| 22 Sep 2025
A Fast and Physically Grounded Ocean Model for GCMs: The Dynamical Slab Ocean Model of the Generic-PCM (rev. 3423)
Abstract. We present the new dynamical slab ocean model implemented in a 3-D General Circulation Model (GCM) called the Generic Planetary Climate Model (Generic-PCM; formerly the LMD-Generic GCM). Our two-layer slab ocean model features emergent ocean heat transport (OHT) arising from wind-driven Ekman transport, horizontal diffusion, convective adjustment, and a newly implemented Gent–McWilliams (GM) parameterisation for mesoscale eddies. Sea ice evolution is spectrally-dependent and varies with ice thickness. We first validate the model in an idealised aquaplanet setting under various OHT configurations. We show that enabling OHT transforms not only surface features – such as cooler tropical sea surface temperatures (SSTs) and reduced sea ice coverage – but also atmospheric structures, notably producing a double-banded precipitation pattern across the equator driven by Ekman-induced upwelling. Our modelled meridional OHT profiles are in agreement with fully coupled atmosphere-ocean GCMs, with Ekman transport dominating in the tropics and GM advection and diffusion peaking near the ice edge. When applied to modern Earth, the OHT-enabled configuration yields an annual global average surface temperature of 13 °C, within 1 °C of reanalysis estimates, and improves extrapolar SSTs and sea ice coverage relative to the OHT-disabled baseline. Seasonal SST and sea ice biases relative to observations are also significantly reduced to within 0.6 °C and 3 million km2, respectively. We obtain a planetary bond albedo of around 0.32, in close agreement with observations. We additionally find that GM-induced mixing mimics vertical convection, while the inclusion of OHT reduces hemispheric asymmetries and improves the overall GCM numerical stability. Notably, these improvements are achieved at almost no additional computational cost compared to OHT-disabled simulations run over the same number of model years. This balance of computational efficiency and physical realism makes the model particularly well-suited for sensitivity studies and large parameter sweeps – crucial in exoplanet and paleoclimate applications where observational constraints are limited.
