The Intergovernmental Panel on Climate Change (IPCC) currently prepares its Sixth Assessment Report (AR6). Its authors assess peer-reviewed scientific literature and recent climate datasets to inform policy-makers about the current state of the science regarding climate change and its impacts, as well as adaptation and mitigation options. For AR6, efforts are underway to make its main results FAIR and preserve them in the TRUSTworthy repositories of the IPCC Data Distribution Centre (DDC), jointly managed by CEDA, DKRZ, and CIESIN. The AR6 FAIR initiative was kickstarted by the IPCC DDC and Working Group I (WGI) [Stockhause et al., 2019], then adopted by IPCC TG-Data (Task Group on Data Support for Climate Change Assessments) shortly after its creation. All three WGs have adopted the FAIR data guidelines. IPCC assessments are large and diverse in in terms of scientists involved as well as included scientific objects. Challenges for digital data curation are related to the scale and diversity of papers, reports, datasets, the variety of software, and the different familiarity of the scientists with these technical aspects. The following priority areas for improved data stewardship were selected based on the aims to enhance the traceability of AR6 key findings and their reusability: preserve figure datasets in the DDC; - preserve analysis software; . preserve main input datasets in the DDC; . assemble datasets and provenance information on the figure creation from IPCC authors; and . interlink datasets to the IPCC report. Datasets are transferred to the DDC at the end of AR6. The DDC partners are responsible to preserve the data for future reuse by different stakeholders and under a variety of current and future scientific and policy-related questions. As the role for the DDC expands within the IPCC, new partners are sought. The TRUST principles provide a framework for the communication of DDC tasks to different stakeholders, e.g. to countries interested to host a DDC. The presentation will give an overview over the IPCC AR6 approaches towards FAIR data maintained in TRUSTworthy repositories, their challenges, their approach to meet these challenges and open questions, e.g. the integration of digital data into the IPCC Error Protocol, targeted within TG-Data.

Climate change adaptation under resource constraints and future climate uncertainties would benefit from fully probabilistic climate risks assessments. Conducting such risk analyses requires assigning probabilities to the future greenhouse gases (GHG) and land-use scenarios used by global climate models. This paper proposes an approach to estimate the relative likelihood of carbon dioxide (CO2) concentration scenarios used in key climate change modeling experiments. The approach relies on the comparison of CO2 emissions from probabilistic simulations of Integrated Assessment Models (IAM) with compatible CO2 emissions diagnosed by global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and 6 (CMIP6). The approach is demonstrated with five emission simulations from four IAMs, leading to independent estimates of the relative likelihood of CMIP5 Representation Concentration Pathways and CMIP6’ Shared Socioeconomic Pathways (SSP) up to 2100. Results suggest that SSP5-8.5 is an unlikely scenario for the second half of the century, but there is no clear consensus on the most likely scenario. Scenario likelihood is affected by a number of potential errors, including sampling errors, differences in emission sources simulated by the IAMs, and the lack of a common experimental framework for IAM simulations. These errors, along with the small IAM ensemble size, limit the applicability of the results. The delivery of fully probabilistic climate risk assessments would benefit from a coordinated probabilistic IAM experiment jointly designed with a coordinated climate modeling experiment where Earth System Model are driven by representative emission pathways.