UK Earth System Model Research Articles

Spin‐up of UK Earth System Model 1 (UKESM1) for CMIP6

AbstractFor simulations intended to study the influence of anthropogenic forcing on climate, temporal stability of the Earth's natural heat, freshwater, and biogeochemical budgets is critical. Achieving such coupled model equilibration is scientifically and computationally challenging. We describe the protocol used to spin‐up the UK Earth system model (UKESM1) with respect to preindustrial forcing for use in the sixth Coupled Model Intercomparison Project (CMIP6). Due to the high computational cost of UKESM1's atmospheric model, especially when running with interactive full chemistry and aerosols, spin‐up primarily used parallel configurations using only ocean/land components. For the ocean, the resulting spin‐up permitted the carbon and heat contents of the ocean's full volume to approach equilibrium over 5,000 years. On land, a spin‐up of 1,000 years brought UKESM1's dynamic vegetation and soil carbon reservoirs toward near‐equilibrium. The end‐states of these parallel ocean‐ and land‐only phases then initialized a multicentennial period of spin‐up with the full Earth system model, prior to this simulation continuing as the UKESM1 CMIP6 preindustrial control (piControl). The realism of the fully coupled spin‐up was assessed for a range of ocean and land properties, as was the degree of equilibration for key variables. Lessons drawn include the importance of consistent interface physics across ocean‐ and land‐only models and the coupled (parent) model, the extreme simulation duration required to approach equilibration targets, and the occurrence of significant regional land carbon drifts despite global‐scale equilibration. Overall, the UKESM1 spin‐up underscores the expense involved and argues in favor of future development of more efficient spin‐up techniques.

Underestimation of Global Photosynthesis in Earth System Models Due to Representation of Vegetation Structure

AbstractThe impact of vegetation structure on the absorption of shortwave radiation in Earth System Models (ESMs) is potentially important for accurate modeling of the carbon cycle and hence climate projections. A proportion of incident shortwave radiation is used by plants to photosynthesize and canopy structure has a direct impact on the fraction of this radiation which is absorbed. This paper evaluates how modeled carbon assimilation of the terrestrial biosphere is impacted when clumping derived from satellite data is incorporated. We evaluated impacts of clumping on photosynthesis using the Joint UK Land Environment Simulator, the land surface scheme of the UK Earth System Model. At the global level, Gross Primary Productivity (GPP) increased by 5.53 ± 1.02 PgC/year with the strongest absolute increase in the tropics. This is contrary to previous studies that have shown a decrease in photosynthesis when similar clumping data sets have been used to modify light interception in models. In our study additional transmission of light through upper canopy layers leads to enhanced absorption in lower layers in which photosynthesis tends to be light limited. We show that this result is related to the complexity of canopy scheme being used.

Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1

AbstractAerosol processes and, in particular, aerosol‐cloud interactions cut across the traditional physical‐Earth system boundary of coupled Earth system models and remain one of the key uncertainties in estimating anthropogenic radiative forcing of climate. Here we calculate the historical aerosol effective radiative forcing (ERF) in the HadGEM3‐GA7 climate model in order to assess the suitability of this model for inclusion in the UK Earth system model, UKESM1. The aerosol ERF, calculated for the year 2000 relative to 1850, is large and negative in the standard GA7 model leading to an unrealistic negative total anthropogenic forcing over the twentieth century. We show how underlying assumptions and missing processes in both the physical model and aerosol parameterizations lead to this large aerosol ERF. A number of model improvements are investigated to assess their impact on the aerosol ERF. These include an improved representation of cloud droplet spectral dispersion, updates to the aerosol activation scheme, and black carbon optical properties. One of the largest contributors to the aerosol forcing uncertainty is insufficient knowledge of the preindustrial aerosol climate. We evaluate the contribution of uncertainties in the natural marine emissions of dimethyl sulfide and organic aerosol to the ERF. The combination of model improvements derived from these studies weakens the aerosol ERF by up to 50% of the original value and leads to a total anthropogenic historical forcing more in line with assessed values.

The Low-Resolution Version of HadGEM3 GC3.1: Development and Evaluation for Global Climate.

