Effective climate sensitivity distributions from a 1D model of global ocean and land temperature trends, 1970–2021
Abstract Current theoretically based Earth system models (ESMs) produce Effective Climate Sensitivities (EffCS) that range over a factor of three, with 80% of those models producing stronger global warming trends for 1970–2021 than do observations. To make a more observationally based estimate of EffCS, a 1D time-dependent forcing-feedback model of temperature departures from energy equilibrium is used to match measured ranges of global-average surface and sub-surface land and ocean temperature trends during 1970–2021. In response to two different radiative forcing scenarios, a full range of three model free parameters are evaluated to produce fits to a range of observed surface temperature trends (± 2σ) from four different land datasets and three ocean datasets, as well as deep-ocean temperature trends and borehole-based trend retrievals over land. Land-derived EffCS are larger than over the ocean, and EffCS is lower using the newer Shared Socioeconomic Pathways (SSP245, 1.86 °C global EffCS, ± 34% range 1.48–2.15 °C) than the older Representative Concentration Pathway forcing (RCP6, 2.49 °C global average EffCS, ± 34% range 2.04–2.87 °C). The strongest dependence of the EffCS results is on the assumed radiative forcing dataset, underscoring the role of radiative forcing uncertainty in determining the sensitivity of the climate system to increasing greenhouse gas concentrations from observations alone. The results are consistent with previous observation-based studies that concluded EffCS during the observational period is on the low end of the range produced by current ESMs.
- Research Organization:
- University of Alabama in Huntsville, AL (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- SC0019296
- OSTI ID:
- 2000603
- Journal Information:
- Theoretical and Applied Climatology, Journal Name: Theoretical and Applied Climatology Journal Issue: 1 Vol. 155; ISSN 0177-798X
- Publisher:
- Springer Science + Business MediaCopyright Statement
- Country of Publication:
- Austria
- Language:
- English
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