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Drought is predicted to increase in the future due to climate change, bringing with it a myriad of impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance, in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local/regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales, and evaluated ten different representations of stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high latitudes/cold region sites, while LE was best simulated in temperate and high latitude/cold sites. Errors not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savannah and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14, and the soil depth from 3m to 10.8m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation, when the onset of stress was delayed, and when roots extended deeper into the soil. For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and made the simulation worse. Further evaluation into the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We describe developments to a land surface model, allowing for flexible user-prescribed harvest regimes of various perennial bioenergy crops or natural vegetation types. Our aim is to integrate the most useful aspects of dedicated bioenergy models into dynamic global vegetation models, in order that assessment of bioenergy options can benefit from state-of-the-art Earth system modelling. A new plant functional type (PFT) representing Miscanthus is also presented. The Miscanthus PFT fits well with growth parameters observed at a site in Lincolnshire, UK; however, global observed yields of Miscanthus are far more variable than is captured by the model, suggesting missing model components that influence growth and yields. Global expansion of bioenergy crop areas under a 2 °C emissions scenario and balanced greenhouse gas mitigation strategy from the IMAGE integrated assessment model (RCP2.6-SSP2) achieves a mean yield of 4.3 billion tonnes dry matter per year over 2040-2099, around 30 % higher than the biomass availability projected by IMAGE. In addition to perennial grasses, JULES-BE can also be used to represent short-rotation coppicing; residue harvesting from cropland or forestry; and rotation forestry. [ABSTRACT FROM AUTHOR]

We present the latest global land configuration of the Joint UK Land Environment Simulator (JULES) model as used in the latest international coupled model intercomparison project (CMIP6). The configuration is defined by the combination of switches, parameter values and ancillary data, which we provide alongside a set of historical forcing data that defines the experimental setup. In addition, we provide a standardised modelling system that runs on the NERC JASMIN cluster accessible to all with links to JULES. This is provided so that users can test and evaluate their own science against the standard configuration to promote community engagement in the development of land surface modelling capability through JULES. It is intended that JULES configurations should be independent of the underlying code base and thus they will be available at the latest release of the JULES code. This means that different code releases will produce scientifically comparable results for a given configuration version. Versioning is therefore determined by the configuration as opposed to the underlying code base. [ABSTRACT FROM AUTHOR]

The First ISLSCP Field Experiment (FIFE), Kansas, US, 1987--1989, made important contributions to the understanding of energy and CO2 exchanges between the land-surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Thirty years on, we demonstrate how the wealth of data collected at FIFE and its subsequent in-depth analysis in the literature continues to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating "unstressed" vegetation parameters and thresholds for water stress. In particular, the response to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES. [ABSTRACT FROM AUTHOR]

Dynamic global vegetation models (DGVMs) are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES (the Joint UK Land Environment Simulator) represents the land surface in the Hadley Centre climate models and in the UK Earth System Model. Recently the number of plant functional types (PFTs) in JULES were expanded from 5 to 9 to better represent functional diversity in global ecosystems. Here we introduce a more mechanistic representation of vegetation dynamics in TRIFFID, the dynamic vegetation component of JULES, that allows for any number of PFTs to compete based solely on their height, removing the previous hardwired dominance hierarchy where dominant types are assumed to outcompete subdominant types. With the new set of 9 PFTs, JULES is able to more accurately reproduce global vegetation distribution compared to the former 5 PFT version. Improvements include the coverage of trees within tropical and boreal forests, and a reduction in shrubs, which dominated at high latitudes. We show that JULES is able to realistically represent several aspects of the global carbon cycle. The simulated gross primary productivity (GPP) is within the range of observations, but simulated net primary productivity (NPP) is slightly too high. GPP in JULES from 1982-2011 was 133PgCyr-1, compared to observation-based estimates between 123±8 (over the same time period) and 150-175PgCyr-1. NPP from 2000-2013 was 72PgCyr-1, compared to satellite-derived NPP of 55PgCyr-1 over the same period and independent estimates of 56.2±14.3PgCyr-1. The simulated carbon stored in vegetation is 542PgC, compared to an observation-based range of 400-600PgC. Soil carbon is much lower (1422PgC) than estimates from measurements (>2400PgC), with large underestimations of soil carbon in the tropical and boreal forests. We also examined some aspects of the historical terrestrial carbon sink as simulated by JULES. Between the 1900s and 2000s, increased atmospheric carbon dioxide levels enhanced vegetation productivity and litter inputs into the soils, while land-use change removed vegetation and reduced soil carbon. The result was a simulated increase in soil carbon of 57PgC but a decrease in vegetation carbon by of PgC. JULES simulated a loss of soil and vegetation carbon of 14 and 124PgC, respectively, due to land-use change from 1900-2009. The simulated land carbon sink was 2.0±1.0PgCyr-1 from 2000-2009, in close agreement to estimates from the IPCC and Global Carbon Project. [ABSTRACT FROM AUTHOR]