Under High Greenhouse Gas Forcing as Simulated by the Coupled CESM2.1‐CISM2.1

“…The pre‐industrial GrIS SMB is 585 Gt yr −1 (Table 1), which is higher than present‐day SMB (Fettweis et al., 2017; Noël et al., 2015, 2016), primarily due to a larger ice sheet and overestimated snowfall (Lofverstrom et al., 2020; van Kampenhout et al., 2020). In the 1% simulation, the evolution of surface mass loss can be roughly divided into three periods (Figure 5c, black line, and Table S1), similar to the total mass loss in section 3.1.…”

Accelerated Greenland Ice Sheet Mass Loss under High Greenhouse Gas Forcing as Simulated by the Coupled CESM2.1-CISM2.1

“…The pre-industrial GrIS SMB is 585 Gt yr −1 (Table 1), which is higher than present-day SMB (Fettweis et al, 2017;Noël et al, 2015Noël et al, , 2016, primarily due to a larger ice sheet and overestimated snowfall (Lofverstrom et al, 2020;van Kampenhout et al, 2020). In the 1% simulation, the evolution of surface mass loss can be roughly divided into three periods (Figure 5c, black line, and Table S1), similar to the total mass loss in section 3.1.…”

“…Both simulations start from the spun-up pre-industrial Earth system/ice sheet state described by Lofverstrom et al (2020). A near-equilibrium state was obtained by alternating between a fully coupled configuration with all model components active and a more efficient partially coupled configuration with a data…”

Description and Demonstration of the Coupled Community Earth System Model v2 – Community Ice Sheet Model v2 (CESM2‐CISM2)

“…The simulated ice sheet area is 15% larger than observed, with most of the differences in the north. See Lofverstrom et al (2020) for a more detailed comparison with observations and regional climate model reconstructions.…”

“…Previous work on integrating ice sheets into Earth System Models (ESMs) for present-day ice sheet configurations has been done byfor example, Lipscomb et al (2013), Lofverstrom et al (2020), Mikolajewicz et al (2007), Ridley et al (2005), and Vizcaino et al (2008Vizcaino et al ( , 2014. Work on paleo climates, which usually spans longer time scales, has been done with ESMs of Intermediate Complexity (EMICs; Fyke et al, 2011;Liakka et al, 2012), and ESMs using asynchronous climate/ice-sheet coupling (Gregory et al, 2012;Lofverstrom & Liakka, 2018;Lofverstrom et al, 2015).…”