CIMRecord
CIM record:
  model component:
    short name: HadGEM2-ES
    long name: Hadley Global Environment Model 2 - Earth System
    description: The HadGEM2-ES model was a two stage development from HadGEM1, representing improvements in the physical model (leading to HadGEM2-AO) and the addition of earth system components and (leading to HadGEM2-ES). [1] The HadGEM2-AO project targeted two key features of performance: ENSO and northern continent land-surface temperature biases. The latter had a particularly high priority in order for the model to be able to adequately model continental vegetation. Through focussed working groups a number of mechanisms that improved the performance were identified. Some known systematic errors in HadGEM1, such as the Indian monsoon, were not targeted for attention in HadGEM2-AO. HadGEM2-AO substantially improved mean SSTs and wind stress and improved tropical SST variability compared to HadGEM1. The northern continental warm bias in HadGEM1 has been significantly reduced. The power spectrum of El Nino is made worse, but other aspects of ENSO are improved. Overall there is a noticeable improvement from HadGEM1 to HadGEM2-AO when comparing global climate indices. [2] In HadGEM2-ES the vegetation cover is better than in the previous HadCM3LC model especially for trees, and the productivity is better than in the non-interactive HadGEM2-AO model. The presence of too much bare soil in Australia though may cause problems for the dust emissions scheme. The simulation of global soil and biomass carbon stores are good and agree well with observed estimates except in regions of errors in the vegetation cover. HadGEM2-ES compares well with the C4MIP ensemble of models. The distribution of NPP is much improved relative to HadCM3LC. At a site level the component carbon fluxes validate better against observations and in particular the timing of the growth season is significantly improved. The ocean biology (HadOCC) allows the completion of the carbon cycle and the provision of di-methyl sulphide (DMS) emissions from phytoplankton. DMS is a significant source of sulphate aerosol over the oce…
    responsible party:
      CI responsible party:
        role: CI RoleCode
      abbreviation: Chris Jones
    responsible party:
      CI responsible party:
        role: CI RoleCode
      abbreviation: MOHC
    responsible party:
      CI responsible party:
        role: CI RoleCode
      abbreviation: Chris Jones
    responsible party:
      CI responsible party:
        role: CI RoleCode
      abbreviation: MOHC
    release date: 2009
    citation:
      CI citation:
        presentation form: CI PresentationFormCode
      CI citation: date
    citation:
      CI citation:
        presentation form: CI PresentationFormCode
      CI citation: date
    composition:
      coupling: description
      coupling: type
      coupling:
        time transformation: mappingType
      description: Coupling details for component HadGEM2-ES
    child component:
      model component:
        short name: Aerosols
        long name: Aerosols
        description: The model includes interactive schemes for sulphate, sea salt, black carbon from fossil-fuel emissions, organic carbon from fossil-fuel emissions, mineral dust, and biomass-burning aerosols. The model also includes a fixed monthly climatology of mass-mixing ratios of secondary organic aerosols from terpene emissions (biogenic aerosols).
        document version: 1
        document creation date: 2010-09-30T11:12:59.593000
    child component:
      model component:
        short name: Atmosphere
        long name: Atmosphere
        description: The HadGEM2-ES model incorporates the Met Office's New Dynamics framework that provides a non-hydrostatic, fully compressible, deep atmosphere formulation with fewer approximations to the basic equations; semi-Lagrangian advection of all prognostic variables except density, permitting relatively long timesteps to be used at higher resolution; a conservative and monotone treatment of tracer transport; and improved geostrophic adjustment properties bringing better balance to the coupling. HadGEM2-ES includes interactive modelling of atmospheric aerosols, driven by surface and elevated emissions and including tropospheric chemical processes as well as physical removal processes such as washout. The aerosol species represented in the model are sulphate, black carbon, biomass smoke, sea salt, organic carbon, mineral dust and a biogenic climatology. The atmospheric component has a horizontal resolution of 1.25 degrees of latitude by 1.875 degrees of longitude with 38 layers in the vertical extending to over 39 km in height. The model uses the Arakawa C-grid horizontally and the Charney-Phillips grid vertically. The atmospheric timestep period is 30 minutes (48 timesteps per day).
        document version: 1
        document creation date: 2010-09-30T11:13:03.921000
    child component:
      model component:
        short name: Atmospheric Chemistry
        long name: Atmospheric Chemistry
        description: The atmospheric chemistry component of HadGEM2-ES is a configuration of the United Kingdom Chemistry and Aerosols (UKCA) model (O'Connor et al., 2009; 2010; www.ukca.ac.uk) running a relatively thorough description of inorganic odd oxygen (Ox), nitrogen (NOy), hydrogen (HOx), and carbon monoxide (CO) chemistry with near-explicit treatment of methane (CH4), ethane (C2H6), propane (C3H8), and acetone (Me2CO) degradation (including formaldehyde (HCHO), acetaldehyde (MeCHO), peroxy acetyl nitrate (PAN), and peroxy propionyl nitrate (PPAN)). It makes use of 25 tracers and represents 41 species. Large-scale transport, convective transport, and boundary layer mixing are treated. The chemistry scheme accounts for 25 photolytic reactions, 83 bimolecular reactions, and 13 uni- and termolecular reactions.
        document version: 1
        document creation date: 2010-09-30T11:13:06.765000
    child component:
      model component:
        short name: Land Ice
        long name: Land Ice
        description: The major ice sheets (Greenland and Antarctica), and minor ice caps (Ellesmere, Devon and Baffin islands, Iceland, Svalbard, Novaya and Severnaya Zemlya, and Stikine) are depicted as static ice. They are initialised with a snow depth of 50,000 mm of water equivalent. Further ablation or accumulation has an impact on sea level. Runoff follows the river routing scheme and enters the oceans at predefined river outflow points. Calving at the coastal boundaries is simulated through a fresh water flux to the ocean evenly distributed over the area of observed icebergs in both hemispheres. The value of the freshwater flux is calculated to exactly balance the time mean ice sheet surface mass balance over the preindustrial control simulation.
        document version: 1
        document creation date: 2010-09-30T11:13:07.171000
    child component:
      model component:
        short name: Land Surface
        long name: Land Surface
        description: The second version of the U.K. Met Office Surface Exchange Scheme (MOSES-II) (Cox et al. 1999; Essery et al. 2003) is used. This allows tiling of land surface heterogeneity using nine different surface types. A separate surface energy balance is calculated for each tile and area-weighted grid box mean fluxes are computed, which are thus much more realistic than when a single surface type is assumed. In addition, vegetation leaf area is allowed to vary seasonally, providing a more realistic representation of seasonal changes in surface fluxes. Tiling of coastal grid points allows separate treatment of land and sea fractions. This in combination with the increased ocean model resolution greatly improves the coastline, particularly in island regions.
        document version: 1
        document creation date: 2010-09-30T11:13:12.187000
    child component:
      model component:
        short name: Ocean
        long name: Ocean
        description: The ocean component is based on the Bryan-Cox code (Bryan 1969; Cox 1984) and follows the ocean component of HadGEM1 (Johns et al., 2006) very closely. The model uses a latitude-longitude grid with a zonal resolution of 1 degree, and a meridional resolution of 1 degree between the poles and 30 degrees, from which it increases smoothly to 0.333 degrees at the equator - giving a grid of 360 x 216 points. It has 40 unevenly spaced levels in the vertical, with enhanced resolution near the surface better to resolve the mixed layer and thermocline. The forward timestep period is 1 hour, with a mixing timestep of once per day. HadGEM2 uses a bathymetry derived from the Smith and Sandwell (1997) 1/30 degrees depth dataset merged with ETOPO5 (1988) 1/12 degrees data at high latitudes, interpolated to the model grid and smoothed using a five-point (1:4:1) two-dimensional filter. Where this procedure obstructs important narrow pathways (e.g., Denmark Strait, Faroes-Shetland Channel, Vema Channel, and around the Indonesian archipelago), the bathymetry is adjusted to allow some flow at realistic depths (with reference to Thompson 1995). The land masks for the ocean grid differs from that used for the atmosphere model, due to the differences in model resolutions. To enable daily coupling between the models a tiling scheme has been introduced. For each atmosphere grid box, fractions of the fluxes can be coupled to land, sea and sea ice models so that the total flux is conserved - though locally the flux may not be conserved so diagnosis can be difficult. The only ancillary flux used by the ocean model is to enable a balance in the freshwater flux to be maintained, since the accumulation of frozen water on land is not returned into the freshwater cycle, i.e there is no representation of icebergs calving off ice shelves. The ancillary flux is used to add freshwater back into the model, calibrated from a HadGEM2 reference integration to give a balanced freshwater budget.
        document version: 1
        document creation date: 2010-09-30T11:13:18.015000
    child component:
      model component:
        short name: Ocean Biogeo Chemistry
        long name: Ocean Biogeo Chemistry
        description: There is a simple prognostic ecosystem model (the Diat-HadOCC model), with three nutrients (combined nitrate and ammonium, dissolved silicate and dissolved iron), two phytoplankton (diatoms and other phytoplankton), one zooplankton and three detrital compartments (detrital nitrogen, detrital carbon and detrital silicate). There are also two prognostic tracers that are only used in a diagnostic capacity (i.e. their concentrations are affected by, but do not affect, the other compartments): these are dissolved ammonium and dissolved oxygen. Nitrogen is used as the model currency. The diatoms have a variable silicate:nitrate ratio, so diatom silicate is another compartment. All three of the detrital compartments sink with a constant velocity, and are remineralised at a rate that is depth-dependent The zooplankton and both phytoplankton compartments have fixed elemental carbon:nitrogen ratios which allow the flows of carbon through the ecosystem to be linked to the corresponding nitrogen flows. As well as the ecosystem compartments listed above dissolved inorganic carbon (DIC) and total alkalinity (TAlk) are included as prognostic tracers. Those two compartments, along with the model temperature and salinity, are used to calculate the ocean surface pCO2, the air-sea flux of CO2 and the ocean pH. The air-sea fluxes of CO2 and DMS are each calculated every ocean time-step and their daily means are passed through the coupler to the atmosphere each day.
        document version: 1
        document creation date: 2010-09-30T11:13:20.656000
    child component:
      model component:
        short name: Sea Ice
        long name: SeaIce
        description: The sea-ice model is split between the atmosphere and ocean model components. The atmosphere part calculates the atmosphere-ice heat fluxes, the diffusive heat flux through the ice, the ice surface temperature and surface melting. This allows the diurnal cycle of the surface temperature to be modelled whilst only coupling betwen the atmosphere and ocean components once a day. The ocean part deals with the remaining thermodynamics, calculates basal melting by heat supplied from the mixed layer, keeps account of snow and ice thickness changes including conversion of submerged snow to ice, and deals with ice dynamics (including ridging) using daily mean fields of the atmospheric forcings supplied via coupling routines. A multiple ice thickness category model which solves the basic equation of Thorndike et al. (1975), is used to capture the sub-gridscale ice thickness distribution. HadGEM2-ES uses 5 ice categories plus open water (leads). Ice thickness affects many sea ice properties and processes, including the growth rate, ice strength and surface energy fluxes. As ice thickness can vary greatly within the grid box length scale, a multiple ice category model should lead to an improved representation of sea ice processes.
        document version: 1
        document creation date: 2010-09-30T11:13:22.046000
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    document author:
      CI responsible party:
        role: CI RoleCode
    document creation date: 2010-09-30T11:13:22.046000

