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Indices of climate change based on patterns from CMIP5 models, and the range of projections

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Abstract

Changes in temperature, precipitation, and other variables simulated by 40 current climate models for the 21st century are approximated as the product of the global mean warming and a spatial pattern of scaled changes. These fields of standardized change contain consistent features of simulated change, such as larger warming over land and increased high-latitude precipitation. However, they also differ across the ensemble, with standard deviations exceeding 0.2 for temperature over most continents, and 6% per degree for tropical precipitation. These variations are found to correlate, often strongly, with indices based on those of modes of interannual variability. Annular mode indices correlate, across the 40 models, with regional pressure changes and seasonal rainfall changes, particularly in South America and Europe. Equatorial ocean warming rates link to widespread anomalies, similarly to ENSO. A Pacific–Indian Dipole (PID) index representing the gradient in warming across the maritime continent is correlated with Australian rainfall with coefficient r of − 0.8. The component of equatorial warming orthogonal to this index, denoted EQN, has strong links to temperature and rainfall in Africa and the Americas. It is proposed that these indices and their associated patterns might be termed “modes of climate change”. This is supported by an analysis of empirical orthogonal functions for the ensemble of standardized fields. Can such indices be used to help constrain projections? The relative similarity of the PID and EQN values of change, from models that have more skilful simulation of the present climate tropical pressure fields, provides a basis for this.

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Acknowledgements

This work was supported by the Australian Government’s Regional Natural Resources Management Planning for Climate Change Fund. The author is grateful to the modelling groups, PCMDI, and others who established the CMIP5 archive, and to colleagues who provided the global means and trend data used, in particular Louise Wilson and Tim Erwin, and Penny Whetton for support and advice over many years. Comments from two reviewers led to major improvements in the presentation, including the analysis of statistical significance in Sect. 6.

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  1. CSIRO, Aspendale, Australia

    I. G. Watterson

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Watterson, I.G. Indices of climate change based on patterns from CMIP5 models, and the range of projections. Clim Dyn 52, 2451–2466 (2019). https://doi.org/10.1007/s00382-018-4260-x

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