Spatially resolved emulated annual temperature projections for overshoot pathways

• Published in: Scientific data Vol. 11; no. 1; pp. 1262 - 10
• Main Authors: Schwaab, Jonas, Hauser, Mathias, Lamboll, Robin D., Beusch, Lea, Gudmundsson, Lukas, Quilcaille, Yann, Lejeune, Quentin, Schöngart, Sarah, Schleussner, Carl-Friedrich, Nath, Shruti, Rogelj, Joeri, Nicholls, Zebedee, Seneviratne, Sonia I.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 21.11.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 704/106/694/1108; 704/106/694/2739/2819; 704/106/694/682; Climate change; Data Descriptor; Datasets; Global warming; Humanities and Social Sciences; multidisciplinary; Science; Science (multidisciplinary); Sensitivity analysis; Temperature; Temperature requirements
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-024-04122-1

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 st 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.