CIMRecord
CIM record:
  simulation run:
    responsible party:
      CI responsible party:
        role: CI RoleCode
      abbreviation: Chris Jones
    responsible party:
      CI responsible party:
        role: CI RoleCode
      abbreviation: Chris Jones
    responsible party:
      CI responsible party:
        role: CI RoleCode
      abbreviation: MOHC
    responsible party:
      abbreviation: MOHC
    short name: piControlBaseSimulation
    long name: Base Simulation of Ensemble3.1 Pre-industrial Control (1860 - 2360)
    description: Impose non-evolving, pre-industrial conditions, which may include: Prescribed atmospheric concentrations of - all well mixed gases (including CO2) - some short-lived (reactive) species Prescribed non-evolving emissions or concentrations of - natural aerosols or their precursors - some short-lived (reactive) species Unperturbed land use.
    document version: 1
    document creation date: 2010-09-30T11:13:22.437000

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character string: Bellouin et al. 2007

character string: Bellouin N., O. Boucher, J. Haywood, C. Johnson, A. Jones, J. Rae, and S. Woodward. (2007) Improved representation of aerosols for HadGEM2.. Meteorological Office Hadley Centre, Technical Note 73, March 2007

character string: Collins et al. 2008

character string: Collins W.J. , N. Bellouin, M. Doutriaux-Boucher, N. Gedney, T. Hinton, C.D. Jones, S. Liddicoat, G. Martin, F. O'Connor, J. Rae, C. Senior, I. Totterdell, and S. Woodward (2008) Evaluation of the HadGEM2 model. Meteorological Office Hadley Centre, Technical Note 74

rate: 1

spatial regridding order: TBD

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abbreviation: Chris Jones

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abbreviation: MOHC

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  role: CI RoleCode
abbreviation: Nicolas Bellouin

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model component:
  short name: Aerosol Emission And Conc
  long name: Aerosol Emission And Concentration
  description: Emissions for the sulphur cycle include emissions of ammonium sulphate aerosol precursors: sulphur dioxide and dimethylsulphide. For sulphur dioxide, anthropogenic emissions are split into surface and chimney-level emissions. Natural emissions from volcanoes are provided as a 3D field. DMS emissions are provided by the ocean biogeochemistry scheme over the ocean, and provided through a dataset over land surfaces. All sulphur-cycle emissions are expressed in term of mass of sulphur within HadGEM2-ES. For black-carbon and organic-carbon aerosols from fossil-fuel and biofuel emissions, emissions are provided at near-surface level. These emissions are expressed in term of mass of carbon. For biomass-burning aerosol, emissions are provided as two fields: surface emissions, and high-level emissions. The latter field is homogeneously distributed across the boundary layer. Biomass emissions are expressed in term of mass of carbon. Emissions for sea-salt and mineral dust aerosols are computed interactively from the modelled meteorology and soil properties by their respective schemes. The climatology of monthly-averaged mass-mixing ratios of secondary organic aerosol from terpene emissions was derived from the chemistry-transport model STOCHEM (Derwent et al., 2003). Emissions based on datasets: All emission fields are provided as monthly means, which are time interpolated by the model every 5 days. Sulphur dioxide emissions are derived from sector-based emissions datasets for IPCC AR5 (Lamarque et al., 2009). Emissions for all sectors are considered surface emissions, except for energy emissions and half of industrial emissions which are considered chimney-level emissions. Emissions for land-based dimethylsulphide are taken from Spiro et al. (1992). Anthropogenic emissions for black carbon and organic carbon are from the sum of all sector-based emissions in the IPCC AR5 dataset. They are emitted in the second level of HadGEM2-ES (near-surface emissions). Anthropogenic emissi…
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        long name: PrescribedLowerBoundary
  responsible party:
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    abbreviation: Nicolas Bellouin
  responsible party:
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  citation:
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        character string: Andres, R.J. and Kasgnoc, A.D. (1998) A time-averaged inventory of subaerial volcanic sulfur emissions. J. Geophys. Res., 103, 25251-25261, 1998.
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        character string: Derwent, R.G., Collins, W.J., Jenkin, M.E., and Johnson, C.E. (2003) The global distribution of secondary particulate matter in a 3-D Lagrangian chemistry transport model. J. Atmos. Chem., 44, 57-95, 2003.
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      collective title:
        character string: Jones A., D.L. Roberts, M.J. Woodage and C.E. Johnson (2001) Indirect sulphate aerosol forcing in a climate model with an interactive sulpher cycle.. J. Geophys Res., 106, 20293-20310.
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        character string: Lamarque 2009
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        character string: Lamarque, J.F. et al. (2009) Gridded emissions in support of IPCC AR5.. IGACtivities 41, 12-18, May 2009.
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        character string: Spiro 1992
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      collective title:
        character string: Spiro, P.A., Jacob, D.J., and Logan, J.A. (1992) Global inventory of sulfur emissions with 1x1 resolution. J. Geophys. Res., 97, 6023-6036, 1992.
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        character string: Woodward 2001
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      collective title:
        character string: Woodward S., (2001) Modelling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model. J. Geophys. Res., 106, D16, 18,155-18,166, 2001.
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  document creation date: 2010-09-30T11:12:58.171000

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model component:
  short name: Aerosol Key Properties
  long name: Aerosol Key Properties
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      long name: NumberOfTracers
      value: 20
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      value: 3D mass/volume mixing ratio for aerosols
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      value: Modal scheme, mass as a tracer, number inferred from prescribed size distributions
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      value: whole atmosphere
    component property:
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      component property:
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        long name: Method
        value: uses AtmosphericChemistry time stepping
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model component:
  short name: Aerosol Model
  long name: Aerosol Model
  description: The model includes interactive schemes for sulphate, sea salt, black carbon from fossil-fuel emissions, organic carbon from fossil-fuel emissions, mineral dust, and biomass-burning aerosols. The model also includes a fixed monthly climatology of mass-mixing ratios of secondary organic aerosols from terpene emissions (biogenic aerosols). All aerosol species, except sea-salt and biogenic aerosols, are advected using the tracer advection scheme and undergo wet and dry deposition. Wet deposition accounts for re-evaporation of precipitation (Bellouin et al., 2007). All aerosol species exert a direct effect (scattering and absorption of shortwave and longwave radiation) and thereby also a semi-direct effect (impact on atmospheric temperature and cloud profiles of aerosol absorption). All aerosol species, except black carbon and mineral dust, also contribute to both the first and second indirect effects on clouds, modifying cloud albedo and precipitation efficiency, respectively. The version of the sulphur cycle included in HadGEM2-ES is described in Jones et al. [2001] and Roberts and Jones [2004] with further improvements described hereafter. The sulphate scheme is a modal scheme where the free aerosol is assumed to have a log-normal size distribution in the Aitken and accumulation size ranges, which include particles with a radius less than 0.05 and 0.5 m, respectively. Sulphate aerosol may also be in a dissolved mode where layer clouds are present, thus affecting the cloud droplet size and exerting first and second indirect effects (modification of cloud albedo and precipitation efficiency, respectively). The sulphur cycle in HadGEM2-ES also includes improvements described by Bellouin et al. [2007]: condensation of sulphuric acid from dry oxidation of sulphur dioxide and dimethysulphide, and conversion from Aitken to accumulation mode particles by condensation. In addition, the oxidation of SO2 and DMS is now using oxidant concentrations (OH, HO2, H2O2, O3) provided by…
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CI citation: date

