Green Sahara spatial and temporal patterns

Social, biological and environmental dynamics have affected the way of humans out of Africa during the late Quaternary. Hence understanding the dynamics of these three factors and their interaction is a prerequisite for understanding human migration. Conceptual climate and environmental modeling is often based on individual paleo climate records which are sparsely distributed in space and time, and fewer and fewer records exist the further one looks into the past. Can climate system modeling provide a way forward? So far, different climate system models yield completely different patterns of past greening in the Sahara. None of the global models is able to generate local landscape changes like the emergence of gallery forests or wetlands that could provide green corridors or barriers for migration. Considering a spectrum of models of different complexity might be the way forward. Coarse-scale models can be used to explore multi-millennial-scale and continent-scale dynamics, thereby providing information on the large-scale effect of orbital forcing or the gross differences in the overall dynamics of the last African Humid Periods, for example. Global climate system models with a grid size of some 100 km, e.g. the CMIP models, yield interesting insight into large-scale atmospheric dynamics and regional heterogeneity, like differences between West and East Sahara weather and vegetation patterns. This type of models can also help reconciling seemingly divergent reconstructions, such as the discussion of abrupt vs gradual termination of Saharan greening some 5000 years ago. For a more detailed view on local landscape changes, regional climate models operating at km-scale are necessary to resolve the complex orography, mesoscale convection and related local climate changes. These models can currently be run over seasons only. However, development of a new generation of Earth system models bodes well for the potential use of global high-resolution simulations. In summary, we suppose that using the spectrum of climate system models will bring models and proxy data closer together and will advance our understanding of past climate change and human migration.