2010: Investigating the climate impacts of global land cover change in the community climate system model

Recently, [Pitman, et al., 2009] found a wide range of bio-geophysical climate impacts from historical land cover change when modeled in a suite of current Global Climate Models (GCMs). The bio-geophysical climate impacts of human land cover change however, have been investigated by a wide range of general circulation modeling, regional climate modeling, and observational studies. In this regard the IPCC 4th assessment report specifies radiative cooling of-0.2 W/m2 as the dominant global impact of human land cover change since 1750, but states this has a low to medium level of scientific understanding. To further contribute to the understanding of the possible climate impacts of anthropogenic land cover change, we have performed a series of land cover change experiments with the Community Land Model (CLM) within the Community Climate System Model (CCSM). To do this we have developed a new set of potential vegetation land surface parameters to represent land cover change in CLM. The new parameters are consistent with the potential vegetation biome mapping of [Ramankutty and Foley, 1999], with the Plant Functional Types and plant phenology consistent with the current day MODIS land surface parameters of [Lawrence and Chase, 2007]. We found that land cover change in CCSM resulted in widespread regional warming of the near surface atmosphere, but with limited impact on near surface temperatures globally. The experiments also found changes in precipitation, with drier conditions regionally, but with limited impact on average global precipitation. Analysis of the surface fluxes in the CCSM experiments found the current day warming was predominantly driven by changes in surface hydrology through reduced evapo-transpiration and latent heat flux, with the radiative forcing playing a secondary role. We show these finding are supported by a wide range of observational field studies, satellite studies, and regional and global climate modeling studies