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      description: The large-scale cloud scheme for liquid cloud is that of Smith (1990), in which cloud water and cloud amount are diagnosed from total moisture and liquid water potential temperature using a triangular probability distribution function. The width of this distribution is diagnosed from the variability of the moisture and temperature of the surrounding grid points. A representation of the difference between cloud area fraction and cloud volume fraction is made by subdividing a single model layer into three. HadGEM1 and later models introduced an updated version of the Wilson and Ballard (1999) microphysics scheme. Transfers between water categories (ice, liquid water, vapor, and rain) are calculated based on physical process equations using particle size information.
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  description: The dynamical core for HadGEM2-ES (Davies et al., 2005) was designed to avoid unnecessary approximations and includes the following features: - non-hydrostatic, fully compressible, deep atmosphere formulation using a terrain following, height-based vertical coordinate. - discretization using a horizontally staggered Arakawa C-grid and vertically staggered Charney-Phillips grid; - semi-Lagrangian advection for all prognostic variables, except density, with conservative and monotone treatment of tracers, - Eulerian treatment of the continuity equation for mass conservation; - predictor-corrector implementation of a two time level, semi-implicit, time integration scheme, - three dimensional iterative solution of a variable-coefficient elliptic equation for the pressure increment at each time step.
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CI citation: date

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  short name: Atm Chem Emission And Conc
  long name: Atmospheric Chemistry Emission and Concentration
  description: The tropospheric chemistry can be run fully interactively, taking account of surface emissions of CH4, CO, NOx, HCHO, C2H6, C3H8, Me2CO, and MeCHO. These are added in the surface layer of the model and then mixed within the boundary layer by mixing (Lock et al., 2000). In the case of CH4, surface emissions from all anthropogenic and natural sectors can be prescribed. Alternatively, interactive wetland emissions (Gedney et al., 2004) can be used in place of prescribed wetland emissions. Prescribed emissions for all emitted speces are provided on the model's horizontal grid as monthly mean emissions rates. The model then reads in the monthly mean emission rates and calculates an instantaneous emission rate based on a time interpolation of the monthly mean fields. Typically, this time-interpolated rate is recalculated every 5 days. The corresponding tracers are incremented in the surface layer using this time-interpolated emission rate and the dynamical timestep, followed by boundary layer mixing. The interactive chemistry in the model also includes aircraft emissions of NOx. These are provided on the 3D model grid as monthly mean emissions rates and time interpolated as for the surface emissions. The model then reads in the monthly mean emission rates and calculates an instantaneous emission rate based on a time interpolation of the monthly mean fields. Typically, this time-interpolated rate is recalculated every 5 days. The NO tracer in the model is then incremented, using this time-interpolated emission rate and the timestep. Interactive lightning emissions of NOx are also considered (Price and Rind, 1994), which have been scaled to give approximatly 5 TgN/year at the present day. These are diagnosed every dynamical timestep using convective cloud top and base from the climate model's convection scheme and added to the NO tracer every dynamical timestep. The chemistry also has the option of fixing the surface methane concentration based on concentrations provided (e…
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model component:
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  description: see description for "Atmospheric Chemistry" component
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model component:
  short name: Atm Chem Photo Chemistry
  long name: Atospheric Chemistry Photo Chemistry
  description: The atmospheric chemistry component (UKCA) of HadGEM2-ES takes account of 25 photolytic reactions. The corresponding photolysis rates are calculated offline in the Cambridge 2D model (Law and Pyle, 1993) using the Hough (1988) scheme. These are then read in by UKCA on the first time step of the model integration and interpolated in time and space at each model grid box.
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  document creation date: 2010-09-30T11:13:06.500000

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  long name: Atmospheric Chemistry Transport
  description: The tracers in the UKCA atmospheric chemistry in HadGEM2-ES are subject to large-scale advection (Davies et al. 2005), convective transport (Gregory and Rowntree, 1990), and boundary layer mixing (Lock et al. 2000).
  component properties:
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      short name: SchemeType
      long name: SchemeType
    component property:
      short name: MassConservation
      long name: MassConservation
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      short name: Convection
      long name: Convection
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      short name: Turbulence
      long name: Turbulence
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        short name: Type
        long name: Type
      component property:
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        long name: CouplingWithChemicalReactivity
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    abbreviation: MOHC
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electronic mail address: CharacterString

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    character string: UK Met Office Hadley Centre
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model component:
  short name: Land Ice Key Properties
  component properties:
    component property:
      short name: AlbedoFunctionOf
      long name: AlbedoFunctionOf
    component property:
      short name: GroundingLineMethod
      long name: GroundingLineMethod
    component property:
      short name: LandIceAlbedo
      long name: LandIceAlbedo
    component property:
      short name: CouplingIceSheet-IceShelves
      long name: CouplingIceSheet-IceShelves
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    abbreviation: MOHC
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CI citation: date

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CI citation: date

model component:
  short name: Land Surface Albedo
  long name: Land Surface Albedo
  description: A bulk albedo is used for each of the surface types within the tile scheme. Non vegetation surfaces have a fixed specified snow free albedo. For vegetation the albedo is a combination of the bare soil albedo and the vegetation albedo, using Bear's law to determine the fraction of bare soil. The overall albedo then depends upon the amount of snow, varying between the snow free albedo and a specified deep snow albedo according to the depth of snow (Essery et al. 2001).
  component properties:
    component property:
      short name: SpecificTiling
      long name: SpecificTiling
    component property:
      short name: SnowFreeAlbedo
      long name: SnowFreeAlbedo
      component property:
        short name: FunctionOf
        long name: FunctionOf
      component property:
        short name: Direct-Diffuse
        long name: Direct-Diffuse
      component property:
        short name: FunctionOf
        long name: FunctionOf
      component property:
        short name: Type
        long name: Type
    component property:
      short name: SnowAlbedo
      long name: SnowAlbedo
      component property:
        short name: FunctionOf
        long name: FunctionOf
      component property:
        short name: Type
        long name: Type
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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        character string: Chris Jones
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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model component:
  short name: Land Surface Carbon Cycle
  long name: Land Surface Carbon Cycle
  description: The land surface scheme simulates the storage of carbon in the terrestrial biosphere and its exchange with the atmosphere. Vegetation takes up carbon through photosynthesis and releases it through autotrophic respiration. The net balance (NPP) is allocated to root, wood and leaf carbon. Turnover of vegetation carbon falls as litter to the soil, which is representedf by the 4-pool soil carbon model RothC (Coleman and Jenkinson, 1999). Decomposition of soil organic material depends on a Q10 function of temperature (q10=2) and a function of soil moisture (Cox, 2001).
  component properties:
    component property:
      short name: Soil
      long name: Soil
      component property:
        short name: ListOfCarbonPools
        long name: ListOfCarbonPools
      component property:
        short name: NumberOfCarbonPools
        long name: NumberOfCarbonPools
      component property:
        short name: Method
        long name: Method
    component property:
      short name: Permafrost
      long name: Permafrost
      component property:
        short name: ListOfGases
        long name: ListOfGases
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        character string: Chris Jones
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    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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      role: CI RoleCode
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        character string: UK Met Office Hadley Centre
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    abbreviation: MOHC
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      collective title:
        character string: Cox, P.M. (2001) Description of the TRIFFID dynamic global vegetation model.. Hadley Centre Technical Note 24, Hadley Centre, Met Office, UK.
    CI citation: date
  child component:
    model component:
      short name: Vegetation Carbon Cycle
      long name: Vegetation Carbon Cycle
      description: (described under Land Surface Carbon Cycle)
      responsible party:
        abbreviation: Chris Jones
      responsible party:
        abbreviation: MOHC
      responsible party:
        abbreviation: Chris Jones
      responsible party:
        abbreviation: MOHC
      document version: 1
      document creation date: 2010-09-30T11:13:08.375000
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short name: NumberOfCarbonPools
long name: NumberOfCarbonPools

short name: ListOfCarbonPools
long name: ListOfCarbonPools

short name: Photosynthesis
long name: Photosynthesis
component property:
  short name: Method
  long name: Method

short name: AutotrophicRespiration
long name: AutotrophicRespiration
component property:
  short name: MaintenanceRespiration
  long name: MaintenanceRespiration
component property:
  short name: Method
  long name: Method

short name: Allocation
long name: Allocation
component property:
  short name: AllocationBins
  long name: AllocationBins
component property:
  short name: AllocationFractions
  long name: AllocationFractions

short name: Phenology
long name: Phenology
component property:
  short name: Method
  long name: Method

individual name:
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character string: Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PB

