Effects of land use change on North American climate: impact of surface datasets and model biogeophysics

This study examines the impact of historical land-cover change on North American surface climate, focusing on the robustness of the climate signal with respect to representation of sub-grid heterogeneity and land biogeophysics within a climate model. We performed four paired climate simulations with the Community Atmosphere Model using two contrasting land models and two different representations of land-cover change. One representation used a biome classification without subgrid-scale heterogeneity while the other used high-resolution satellite data to prescribe multiple vegetation types within a grid cell. Present-day and natural vegetation datasets were created for both representations. All four sets of climate simulations showed that present-day vegetation has cooled the summer climate in regions of North America compared to natural vegetation. The simulated magnitude and spatial extent of summer cooling due to land-cover change was reduced when the biome-derived land-cover change datasets were replaced by the satellite-derived datasets. The diminished cooling is partly due to reduced intensity of agriculture in the satellite-derived datasets. Comparison of the two land-surface models showed that the use of a comparatively warmer and drier land model in conjunction with satellite-derived datasets further reduced the simulated magnitude of summer cooling. These results suggest that the cooling signal associated with North American land-cover change is robust but the magnitude and therefore detection of the signal depends on the realism of the datasets used to represent land-cover change and the parametrisation of land biogeophysics.