- 1Barcelona Supercomputing Center, Earth Sciences, Spain (lina.teckentrup@bsc.es)
- 2UK Met Office, FitzRoy Road, Exeter EX1 3PB, United Kingdom
- 3Université catholique de Louvain, Earth and Life Institute, Louvain-la-Neuve, Belgium
- 4Department of Environmental Science, University of Arizona, Tucson, AZ, USA
- 5Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, United Kingdom
- 6Centre for Earth, Ocean and Atmospheric Sciences, School of Physics, University of Hyderabad, Hyderabad, India
- 7Department of Earth and Environmental Sciences, Dalhousie University, Halifax, Nova Scotia, Canada
- 8Department of Geography, Simon Fraser University, Burnaby, British Columbia, Canada
- 9National Centre for Atmospheric Science, University of Reading, Reading, United Kingdom
- 10School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom
- 11Climate Change Research Centre, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, Australia
- 12University College London (UCL), London, UK
- 13CSIRO Environment, Hobart, Tasmania, Australia
- 14Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
- 15Max Planck Institute for Biogeochemistry, Jena 07745, Germany
Output generated by the different phases of the Coupled Model Intercomparison Project (CMIP) has underpinned countless scientific projects and serves as the foundation of the United Nations climate change reports. While initially CMIP was largely driven by the scientific curiosity in the broader climate modeling community, CMIP output has also become a crucial data source for disciplines more tangentially related to physical climate science such as the economic modelling community. The upcoming CMIP phase 7 is expected to produce the largest amount of CMIP-related data to date. However, with an increasing number of modelling systems, represented realms, model complexity, variable names, experiments, and different grid types, the initial exposure to CMIP output has undoubtedly become an overwhelming experience for first-time users. For this presentation, we would like to start a conversation with users who are in or have recent experience of being in the early stages of employing CMIP outputs for their research, and together identify:
- Key barriers and challenges experienced when first using CMIP data
- Additional documentation/tools needed to facilitate the use of CMIP data
- Key pieces of advice for new CMIP users
How to cite: Teckentrup, L., Pope, J. O., Francis, F., Green, J. K., Jenkins, S., Varghese, S. J., Kou-Giesbrecht, S., Leclerc, C., Madan, G., Ng, K., Prasad, A., Roy, I., Schroeter, S., Winkelbauer, S., and Winkler, A. J.: Navigating the Jungle of CMIP Data as a First-Time User: Key Challenges and Future Directions , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19107, https://doi.org/10.5194/egusphere-egu25-19107, 2025.