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model component:
  short name: Land Surface Energy Balance
  long name: Land Surface Energy Balance
  description: The surface energy balance is derived following the Penman-Montheith approach. This is extended to include thermal inertia for the surface and weakening of the coupling to the underlying soil through radiative processes (Essery et al. 2001). Surface heterogeneity is modelled using the tile approach, with a separate surface energy balance calculation for each tile. The temperature change associated with the outgoing longwave radiation is taken into account in the surface energy balance, but the net change to the radiative balance is not applied throughout the atmosphere. Instead it is assumed that the small changes to the longwave radiation pass through the atmosphere and are added to the top of atmosphere balance through an additional diagnostic. The surface is implicitly coupled to the atmosphere using the method of Best et al. (2004).
  component properties:
    component property:
      short name: SubsurfaceTiling
      long name: SubsurfaceTiling
    component property:
      short name: NumberOfSurfaceTemperatures
      long name: NumberOfSurfaceTemperatures
    component property:
      short name: SpecificTiling
      long name: SpecificTiling
    component property:
      short name: SchemeMethod
      long name: SchemeMethod
      component property:
        short name: Processes
        long name: Processes
      component property:
        short name: TypeOfEvaporationFormulation
        long name: TypeOfEvaporationFormulation
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      role: CI RoleCode
    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
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        character string: Best 2004
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      other citation details: CharacterString
      collective title:
        character string: Best, M.J., Beljaars, A., Polcher, J., Viterbo, P., (2004) A proposed structure for coupling tiled land-surfaces with the planetary boundary layer Journal of Hydrometeorology, 5, 1271-1278
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  document creation date: 2010-09-30T11:13:08.703000

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model component:
  short name: Land Surface Key Properties
  component properties:
    component property:
      short name: TilingMethod
      long name: TilingMethod
    component property:
      short name: Tiling
      long name: Tiling
    component property:
      short name: ListOfPrognosticVariables
      long name: ListOfPrognosticVariables
    component property:
      short name: LandCoverTypes
      long name: LandCoverTypes
    component property:
      short name: CouplingWithAtmosphere
      long name: CouplingWithAtmosphere
    component property:
      short name: Genealogy
      long name: Genealogy
    component property:
      short name: BasicApproximations
      long name: BasicApproximations
    component property:
      short name: ConservationOfProperties
      long name: ConservationOfProperties
      component property:
        short name: WaterStorageMethod
        long name: WaterStorageMethod
      component property:
        short name: LagOfWaterDischarge
        long name: LagOfWaterDischarge
      component property:
        short name: WaterTreatment
        long name: WaterTreatment
    component property:
      short name: TimeSteppingFramework
      long name: TimeSteppingFramework
      component property:
        short name: TimeStep
        long name: TimeStep
      component property:
        short name: Method
        long name: Method
  responsible party:
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      individual name:
        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
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      individual name:
        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
    CI responsible party:
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        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
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    abbreviation: MOHC
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  document creation date: 2010-09-30T11:13:09.375000

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model component:
  short name: Land Surface Lakes
  long name: Land Surface Lakes
  description: Lakes are represented as a fixed, specified fraction of each gridbox. They provide a source of water to evaporate to the atmosphere but do not prognostically simulate water depth, storage or areal extent. Evaporated water from lakes is removed from soil moisture in unstressed regions. The model calculates the accumulated lake evaporation globally over a whole day and then applies an equal correction to all the 4 soil moisture levels for each grid box where the soil moisture is greater than the wilting point.
  component properties:
    component property:
      short name: QuantitiesExchangedWithRivers
      long name: QuantitiesExchangedWithRivers
    component property:
      short name: CouplingWithRivers
      long name: CouplingWithRivers
    component property:
      short name: SchemeMethod
      long name: SchemeMethod
      component property:
        short name: IceTreatment
        long name: IceTreatment
      component property:
        short name: LakesAlbedo
        long name: LakesAlbedo
      component property:
        short name: LakesDynamics
        long name: LakesDynamics
      component property:
        short name: DynamicLakesExtent
        long name: DynamicLakesExtent
      component property:
        short name: EndorheicBasins
        long name: EndorheicBasins
  responsible party:
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        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
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    CI responsible party:
      individual name:
        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
    CI responsible party:
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        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
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      individual name:
        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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        character string: Metafor Questionnaire
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  document creation date: 2010-09-30T11:13:09.703000

address:
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model component:
  short name: Land Surface Snow
  long name: Land Surface Snow
  description: Snow at the land surface is represented with a single layer. This layer is merged with the first soil layer in such a way that if the total depth of snow is less than the thickness of the first soil layer, then the thermal properties become a linear weighting of those from the snow and soil. If the snow depth exceeds the first soil layer thickness, then this layer can increase in thickness and adopts only the snow thermal properties (Essery et al. 2001).
  component properties:
    component property:
      short name: SpecificTiling
      long name: SpecificTiling
    component property:
      short name: NumberOfSnowLayers
      long name: NumberOfSnowLayers
    component property:
      short name: SchemeMethod
      long name: SchemeMethod
      component property:
        short name: SnowAlbedo
        long name: SnowAlbedo
      component property:
        short name: SnowDensity
        long name: SnowDensity
      component property:
        short name: SnowWaterEquivalent
        long name: SnowWaterEquivalent
      component property:
        short name: SnowHeatContent
        long name: SnowHeatContent
      component property:
        short name: SnowTemperature
        long name: SnowTemperature
      component property:
        short name: SnowLiquidWaterContent
        long name: SnowLiquidWaterContent
      component property:
        short name: SnowCoverFractions
        long name: SnowCoverFractions
      component property:
        short name: Processes
        long name: Processes
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      individual name:
        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
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      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
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      role: CI RoleCode
    abbreviation: MOHC
  citation:
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        character string: Essery 2001
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      collective title:
        character string: Essery R., M. Best, and P. Cox (2001) MOSES 2.2 technical documentation.. Hadley Centre Technical Note 30, 30 pp.
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  document creation date: 2010-09-30T11:13:10.062000

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model component:
  short name: Land Surface Soil
  long name: Land Surface Soil
  description: The soil has four layers of increasing thickness up to a depth of 3m each with the same soil properties. In addition there is a deeper layer (extending down to 6m below the surface) which has a saturated hydraulic conductivity which decreases exponentially with depth (Gedney et al, 2003). Soil properties are from <REFERENCE REQUIRED>
  component properties:
    component property:
      short name: SoilMap
      long name: SoilMap
      component property:
        short name: Texture
        long name: Texture
      component property:
        short name: Structure
        long name: Structure
      component property:
        short name: Albedo
        long name: Albedo
      component property:
        short name: WaterTable
        long name: WaterTable
  responsible party:
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      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
    CI responsible party:
      individual name:
        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
    CI responsible party:
      individual name:
        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
    CI responsible party:
      individual name:
        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  citation:
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      collective title:
        character string: Gedney, N., and Cox, P. M. (2003) The sensitivity of global climate model simulations to the representation of soil moisture heterogeneity J. Hydromet., 4, 6, 1265-1275
    CI citation: date
  child component:
    model component:
      short name: Land Surf Soil Heat Treatment
      long name: Land Surface Soil Heat Treatment
      description: <INFORMATION REQUIRED>
      responsible party:
        abbreviation: Chris Jones
      responsible party:
        abbreviation: MOHC
      responsible party:
        abbreviation: Chris Jones
      responsible party:
        abbreviation: MOHC
      document version: 1
      document creation date: 2010-09-30T11:13:10.593000
  child component:
    model component:
      short name: Land Surf Soil Hydrology
      long name: Land Surface Soil Hydrology
      description: The large-scale hydrology scheme (Gedney et al, 2003 and Clark and Gedney, 2008) is incorporated into the land surface soil hydrology. This allows for the deeper layers to become saturated and a water table to form. Deep run-off is lost through lateral flow below the water table. Excess (supersaturated) soil water (e.g. through snowmelt) is now drained into the soil layer below instead of simply run-off from the top layer. This increases soil moisture in the lower soil layers and so helps to reduce the water stress on vegetation following snowmelt in Northern Hemispheric continents.
      responsible party:
        abbreviation: Chris Jones
      responsible party:
        abbreviation: MOHC
      responsible party:
        abbreviation: Chris Jones
      responsible party:
        abbreviation: MOHC
      citation:
        CI citation: date
      citation:
        CI citation: date
      document version: 1
      document creation date: 2010-09-30T11:13:11.093000
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short name: SoilHeatTreatmentAttributes
long name: SoilHeatTreatmentAttributes
component property:
  short name: SpecificTiling
  long name: SpecificTiling
component property:
  short name: NumberOfGroundHeatLayers
  long name: NumberOfGroundHeatLayers

short name: Method
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vocabulary name: metafor

individual name:
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role: CI RoleCode

short name: SoilHydrologyAttributes
long name: SoilHydrologyAttributes
component property:
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  long name: SpecificTiling
component property:
  short name: NumberOfGroundWaterLayers
  long name: NumberOfGroundWaterLayers
component property:
  short name: WaterStorageMethod
  long name: WaterStorageMethod

short name: SoilMoistureFreezing
long name: SoilMoistureFreezing
component property:
  short name: NumberOfGroundIceLayers
  long name: NumberOfGroundIceLayers
component property:
  short name: IceStorageMethod
  long name: IceStorageMethod
component property:
  short name: Permafrost
  long name: Permafrost

short name: Runoff-Drainage
long name: Runoff-Drainage
component property:
  short name: Processes
  long name: Processes
component property:
  short name: Method
  long name: Method

individual name:
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character string: Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PB

