Geological evidence of a snowball Earth state indicate persistent tropical sea ice cover during the Neoproterozoic (>635 million years ago). Current theory is that a strengthening of the positive surface albedo feedback with cooling temperatures, eventually exceeding the sum of all other feedbacks, leads to a global climate instability. Several recent high sensitivity climate models with strongly positive cloud feedbacks have not been able to simulate the much warmer Last Glacial Maximum (LGM) state, suggestive that they cool excessively in response to a modest decrease in atmospheric carbon dioxide levels and therefore enter the snowball instability by this mechanism. Using a coupled Earth system model, MPI-ESM1.2, we show that clouds accelerate the transition to a snowball Earth state and reduce the radiative forcing required to trigger the snowball instability. Positive cloud feedbacks over tropical oceans and ahead of the sea-ice edge act to cool down the oceans and promote sea ice formation. Regardless, when approached slowly, the snowball Earth transition appears to occur around a global mean temperature of zero degree Celsius, simultaneously with the sea ice edge advancing into the sub-tropics thereby strengthening the surface albedo feedback. This temperature threshold, if supported by several climate models, could be used as a novel and independent constraint on the upper bound of climate sensitivity by using the relationship of simulated LGM temperatures and the models' equilibrium climate sensitivity. The constraint depends only on the simple fact that Earth did not enter a snowball instability during the recent ice ages. Using the here estimated transition temperature, we find it is implausible that Earth's climate sensitivity exceeds 6.2 °C (3.9–8.4 °C, 5 %–95 % confidence). This upper bound estimate of climate sensitivity is only weakly sensitive to uncertainty in the transition temperature, approximately 0.3° per degree.

The use of paleoclimates to constrain the equilibrium climate sensitivity (ECS) has seen a growing interest. In particular, the Last Glacial Maximum (LGM) and the mid-Pliocene warm period have been used in emergent-constraint approaches using simulations from the Paleoclimate Modelling Intercomparison Project (PMIP). Despite lower uncertainties regarding geological proxy data for the LGM in comparison with the Pliocene, the robustness of the emergent constraint between LGM temperature and ECS is weaker at both global and regional scales. Here, we investigate the climate of the LGM in models through different PMIP generations and how various factors in the atmosphere, ocean, land surface and cryosphere contribute to the spread of the model ensemble. Certain factors have a large impact on an emergent constraint, such as state dependency in climate feedbacks or model dependency on ice sheet forcing. Other factors, such as models being out of energetic balance and sea surface temperature not responding below −1.8^∘C in polar regions, have a limited influence. We quantify some of the contributions and find that they mostly have extratropical origins. Contrary to what has previously been suggested, from a statistical point of view, the PMIP model generations do not differ substantially. Moreover, we show that the lack of high- or low-ECS models in the ensembles critically limits the strength and reliability of the emergent constraints. Single-model ensembles may be promising tools for the future of LGM emergent constraint, as they permit a large range of ECS and reduce the noise from inter-model structural issues. Finally, we provide recommendations for a paleo-based emergent constraint and notably which paleoclimate is ideal for such an approach.

The mechanisms which amplify orbitally driven changes in insolation and drive the glacial cycles of the past 2.6 million years, the Pleistocene, are poorly understood. Previous studies indicate that cloud phase feedbacks oppose ice sheet initiation when orbital configuration supports ice sheet growth. Cloud phase was observationally constrained in a recent study and provides evidence for a weaker negative cloud feedback in response to carbon dioxide doubling. We observationally constrain cloud phase in the Community Earth System Model and explore how changes in orbital configuration impact the climate response. Constraining cloud phase weakens the negative high latitude cloud phase feedback and unmasks positive water vapor and cloud feedbacks (amount and optical depth) that extend cooling to lower latitudes. Snowfall accumulation and ablation metrics also support ice sheet expansion as seen in proxy records. This indicates that well-known cloud and water vapor feedbacks are the mechanisms amplifying orbital climate forcing.

