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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.

We review how the international modelling community, encompassing integrated assessment models, global and regional Earth system and climate models, and impact models, has worked together over the past few decades to advance understanding of Earth system change and its impacts on society and the environment and thereby support international climate policy. We go on to recommend a number of priority research areas for the coming decade, a timescale that encompasses a number of newly starting international modelling activities, as well as the IPCC Seventh Assessment Report (AR7) and the second UNFCCC Global Stocktake. Progress in these priority areas will significantly advance our understanding of Earth system change and its impacts, increasing the quality and utility of science support to climate policy. We emphasize the need for continued improvement in our understanding of, and ability to simulate, the coupled Earth system and the impacts of Earth system change. There is an urgent need to investigate plausible pathways and emission scenarios that realize the Paris climate targets – for example, pathways that overshoot 1.5 or 2 °C global warming, before returning to these levels at some later date. Earth system models need to be capable of thoroughly assessing such warming overshoots – in particular, the efficacy of mitigation measures, such as negative CO2 emissions, in reducing atmospheric CO2 and driving global cooling. An improved assessment of the long-term consequences of stabilizing climate at 1.5 or 2 °C above pre-industrial temperatures is also required. We recommend Earth system models run overshoot scenarios in CO2-emission mode to more fully represent coupled climate–carbon-cycle feedbacks and, wherever possible, interactively simulate other key Earth system phenomena at risk of rapid change during overshoot. Regional downscaling and impact models should use forcing data from these simulations, so impact and regional climate projections cover a more comp

Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient–phytoplankton–zooplankton–detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of lo

Anthropogenic aerosols in the atmosphere have the potential to affect regional-scale land hydrology through solar dimming1, 2. Increased aerosol loading may have reduced historical surface evaporation over some locations3, but the magnitude and extent of this effect is uncertain. Any reduction in evaporation due to historical solar dimming may have resulted in an increase in river flow. Here we formally detect and quantify the historical effect of changing aerosol concentrations, via solar radiation, on observed river flow over the heavily industrialized, northern extra-tropics. We use a state-of-the-art estimate of twentieth century surface meteorology4 as input data for a detailed land surface model5, and show that the simulations capture the observed strong inter-annual variability in runoff in response to climatic fluctuations. Using statistical techniques, we identify a detectable aerosol signal in the observed river flow both over the combined region, and over individual river basins in Europe and North America. We estimate that solar dimming due to rising aerosol concentrations in the atmosphere around 1980 led to an increase in river runoff by up to 25% in the most heavily polluted regions in Europe. We propose that, conversely, these regions may experience reduced freshwater availability in the future, as air quality improvements are set to lower aerosol loading and solar dimming.

Many atmospheric constituents besides carbon dioxide (CO2) contribute to global warming, and it is common to compare their influence on climate in terms of radiative forcing, which measures their impact on the planetary energy budget. A number of recent studies have shown that many radiatively active constituents also have important impacts on the physiological functioning of ecosystems, and thus the ‘ecosystem services’ that humankind relies upon. CO2 increases have most probably increased river runoff and had generally positive impacts on plant growth where nutrients are non-limiting, whereas increases in near-surface ozone (O3) are very detrimental to plant productivity. Atmospheric aerosols increase the fraction of surface diffuse light, which is beneficial for plant growth. To illustrate these differences, we present the impact on net primary productivity and runoff of higher CO2, higher near-surface O3, and lower sulphate aerosols, and for equivalent changes in radiative forcing. We compare this with the impact of climate change alone, arising, for example, from a physiologically inactive gas such as methane (CH4). For equivalent levels of change in radiative forcing, we show that the combined climate and physiological impacts of these individual agents vary markedly and in some cases actually differ in sign. This study highlights the need to develop more informative metrics of the impact of changing atmospheric constituents that go beyond simple radiative forcing.

This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both worldleading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very highprofile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

A decrease in total solar radiation (Liepert, 2002, Stanhill and Cohen, 2001, Wild et al., 2005) has been observed at the earth surface over the 1950-1990 period, called solar dimming. Such dimming gradually started to transform into brightening in some regions of the world since the late 1980s (Wild et al. 2005). Both dimming and brightening are likely to be linked to an increase and decrease in cloud cover and scattering and absorption of light by tropospheric and stratospheric aerosols respectively (Kvalevag and Myhre, 2007). Theoretical and observational studies have shown that plant photosynthesis of forest and crop ecosystems is more efficient under diffuse light conditions (Gu et al., 2003, Niyogi et al., 2004, Oliveira et al., 2007, Roderick et al., 2001). However, this effect has not yet been accounted for in global carbon cycle simulations because such models lack the mechanism that includes the diffuse irradiance effects on photosynthesis. The aim of this study is to estimate the impact of changes in radiation during the 1900-2100 period on land productivity and carbon storage. We use a offline version of the land surface scheme of the Hadley centre model (Mercado et al., 2007) which has been modified to account for variations of direct and diffuse radiation on sunlit and shaded canopy photosynthesis. Additionally, we use short wave and photosynthetic active radiation fields reconstructed from the Hadley centre climate model which takes into account the scattering and absorption of light by tropospheric and stratospheric aerosols. We describe the simulation of the land carbon cycle through the dimming-brightening periods, and diagnose the impact that changes in diffuse radiation had on the land carbon sink. We also discuss the implications of these results for the future land carbon-sink, under likely changes in the atmospheric aerosol loading.

