VISIBLE

Humans already have a deep impact on earth through e.g. land use changes, water management or pollution. Besides that, anthropogenic climate change becomes reality at high pace and additionally affects natural and human systems such as agriculture, forests, coasts and cities. Quantifying the contribution of climate change to observed changes in these systems (impact attribution) is essential to better understand societies’ sensitivities to future climate change. Through my work on the IPCC Sixth Assessment Report I have realized how fragmented this field still is, leaving out many regions and impacts. The analysis is still constrained by the sparse observational data and studies barely exploit the potential of process-based impact models to test our understanding of the observed processes and disentangle the underlying drivers. V-ISI-BLE unfolds the unused power of process-based biophysical impact models by expanding the attribution framework within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) coordinated within my department. To this end, the existing model evaluation set-up based on historical simulations driven by observational climate and socio-economic changes is extended by counterfactual simulations mimicking a world without climate change. Within V-ISI-BLE we develop the required climate forcing data focussing on the representation of extreme events. In addition, we derive high quality estimates of areas affected by extreme events from remote sensing to evaluate the impact models. The counterfactual simulations are then used to estimate the effect of historical climate change on these areas. New empirical approaches translate the climate-induced changes in affected areas into changes in economic losses and human displacement. V-ISI-BLE makes impact attribution actionable for the impact modeling community to initiate a broad quantification of observed impacts of climate change.