The Role of Land Cover in the Earth System: Model Results from ESA’s Land Cover Climate Change Initiative
Poulter, Ben¹; Hartley, A²; Khlystova, I³; Arino, O⁴; Betts, R²; Bontemps, S⁵; Brockmann, C⁶; Defourny, P⁵; Hagemann, S³; Kalogirou, V⁴; Kirches, G⁶; Lamarche, C⁵; Lederer, D⁵; MacBean, N¹; Peylin, P^1
1LSCE, FRANCE; ²UKMO, UNITED KINGDOM; ³MPI, GERMANY; ⁴ESA, ITALY; ⁵UCL, BELGIUM; ⁶Brockmann Consult, GERMANY

Global land cover influences key land surface properties that regulate carbon, water and energy exchange between the atmosphere and biosphere. Human and climate-driven modifications to land cover have direct consequences on the functioning of the earth system, with implications for ecosystems, the services they provide, and how they may respond to climate change. The ESA Land Cover Climate Change Initiative (LC_CCI) has developed an updated MERIS-based global land cover dataset for use in earth system models. The LC_CCI dataset also includes an interactive tool for converting the original 300-meter land cover information from a modified Land Cover Classification System to the required model specifications for spatial resolution and to plant functional type (PFT) categories. Three earth system modeling teams based at the Laboratoire des Sciences du Climat et l'Environnement (LSCE), the UK Met Office (UKMO), and the Max Planck Institute for Meteorology (MPI) performed model simulations to evaluate model improvement using the new LC_CCI dataset against a set of benchmarks. Model experiments included offline as well as coupled carbon-climate simulations, and a dynamic vegetation simulation. For the offline prescribed and prognostic vegetation simulations, the models ORCHIDEE, JSBACH, and JULES, were run with climate forcing from the EU WATCH WFDEI dataset (Watch Forcing Data Methodology Applied to the ERA-Interim data). Benchmarks for the carbon cycle included an analysis of the seasonal cycle of atmospheric CO2 concentrations and of aboveground carbon stocks; for water, the seasonality and magnitude of catchment level runoff was evaluated; and for energy fluxes, a comparison to observations of surface temperature and latent energy fluxes was performed. The LC_CCI effort represents a significant improvement for earth system modeling by providing a recent land-cover dataset that is global in extent, validated with ground observations, and uses a single global algorithm for cross-walking high-resolution land cover data to model-grid requirements.