The amount of solar radiation reaching the earth surface is one of the major drivers of plant photosynthesis and therefore changes in radiation are likely to indirectly have an effect on the terrestrial carbon cycle. For example, changes in surface radiation that lead to increasing diffuse surface irradiance are reported to enhance plant photosynthesis (Gu et al., 2003, Niyogi et al., 2004, Oliveira et al., 2007, Roderick et al., 2001). Solar radiation reaching the land surface has changed over the industrial era due to aerosols emitted from volcanoes and various anthropogenic sources (Kvalevag and Myhre, 2007). Such changes in total surface radiation are accompanied by changes in direct and diffuse surface solar radiation. Recent major volcanic events include the eruptions of el Chichón in 1986 and Mount Pinatubo in 1991. In this study we estimate the impact of changes in surface radiation on photosynthetic carbon uptake during the Post Pinatubo period. We use an offline version of the Hadley Centre land surface scheme (Mercado et al., 2007) modified to account for variations in direct and diffuse radiation on sunlit and shaded canopy photosynthesis. We use meteorological forcing from the Climate Research Unit Data set. Additionally short wave and photosynthetic active radiation are reconstructed from the Hadley centre climate model, which accounts for the scattering and absorption of light by tropospheric and stratospheric aerosols. We describe the development of the land carbon cycle through the Pinatubo event and diagnose the impact of changes in diffuse radiation on the atmospheric [CO2] growth-rate.

The evolution of the Earth's climate over the twenty-first century depends on the rate at which anthropogenic carbon dioxide emissions are removed from the atmosphere by the ocean and land carbon cycles1. Coupled climate–carbon cycle models suggest that global warming will act to limit the land-carbon sink2, but these first generation models neglected the impacts of changing atmospheric chemistry. Emissions associated with fossil fuel and biomass burning have acted to approximately double the global mean tropospheric ozone concentration3, and further increases are expected over the twenty-first century4. Tropospheric ozone is known to damage plants, reducing plant primary productivity and crop yields5, yet increasing atmospheric carbon dioxide concentrations are thought to stimulate plant primary productivity6. Increased carbon dioxide and ozone levels can both lead to stomatal closure, which reduces the uptake of either gas, and in turn limits the damaging effect of ozone and the carbon dioxide fertilization of photosynthesis6. Here we estimate the impact of projected changes in ozone levels on the land-carbon sink, using a global land carbon cycle model modified to include the effect of ozone deposition on photosynthesis and to account for interactions between ozone and carbon dioxide through stomatal closure7. For a range of sensitivity parameters based on manipulative field experiments, we find a significant suppression of the global land-carbon sink as increases in ozone concentrations affect plant productivity. In consequence, more carbon dioxide accumulates in the atmosphere. We suggest that the resulting indirect radiative forcing by ozone effects on plants could contribute more to global warming than the direct radiative forcing due to tropospheric ozone increases.

Twenty-one land surface schemes (LSSs) performed simulations forced by 18 yr of observed meteorological data from a grassland catchment at Valdai, Russia, as part of the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS) Phase 2(d). In this paper the authors examine the simulation of snow. In comparison with observations, the models are able to capture the broad features of the snow regime on both an intra-and interannual basis. However, weaknesses in the simulations exist, and early season ablation events are a significant source of model scatter. Over the 18-yr simulation, systematic differences between the models' snow simulations are evident and reveal specific aspects of snow model parameterization and design as being responsible. Vapor exchange at the snow surface varies widely among the models, ranging from a large net loss to a small net source for the snow season. Snow albedo, fractional snow cover, and their interplay have a large effect on energy available for ablation, with differences among models most evident at low snow depths. The incorporation of the snowpack within an LSS structure affects the method by which snow accesses, as well as utilizes, available energy for ablation. The sensitivity of some models to longwave radiation, the dominant winter radiative flux, is partly due to a stability-induced feedback and the differing abilities of models to exchange turbulent energy with the atmosphere. Results presented in this paper suggest where weaknesses in macroscale snow modeling lie and where both theoretical and observational work should be focused to address these weaknesses.

The continued increase in the atmospheric concentration of carbon dioxide due to anthropogenic emissions is predicted to lead to significant changes in climate. About half of the current emissions are being absorbed by the ocean and by land ecosystems, but this absorption is sensitive to climate as well as to atmospheric carbon dioxide concentrations, creating a feedback loop. General circulation models have generally excluded the feedback between climate and the biosphere, using static vegetation distributions and CO2 concentrations from simple carbon-cycle models that do not include climate change. Here we present results from a fully coupled, three-dimensional carbon–climate model, indicating that carbon-cycle feedbacks could significantly accelerate climate change over the twenty-first century. We find that under a 'business as usual' scenario, the terrestrial biosphere acts as an overall carbon sink until about 2050, but turns into a source thereafter. By 2100, the ocean uptake rate of 5 Gt C yr-1 is balanced by the terrestrial carbon source, and atmospheric CO2 concentrations are 250 p.p.m.v. higher in our fully coupled simulation than in uncoupled carbon models, resulting in a global-mean warming of 5.5 K, as compared to 4 K without the carbon-cycle feedback.