Abstract. Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing withPublished by Copernicus Publications on behalf of the European Geosciences Union. observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.

The growth of the Tibetan Plateau throughout the past 66 million years has profoundly affected the Asian climate, but how this unparalleled orogenesis might have driven vegetation and plant diversity changes in eastern Asia is poorly understood. We approach this question by integrating modeling results and fossil data. We show that growth of north and northeastern Tibet affects vegetation and, crucially, plant diversity in eastern Asia by altering the monsoon system. This northern Tibetan orographic change induces a precipitation increase, especially in the dry (winter) season, resulting in a transition from deciduous broadleaf vegetation to evergreen broadleaf vegetation and plant diversity increases across southeastern Asia. Further quantifying the complexity of Tibetan orographic change is critical for understanding the finer details of Asian vegetation and plant diversity evolution.

Abstract. The nitrogen cycle and its effect on carbon uptake in the terrestrial biosphere is a recent progression in earth system models. As with any new component of a model, it is important to understand the behaviour, strengths, and limitations of the various process representations. Here we assess and compare five models with nitrogen cycles that will be used as the terrestrial components of some of the earth system models in CMIP6. We use a historical control simulation and two perturbations to assess the models' nitrogen-related performance: a simulation with atmospheric carbon dioxide 200 ppm higher, and one with nitrogen deposition increased by 50 kg N ha−1 yr−1. We find that, despite differing nitrogen cycle representations, all models simulate recent global trends in terrestrial productivity and net carbon uptake commensurate with observations. The between-model variation is likely more influenced by other, non-nitrogen parts of the models. Globally, the productivity response to increased carbon dioxide is commensurate with observations for four of the five models, but highly spatially variable within and between models. The productivity response to increased nitrogen is significantly lower than observed in two of the five models. The global and tropical values are generally better represented than boreal, tundra, or other high latitude areas. These results are due to divergent though valid choices in the representation of key processes. They show the need for better understanding and more provision of observational constraints of nitrogen processes, especially nitrogen-use efficiency and biological nitrogen fixation.

Biological nitrogen fixation is a key contributor to sustaining the terrestrial carbon cycle, providing nitrogen input that plants require. However, the amount and global distribution of this fixation is highly disputed. Using a comprehensive meta‐analysis of field measurements, we make a new assessment of global biological nitrogen fixation (BNF). We assessed the relationship between BNF in natural terrestrial environments and empirical predictors of BNF commonly used in terrestrial ecosystem and earth system models. We found no evidence for any statistically significant relationship between BNF and evapotranspiration and net or gross primary terrestrial productivity. We assessed the relationship between BNF and 11 other climate variables and soil properties at a global scale. We found that all the variables we considered had little predictive power for BNF. Using averaged biome values upscaled we calculated the median global inputs of BNF in natural ecosystems as 88 Tg N year−1. The range (52–130 Tg N year−1) encompasses most recent estimates and broadly agrees with recent independent top‐down estimates of BNF. The global values indicate a significant role for free living, as opposed to symbiotic, BNF, accounting for at least a third of all BNF. This work provides a new global benchmark and spatial distribution data set of BNF using a bottom‐up methodology.

Abstract. The nitrogen cycle and its effect on carbon uptake in the terrestrial biosphere is a recent progression in earth system models. As with any new component of a model, it is important to understand the behaviour, strengths, and limitations of the various process representations. Here we assess and compare five land surface models with nitrogen cycles that are used as the terrestrial components of some of the earth system models in CMIP6. The land surface models were run offline with a common spin-up and forcing protocol. We use a historical control simulation and two perturbations to assess the model nitrogen-related performances: a simulation with atmospheric carbon dioxide increased by 200 ppm and one with nitrogen deposition increased by 50 kgN ha−1 yr−1. There is generally greater variability in productivity response between models to increased nitrogen than to carbon dioxide. Across the five models the response to carbon dioxide globally was 5 % to 20 % and the response to nitrogen was 2 % to 24 %. The models are not evenly distributed within the ensemble range, with two of the models having low productivity response to nitrogen and another one with low response to elevated atmospheric carbon dioxide, compared to the other models. In all five models individual grid cells tend to exhibit bimodality, with either a strong response to increased nitrogen or atmospheric carbon dioxide but rarely to both to an equal extent. However, this local effect does not scale to either the regional or global level. The global and tropical responses are generally more accurately modelled than boreal, tundra, or other high-latitude areas compared to observations. These results are due to divergent choices in the representation of key nitrogen cycle processes. They show the need for more observational studies to enhance understanding of nitrogen cycle processes, especially nitrogen-use efficiency and biological nitrogen fixation.

