Overshooting tipping point thresholds in a changing climate.

Palaeorecords suggest that the climate system has tipping points, where small changes in forcing cause substantial and irreversible alteration to Earth system components called tipping elements. As atmospheric greenhouse gas concentrations continue to rise as a result of fossil fuel burning, human activity could also trigger tipping, and the impacts would be difficult to adapt to. Previous studies report low global warming thresholds above pre-industrial conditions for key tipping elements such as ice-sheet melt. If so, high contemporary rates of warming imply that exceeding these thresholds is almost inevitable, which is widely assumed to mean that we are now committed to suffering these tipping events. Here we show that this assumption may be flawed, especially for slow-onset tipping elements (such as the collapse of the Atlantic Meridional Overturning Circulation) in our rapidly changing climate. Recently developed theory indicates that a threshold may be temporarily exceeded without prompting a change of system state, if the overshoot time is short compared to the effective timescale of the tipping element. To demonstrate this, we consider transparently simple models of tipping elements with prescribed thresholds, driven by global warming trajectories that peak before returning to stabilize at a global warming level of 1.5 degrees Celsius above the pre-industrial level. These results highlight the importance of accounting for timescales when assessing risks associated with overshooting tipping point thresholds.

Land surface conductance linked to precipitation: Co-evolution of vegetation and climate in Earth system models.

Vegetation and precipitation are known to fundamentally influence each other. However, this interdependence is not fully represented in climate models because the characteristics of land surface (canopy) conductance to water vapor and CO2 are determined independently of precipitation. Working within a coupled atmosphere and land modelling framework (CAM6/CLM5; coupled Community Atmosphere Model v6/Community Land Model v5), we have developed a new theoretical approach to characterizing land surface conductance by explicitly linking its dynamic properties to local precipitation, a robust proxy for moisture available to vegetation. This will enable regional surface conductance characteristics to shift fluidly with climate change in simulations, consistent with general principles of co-evolution of vegetation and climate. Testing within the CAM6/CLM5 framework shows that climate simulations incorporating the new theory outperform current default configurations across several error metrics for core output variables when measured against observational data. In climate simulations for the end of this century the new, adaptive stomatal conductance scheme provides a revised prognosis for average and extreme temperatures over several large regions, with increased primary productivity through central and east Asia, and higher rainfall through North Africa and the Middle East. The new projections also reveal more frequent heatwaves than originally estimated for the south-eastern US and sub-Saharan Africa but less frequent heatwaves across east Europe and northeast Asia. These developments have implications for evaluating food security and risks from extreme temperatures in areas that are vulnerable to climate change.

Emergent constraint on equilibrium climate sensitivity from global temperature variability.

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the 'likely' range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC 'likely' range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2.

Uncertainties in the response of vegetation to rising atmospheric CO2 concentrations contribute to the large spread in projections of future climate change. Climate-carbon cycle models generally agree that elevated atmospheric CO2 concentrations will enhance terrestrial gross primary productivity (GPP). However, the magnitude of this CO2 fertilization effect varies from a 20 per cent to a 60 per cent increase in GPP for a doubling of atmospheric CO2 concentrations in model studies. Here we demonstrate emergent constraints on large-scale CO2 fertilization using observed changes in the amplitude of the atmospheric CO2 seasonal cycle that are thought to be the result of increasing terrestrial GPP. Our comparison of atmospheric CO2 measurements from Point Barrow in Alaska and Cape Kumukahi in Hawaii with historical simulations of the latest climate-carbon cycle models demonstrates that the increase in the amplitude of the CO2 seasonal cycle at both measurement sites is consistent with increasing annual mean GPP, driven in part by climate warming, but with differences in CO2 fertilization controlling the spread among the model trends. As a result, the relationship between the amplitude of the CO2 seasonal cycle and the magnitude of CO2 fertilization of GPP is almost linear across the entire ensemble of models. When combined with the observed trends in the seasonal CO2 amplitude, these relationships lead to consistent emergent constraints on the CO2 fertilization of GPP. Overall, we estimate a GPP increase of 37 ± 9 per cent for high-latitude ecosystems and 32 ± 9 per cent for extratropical ecosystems under a doubling of atmospheric CO2 concentrations on the basis of the Point Barrow and Cape Kumukahi records, respectively.

Stomatal optimization based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate.

Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate. We developed an analytical stomatal optimization model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf- and ecosystem-level observations. SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem-level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root-mean-square error in GPP by up to 45% in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites. SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors.