In this paper we introduce a Bayesian framework, which is explicit about 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 2.7K (0.6-5.2, 5th-95th percentiles) using the PMIP2, PMIP3, and PMIP4 datasets for the LGM and 2.3K (0.5-4.4) with the PlioMIP1 and PlioMIP2 datasets for the mPWP. Restricting the ensembles to include only the most recent version of each model, we obtain 2.7K (0.7-5.2) using the LGM and 2.3K (0.4-4.5) 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 tighter constraint of 2.5K (0.8-4.0) using the restricted ensemble. 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 5K and only exceeding 6K in a single and most uncertain case assuming a large structural uncertainty. 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, an artefact due to a flatter regression line in the case of lack of correlation. Although some fundamental challenges related to the use of emergent constraints remain, this paper provides a step towards a better foundation for their potential use in future probabilistic estimations of climate sensitivity.

Airborne mineral dust influences cloud occurrence and optical properties, which may provide a pathway for recent and future changes in dust concentration to alter the temperature at Earth's surface. However, despite prior suggestions that dust-cloud interactions are an important control on the Earth's radiation balance, we find global mean cloud radiative effects to be insensitive to widespread dust changes. Here we simulate uniformly applied shifts in dust amount in a present-day atmosphere using a version of the CAM5 atmosphere model (within CESM v1.2.2) modified to incorporate laboratory-based ice nucleation parameterizations in stratiform clouds. Increasing and decreasing dustiness from current levels to paleoclimate extremes caused effective radiative forcings through clouds of +0.02 +/- 0.01 and -0.05 +/- 0.02 W/m(2), respectively, with ranges of -0.26 to +0.13 W/m(2) and -0.21 to +0.39 W/m(2) from sensitivity tests. Our simulations suggest that these forcings are limited by several factors. Longwave and shortwave impacts largely cancel, particularly in mixed-phase clouds, while in warm and cirrus clouds opposite responses between regions further reduce each global forcing. Additionally, changes in dustiness cause opposite forcings through aerosol indirect effects in mixed-phase clouds as in cirrus, while in warm clouds indirect effects are weak at nearly all locations. Nevertheless, regional forcings and global impacts on longwave and shortwave radiation were found to be nonnegligible, suggesting that cloud-mediated dust effects have significance in simulations of present and future climate.

As the world warms, there is a profound need to improve projections of climate change. Although the latest Earth system models offer an unprecedented number of features, fundamental uncertainties continue to cloud our view of the future. Past climates provide the only opportunity to observe how the Earth system responds to high carbon dioxide, underlining a fundamental role for paleoclimatology in constraining future climate change. Here, we review the relevancy of paleoclimate information for climate prediction and discuss the prospects for emerging methodologies to further insights gained from past climates. Advances in proxy methods and interpretations pave the way for the use of past climates for model evaluation—a practice that we argue should be widely adopted.

Many higher level avian clades are restricted to Earth's lower latitudes, leading to historical biogeographic reconstructions favoring a Gondwanan origin of crown birds and numerous deep subclades. However, several such tropical-restricted clades (TRCs) are represented by stem-lineage fossils well outside the ranges of their closest living relatives, often on northern continents. To assess the drivers of these geographic disjunctions, we combined ecological niche modeling, paleoclimate models, and the early Cenozoic fossil record to examine the influence of climatic change on avian geographic distributions over the last similar to 56 million years. By modeling the distribution of suitable habitable area through time, we illustrate that most Paleogene fossil-bearing localities would have been suitable for occupancy by extant TRC representatives when their stem-lineage fossils were deposited. Potentially suitable habitat for these TRCs is inferred to have become progressively restricted toward the tropics throughout the Cenozoic, culminating in relatively narrow circumtropical distributions in the present day. Our results are consistent with coarse-scale niche conservatism at the clade level and support a scenario whereby climate change over geological timescales has largely dictated the geographic distributions of many major avian clades. The distinctive modern bias toward high avian diversity at tropical latitudes for most hierarchical taxonomic levels may therefore represent a relatively recent phenomenon, overprinting a complex biogeographic history of dramatic geographic range shifts driven by Earth's changing climate, variable persistence, and intercontinental dispersal. Earth's current climatic trajectory portends a return to a megathermal state, which may dramatically influence the geographic distributions of many range-restricted extant clades.