For a balanced risk assessment of climate change, understanding and quantifying the impacts of climate change on human and natural systems is crucial. A range of advanced numerical models are available to simulate the response of agriculture, natural vegetation, hydrology, and other parts of the human environment and economy to global climate change. However, climate impact projections can diverge substantially between different impact models, reflecting uncertainty in model structure and parameters. Together with further layers of uncertainty e.g. in the climate and socio-economic spheres, this impedes reliable estimates of the costs and damages expected at different levels of global warming.
To make impact projections more robust, it is important to systematically validate the models in the context of the most important types of impacts, and, if necessary, improve the representation of the related processes. For example, evaluating and improving the models’ response to extreme climate and weather events is a key challenge, because of the damage these events entail and because they are expected to get more frequent, widespread, and/or severe with each additional degree of global warming. Comparison of multiple models can help identify the processes that govern the response to extreme events and highlight opportunities for model improvement.
This session welcomes contributions that focus on evaluating state-of-the-art climate impact simulations, assessing their fidelity with regard to past and/or future extreme events or other relevant features, and/or further advancing existing modelling techniques. Contributions based on multi-model comparison projects such as the Coupled Model Intercomparison Project (CMIP), the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), or the Agricultural Model Improvement and Intercomparison Project (AgMIP) are encouraged.