No increase in global temperature variability despite changing regional patterns.

Evidence from Greenland ice cores shows that year-to-year temperature variability was probably higher in some past cold periods, but there is considerable interest in determining whether global warming is increasing climate variability at present. This interest is motivated by an understanding that increased variability and resulting extreme weather conditions may be more difficult for society to adapt to than altered mean conditions. So far, however, in spite of suggestions of increased variability, there is considerable uncertainty as to whether it is occurring. Here we show that although fluctuations in annual temperature have indeed shown substantial geographical variation over the past few decades, the time-evolving standard deviation of globally averaged temperature anomalies has been stable. A feature of the changes has been a tendency for many regions of low variability to experience increases, which might contribute to the perception of increased climate volatility. The normalization of temperature anomalies creates the impression of larger relative overall increases, but our use of absolute values, which we argue is a more appropriate approach, reveals little change. Regionally, greater year-to-year changes recently occurred in much of North America and Europe. Many climate models predict that total variability will ultimately decrease under high greenhouse gas concentrations, possibly associated with reductions in sea-ice cover. Our findings contradict the view that a warming world will automatically be one of more overall climatic variation.

Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability.

The release of carbon from tropical forests may exacerbate future climate change, but the magnitude of the effect in climate models remains uncertain. Coupled climate-carbon-cycle models generally agree that carbon storage on land will increase as a result of the simultaneous enhancement of plant photosynthesis and water use efficiency under higher atmospheric CO(2) concentrations, but will decrease owing to higher soil and plant respiration rates associated with warming temperatures. At present, the balance between these effects varies markedly among coupled climate-carbon-cycle models, leading to a range of 330 gigatonnes in the projected change in the amount of carbon stored on tropical land by 2100. Explanations for this large uncertainty include differences in the predicted change in rainfall in Amazonia and variations in the responses of alternative vegetation models to warming. Here we identify an emergent linear relationship, across an ensemble of models, between the sensitivity of tropical land carbon storage to warming and the sensitivity of the annual growth rate of atmospheric CO(2) to tropical temperature anomalies. Combined with contemporary observations of atmospheric CO(2) concentration and tropical temperature, this relationship provides a tight constraint on the sensitivity of tropical land carbon to climate change. We estimate that over tropical land from latitude 30° north to 30° south, warming alone will release 53 ± 17 gigatonnes of carbon per kelvin. Compared with the unconstrained ensemble of climate-carbon-cycle projections, this indicates a much lower risk of Amazon forest dieback under CO(2)-induced climate change if CO(2) fertilization effects are as large as suggested by current models. Our study, however, also implies greater certainty that carbon will be lost from tropical land if warming arises from reductions in aerosols or increases in other greenhouse gases.

Large sensitivity in land carbon storage due to geographical and temporal variation in the thermal response of photosynthetic capacity.

Plant temperature responses vary geographically, reflecting thermally contrasting habitats and long-term species adaptations to their climate of origin. Plants also can acclimate to fast temporal changes in temperature regime to mitigate stress. Although plant photosynthetic responses are known to acclimate to temperature, many global models used to predict future vegetation and climate-carbon interactions do not include this process. We quantify the global and regional impacts of biogeographical variability and thermal acclimation of temperature response of photosynthetic capacity on the terrestrial carbon (C) cycle between 1860 and 2100 within a coupled climate-carbon cycle model, that emulates 22 global climate models. Results indicate that inclusion of biogeographical variation in photosynthetic temperature response is most important for present-day and future C uptake, with increasing importance of thermal acclimation under future warming. Accounting for both effects narrows the range of predictions of the simulated global land C storage in 2100 across climate projections (29% and 43% globally and in the tropics, respectively). Contrary to earlier studies, our results suggest that thermal acclimation of photosynthetic capacity makes tropical and temperate C less vulnerable to warming, but reduces the warming-induced C uptake in the boreal region under elevated CO2 .

Impact of changes in diffuse radiation on the global land carbon sink.

