Should we think of observationally constrained multidecade climate projections as predictions?

Empirical evidence indicates that the range of model-projected future warming can be successfully narrowed by conditioning the projected warming on past observed warming. We demonstrate that warming projections conditioned on the entire instrumental annual surface temperature record are of sufficiently high quality and should be considered as long-term predictions rather than merely as projections. We support this view by considering the skill of predicted 20- and 50-year lead temperature changes under the Shared Economic Pathway (SSP)1-2.6 and SSP5-8.5 emission scenarios in climates of different sensitivities. Using climate model simulations, we show that adjusting raw multimodel projections of future warming with the Kriging for Climate Change (KCC) method eliminates most biases and reduces the uncertainty of warming projections irrespective of the sensitivity of the climate being considered. Simpler methods, or using only the more recent part of the temperature record, provide less effective constraints. The high-skill future warming predictions obtained via KCC have a serious place in informing global climate policies.

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Publication Details

Journal
Science Advances
Published
2025-05-16
DOI
https://doi.org/10.1126/sciadv.adt6485
Citations
4
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
4.42
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article

Should we think of observationally constrained multidecade climate projections as predictions?

Francis W. Zwiers, Tong Li, Xuebin Zhang
4 citations
Science Advances
Climate variability and models
4.42
article

Should we think of observationally constrained multidecade climate projections as predictions?

Francis W. Zwiers, Tong Li, Xuebin Zhang
article en
4 citations

Abstract

Empirical evidence indicates that the range of model-projected future warming can be successfully narrowed by conditioning the projected warming on past observed warming. We demonstrate that warming projections conditioned on the entire instrumental annual surface temperature record are of sufficiently high quality and should be considered as long-term predictions rather than merely as projections. We support this view by considering the skill of predicted 20- and 50-year lead temperature changes under the Shared Economic Pathway (SSP)1-2.6 and SSP5-8.5 emission scenarios in climates of different sensitivities. Using climate model simulations, we show that adjusting raw multimodel projections of future warming with the Kriging for Climate Change (KCC) method eliminates most biases and reduces the uncertainty of warming projections irrespective of the sensitivity of the climate being considered. Simpler methods, or using only the more recent part of the temperature record, provide less effective constraints. The high-skill future warming predictions obtained via KCC have a serious place in informing global climate policies.

Science AdvancesVol. 11(20)
Nanjing University of Information Science and Technology (CN), University of Victoria (CA), Pacific Institute for Climate Solutions (CA), Ministry of Education (BD)
Climate action
Openalex Percentile: Top 6%
Climate variability and models
4.42
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