Transient and Equilibrium Climate Sensitivity
Projections of the severity of anthropogenic climate change are strongly dependent on our estimates of climate sensitivity, traditionally defined as the global average warming at the Earth’s surface due to a doubling of the carbon dioxide from pre-industrial levels. This importance arises not because global temperature change directly causes all of the impacts of major concern, but because many effects of climate change are predicted to increase in severity with larger global warming.
An important distinction is made between the equilibrium sensitivity — the temperature change realized after allowing the climate system to equilibrate with a higher value of CO2 — and the response on shorter time scales, before the deep oceans have had time to equilibrate, that is of more direct relevance to the changes we are likely to see in the 21st century. The latter is often quantified by raising the carbon dioxide in a model at the rate of 1% per year and examining the response at the time when carbon dioxide concentration has doubled, referred to as the transient climate sensitivity or response. (At a rate of 1% per year, doubling requires 70 years.)
Equilibrium sensitivities in global climate models typically range from 2 to 5K, while the transient climate responses are smaller, in range of 1.0-2.5 K, due to the cooling influence of ocean heat uptake. GFDL climate model sensitivities are routinely evaluated and published as part of model documentation:
| Model | Transient Climate Response | Equilibrium Climate Sensitivity |
|---|---|---|
| CM2.1 | 1.5 K (Randall et al 2007) | 3.4 K (Stouffer et al 2006) |
| ESM2M | 1.3 K (Flato et al 2013) | 3.3 K (Paynter et al 2018) |
| ESM2G | 1.1 K (Flato et al 2013) | 3.3 K (Krasting et al 2018) |
| CM3 | 2.0 K (Flato et al 2013) | 4.8 K (Paynter et al 2018) |
| CM4 | 2.1 K (Winton et al submitted) | 5.0 K (Winton et al submitted) |
| ESM4 | 1.6 K (Dunne et al in prep) | 3.2 K (Dunne et al in prep) |
The ratio of transient to equilibrium sensitivity varies from 1/3 to 1/2 in this group of GFDL models indicating significant variation of the transient cooling influence of the ocean. The relationship of the ocean’s cooling influence to ocean heat uptake and circulation changes has been an ongoing thread of GFDL research. For example, He et al (2017) noted that stronger deep ocean circulation prior to forcing reduced the magnitude of transient warming in a GFDL model.
Cloud feedbacks are widely considered to contribute the largest uncertainty to climate sensitivity. Simulated climate sensitivity varies considerably with choices made about cloud parameterizations that are not well constrained by observations (Zhao et al 2016). Simulated cloud responses depend on the pattern of surface temperature change, not just its global magnitude (Silvers et al 2018). Because of the importance and complexity of the interactions of clouds and climate GFDL is focusing effort on a cloud climate initiative.
Isaac Held’s Blog (2011-2016) discussed many topics related to climate sensitivity.