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title:
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vocabulary name: metafor

individual name:
  character string: Metafor Questionnaire
role: CI RoleCode

model component:
  short name: Land Surface Vegetation
  long name: Land Surface Vegetation
  description: The land surface scheme represents 5 vegetation functional types (PFTs): broadleaf and needleleaf tree, C3 and C4 grass and shrub, the fractions of which can be specified or simulated by the model (Cox 2001). When simulated, fractional coverage of each PFT evolves due to competition between types based on carbon balance and available land area and is represented by Lotka-Voltera competition equations. As it does not explicitly simulate crop growth, crop areas are treated as natural grass. The impact of land-use is implemented by removing trees and shrubs in regions specified as agriculture. The representation of photosynthesis is that of Collatz et al. (1991) for C3-type photosynthesis and Collatz et al. (1992) for C4-type photosynthesis, as described in Cox et al. (1999). Photosynthesis is also directly sensitive to the leaf nitrogen concentrations (specified) and the leaf temperature. The phenological status alters the leaf area index (LAI) of the canopy and is soley a function of leaf temperature (with pre-specified tolerances to low temperatures) and includes the effects of leaf dropping and budburst in a way corresponding to a chill-day parametrization. It also includes a representation of the vertical profiles of light and nitrogen through the canopy (Mercardo et al., 2007).
  component properties:
    component property:
      short name: VegetationTypes
      long name: VegetationTypes
      value: broadleaf tree
      value: C3 grass
      value: C4 grass
      value: needleleaf tree
      value: other
    component property:
      short name: Interception
      long name: Interception
      value: yes
    component property:
      short name: VegetationTimeVariation
      long name: VegetationTimeVariation
      value: dynamical (varying from simulation)
    component property:
      short name: VegetationRepresentation
      long name: VegetationRepresentation
      value: vegetation types
    component property:
      short name: SpecificTiling
      long name: SpecificTiling
      value: yes
    component property:
      short name: SchemeMethod
      long name: SchemeMethod
      component property:
        short name: StomatalResistanceFunctionOf
        long name: StomatalResistanceFunctionOf
        value: CO2
        value: light
        value: temperature
        value: water availability
      component property:
        short name: BioGeography
        long name: BioGeography
      component property:
        short name: Biomass
        long name: Biomass
        value: diagnostic
      component property:
        short name: LAI
        long name: LAI
        value: prognostic
      component property:
        short name: Phenology
        long name: Phenology
        value: prognostic
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      individual name:
        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
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      individual name:
        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
    CI responsible party:
      individual name:
        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
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        character string: UK Met Office Hadley Centre
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    abbreviation: MOHC
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        character string: Clark 2008
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      collective title:
        character string: Clark, D. B., and Gedney, N. (2008) Representing the effects of subgrid variability of soil moisture on runoff generation in a land surface model J. Geophys. Res., 113, D10, D10111.
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  citation:
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        character string: Collatz 1991
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      other citation details: CharacterString
      collective title:
        character string: Collatz, G. J., Ball, J. T., Grivet, C., and Berry, J. A. (1991) Physiological and environmental-regulation of stomatal conductance, photosynthesis and transpiration - a model that includes a laminar boundary-layer Agr. Forest Meteorol., 54, 107-136.
    CI citation: date
  citation:
    CI citation:
      title:
        character string: Collatz 1992
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      other citation details: CharacterString
      collective title:
        character string: Collatz, G. J., Ribas-Carbo, M., and Berry, J. A. (1992) Coupled photosynthesis-stomatal conductance model for leaves of C4 plants Aust. J. Plant Physiol., 19, 519-538.
    CI citation: date
  citation:
    CI citation:
      title:
        character string: Cox 1999
      presentation form: CI PresentationFormCode
      other citation details: CharacterString
      collective title:
        character string: Cox P. M., R. A. Betts, C. B. Bunton, R. L. H. Essery, P. R. Rowntree, and J. Smith (1999) The impact of new land surface physics on the GCM simulation of climate and climate sensitivity.. Climate Dynamics., 15, 183-203.
    CI citation: date
  citation:
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        character string: Cox 2001
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      other citation details:
        character string: http://www.metoffice.gov.uk/publications/HCTN/HCTN_24.pdf
      collective title:
        character string: Cox, P.M. (2001) Description of the TRIFFID dynamic global vegetation model.. Hadley Centre Technical Note 24, Hadley Centre, Met Office, UK.
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  citation:
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      title:
        character string: Mercado 2007
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      other citation details: CharacterString
      collective title:
        character string: Mercado, L. M., Huntingford, C., Gash, J. H. C., Cox, P. M., and Jogireddy, V. (2007) Improving the representation of radiation interception and photosynthesis for climate model applications. Tellus, 59B, 553-565.
    CI citation: date
  type:
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        character string: Metafor Questionnaire
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  document creation date: 2010-09-30T11:13:11.750000

address:
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      character string: Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PB
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online resource:
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      URL: http://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jones

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      URL: http://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jones

model component:
  short name: River Routing
  long name: Land Surface River Routing
  description: Realistic river flow is important for the freshwater contribution to the thermohaline circulation. The new Total Runoff Integrating Pathways (TRIP) dynamic river routing scheme (Oki and Sud 1998) advects runoff along prescribed channels using an embedded 1degree x 1degree river transport submodel. All rivers flow with an effective velocity of 0.4 m/s and a meander ratio of 1.4. River outflow to the ocean is included. Ancillary files specify 'inland basins' in which the river flows into an inland delta and the moisture enters the soil column. The model also allows for inland basins to be defined seperately, and spreads water proportionately over the river outflow points.
  component properties:
    component property:
      short name: QuantitiesExchangedWithAtmosphere
      long name: QuantitiesExchangedWithAtmosphere
    component property:
      short name: DrainageMap
      long name: DrainageMap
    component property:
      short name: SpecificTiling
      long name: SpecificTiling
    component property:
      short name: Resolution
      long name: Resolution
    component property:
      short name: NumberOfReservoirs
      long name: NumberOfReservoirs
    component property:
      short name: ListOfPrognosticVariables
      long name: ListOfPrognosticVariables
    component property:
      short name: WaterRe-evaporation
      long name: WaterRe-evaporation
    component property:
      short name: CouplingWithAtmosphere
      long name: CouplingWithAtmosphere
    component property:
      short name: OceanicDischarge
      long name: OceanicDischarge
      component property:
        short name: Type
        long name: Type
      component property:
        short name: QuantitiesTransported
        long name: QuantitiesTransported
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      individual name:
        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
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      individual name:
        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
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        character string: UK Met Office Hadley Centre
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    abbreviation: MOHC
  citation:
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      title:
        character string: Oki 1998
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      other citation details: CharacterString
      collective title:
        character string: Oki T., and Y.C. Sud (1998) Design of the Total Runoff Integrating Pathways [TRIP] - A global river channel network.. Earth Interactions, 2.
    CI citation: date
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        character string: Metafor Questionnaire
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  document creation date: 2010-09-30T11:13:12.187000

address:
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      character string: Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PB
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      URL: http://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jones

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vocabulary server:
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    character string: Metafor Questionnaire
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    character string: Chris Jones
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abbreviation: Chris Jones

delivery point:
  character string: Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PB
electronic mail address: CharacterString

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  individual name:
    character string: UK Met Office Hadley Centre
  role: CI RoleCode
abbreviation: MOHC

CI responsible party:
  individual name:
    character string: Malcolm Roberts
  role: CI RoleCode
abbreviation: Malcolm Roberts

delivery point:
  character string: Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PB
electronic mail address: CharacterString

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    character string: UK Met Office Hadley Centre
  role: CI RoleCode
abbreviation: MOHC

