Abstract for:Modeling spatial discordance in greenhouse gas emissions and climate impacts on future climate change

Anthropogenic emissions of greenhouse gases (GHG) over the past two centuries have resulted in rapid global change. Current projections of climate change, driven by fixed greenhouse gas (GHG) emission trajectories reflect static assumptions of human emissions behaviors in response to climate change. In reality, GHG emissions will be driven by dynamic interactions between physical and human systems as climate change alters the frequency or severity of extreme climate events, influencing human perception of climate change and associated risk to existing social structures, and potentially feedback to influence emissions behaviors.  Feedbacks between the human and climate systems are likely to be sensitive to the spatial discordance of climate impacts and GHG emissions. The emissions behavior of populations in regions that are experiencing lesser impacts of global climate change is likely to diverge from populations experiencing larger climate change impacts. The global distribution of GHG emissions are largely spatially discordant with climate change impacts. We develop a spatially implicit dynamical model that couples a spatially referenced, climate and emissions behavior models to examine the effect of spatial discordance of global patterns of GHG emissions and climate impacts.