Abstract. Understanding future changes in the terrestrial carbon cycle is important for reliable projections of climate change and impacts on ecosystems. It is known that nitrogen could limit plants' response to increased atmospheric carbon dioxide and is therefore important to include in Earth System Models. Here we present the implementation of the terrestrial nitrogen cycle in the JULES land surface model (JULES-CN). Two versions are discussed – the one implemented within the UK Earth System Model (UKESM1) which has a bulk soil biogeochemical model and a development version which resolves the soil biogeochemistry with depth. The nitrogen cycle is based on the existing carbon cycle in the model. It represents all the key terrestrial nitrogen processes in an efficient way. Biological fixation and nitrogen deposition are external inputs, and loss occurs via leaching and a bulk gas loss parameterisation. Nutrient limitation reduces carbon-use efficiency (CUE – ratio of net to gross primary productivity) and can slow soil decomposition. We show that ecosystem level limitation of net primary productivity by nitrogen is consistent with observational estimates and that simulated carbon and nitrogen pools and fluxes are comparable to the limited available observations. The impact of N limitation is most pronounced in northern mid-latitudes. The introduction of a nitrogen cycle improves the representation of interannual variability of global net ecosystem exchange which was much too pronounced in the carbon cycle only versions of JULES (JULES-C). It also reduces the CUE and alters its response over the twentieth century and limits the CO2-fertilisation effect, such that the simulated current day land carbon sink is reduced by about 0.5 Pg C yr−1. The inclusion of a prognostic land nitrogen scheme marks a step forward in functionality and realism for the JULES and UKESM models.

Climate change is projected to cause substantial alterations in vegetation distribution, but these have been given little attention in comparison to land use in the Representative Concentration Pathway (RCP) scenarios. Here we assess the climate-induced land cover changes (CILCC) in the RCPs and compare them to land use land cover change (LULCC). To do this, we use an ensemble of simulations with and without LULCC in Earth System Model HadGEM2-ES (Hadley Centre Global Environmental Model 2) -for RCP2.6, RCP4.5, and RCP8.5. We find that climate change causes an expansion poleward of vegetation that affects more land area than LULCC in all of the RCPs considered here. The terrestrial carbon changes from CILCC are also larger than for LULCC. When considering only forest, the LULCC is larger, but the CILCC is highly variable with the overall radiative forcing of the scenario. The CILCC forest increase compensates 90% of the global anthropogenic deforestation by 2100 in RCP8.5 but just 3% in RCP2.6. Overall, bigger land cover changes tend to originate from LULCC in the shorter term or lower radiative forcing scenarios and from CILCC in the longer term and higher radiative forcing scenarios. The extent to which CILCC could compensate for LULCC raises difficult questions regarding global forest and biodiversity offsetting, especially at different time scales. This research shows the importance of considering the relative size of CILCC to LULCC, especially with regard to the ecological effects of the different RCPs.

Future land use change (LUC) is an important component of the IPCC representative concentration pathways (RCPs), but in these scenarios' radiative forcing targets the climate impact of LUC only includes greenhouse gases. However, climate effects due to physical changes of the land surface can be as large. Here we show the critical importance of including non-carbon impacts of LUC when considering the RCPs. Using an ensemble of climate model simulations with and without LUC, we show that the net climate effect is very different from the carbon-only effect. Despite opposite signs of LUC, all the RCPs assessed here have a small net warming from LUC because of varying biogeophysical effects, and in RCP4.5 the warming is outside of the expected variability. The afforestation in RCP4.5 decreases surface albedo, making the net global temperature anomaly over land around five times larger than RCPs 2.6 and 8.5, for around twice the amount of LUC. Consequent changes to circulation in RCP4.5 in turn reduce Arctic sea ice cover. The small net positive temperature effect from LUC could make RCP4.5's universal carbon tax, which incentivizes retaining and growing forest, counter productive with respect to climate. However, there are spatial differences in the balance of impacts, and potential climate gains would need to be assessed against other environmental aims.