At today's 1°C of global warming the local signals of climate change emerge from natural variability and manifest in more frequent heat waves and droughts, heavy rainfall events, long-term local trends in temperature and precipitation as well as sea-level rise and associated shifts in extreme sea levels. A global synthesis and understanding of societies’ sensitivities to these changes is still severely limited due to fragmentary observational records and the concurrent direct human influence through, for example, land-use change, pollution, or changes in exposure and vulnerability due to population and protection measures. In principle, process-based climate impact simulations are ideal tools to address the issues of fragmentary observations and concurrent human factors. Many impact models do however not yet stand up to this challenge due to missing detail in the representation of socio-economic conditions and dynamics but also due to missing representation of physical processes. For example, the approaches to estimate damages induced by tropical cyclones do not explicitly resolve the associated flooding events from tropical cyclones, though these events cause a large part of losses.
In the emerging era of data richness, we especially aim at sourcing non-traditional datasets derived from satellite imagery to increase the regional relevance of global climate impact simulations, addressing also the growing demands for financial climate risk assessments. We aim to better understand and separate the contribution of weather fluctuation (extreme events or long term trends) versus direct human influence as drivers of bio-physical or socio-economic impacts. We will pursue this work in close collaboration with impact modelers from the ISIMIP community as an efficient way to generate community-wide progress in impact modelling across sectors. Our data team manages and coordinates the ISIMIP simulation rounds providing the technical infrastructure to synthesize global impact modeling efforts. In cooperation with impact modelers across the globe we develop standardized simulation protocols and continuously improve usability and quality of ISIMIP data.
Part of our work is dedicated to the processing and development of climate related forcing serving as input for impact models, including bias-corrected and downscaled climate projections, as well as counterfactual historical climate simulations representing a world without climate change. Our climate related forcing encompasses approaches to describe coastal system change including changes in compound tropical cyclone hazards. Furthermore, we process outputs from the ISIMIP impact simulations from several sectors to derive weather extreme event indicators to further quantify the impacts of devastating extremes such as floods, droughts and crop failure.
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The work will finally put us in the position to push forward the attribution of climate-change impacts, going beyond physical climate change attribution and paving the path to climate liability. To better quantify the link between greenhouse gas emissions and past, present and future impacts we will streamline the development of the global emission database and simple climate modeling at PIK. ISIMIP-based impact functions linking impacts to global mean temperature change and the ability to trace incremental temperature increases back to emission sources will help to ultimately attribute past, present and future damages to major global greenhouse gas emitters.
