2022Unpublished venueOpen access

Projected Changes and Time of Emergence of Temperature Extremes over Australia in CMIP5 and CMIP6

Xu Deng, Sarah Perkins‐Kirkpatrick

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Abstract

This study focuses on the projections and time of emergence (TOE) for temperature extremes over Australian regions in the phase 6 of Coupled Model Intercomparison Project (CMIP6) models. The model outputs are based on the Shared Socioeconomic Pathways (SSPs) from the Tier 1 experiments (i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) in the Scenario Model Intercomparison Project (ScenarioMIP), which is compared with the Representative Concentration Pathways (RCPs) in CMIP5 (i.e., RCP2.6, RCP4.5 and RCP8.5). Furthermore, two large ensembles (LEs) in CMIP6 are used to investigate the effects of internal variability on the projected changes and TOE. As shown in the temporal evolution and spatial distribution, the strongest warming levels are projected under the highest future scenario and the changes for some extremes follow a “warm-get-warmer” pattern over Australia. Over subregions, tropical Australia usually shows the highest warming. Compared to the RCPs in CMIP5, the multi-model medians in SSPs are higher for some indices and commonly exhibit wider spreads, likely related to the different forcings and higher climate sensitivity in a subset of the CMIP6 models. Based on a signal-to-noise framework, we confirm that the emergence patterns differ greatly for different extreme indices and the large uncertainty in TOE can result from the inter-model ranges of both signal and noise, for which internal variability contributes to the determination of the signal. We further demonstrate that the internally-generated variations influence the noise. Our findings can provide useful information for mitigation strategies and adaptation planning over Australia.

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What this paper is about

This study focuses on the projections and time of emergence (TOE) for temperature extremes over Australian regions in the phase 6 of Coupled Model Intercomparison Project (CMIP6) models. The model outputs are based on the Shared Socioeconomic Pathways (SSPs) from the Tier 1 experiments (i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) in the Scenario Model Intercomparison Project (ScenarioMIP), which is compared with the Representative Concentration Pathways (RCPs) in CMIP5 (i.e., RCP2.6, RCP4.5 and RCP8.5). Furthermore, two large ensembles (LEs) in CMIP6 are used to investigate the effects of internal variability on the projected changes and TOE. As shown in the temporal evolution and spatial distribution, the strongest warming levels are projected under the highest future scenario and the changes for some extremes follow a “warm-get-warmer” pattern over Australia. Over subregions, tropical Australia usually shows the highest warming. Compared to the RCPs in CMIP5, the multi-model medians in SSPs are higher for some indices and commonly exhibit wider spreads, likely related to the different forcings and higher climate sensitivity in a subset of the CMIP6 models. Based on a signal-to-noise framework, we confirm that the emergence patterns differ greatly for different extreme indices and the large uncertainty in TOE can result from the inter-model ranges of both signal and noise, for which internal variability contributes to the determination of the signal. We further demonstrate that the internally-generated variations influence the noise. Our findings can provide useful information for mitigation strategies and adaptation planning over Australia.

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Available abstract

This study focuses on the projections and time of emergence (TOE) for temperature extremes over Australian regions in the phase 6 of Coupled Model Intercomparison Project (CMIP6) models. The model outputs are based on the Shared Socioeconomic Pathways (SSPs) from the Tier 1 experiments (i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) in the Scenario Model Intercomparison Project (ScenarioMIP), which is compared with the Representative Concentration Pathways (RCPs) in CMIP5 (i.e., RCP2.6, RCP4.5 and RCP8.5). Furthermore, two large ensembles (LEs) in CMIP6 are used to investigate the effects of internal variability on the projected changes and TOE. As shown in the temporal evolution and spatial distribution, the strongest warming levels are projected under the highest future scenario and the changes for some extremes follow a “warm-get-warmer” pattern over Australia. Over subregions, tropical Australia usually shows the highest warming. Compared to the RCPs in CMIP5, the multi-model medians in SSPs are higher for some indices and commonly exhibit wider spreads, likely related to the different forcings and higher climate sensitivity in a subset of the CMIP6 models. Based on a signal-to-noise framework, we confirm that the emergence patterns differ greatly for different extreme indices and the large uncertainty in TOE can result from the inter-model ranges of both signal and noise, for which internal variability contributes to the determination of the signal. We further demonstrate that the internally-generated variations influence the noise. Our findings can provide useful information for mitigation strategies and adaptation planning over Australia.

Key concepts: Coupled model intercomparison project, Representative Concentration Pathways, Climatology, Environmental science, Climate change, Noise (video), Climate model, Geology

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