Could the Pliocene constrain the equilibrium climate sensitivity?

Hargreaves, J. C.

doi:10.5194/cp-12-1591-2016

Cited by 21 publications

(45 citation statements)

References 35 publications

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“…Paleoclimate is a useful testbed for simple and complex climate models [400][401][402][403][404][405] and numerous studies have estimated climate sensitivity from past periods, in particular the Last Glacial Maximum or the last few glacial cycles, but also the Holocene and warm periods millions of years back 95,102,400, . Uncertainties in some individual studies are small but the range across studies is similar to the range derived from other methods.…”

Section: Paleoclimatementioning

confidence: 99%

“…Super-parameterizations and large eddy simulations offer new opportunities to better represent clouds 100,101 . Using GCM ensembles for paleoclimate studies and for the historical period allow to better use spatial information, to estimate how past warming or cooling relates future warming as feedbacks vary over time 102 . The challenge then is that climate model information (and potential biases) are part of each line of evidence, making them less independent.…”

Section: Conclusion and Implications For Research And Policymentioning

confidence: 99%

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Beyond equilibrium climate sensitivity

2017

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Equilibrium climate sensitivity characterizes the Earth' long-term global temperature response to an increased atmospheric carbon dioxide concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus 'likely' range for climate sensitivity of 1.5-4.5 o C today is the same as given by Jule Charney in 1979, but is now based on quantitative evidence from across the climate system, and through climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability, limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which open avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 o C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.If we increase the amount of CO2 in the Earth's atmosphere and wait for climate to respond, how much warmer would surface temperatures eventually get? What seems like a simple but important question to ask given current and projected human-induced CO2 emissions, is an issue that scientists have struggled with since the first rough estimates were made more than a century ago 1,2 . To answer that question, starting in the 1960s, scientists have used energy balance arguments combined with observed changes in the global energy budget, evaluated comprehensive climate models against observations, and analyzed the relationship between external forcing and climate change over different climate states in the past (see Methods for a list of early publications). The idea of using those different lines of evidence has not changed, but progress in simulating climate, a longer and more accurate observed record of past warming, and better constrained paleoclimate reconstructions now offer more possibilities to evaluate and constrain models. However, recent research has pointed out previously unknown limitations in some of the concepts and assumptions underlying a single constant climate sensitivity 3 . While publications have appeared using various methods, arguably the most important conceptual recent insights is that feedbacks change with equilibration time, an insight that is based on studies in comprehensive climate models. Other recent insights show that the treatment of observations is important 4 . Knowing, to first order, how the global climate will warm in response to increased CO2 is critical: for unabated emissions, it is the difference between a hot and an extremely hot future. The value of halving the uncertainty in that projection may be in the trillions of dollars 5 . Here w...

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Section: Paleoclimatementioning

confidence: 99%

Section: Conclusion and Implications For Research And Policymentioning

confidence: 99%

Beyond equilibrium climate sensitivity

2017

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“…In the context of constraining climate sensitivity, the parameter of interest (i.e. the ECS) is 90 considered as a predicted variable Schmidt et al, 2014;Hargreaves and Annan, 2016). This may be written as…”

Section: Ordinary Least Squaresmentioning

confidence: 99%

“…These are usually presented in probabilistic terms, mostly based on Ordinary Least Squares (OLS) methods. For example, studies have explored the constraint on equilibrium climate sensitivity (ECS), which is the global mean equilibrium temperature after a sustained doubling of CO 2 over pre-industrial levels, using model outputs from the Paleoclimate Model Intercomparison Project (PMIP) Schmidt et al, 2014;Hopcroft and Valdes, 2015;Hargreaves and Annan, 2016). Because of their relatively strong temperature signal, paleoclimate states like the Last Glacial Maximum 30 (LGM) and the mid-Pliocene Warm Period (mPWP) are often considered as promising constraints for the ECS Hargreaves and Annan, 2016), in particular at the high end.…”

Section: Introductionmentioning

confidence: 99%

“…Because of that, it does not appear to correspond to the choice which is usually made, In Section 2 we provide an overview of the concept of emergent constraints, the previous methods used for these analyses, introduce the Bayesian linear regression method as well as the models and data employed in the paper. Section 3 describes the results, starting with analysis of models and data from the Paleoclimate Intercomparison Project (PMIP) Phases 2 and 3 for the LGM and mPWP, that have previously been analysed for an emergent constraint on climate sensitivity (Schmidt et al,60 2014; Hargreaves and Annan, 2016). We then incorporate some CMIP6/PMIP4 model outputs that have been made available to us for these periods to illustrate how these outputs fit into the same analysis.…”

