The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics

Abstract. 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.

[1]  C. Jones,et al.  Direct soil moisture controls of future global soil carbon changes: An important source of uncertainty , 2011 .

[2]  P. Cox,et al.  The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes , 2011 .

[3]  P. Cox,et al.  Highly contrasting effects of different climate forcing agents on terrestrial ecosystem services , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[4]  Stephen Sitch,et al.  IMOGEN: an intermediate complexity model to evaluate terrestrial impacts of a changing climate , 2010 .

[5]  A. Arneth,et al.  Evaluation of a photosynthesis-based biogenic isoprene emission scheme in JULES and simulation of isoprene emissions under present-day climate conditions , 2010 .

[6]  S. Los,et al.  A comprehensive set of benchmark tests for a land surface model of simultaneous fluxes of water and carbon at both the global and seasonal scale , 2010 .

[7]  F. Woodward,et al.  Assessing uncertainties in a second-generation dynamic vegetation model caused by ecological scale limitations. , 2010, The New phytologist.

[8]  Sandy P. Harrison,et al.  The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model , 2010 .

[9]  W. Brand,et al.  Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees , 2010 .

[10]  P. Ciais,et al.  Benchmarking coupled climate‐carbon models against long‐term atmospheric CO2 measurements , 2010 .

[11]  Corinna Rebmann,et al.  Treatment and assessment of the CO2-exchange at a complex forest site in Thuringia, Germany , 2010 .

[12]  Corinne Le Quéré,et al.  Trends in the sources and sinks of carbon dioxide , 2009 .

[13]  A. Arneth,et al.  From biota to chemistry and climate: towards a comprehensive description of trace gas exchange between the biosphere and atmosphere. , 2009 .

[14]  P. Cox,et al.  Impact of changes in diffuse radiation on the global land carbon sink , 2009, Nature.

[15]  J. Terborgh,et al.  Drought Sensitivity of the Amazon Rainforest , 2009, Science.

[16]  C. Jones,et al.  Sources of uncertainty in global modelling of future soil organic carbon storage , 2009 .

[17]  Y. Malhi,et al.  Carbon cost of plant nitrogen acquisition: A mechanistic, globally applicable model of plant nitrogen uptake, retranslocation, and fixation , 2010 .

[18]  I. C. Prentice,et al.  Evaluation of the terrestrial carbon cycle, future plant geography and climate‐carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs) , 2008 .

[19]  Andrei P. Sokolov,et al.  Consequences of Considering Carbon–Nitrogen Interactions on the Feedbacks between Climate and the Terrestrial Carbon Cycle , 2008 .

[20]  Tim E. Jupp,et al.  Increasing risk of Amazonian drought due to decreasing aerosol pollution , 2008 .

[21]  Peter E. Thornton,et al.  Influence of carbon‐nitrogen cycle coupling on land model response to CO2 fertilization and climate variability , 2007 .

[22]  C. Huntingford,et al.  Indirect radiative forcing of climate change through ozone effects on the land-carbon sink , 2007, Nature.

[23]  Philippe Ciais,et al.  Weak Northern and Strong Tropical Land Carbon Uptake from Vertical Profiles of Atmospheric CO2 , 2007, Science.

[24]  Jo U. Smith,et al.  ECOSSE: Estimating Carbon in Organic Soils - Sequestration and Emissions: Final Report , 2007 .

[25]  John H. C. Gash,et al.  Improving the representation of radiation interception and photosynthesis for climate model applications , 2007 .

[26]  Stephen Sitch,et al.  Dynamic global vegetation modelling: quantifying terrestrial ecosystem responses to large-scale environmental change , 2007 .

[27]  T. Pons,et al.  High thermal acclimation potential of both photosynthesis and respiration in two lowland Plantago species in contrast to an alpine congeneric , 2006 .

[28]  J. Edmonds,et al.  The economic implications of carbon cycle uncertainty , 2006 .

[29]  Chris D. Jones,et al.  Climate-carbon cycle feedbacks under stabilization: uncertainty and observational constraints , 2006 .

[30]  R. Schnur,et al.  Climate-carbon cycle feedback analysis: Results from the C , 2006 .

[31]  M. Ashmore.  Assessing the future global impacts of ozone on vegetation , 2005 .

[32]  P. Cox,et al.  Global climate change and soil carbon stocks; predictions from two contrasting models for the turnover of organic carbon in soil , 2005 .

[33]  Peter M. Cox,et al.  Climate feedback from wetland methane emissions , 2004 .

[34]  Robert E. Dickinson,et al.  A Two-Big-Leaf Model for Canopy Temperature, Photosynthesis, and Stomatal Conductance , 2004 .

[35]  R. Betts,et al.  The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming , 2004 .

[36]  B. Gimeno,et al.  New critical levels for ozone effects on young trees based on AOT40 and simulated cumulative leaf uptake of ozone , 2004 .

[37]  H. Pleijel,et al.  Relationships between ozone exposure and yield loss in European wheat and potato—a comparison of concentration- and flux-based exposure indices , 2004 .

[38]  R. Betts,et al.  Amazonian forest dieback under climate-carbon cycle projections for the 21st century , 2004 .