Plant photosynthesis tends to increase with irradiance. However, recent theoretical and observational studies have demonstrated that photosynthesis is also more efficient under diffuse light conditions. Changes in cloud cover or atmospheric aerosol loadings, arising from either volcanic or anthropogenic emissions, alter both the total photosynthetically active radiation reaching the surface and the fraction of this radiation that is diffuse, with uncertain overall effects on global plant productivity and the land carbon sink. Here we estimate the impact of variations in diffuse fraction on the land carbon sink using a global model modified to account for the effects of variations in both direct and diffuse radiation on canopy photosynthesis. We estimate that variations in diffuse fraction, associated largely with the 'global dimming' period, enhanced the land carbon sink by approximately one-quarter between 1960 and 1999. However, under a climate mitigation scenario for the twenty-first century in which sulphate aerosols decline before atmospheric CO(2) is stabilized, this 'diffuse-radiation' fertilization effect declines rapidly to near zero by the end of the twenty-first century.

Increasing risk of Amazonian drought due to decreasing aerosol pollution.

The Amazon rainforest plays a crucial role in the climate system, helping to drive atmospheric circulations in the tropics by absorbing energy and recycling about half of the rainfall that falls on it. This region (Amazonia) is also estimated to contain about one-tenth of the total carbon stored in land ecosystems, and to account for one-tenth of global, net primary productivity. The resilience of the forest to the combined pressures of deforestation and global warming is therefore of great concern, especially as some general circulation models (GCMs) predict a severe drying of Amazonia in the twenty-first century. Here we analyse these climate projections with reference to the 2005 drought in western Amazonia, which was associated with unusually warm North Atlantic sea surface temperatures (SSTs). We show that reduction of dry-season (July-October) rainfall in western Amazonia correlates well with an index of the north-south SST gradient across the equatorial Atlantic (the 'Atlantic N-S gradient'). Our climate model is unusual among current GCMs in that it is able to reproduce this relationship and also the observed twentieth-century multidecadal variability in the Atlantic N-S gradient, provided that the effects of aerosols are included in the model. Simulations for the twenty-first century using the same model show a strong tendency for the SST conditions associated with the 2005 drought to become much more common, owing to continuing reductions in reflective aerosol pollution in the Northern Hemisphere.

Emergent constraints on carbon budgets as a function of global warming.

Earth System Models (ESMs) continue to diagnose a wide range of carbon budgets for each level of global warming. Here, we present emergent constraints on the carbon budget as a function of global warming, which combine the available ESM historical simulations and future projections for a range of scenarios, with observational estimates of global warming and anthropogenic CO2 emissions to the present day. We estimate mean and likely ranges for cumulative carbon budgets for the Paris targets of 1.5 °C and 2 °C of global warming of 812 [691, 933] PgC and 1048 [881, 1216] PgC, which are more than 10% larger than the ensemble mean values from the CMIP6 models. The linearity between cumulative emissions and global warming is found to be maintained at least until 4 °C, and is consistent with an effective Transient Climate Response to Emissions (eTCRE) of 2.1 [1.8, 2.6] °C/1000PgC, from a global warming of 1.2 °C onwards.

Projected increase in continental runoff due to plant responses to increasing carbon dioxide.

In addition to influencing climatic conditions directly through radiative forcing, increasing carbon dioxide concentration influences the climate system through its effects on plant physiology. Plant stomata generally open less widely under increased carbon dioxide concentration, which reduces transpiration and thus leaves more water at the land surface. This driver of change in the climate system, which we term 'physiological forcing', has been detected in observational records of increasing average continental runoff over the twentieth century. Here we use an ensemble of experiments with a global climate model that includes a vegetation component to assess the contribution of physiological forcing to future changes in continental runoff, in the context of uncertainties in future precipitation. We find that the physiological effect of doubled carbon dioxide concentrations on plant transpiration increases simulated global mean runoff by 6 per cent relative to pre-industrial levels; an increase that is comparable to that simulated in response to radiatively forced climate change (11 +/- 6 per cent). Assessments of the effect of increasing carbon dioxide concentrations on the hydrological cycle that only consider radiative forcing will therefore tend to underestimate future increases in runoff and overestimate decreases. This suggests that freshwater resources may be less limited than previously assumed under scenarios of future global warming, although there is still an increased risk of drought. Moreover, our results highlight that the practice of assessing the climate-forcing potential of all greenhouse gases in terms of their radiative forcing potential relative to carbon dioxide does not accurately reflect the relative effects of different greenhouse gases on freshwater resources.

Modelling the impact of forest management and CO2-fertilisation on growth and demography in a Sitka spruce plantation.