Section: Introductionmentioning

confidence: 99%

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A Bayesian framework for emergent constraints: case studies of climate sensitivity with PMIP

Renoult¹,

Hargreaves²,

Sagoo³

et al. 2020

Preprint

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<p>In this study we introduce a Bayesian framework, which is flexible and explicit about the prior assumptions, for using model ensembles and observations together to constrain future climate change. The emergent constraint approach has seen broad application in recent years, including studies constraining the equilibrium climate sensitivity (ECS) using the Last Glacial Maximum (LGM) and the mid-Pliocene Warm Period (mPWP). Most of these studies were based on Ordinary Least Squares (OLS) fits between a variable of the climate state, such as tropical temperature, and climate sensitivity. Using our Bayesian method, and considering the LGM and mPWP separately, we obtain values of ECS of 2.7 K (1.1 - 4.8, 5 - 95 percentiles) using the PMIP2, PMIP3 and PMIP4 data sets for the LGM, and 2.4 K (0.4 - 5.0) with the PlioMIP1 and PlioMIP2 data sets for the mPWP. Restricting the ensembles to include only the most recent version of each model, we obtain 2.7 K (1.1 - 4.3) using the LGM and &#160;2.4 K (0.4 - 5.1) using the mPWP. An advantage of the Bayesian framework is that it is possible to combine the two periods assuming they are independent, whereby we obtain a slightly tighter constraint of 2.6 K (1.1 - 3.9). We have explored the sensitivity to our assumptions in the method, including considering structural uncertainty, and in the choice of models, and this leads to 95% probability of climate sensitivity mostly below 5 and never exceeding 6 K. The approach is compared with other approaches based on OLS, a Kalman filter method and an alternative Bayesian method. An interesting implication of this work is that OLS-based emergent constraints on ECS generate tighter uncertainty estimates, in particular at the lower end, suggesting a higher bound by construction in case of weaker correlation. Although some fundamental challenges related to the use of emergent constraints remain, this paper provides a step towards a better foundation of their potential use in future probabilistic estimation of climate sensitivity.</p>

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Simulating Miocene warmth: insights from an opportunistic Multi-Model ensemble (MioMIP1)

Burls

Bradshaw

Boer

et al. 2021

Preprint

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The Miocene epoch, spanning 23.03-5.33 Ma, was a dynamic climate of sustained, polar amplified warmth. Miocene atmospheric CO 2 concentrations are typically reconstructed between 300 and 600 ppm and were potentially higher during the Miocene Climatic Optimum (16.75-14.5 Ma). With surface temperature reconstructions pointing to substantial midlatitude and polar warmth, it is unclear what processes maintained the much weaker-than-modern equator-to-pole temperature difference. Here, we synthesize several Miocene climate modeling efforts together with available terrestrial and ocean surface temperature reconstructions. We evaluate the range of model-data agreement, highlight robust mechanisms operating across Miocene modeling efforts and regions where differences across experiments result in a large spread in warming responses. Prescribed CO 2 is the primary factor controlling global warming across the ensemble. On average, elements other than CO 2 , such as Miocene paleogeography and ice sheets, raise global mean temperature by ∼2°C, with the spread in warming under a given CO 2 concentration (due to a combination of the spread in imposed boundary conditions and climate feedback strengths) equivalent to ∼1.2 times a CO 2 doubling. This study uses an ensemble of opportunity: models, boundary conditions, and reference data sets represent the state-of-art for the Miocene, but are inhomogeneous and not ideal for a formal intermodel comparison effort. Acknowledging this caveat, this study is nevertheless the first Miocene multi-model, multi-proxy comparison attempted so far. This study serves to take stock of the current progress toward simulating Miocene warmth while isolating remaining challenges that may be well served by community-led efforts to coordinate modeling and data activities within a common analytical framework.Plain Language Summary As human activity continues to increase atmospheric carbon dioxide concentrations, scientists turn to warm intervals in Earth's history to develop insight into the behavior of the climate system under elevated carbon dioxide and temperature. One such interval is the Miocene epoch which has become increasingly relevant as reconstructions of Miocene atmospheric CO 2 concentrations point to values ranging between current concentrations of ∼400 ppm and those projected for the end of this century under Shared Socioeconomic Pathways 3 and 4. In this study, we evaluate the BURLS ET AL.

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Could the Pliocene constrain the equilibrium climate sensitivity?

Cited by 21 publications

References 35 publications

Beyond equilibrium climate sensitivity

Beyond equilibrium climate sensitivity

A Bayesian framework for emergent constraints: case studies of climate sensitivity with PMIP

Simulating Miocene warmth: insights from an opportunistic Multi-Model ensemble (MioMIP1)

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