Spatially resolved emulated annual temperature projections for overshoot pathways
Due to insufficient climate action over the past decade, it is increasingly likely that 1.5 °C of global warming will be exceeded - at least temporarily - in the 21<sup>st</sup> century. Such a temporary temperature overshoot carries additional climate risks which are poorly understood. Earth System Model climate projections are only available for a very limited number of overshoot pathways, thereby preventing comprehensive analysis of their impacts. Here, we address this issue by presenting a novel dataset of spatially resolved emulated annual temperature projections for different overshoot pathways. The dataset was created using the FaIR and MESMER emulators. First, FaIR was employed to translate ten different emission scenarios, including seven that are characterised by overshoot, into a large ensemble of forced global mean temperatures. These global mean temperatures were then converted into stochastic ensembles of local annual temperature fields using MESMER. To ensure an optimal tradeoff between accurate characterization of the ensemble spread and storage requirements for large ensembles, this procedure was accompanied by testing the sensitivity of sample quantiles to different ensemble sizes. The resulting dataset offers the unique opportunity to study local and regional climate change impacts of a range of overshoot scenarios, including the timing and magnitude of temperature thresholds exceedance.
Authors
- Sonia Isabelle Seneviratne (ORCID: https://orcid.org/0000-0001-9528-2917)
- Joeri Rogelj (ORCID: https://orcid.org/0000-0003-2056-9061)
- Lea Beusch (ORCID: https://orcid.org/0000-0002-3692-7962)
- Shruti Nath (ORCID: https://orcid.org/0009-0007-4449-1621)
- Carl‐Friedrich Schleussner (ORCID: https://orcid.org/0000-0001-8471-848X)
- Mathias Hauser (ORCID: https://orcid.org/0000-0002-0057-4878)
- Zebedee Nicholls (ORCID: https://orcid.org/0000-0002-4767-2723)
- Quentin Lejeune (ORCID: https://orcid.org/0000-0001-9152-3197)
- Jonas Schwaab (ORCID: https://orcid.org/0000-0003-4625-3882)
- Robin Lamboll (ORCID: https://orcid.org/0000-0002-8410-037X)
- Lukas Gudmundsson (ORCID: https://orcid.org/0000-0003-3539-8621)
- Yann Quilcaille (ORCID: https://orcid.org/0000-0002-1474-0144)
- Sarah Schöngart
Institutions
- International Institute for Applied Systems Analysis (AT)
- Federal Office of Meteorology and Climatology MeteoSwiss (CH)
- The University of Melbourne (AU)
- ETH Zurich (CH)
- Humboldt-Universität zu Berlin (DE)
- Victorian Aboriginal Health Service (AU)
- Climate Analytics (DE)
- Center for Snow and Avalanche Studies (US)
- Klinikum im Friedrichshain (DE)
- Imperial College London (GB)
Publication Details
- Journal
- Scientific Data
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1038/s41597-024-04122-1
- Citations
- 7
- Primary Topic
- Climate variability and models
- Type
- article
- Field-Weighted Citation Impact
- 1.98
Funders
- Eidgenössische Technische Hochschule Zürich