Closing the loop between integrated assessment and climate risk research – rapid climate risk emulation

Climate model emulation has long been and is increasingly applied to the results of integrated assessment modelling (IAM)models (IAMs), to determine the climate outcomes, primarily global mean surface temperature (GMST), of emissions pathways. Originally provided at the global level, more recently approaches have been developed to reproduce a growing number of climate variables, also with spatial, even gridded, resolution. Here we build on these approaches to demonstrate a workflow and post-processing package, that takes the GMST trajectory, e.g. from a simple climate model (SCM) and calculates a range of climate impacts and exposure indicators based on the GMST trajectory. To do this, we built a database of post-processed climate impacts from global climate [WM1] CMIP6 & ISIMIP-3 GCMs and impacts [WM2] models, and also calculated population and land area exposure to the indicators through time and for spatial units, e.g. countries. Indicators include temperature and precipitation extremes, heatwaves, degree days, drought intensity, water stress, and indicators of hydrological variability. Using a high-resolution temperature time timeslice approach, GMST trajectories are then mapped to the impact and exposure indicators to produce gridded maps of climate impacts through time, and trajectories of climate exposure by spatial unit. Using this approach we demonstrate the rapid post-processing of SCM [WM3] results such that ensembles of global IAM [WM4] mitigation pathways, such as those from AR6, can be accompanied by a new suite of climate impacts and risk information – and discuss related uncertainties and avenues for further research to incorporate vulnerabilities.