CI citation:
  title:
    character string: Bryan 1969
  presentation form: CI PresentationFormCode
  other citation details: CharacterString
  collective title:
    character string: Bryan K., (1969) A numerical method for the study of the circulation of the world ocean.. Journal of Computational Physics, 4, 347-376.
CI citation: date

CI citation:
  title:
    character string: Cox 1984
  presentation form: CI PresentationFormCode
  other citation details: CharacterString
  collective title:
    character string: Cox M.D., (1984) A primitive equation, three dimensional model of the ocean.. Ocean Group Technical Report 1, GFDL, Princeton.
CI citation: date

CI citation:
  title:
    character string: Johns_2006
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  other citation details: CharacterString
  collective title:
    character string: Johns T.C., C.F. Durman, H.T. Banks, M.J. Roberts, A.J. McLaren, J.K. Ridley, C.A. Senior, K.D. Williams, A. Jones, G.J. Rickard, S. Cusack, W.J. Ingram, M. Crucifix, D.M.H. Sexton, M.M. Joshi, B-W. Dong, H. Spencer, R.S.R. Hill, J.M. Gregory, A.B. Keen, A.K. Pardaens, J.A. Lowe, A. Bodas-Salcedo, S (2006). "The new Hadley Centre climate model HadGEM1: Evaluation of coupled simulations." Journal of Climate, American Meteorological Society, Vol. 19, No. 7, pages 1327-1353.
CI citation: date

model component:
  short name: Ocean Advection
  long name: Ocean Advection
  description: A pseudo fourth-order advection scheme (Pacanowski and Griffies 1998) is used, which is more accurate and generates less grid-scale noise than a second-order scheme, and includes upstream mixing at the ocean bottom to improve model stability there. A simple semi-implicit representation of linear bottom friction is included which removes momentum at the ocean bottom depending on the magnitude of the velocities found there.
  component properties:
    component property:
      short name: Momentum
      long name: Momentum
      component property:
        short name: SchemeName
        long name: SchemeName
      component property:
        short name: SchemeType
        long name: SchemeType
    component property:
      short name: LateralTracers
      long name: LateralTracers
      component property:
        short name: SchemeType
        long name: SchemeType
      component property:
        short name: MonotonicFluxLimiter
        long name: MonotonicFluxLimiter
    component property:
      short name: VerticalTracers
      long name: VerticalTracers
      component property:
        short name: SchemeType
        long name: SchemeType
      component property:
        short name: MonotonicFluxLimiter
        long name: MonotonicFluxLimiter
  responsible party:
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      individual name:
        character string: Chris Jones
      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
    CI responsible party:
      individual name:
        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
    CI responsible party:
      individual name:
        character string: Malcolm Roberts
      role: CI RoleCode
    abbreviation: Malcolm Roberts
  responsible party:
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      individual name:
        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  citation:
    CI citation:
      title:
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  description: Isopycnal diffusivity takes a constant value of 500 m2 s-1 using the Griffies et al. (1998) scheme; the Gent and McWilliams (1990) adiabatic mixing scheme in the skew flux form (Griffies 1998) is used with a spatially and temporally varying coefficient (Visbeck et al. 1997; Roberts 2004), a minimum value of 150 m2s-1 and maximum of 2000 m2s-1, and spatial distribution with higher values in the western boundary currents and Antarctic Circumpolar Current. The biharmonic adiabatic scheme of Roberts and Marshall (1998) is used with a coefficient of 1.0e+12 cos3(latitude) m4 s-1. The cos(latitude) factor is required for numerical reasons owing to the convergence of meridians at high latitude. Horizontally aligned biharmonic tracer mixing in the top 20m (top two model layers), with coefficient 2.5e+12 cos3(latitude) m4 s-1 is included to partially represent enhanced mixing at the ocean surface. Momentum diffusion uses both a modified Laplacian scheme with a coefficient of 750(1-cos(latitude)) m2s-1 (modified to reduce the westward currents on the equator, giving better agreement with observations) and a biharmonic scheme with coefficient 1.0e+13 cos3(lat) m4 s-1.
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      document version: 1
      document creation date: 2010-09-30T11:13:16.187000
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  description: There is no reference salinity, instead salinity limits are applied: 5-45 psu. An enhancement of the vertical and horizontal diffusion in the ocean wherever a river outflow occurs has been introduced to correct a known systematic salty bias close to the Amazon at a depth of 150m.
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  document creation date: 2010-09-30T11:13:16.406000

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  long name: Ocean Vertical Physics
  description: Convective mixing in the model uses the Rahmstorf (1993) full convection scheme. The equation of state remains the UNESCO 1981 polynomial approximation. There are limits on the model surface salinity which is not allowed to go outside the range 5 - 45 psu. The vertical tracer diffusivity has been lowered in the upper 1000m of the ocean to the edge of the uncertainty range. This has the effect of reducing mixing with the cooler subsurface water, increasing the SSTs and alleviating the subsurface cooling in the tropics.
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    CI citation: date
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      short name: Ocean Interior Mixing
      long name: Ocean Interior Mixing
      description: needs text
      responsible party:
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      responsible party:
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      document version: 1
      document creation date: 2010-09-30T11:13:17.390000
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      long name: Ocean Mixed Layer
      description: The mixed layer is represented by the Kraus and Turner (1967) bulk mixed layer for tracers, together with a quadratic representation of the Large et al. (1994) scheme for momentum mixing in the mixed layer. Vertical mixing beneath the mixed layer is performed by the Peters et al. (1988) scheme; this is a Richardson-number dependent scheme, and its parameters have been altered to better fit the observed data in their paper by Cusack (2004). This change reduces the excessive noise near the ocean surface. There is also a modification to the standard vertical mixing scheme to enhance the mixing at the base of the mixed layer, to increase the communication between the ocean surface and the deeper layers and make the profile more similar to that observed.
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      document creation date: 2010-09-30T11:13:17.906000
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model component:
  short name: OceanSunlightPenetration
  long name: OceanSunlightPenetration
  description: A two band scheme (one more penetrative) from Paulson and Simpson (1977), assuming pure water type 1B with coefficients adjusted.
  responsible party:
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        character string: Chris Jones
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    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
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        character string: Malcolm Roberts
      role: CI RoleCode
    abbreviation: Malcolm Roberts
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  document creation date: 2010-09-30T11:13:18.015000

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abbreviation: Chris Jones

delivery point:
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electronic mail address: CharacterString

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    character string: UK Met Office Hadley Centre
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abbreviation: MOHC

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abbreviation: Ian Totterdell

delivery point:
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electronic mail address: CharacterString

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    character string: UK Met Office Hadley Centre
  role: CI RoleCode
abbreviation: MOHC

model component:
  short name: Ocean Bio Boundary Forcing
  long name: Ocean Biogeo Chemistry Boundary Forcing
  description: There are no exchanges of biogeochemical variables with the land (including rivers), with sea-ice or with the sea-floor sediments (which are not included in the model). Only the air-sea interface has any forcing for the ocean biogeochemistry directly. Dust from the atmospheric model is deposited on the ocean and absorbed in the top layer; its soluble iron content is added to the dissolved iron in the water and is available for biological uptake and can be transported like any other ocean tracer. In the atmospheric model the rate of dust deposition is calculated in six size classes and by four deposition processes, but on being passed to the ocean all these combinations are summed to get the total deposition. DMS is passed from the ocean to the atmosphere, but the atmospheric concentration is assumed to be zero in the calculation so there is no air-to-sea flux. In the case of CO2 the flux is calculated in both directions, with the atmospheric pCO2 required for the calculation being prescribed as specified in the CMIP5 protocols. For both DMS and CO2 the piston velocity uses the 10m wind-speed, passed from the atmosphere. In the case of dissolved oxygen, which is a prognostic tracer but whose concentration does not affect any other biogeochemical process, the surface ocean layer is assumed to be 3% over-saturated, the saturation being determined according to Equation 8 on p1310 of Garcia and Gordon (1992), modified by removing the incorrect term on the first line as indicated in the o2sato.f function in the OCMIP-2 Biotic-HOWTO document (www.ipsl.jussieu.fr/OCMIP/). The flux is determined by the change in the top-layer ocean concentration required to achieve that oversaturation, and is applied to the ocean concentration but not the atmosphere, and no forcing from the atmosphere is required. More details of the gas exchange formulations is given in the Ocean Bio Gas Exchange component. Note that all information passed from the atmosphere is passed through the coupler, …
  component properties:
    component property:
      short name: AtmosphericDeposition
      long name: AtmosphericDeposition
    component property:
      short name: RiverInput
      long name: RiverInput
    component property:
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      long name: SedimentInteractions
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    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
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      role: CI RoleCode
    abbreviation: Ian Totterdell
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        character string: UK Met Office Hadley Centre
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      collective title:
        character string: Garcia, H.E. & Gordon, L.I. (1992) Oxygen solubility in seawater: Better fitting equations. Limnol. Oceanogr., 37, 1307-1312
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  document creation date: 2010-09-30T11:13:18.296000

