A machine learning approach to rapidly project climate responses under a multitude of net-zero emission pathways

Author:

Kitsios VassiliORCID,O’Kane Terence John,Newth David

Abstract

AbstractNavigating a path toward net-zero, requires the assessment of physical climate risks for a broad range of future economic scenarios, and their associated carbon concentration pathways. Climate models typically simulate a limited number of possible pathways, providing a small fraction of the data needed to quantify the physical risk. Here machine learning techniques are employed to rapidly and cheaply generate output mimicking these climate simulations. We refer to this approach as QuickClim, and use it here to reconstruct plausible climates for a multitude of concentration pathways. Higher mean temperatures are confirmed to coincide with higher end-of-century carbon concentrations. The climate variability uncertainty saturates earlier, in the mid-century, during the transition between current and future climates. For pathways converging to the same end-of-century concentration, the climate is sensitive to the choice of trajectory. In net-zero emission type pathways, this sensitivity is of comparable magnitude to the projected changes over the century.

Funder

Commonwealth Scientific and Industrial Research Organisation

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference49 articles.

1. Raworth, K. Doughnut economics: seven ways to think like a 21st-century economist (Chelsea Green Publishing, White River Junction, Vermont, 2017).

2. UN-DESA. The sustainable development goals report 2022. Tech. Rep. https://unstats.un.org/sdgs/report/2022/SDG2022_Flipbook_final.pdf, UN-DESA, New York, USA (2022).

3. Rockström, J. A safe operating space for humanity. Nature 461, 472–475 (2009).

4. IPCC. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, United Kingdom and New York, 2013).

5. O’Kane, T. J., Risbey, J., Franzke, C. J. E., Horenko, I. & Monselesan, D. Changes in the metastability of the midlatitude southern hemisphere circulation and the utility of nonstationary cluster analysis and split-flow blocking indices as diagnostic tools. J. Atmos. Sci. 70, 824–842 (2013).

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