Afforestation and reforestation to meet 'Net Zero' emissions targets are considered a necessary policy by many countries. Their potential benefits are usually assessed through forest carbon and growth models. The implementation of vegetation demography gives scope to represent forest management and other size-dependent processes within land surface models (LSMs). In this paper, we evaluate the impact of including management within an LSM that represents demography, using both in-situ and reanalysis climate drivers at a mature, upland Sitka spruce plantation in Northumberland, UK. We compare historical simulations with fixed and variable CO2 concentrations, and with and without tree thinning implemented. Simulations are evaluated against the observed vegetation structure and carbon fluxes. Including thinning and the impact of increasing CO2 concentration ('CO2 fertilisation') gave more realistic estimates of stand-structure and physical characteristics. Historical CO2 fertilisation had a noticeable effect on the Gross Primary Productivity seasonal-diurnal cycle and contributed to approximately 7% higher stand biomass by 2018. The net effect of both processes resulted in a decrease of tree density and biomass, but an increase in tree height and leaf area index.

Strong present-day aerosol cooling implies a hot future.

Atmospheric aerosols counteract the warming effects of anthropogenic greenhouse gases by an uncertain, but potentially large, amount. This in turn leads to large uncertainties in the sensitivity of climate to human perturbations, and therefore also in carbon cycle feedbacks and projections of climate change. In the future, aerosol cooling is expected to decline relative to greenhouse gas forcing, because of the aerosols' much shorter lifetime and the pursuit of a cleaner atmosphere. Strong aerosol cooling in the past and present would then imply that future global warming may proceed at or even above the upper extreme of the range projected by the Intergovernmental Panel on Climate Change.

Development of probability density functions for future South American rainfall.

*We estimate probability density functions (PDFs) for future rainfall in five regions of South America, by weighting the predictions of the 24 Coupled Model Intercomparison Archive Project 3 (CMIP3) General Circulation Models (GCMs). The models are rated according to their relative abilities to reproduce the inter-annual variability in seasonal rainfall. *The relative weighting of the climate models is updated sequentially according to Bayes' theorem, based on the biases in the mean of the predicted time-series and the distributional fit of the bias-corrected time-series. *Depending on the season and the region, we find very different rankings of the GCMs, with no single model doing well in all cases. However, in some regions and seasons, differential weighting of the models leads to significant shifts in the derived rainfall PDFs. *Using a combination of the relative model weightings for each season we have also derived a set of overall model weightings for each region that can be used to produce PDFs of forest biomass from the simulations of the Lund-Potsdam-Jena Dynamic Global Vegetation Model for managed land (LPJmL).

A spatial emergent constraint on the sensitivity of soil carbon turnover to global warming.

Carbon cycle feedbacks represent large uncertainties in climate change projections, and the response of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil carbon depend on changes in litter and root inputs from plants and especially on reductions in the turnover time of soil carbon (τs) with warming. An approximation to the latter term for the top one metre of soil (ΔCs,τ) can be diagnosed from projections made with the CMIP6 and CMIP5 Earth System Models (ESMs), and is found to span a large range even at 2 °C of global warming (-196 ± 117 PgC). Here, we present a constraint on ΔCs,τ, which makes use of current heterotrophic respiration and the spatial variability of τs inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in ΔCs,τ at 2 °C to -232 ± 52 PgC.

Emergent Constraints on Climate-Carbon Cycle Feedbacks.

PURPOSE OF REVIEW: Feedbacks between CO2-induced climate change and the carbon cycle are now routinely represented in the Earth System Models (ESMs) that are used to make projections of future climate change. The inconclusion of climate-carbon cycle feedbacks in climate projections is an important advance, but has added a significant new source of uncertainty. This review assesses the potential for emergent constraints to reduce the uncertainties associated with climate-carbon cycle feedbacks. RECENT FINDINGS: The emergent constraint technique involves using the full ensemble of models to find an across-ensemble relationship between an observable feature of the Earth System (such as a trend, interannual variation or change in seasonality) and an uncertain aspect of the future. Examples focussing on reducing uncertainties in future atmospheric CO2 concentration, carbon loss from tropical land under warming and CO2 fertilization of mid- and high-latitude photosynthesis are exemplars of these different types of emergent constraints. SUMMARY: The power of emergent constraints is that they use the enduring range in model projections to reduce uncertainty in the future of the real Earth System, but there are also risks that indiscriminate data-mining, and systematic model errors could yield misleading constraints. A hypothesis-driven theory-led approach can overcome these risks and also reveal the true promise of emergent constraints-not just as ways to reduce uncertainty in future climate change but also to catalyse advances in our understanding of the Earth System.