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model component:
  short name: Ocean Bio Chemistry
  component properties:
    component property:
      short name: CarbonChemistry
      long name: CarbonChemistry
      component property:
        short name: pH-scale
        long name: pH-scale
      component property:
        short name: CarbonChemConstants
        long name: CarbonChemConstants
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    abbreviation: Ian Totterdell
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  short name: Ocean Bio Gas Exchange
  long name: Ocean Bio Gas Exchange
  description: The gasses exchanged between the ocean and atmosphere are DMS (only ocean to air) and CO2 (both directions). Oxygen is not passed between ocean and atmosphere although it exists as a tracer in both models and the ocean tracer has a surface boundary condition as described in the preceding section Ocean Bio Boundary Forcing. For both DMS and CO2 the air-sea flux is calculated each (ocean) time-step in the ocean model and applied to the appropriate ocean tracers; the daily mean flux is passed through the coupler (once a day) to the atmospheric model. In the case of DMS there is no attempt to model the sulphur cycle in the ocean, a simple parameterisation being used to calculate the surface ocean concentration of DMS and thence the flux out of the ocean. The parameterisation used is that of Simo and Dachs (2002), which sets the DMS concentration as a function of chlorophyll divided by the mixed layer depth while that ratio is greater than 0.02 mg-Chla/m^2, and as a function of the log of the mixed layer depth otherwise. However, here in the latter case if the mixed layer is more than 182.536 m the scheme of Aranami & Tsunogai (2004), which make the DMS concentration inversely proportional to the mixed layer depth, is used to avoid negative concentrations. In all cases the chlorophyll is calculated from the non-diatom phytoplankton concentration only, and the mixed layer depth is calculated according to the 0.5C temperature criterion. The Schmidt number for DMS is calculated according to Saltzman et al. (1993). In the case of CO2 the atmospheric pCO2 (time-varying and prescribed according to CMIP5 protocols) is converted from partial pressure (in ppmv) to Moles-C/kg-seawater using the solubility parameterisation of Weiss (1974). The concentration of carbonic acid ([H2CO3], taken to include dissolved CO2 gas) is calculated from the model DIC and TAlk concentrations and the model temperature and salinity. The definition of TAlk used is [HCO3(-)] + 2[CO3(2-)] + [B(OH)4(-)] …
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      long name: CO2
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      short name: O2
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        long name: SchemeType
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        short name: Present
        long name: Present
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        long name: Present
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        long name: SchemeType
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        long name: Present
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        character string: UK Met Office Hadley Centre
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    abbreviation: MOHC
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        character string: Ian Totterdell
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    abbreviation: Ian Totterdell
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        character string: doi:10.1029/2003JD004288
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        character string: Aranami, K. & Tsunogai, S. (2004) Seasonal and regional comparison of oceanic and atmospheric dimethylsulfide in the northern North Pacific: Dilution effects on its concentration during winter J. Geophys. Res., 109, D12303,
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        character string: Dickson, A.G. (1990) Thermodynamics of the dissociation of boric acid in synthetic seawater from 273.15 to 318.15 K, Deep-Sea Res., 37, 755-766
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        character string: US Dept. of Energy. (1994) Handbook of methods for the analysis of the various parameters of the carbon dioxide system in sea water; version 2. Dickson, A.G. & Goyet, C., editors, ORNL/CDIAC-74
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        character string: Jahne, B., Heinz, G. & Dietrich, W. (1987) Measurement of the diffusion coefficients of sparingly soluble gases in water with a modified Barrer method, J. Geophys. Res., 92, 10,767-10,776
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        character string: Peng, T.-H., Takahashi, T., Broecker, W.S. & Olafsson J. (1987) Seasonal variability of carbon dioxide, nutrients and oxygen in the northern North Atlantic surface water: observations and a model, Tellus, 39B, 439-458
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        character string: Roy, R.N., Roy, L.N., Vogel, K.M., Porter-Moore, C.,Pearson, T., Good, C.E., Millero, F.J. & Campbell, D.M. (1993) The dissociation constants of carbonic acid in seawater at salinities 5 to 45 and temperatures 0 to 45C, Mar. Chem., 44, 249-267
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        character string: Saltzman, E.S., King, D.B., Holmen, K. & Leck, C. (1993) Experimental Determination of the Diffusion Coefficient of Dimethylsulfide in Water J. Geophys. Res., 98C, 16481-16486
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        character string: Simo, R. & Dachs, J. (2002) Global ocean emission of dimethylsulfide predicted from biogeophysical data, Global Biogeochem. Cycles, 16(4), 1018
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        character string: Weiss, R.F. (1974) Carbon dioxide in water and seawater: The solubility of a non-ideal gas. Mar. Chem., 2, 203-215
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  document creation date: 2010-09-30T11:13:19.140000

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model component:
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  long name: Ocean Bio Key Properties
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      long name: BasicApproximations
    component property:
      short name: ListOfPrognosticVariables
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      component property:
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        long name: LonMin
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      component property:
        short name: UpperLevel
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        long name: LowerLevel
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      short name: Transport
      long name: Transport
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    abbreviation: MOHC
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      long name: Ocean Bio Time Step Framework
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        abbreviation: MOHC
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      document creation date: 2010-09-30T11:13:19.812000
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short name: PassiveTracers
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short name: Biology
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model component:
  short name: Ocean Bio Tracers
  long name: Ocean Bio Tracers
  description: The fourteen ocean biogeochemical tracers are: dissolved inorganic carbon (DIC); total alkalinity (TAlk); dissolved oxygen; and the eleven ocean ecosystem tracers, as described in the Ocean Bio Tracers Ecosystem component including dissolved inorganic nitrogen (DIN), dissolved silicate, total dissolved iron, diatom nitrogen, diatom silicate, other non-diatom phytoplankton nitrogen, zooplankton nitrogen, detrital nitrogen, detrital carbon, detrital silicate and dissolved ammonium. Dissolved inorganic carbon (DIC): equal to [H2CO3] + [HCO3(-)] + [CO3(2-)],here [H2CO3] is taken to include both carbonic acid and dissolved CO2 gas. It is taken up, in a fixed ratio to nitrogen, by diatoms and other non-diatom phytoplankton during growth (but does not limit their rates of growth). It is recycled through the natural mortalities of diatoms, other non-diatom phytoplankton and zooplankton, zooplankton respiration and messy feeding and by remineralisation of detrital carbon. It has an exchange with the atmosphere, as defined in the Ocean Bio Gas Exchange component Units are mMoles-C/m3; Total alkalinity (TAlk): defined as [HCO3(-)] + 2[CO3(2-)] + [B(OH)4(-)] + [OH(-)] [H(+)]. Biological processes affect TAlk in two ways: when one unit of DIN is taken up (or released) one unit of TAlk is released (taken up), following Goldman and Brewer (1980), and when one unit of calcium carbonate is formed (or dissolved) two units of TAlk are taken up (released). Units are mEquivalents/m^3; Dissolved oxygen: when one unit of DIC is taken up (or released) by biology (except for calcium carbonate formation or dissolution), one unit of dissolved oxygen is released (taken up). The surface ocean boundary condition for dissolved oxygen is described in Ocean Bio Boundary Forcing component. Units are nMoles-O2/m^3.
  component properties:
    component property:
      short name: SulfurCycle
      long name: SulfurCycle
    component property:
      short name: Nutrients
      long name: Nutrients
      component property:
        short name: NitrousSpecies
        long name: NitrousSpecies
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        short name: Processes
        long name: Processes
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        long name: ListOfSpecies
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      long name: DisolvedOrganicMatter
      component property:
        short name: Lability
        long name: Lability
      component property:
        short name: BacteriaRepresentation
        long name: BacteriaRepresentation
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      short name: Particules
      long name: Particules
      component property:
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        long name: TypesOfParticules
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        short name: SizeSpectrum
        long name: SizeSpectrum
      component property:
        short name: SinkingSpeed
        long name: SinkingSpeed
      component property:
        short name: Method
        long name: Method
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      role: CI RoleCode
    abbreviation: Chris Jones
  responsible party:
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
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      role: CI RoleCode
    abbreviation: Ian Totterdell
  responsible party:
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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        character string: Goldman, J.C. & Brewer, P.G. (1980) Effect of nitrogen source and growth rate on phytoplankton-mediated changes in alkalinity Limnol. Oceanogr., 25, 352-357
    CI citation: date
  child component:
    model component:
      short name: Ocean Bio Tracers Ecosystem
      long name: Ocean Bio Tracers Ecosystem
      description: The eleven ocean ecosystem tracers are: a) Nutrients: - dissolved inorganic nitrogen (DIN): the sum of dissolved nitrate (and nitrite) and ammonium; units mMoles-N/m^3. The initial field at the start of the spinup was from the World Ocean Atlas (2005). Taken up by diatoms and other non-diatom phytoplankton, recycled from those compartments and from zooplankton and detrital nitrogen. - dissolved ammonium: optional prognostic tracer, but the rate of diatom and other non-diatom phytoplankton growth rates do not depend on its concentration because they depend on DIN, which includes dissolved ammonia. The cycle of dissolved ammonia is calculated in parallel with that of DIN, so that the cycle of dissolved nitrate (which is not a tracer, but the difference between DIN and ammonium) can be inferred. Units are mMoles-N/m^3. - dissolved silicate: taken up by diatoms for shell formation, recycled from detrital silicate (by dissolution). Units are mMoles-Si/m^3. - dissolved iron: taken up by diatoms and other non-diatom phytoplankton, recycled from those compartments and from zooplankton (no iron is present in detritus). Atmospheric dust deposited on the ocean is a source of dissolved iron. Although all the dissolved iron is available for biological uptake only the free (non-complexed) iron can be adsorbed onto (implicit) mineral particles and removed permanently from the model ocean. To calculate the partition between free and complexed iron a constant density of total (free and complexed) ligand and a partition constant are assumed. Units are uMoles-Fe/m^3. b) Living organisms: - diatoms: described in terms of their nitrogen content (units: mMoles-N/m^3). Their growth is limited by [DIN], dissolved silicate and light. They are subject to predation by the zooplankton and to natural mortality, and they sink at 1 m/day. The rate at which they take up silicate is a factor times the DIN uptake rate, the factor being a function of the dissolved iron concentration with a high Si:N …
      responsible party:
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      responsible party:
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      responsible party:
        abbreviation: Ian Totterdell
      responsible party:
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      document version: 1
      document creation date: 2010-09-30T11:13:20.656000
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short name: UpperTrophicLevels
long name: UpperTrophicLevels