[39]  G. Farquhar,et al.  Effect of temperature on the CO2/O2 specificity of ribulose-1,5-bisphosphate carboxylase/oxygenase and the rate of respiration in the light , 1985, Planta.

[40]  P. E. Karlssona,et al.  New critical levels for ozone effects on young trees based on AOT 40 and simulated cumulative leaf uptake of ozone , 2004 .

[41]  Richard Essery,et al.  Explicit representation of subgrid heterogeneity in a GCM land surface scheme , 2003 .

[42]  Richard Essery,et al.  Strong carbon cycle feedbacks in a climate model with interactive CO2 and sulphate aerosols , 2003 .

[43]  Olaf Kolle,et al.  Large carbon uptake by an unmanaged 250-year-old deciduous forest in Central Germany , 2002 .

[44]  Antonio Donato Nobre,et al.  Acclimation of photosynthetic capacity to irradiance in tree canopies in relation to leaf nitrogen concentration and leaf mass per unit area , 2002 .

[45]  J. Houghton,et al.  Climate change 2001 : the scientific basis , 2001 .

[46]  F. Woodward,et al.  Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models , 2001 .

[47]  I. C. Prentice,et al.  Carbon balance of the terrestrial biosphere in the Twentieth Century: Analyses of CO2, climate and land use effects with four process‐based ecosystem models , 2001 .

[48]  Peter M. Cox,et al.  Description of the "TRIFFID" Dynamic Global Vegetation Model , 2001 .

[49]  R. Betts,et al.  Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model , 2000, Nature.

[50]  P. Cox,et al.  Contrasting responses of a simple terrestrial ecosystem model to global change , 2000 .

[51]  M. Ball,et al.  Leaf respiration of snow gum in the light and dark. Interactions between temperature and irradiance. , 2000, Plant physiology.

[52]  P. G. Jarvis,et al.  Photosynthetic capacity in a central Amazonian rain forest. , 2000, Tree physiology.

[53]  R. Betts,et al.  The impact of new land surface physics on the GCM simulation of climate and climate sensitivity , 1999 .

[54]  Richard Harding,et al.  A canopy conductance and photosynthesis model for use in a GCM land surface scheme , 1998 .

[55]  O. Atkin,et al.  Interdependence between chloroplasts and mitochondria in the light and the dark , 1998 .

[56]  James H. Brown,et al.  Allometric scaling of plant energetics and population density , 1998, Nature.

[57]  K. Siebke,et al.  Relationship between the inhibition of leaf respiration by light and enhancement of leaf dark respiration following light treatment , 1998 .

[58]  V. Brovkin,et al.  A continuous climate-vegetation classification for use in climate-biosphere studies , 1997 .

[59]  D. Pury,et al.  Simple scaling of photosynthesis from leaves to canopies without the errors of big‐leaf models , 1997 .

[60]  H. Lambers,et al.  Leaf Respiration in Light and Darkness (A Comparison of Slow- and Fast-Growing Poa Species) , 1997, Plant physiology.

[61]  D. Randall,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation , 1996 .

[62]  C. Justice,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part II: The Generation of Global Fields of Terrestrial Biophysical Parameters from Satellite Data , 1996 .

[63]  D. Jenkinson,et al.  RothC-26.3 - A Model for the turnover of carbon in soil , 1996 .

[64]  R. Brown.  Effect of temperature , 1996 .

[65]  Suan Chin Wong,et al.  A simple calibrated model of Amazon rainforest productivity based on leaf biochemical properties , 1995 .

[66]  P. Ciais,et al.  A Large Northern Hemisphere Terrestrial CO2 Sink Indicated by the 13C/12C Ratio of Atmospheric CO2 , 1995, Science.

[67]  R. Leuning.  A critical appraisal of a combined stomatal‐photosynthesis model for C3 plants , 1995 .

[68]  C. Jacobs,et al.  Direct impact of atmospheric CO2 enrichment on regional transpiration , 1994 .

[69]  E. Schulze,et al.  Relationships among Maximum Stomatal Conductance, Ecosystem Surface Conductance, Carbon Assimilation Rate, and Plant Nitrogen Nutrition: A Global Ecology Scaling Exercise , 1994 .

[70]  Steven W. Running,et al.  Numerical Terradynamic Simulation Group 4-1993 A Physiology-Based Gap Model of Forest Dynamics , 2017 .

[71]  C. Field,et al.  A reanalysis using improved leaf models and a new canopy integration scheme , 1992 .

[72]  G. Collatz,et al.  Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C4 Plants , 1992 .

[73]  G. Collatz,et al.  Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer , 1991 .

[74]  J. Lynch,et al.  The turnover of organic carbon and nitrogen in soil. , 1990 .

[75]  I. E. Woodrow,et al.  A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions , 1987 .

[76]  P. Sellers.  Canopy reflectance, photosynthesis and transpiration , 1985 .

[77]  T. Kira,et al.  A QUANTITATIVE ANALYSIS OF PLANT FORM-THE PIPE MODEL THEORY : I.BASIC ANALYSES , 1964 .

[78]  M. Monsi.  Uber den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung fur die Stoffproduktion , 1953 .

[79]  S S I T C H,et al.  Evaluation of Ecosystem Dynamics, Plant Geography and Terrestrial Carbon Cycling in the Lpj Dynamic Global Vegetation Model , 2022 .