Assessing Climate Model Projections of Anthropogenic Warming Patterns

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Authors

Henri F. Drake , Tristan H. Abbott, Megan Lickley

Abstract

Projections of future anthropogenic climate change and their uncertainties are determined by analyzing large ensembles of numerical climate models. Since the late 1980s, transient climate models have projected a pronounced global warming, with relatively high warming in the Arctic and over land and low warming over the Southern Ocean. In general, confidence in climate model projections is based on their representations of physical processes and on how well they reproduce past climates. However, the relationship between a models ability to reproduce past climate changes and project future climate changes is unknown, as observations of the future are by definition unavailable. Here, we assess climate model projections of `future global warming patterns published in the 1995 Intergovernmental Panel on Climate Change Second Assessment Report by quantitatively comparing them to observations acquired between 1990 and 2018. Observed patterns of warming follow model projections, falling within 1.64 inter-model standard deviations of the multi-model mean over most of the globe, with the exception of the West Pacific and Southern Oceans where we observe regional cooling trends associated with the `global warming hiatus. We find a correlation between a models ability to reproduce spatially-resolved temperature trends over the 1920-1990 hindcast period and the 1990-2018 `nowcast period, increasing our confidence in their projections of the future and lending support to Bayesian approaches in climate modelling. Climate change mitigation has now been delayed long enough for the first projections of anthropogenic global warming to be borne out in observations, dismissing claims that models are too inaccurate to be useful and reinforcing calls for climate action.

DOI

https://doi.org/10.31223/osf.io/ahq4p

Subjects

Climate, Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

Keywords

Dates

Published: 2019-07-16 19:37

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License

GNU Lesser General Public License (LGPL) 2.1

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