An insufficient subsurface depth biases the long-term surface energy balance in Land Surface Models

The land subsurface stored around 6% of the Earth’s energy imbalance in the last five decades (of around 0.5 Wm^-2, equivalent to 380 ZJ), being the second contributor to the energy partitioning after the ocean (90%). Previous studies have shown that state-of-the-art Earth System Models (ESMs) remarkably underestimate the observational land heat uptake values. This underestimation stems from Land Surface Models (LSMs) within ESMs imposing too shallow zero-flux bottom boundary conditions to correctly represent the conductive propagation and land heat uptake with depth. When realistically deep boundary conditions are prescribed, land heat uptake increases by a factor of five. However, changes in ground surface temperature are negligible. The reasons for this lack of impact of the LSM depth on surface temperatures are assessed herein.

An ensemble of eight historical and RCP8.5 land-only simulations with different subsurface depths was conducted with the LSM of the Max Planck Institute for Meteorology ESM (MPI-ESM), JSBACH. Simulation-derived latent (LHF), sensible (SHF), and ground heat fluxes (GHF) were compared across simulations, and GHF was additionally evaluated against estimates from a one-dimensional heat conduction forward model. Results show that, for a global warming of 1.5 ºC with respect to 1850-1900, GHF increases from 0.04 to 0.07 Wm^-2 when deepening the LSM from 10 to 22 m, saturating at around 0.12 Wm^-2 when the boundary condition is placed at approximately 100 m. The increase in the incoming GHF is mainly compensated by a global decrease in the outgoing SHF, a small decrease of the LHF in wet regions, and a decrease in the surface net radiation in arid and semi-arid regions. These quantities, yet small, evidence that an insufficient LSM depth induces to an inaccurate resolution of the long-term surface energy balance, which may have implications for land-atmosphere interaction. Their accumulation over time also produces biases in the terrestrial energy partitioning.