A new climate model, HadGEM3 N96ORCA1, is presented that is part of the GC3.1 configuration of HadGEM3. N96ORCA1 has a horizontal resolution of ~135 km in the atmosphere and 1° in the ocean and requires an order of magnitude less computing power than its medium‐resolution counterpart, N216ORCA025, while retaining a high degree of performance traceability. Scientific performance is compared to both observations and the N216ORCA025 model. N96ORCA1 reproduces observed climate mean and variability almost as well as N216ORCA025. Patterns of biases are similar across the two models. In the northwest Atlantic, N96ORCA1 shows a cold surface bias of up to 6 K, typical of ocean models of this resolution. The strength of the Atlantic meridional overturning circulation (16 to 17 Sv) matches observations. In the Southern Ocean, a warm surface bias (up to 2 K) is smaller than in N216ORCA025 and linked to improved ocean circulation. Model El Niño/Southern Oscillation and Atlantic Multidecadal Variability are close to observations. Both the cold bias in the Northern Hemisphere (N96ORCA1) and the warm bias in the Southern Hemisphere (N216ORCA025) develop in the first few decades of the simulations. As in many comparable climate models, simulated interhemispheric gradients of top‐of‐atmosphere radiation are larger than observations suggest, with contributions from both hemispheres. HadGEM3 GC3.1 N96ORCA1 constitutes the physical core of the UK Earth System Model (UKESM1) and will be used extensively in the Coupled Model Intercomparison Project 6 (CMIP6), both as part of the UK Earth System Model and as a stand‐alone coupled climate model.

Vegetation distribution and terrestrial carbon cycle in a carbon cycle configuration of JULES4.6 with new plant functional types

Abstract. 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 was expanded from five to nine 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, which allows for any number of PFTs to compete based solely on their height; therefore, the previous hardwired dominance hierarchy is removed. With the new set of nine PFTs, JULES is able to more accurately reproduce global vegetation distribution compared to the former five PFT version. Improvements include the coverage of trees within tropical and boreal forests and a reduction in shrubs, the latter of which dominated at high latitudes. We show that JULES is able to realistically represent several aspects of the global carbon (C) 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 to 2011 is 133 Pg C yr−1, compared to observation-based estimates (over the same time period) between 123 ± 8 and 150–175 Pg C yr−1. NPP from 2000 to 2013 is 72 Pg C yr−1, compared to satellite-derived NPP of 55 Pg C yr−1 over the same period and independent estimates of 56.2 ± 14.3 Pg C yr−1. The simulated carbon stored in vegetation is 542 Pg C, compared to an observation-based range of 400–600 Pg C. Soil carbon is much lower (1422 Pg C) than estimates from measurements (> 2400 Pg C), 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 is a simulated increase in soil carbon of 57 Pg C but a decrease in vegetation carbon of 98 Pg C. The total simulated loss of soil and vegetation carbon due to land use change is 138 Pg C from 1900 to 2009, compared to a recent observationally constrained estimate of 155 ± 50 Pg C from 1901 to 2012. The simulated land carbon sink is 2.0 ± 1.0 Pg C yr−1 from 2000 to 2009, in close agreement with estimates from the IPCC and Global Carbon Project.

A vertical representation of soil carbon in the JULES land surface scheme (vn4.3_permafrost) with a focus on permafrost regions

Abstract. An improved representation of the carbon cycle in permafrost regions will enable more realistic projections of the future climate–carbon system. Currently JULES (the Joint UK Land Environment Simulator) – the land surface model of the UK Earth System Model (UKESM) – uses the standard four-pool RothC soil carbon model. This paper describes a new version of JULES (vn4.3_permafrost) in which the soil vertical dimension is added to the soil carbon model, with a set of four pools in every soil layer. The respiration rate in each soil layer depends on the temperature and moisture conditions in that layer. Cryoturbation/bioturbation processes, which transfer soil carbon between layers, are represented by diffusive mixing. The litter inputs and the soil respiration are both parametrized to decrease with increasing depth. The model now includes a tracer so that selected soil carbon can be labelled and tracked through a simulation. Simulations show an improvement in the large-scale horizontal and vertical distribution of soil carbon over the standard version of JULES (vn4.3). Like the standard version of JULES, the vertically discretized model is still unable to simulate enough soil carbon in the tundra regions. This is in part because JULES underestimates the plant productivity over the tundra, but also because not all of the processes relevant for the accumulation of permafrost carbon, such as peat development, are included in the model. In comparison with the standard model, the vertically discretized model shows a delay in the onset of soil respiration in the spring, resulting in an increased net uptake of carbon during this time. In order to provide a more suitable representation of permafrost carbon for quantifying the permafrost carbon feedback within UKESM, the deep soil carbon in the permafrost region (below 1 m) was initialized using the observed soil carbon. There is now a slight drift in the soil carbon ( < 0.018 % decade−1), but the change in simulated soil carbon over the 20th century, when there is little climate change, is comparable to the original vertically discretized model and significantly larger than the drift.

Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information

Abstract. Dynamic global vegetation models are used to predict the response of vegetation to climate change. They are essential for planning ecosystem management, understanding carbon cycle–climate feedbacks, and evaluating the potential impacts of climate change on global ecosystems. JULES (the Joint UK Land Environment Simulator) represents terrestrial processes in the UK Hadley Centre family of models and in the first generation UK Earth System Model. Previously, JULES represented five plant functional types (PFTs): broadleaf trees, needle-leaf trees, C3 and C4 grasses, and shrubs. This study addresses three developments in JULES. First, trees and shrubs were split into deciduous and evergreen PFTs to better represent the range of leaf life spans and metabolic capacities that exists in nature. Second, we distinguished between temperate and tropical broadleaf evergreen trees. These first two changes result in a new set of nine PFTs: tropical and temperate broadleaf evergreen trees, broadleaf deciduous trees, needle-leaf evergreen and deciduous trees, C3 and C4 grasses, and evergreen and deciduous shrubs. Third, using data from the TRY database, we updated the relationship between leaf nitrogen and the maximum rate of carboxylation of Rubisco (Vcmax), and updated the leaf turnover and growth rates to include a trade-off between leaf life span and leaf mass per unit area.Overall, the simulation of gross and net primary productivity (GPP and NPP, respectively) is improved with the nine PFTs when compared to FLUXNET sites, a global GPP data set based on FLUXNET, and MODIS NPP. Compared to the standard five PFTs, the new nine PFTs simulate a higher GPP and NPP, with the exception of C3 grasses in cold environments and C4 grasses that were previously over-productive. On a biome scale, GPP is improved for all eight biomes evaluated and NPP is improved for most biomes – the exceptions being the tropical forests, savannahs, and extratropical mixed forests where simulated NPP is too high. With the new PFTs, the global present-day GPP and NPP are 128 and 62 Pg C year−1, respectively. We conclude that the inclusion of trait-based data and the evergreen/deciduous distinction has substantially improved productivity fluxes in JULES, in particular the representation of GPP. These developments increase the realism of JULES, enabling higher confidence in simulations of vegetation dynamics and carbon storage.

IMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

Abstract. 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 low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry–climate interactions.

GO5.0: the joint NERC–Met Office NEMO global ocean model for use in coupled and forced applications

Abstract. We describe a new Global Ocean standard configuration (GO5.0) at eddy-permitting resolution, developed jointly between the National Oceanography Centre and the Met Office as part of the Joint Ocean Modelling Programme (JOMP), a working group of the UK's National Centre for Ocean Forecasting (NCOF) and part of the Joint Weather and Climate Research Programme (JWCRP). The configuration has been developed with the seamless approach to modelling in mind for ocean modelling across timescales and for a range of applications, from short-range ocean forecasting through seasonal forecasting to climate predictions as well as research use. The configuration has been coupled with sea ice (GSI5.0), atmosphere (GA5.0), and land-surface (GL5.0) configurations to form a standard coupled global model (GC1). The GO5.0 model will become the basis for the ocean model component of the Forecasting Ocean Assimilation Model, which provides forced short-range forecasting services. The GC1 or future releases of it will be used in coupled short-range ocean forecasting, seasonal forecasting, decadal prediction and for climate prediction as part of the UK Earth System Model. A 30-year integration of GO5.0, run with CORE2 (Common Ocean-ice Reference Experiments) surface forcing from 1976 to 2005, is described, and the performance of the model in the final 10 years of the integration is evaluated against observations and against a comparable integration of an existing standard configuration, GO1. An additional set of 10-year sensitivity studies, carried out to attribute changes in the model performance to individual changes in the model physics, is also analysed. GO5.0 is found to have substantially reduced subsurface drift above the depth of the thermocline relative to GO1, and also shows a significant improvement in the representation of the annual cycle of surface temperature and mixed layer depth.