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short name: Zooplancton
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  character string: Fasham, M.J.R., Ducklow, H.W. & McKelvie, S.M. (1990) A nitrogen-based model of plankton dynamics in the oceanic mixed layer J. Mar. Res., 48, 591-639

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    character string: UK Met Office Hadley Centre
  role: CI RoleCode
abbreviation: MOHC

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abbreviation: Helene Hewitt

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  collective title:
    character string: Thorndike, A. S., D. A. Rothrock, G. A. Maykut and R. Colony (1975) The thickness distribution of sea ice. Journal of Geophysical Research, 80, 4501-4513.
CI citation: date

model component:
  short name: Sea Ice Albedo
  long name: Sea Ice Albedo
  description: The ice albedo scheme is based on the scheme of Ebert and Curry (1993) with a parameterisation based on SHEBA observations. The bare ice albedo is modified (Semtner 1987) to simulate internal scattering processes in the zero layer scheme, which act to delay the onset of melt. In addition, the snow parameterisation scheme used in the land surface scheme is included, which allows for partial and semi-transparent snow cover. The snow albedo is modified by surface temperature, representing the increase in liquid water content. As a consequence the surface albedo, in addition to surface air temperature, is highly responsive to modelled snow fall events.
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    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
  responsible party:
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      individual name:
        character string: Helene Hewitt
      role: CI RoleCode
    abbreviation: Helene Hewitt
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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        character string: Semtner A., (1987) A numerical study of sea ice and ocean circulation in the Arctic.. Journal of Physical Oceanography, 17, 1077-1099.
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  type: SeaIceAlbedo user_defined
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  document creation date: 2010-09-30T11:13:20.906000

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model component:
  short name: Sea Ice Dynamics
  long name: Sea Ice Dynamics
  description: The ice velocities are computed using the Elastic-Viscous-Plastic dynamics of Hunke and Dukowitz (1997). The ice momentum and stress state equations are solved to balance the effect of wind stress, ocean currents, Coriolis term and the internal ice stresses while maintaining a viscous plastic ice rheology. Ice is allowed to flow across the North Pole despite the ocean model having a polar island. Ice is advected using a first-order upwind advection scheme. The mechanical redistribution (or ridging scheme) of the Los Alamos CICE model (Hunke and Lipscomb, 2004) is also included, which can convert thinner ice to thicker ice within a grid box.
  component properties:
    component property:
      short name: Rheology
      long name: Rheology
    component property:
      short name: Advection
      long name: Advection
    component property:
      short name: HorizontalDiscretizationGrid
      long name: HorizontalDiscretizationGrid
    component property:
      short name: Redistribution
      long name: Redistribution
      component property:
        short name: Type
        long name: Type
      component property:
        short name: IceStrengthFormulation
        long name: IceStrengthFormulation
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    abbreviation: Chris Jones
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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        character string: Helene Hewitt
      role: CI RoleCode
    abbreviation: Helene Hewitt
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    abbreviation: MOHC
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      collective title:
        character string: Hunke E., and J. Dukowicz (1997) An elastic-viscous-plastic model for sea-ice dynamics. Journal of Physical Oceanography, 27, 1849-1867.
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      collective title:
        character string: Hunke E. and Lipscomb W. (2004) CICE: The Los Alamos Sea Ice Model, documentation and software, version 3.1. LA-CC-98-16, Los Alamos Natl. Lab., U.S.A.
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  document creation date: 2010-09-30T11:13:21.140000

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      URL: http://www.metoffice.gov.uk/research/out-scientists/cryosphere-oceans/helene-hewitt

model component:
  short name: Sea Ice Key Properties
  long name: Sea Ice Key Properties
  component properties:
    component property:
      short name: BasicApproximations
      long name: BasicApproximations
    component property:
      short name: ListOfPrognosticVariables
      long name: ListOfPrognosticVariables
    component property:
      short name: SeaIceRepresentation
      long name: SeaIceRepresentation
      component property:
        short name: IceTypesScheme
        long name: IceTypesScheme
      component property:
        short name: Multi-LevelsScheme
        long name: Multi-LevelsScheme
      component property:
        short name: SchemeType
        long name: SchemeType
    component property:
      short name: TimeSteppingFramework
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      component property:
        short name: TimeStep
        long name: TimeStep
      component property:
        short name: Method
        long name: Method
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    abbreviation: MOHC
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  document creation date: 2010-09-30T11:13:21.546000

model component:
  short name: Sea Ice Thermodynamics
  long name: Sea Ice Thermodynamics
  description: The zero-layer thermodynamics model of Semtner (1976) is used which is applied separately to each ice thickness category. There is a one snow layer on top of the ice in each category. Once the thermodynamic ice and snow growth rates have been calculated, the linear remapping scheme of Lipscomb (2001) is used to compute the transfer of ice between categories. Ocean to ice heat flux parameterisation uses the McPhee scheme that uses both the ocean-ice temperature difference and the friction velocity in the flux parameterisation (McPhee, 1992). The ocean-ice heat flux is proportional to the ice concentration for concentrations greater than 0.05. For lower concentrations, the grid box integral of the heat flux is independent of concentration to simulate the increased heat flux on small floes in the marginal ice zone.
  component properties:
    component property:
      short name: WaterPonds
      long name: WaterPonds
    component property:
      short name: SurfaceAlbedo
      long name: SurfaceAlbedo
    component property:
      short name: NewIceFormation
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    component property:
      short name: Snow
      long name: Snow
      component property:
        short name: HeatDiffusion
        long name: HeatDiffusion
      component property:
        short name: SchemeType
        long name: SchemeType
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      short name: Ice
      long name: Ice
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        short name: NumberOfLayers
        long name: NumberOfLayers
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        short name: VerticalHeatDiffusion
        long name: VerticalHeatDiffusion
      component property:
        short name: OceanToIceBasalHeatFlux
        long name: OceanToIceBasalHeatFlux
      component property:
        short name: BrineInclusions
        long name: BrineInclusions
      component property:
        short name: Processes
        long name: Processes
      component property:
        short name: TransportInThicknessSpace
        long name: TransportInThicknessSpace
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      role: CI RoleCode
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        character string: UK Met Office Hadley Centre
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    abbreviation: MOHC
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      individual name:
        character string: Helene Hewitt
      role: CI RoleCode
    abbreviation: Helene Hewitt
  responsible party:
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        character string: UK Met Office Hadley Centre
      role: CI RoleCode
    abbreviation: MOHC
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      collective title:
        character string: Lipscomb W., (2001) Remapping the thickness distribution in sea ice models.. Journal of Geophysical Research, 106, 13989-14000
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        character string: McPhee 1992
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      collective title:
        character string: McPhee M. G., (1992) Turbulent heat-flux in the upper ocean under sea ice.. Journal of Geophysical Research-Oceans, American Geophysical Union, 97(C4), 5365-5379.
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        character string: Semtner 1976
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      collective title:
        character string: Semtner A., (1976) A model for the thermodynamic growth of sea ice in numerical investigations of climate.. Journal of Physical Oceanography, 6, 379-389
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  document creation date: 2010-09-30T11:13:22.046000

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description: The HadGEM2-ES model was a two stage development from HadGEM1, representing improvements in the physical model (leading to HadGEM2-AO) and the addition of earth system components and coupling (leading to HadGEM2-ES).
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