Terrestrial processes influence the atmosphere by controlling land-to-atmosphere fluxes of energy, water, and carbon. Prior research has demonstrated that parameter uncertainty drives uncertainty in land surface fluxes. However, the influence of land process uncertainty on the climate system remains underexplored. Here, we quantify how assumptions about land processes impact climate using a perturbed parameter ensemble for 18 land parameters in the Community Earth System Model (CESM2) under preindustrial conditions. We find that an observationally-informed range of land parameters generate biogeophysical feedbacks that significantly influence the mean climate state, largely by modifying evapotranspiration. Global mean land surface temperature ranges by 2.2°C across our ensemble (standard deviation = 0.5°C) and precipitation changes were significant and spatially variable. Our analysis demonstrates that the impacts of land parameter uncertainty on surface fluxes propagates to the entire Earth system, and provides insights into where and how land process uncertainty influences climate.

We ran PPEs under preindustrial conditions using two configurations of CESM2: a partially coupled configuration (“coupled”) and an uncoupled, land only configuration (“land-only”). In both the coupled and land-only PPE, the land model (CLM5) was run with prognostic leaf area. The land was initialized with the spun-up land state from the default model parameterization which includes the carbon content of soil and vegetation pools.  In the coupled ensemble, we ran preindustrial simulations with constant greenhouse gas concentrations using an active atmosphere (CAM6) and a slab ocean which is based on q-fluxes from preindustrial simulations of the full dynamic ocean model. Because these simulations have fixed concentrations of greenhouse gasses including CO2, they capture the biogeophysical impacts of land parameters which is the focus of this project, but they do not capture biogeochemical feedbacks.  The land-only simulations used a custom atmospheric forcing, which was generated by CAM6 in the reference coupled simulation that used default parameters.

Each parameter perturbation simulation, which we refer to as an ensemble member, was run for 140 years under constant preindustrial greenhouse gas concentrations and land use conditions. Our PPEs sampled 18 land parameters (see https://github.com/czarakas/coupled_PPE/blob/main/code/02_set_up_ensemble/CLM5PPE_coupledPPE_crosswalk.csv), and our parameter selection was informed by the CLM5 PPE project (data and methods description are available via https://github.com/djk2120/clm5ppe). The 18 parameters we selected span nine functional categories: soil hydrology, stomatal conductance and plant water use, snow, photosynthesis, boundary layer / roughness, radiation, canopy evaporation, biomass heat storage, and temperature acclimation.

For each parameter, we ran two simulations, where the parameter was perturbed to a minimum and maximum value (ensemble n = 36). We used the parameter ranges from the CLM5 PPE, which were determined by domain-area experts based on literature review and expert judgement. Because some parameters have larger ranges than others, our analysis includes both the sensitivity of the climate system to a change in a parameter combined with the uncertainty in that parameter’s range.