HadGEM2-ESHadley Global Environment Model 2 - Earth SystemThe 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).
[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 oceans. The diat-HadOCC scheme is an improvement over the standard HadOCC scheme as it differentiates between diatom and non-diatom plankton. These have different processes for removing carbon from the surface to the deep ocean, and respond differently to iron nutrients. The HadOCC scheme performs well with very reasonable plankton distributions, rates of productivity and emissions of DMS. The diat-HadOCC scheme has slightly too low levels of productivity which requires further tuning to overcome.
The additions of a tropospheric chemistry scheme, new aerosol species (organic carbon and dust) and coupling between the chemistry and sulphate aerosols have significantly enhanced the earth system capabilities of the model. This has improved the tropospheric ozone distribution and the distributions of aerosol species compared to observations, both of which are important for climate forcing.
Including interactive earth system components has not significantly affected the physical performance of the model. Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHC2009Bellouin et al. 2007http://www.metoffice.gov.uk/publications/HCTN/HCTN_73.pdfBellouin 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 2007Collins et al. 2008http://www.metoffice.gov.uk/publications/HCTN/HCTN_74.pdfCollins 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 74AerosolsAerosolsThe 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).Aerosol Key PropertiesAerosolsAerosolSchemeScopeAerosolSchemeScopewhole atmosphereBasicApproximationsBasicApproximationsModal scheme, mass as a tracer, number inferred from prescribed size distributionsListOfPrognosticVariablesListOfPrognosticVariables3D mass/volume mixing ratio for aerosolsNumberOfTracersNumberOfTracers21FamilyApproachFamilyApproachnoAerosolTimeStepFrameworkAerosolTimeStepFrameworkMethodMethoduses AtmosphericChemistry time steppingbiomass_burningbiomass_burningEmissions of aerosols from biomass burning injected at the surface for grassfires and homogeneously throughout the boundary layer for forest fire emissions. Represented as a monthly mean field on the N96 gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfossil_fuel_black_carbonfossil_fuel_black_carbonEmissions of primary black carbon from fossil fuel and biofuel injected at 80m as a monthly mean field on the N96 gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfossil_fuel_organic_carbfossil_fuel_organic_carbEmissions of primary organic carbon from fossil fuel and biofuel injected at 80m as a monthly mean field on the N96 gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCNicolas BellouinMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/nicolas-bellouinNicolas BellouinUK Met Office Hadley CentreMOHCBellouin et al. 2007http://www.metoffice.gov.uk/publications/HCTN/HCTN_73.pdfBellouin 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 2007Aerosol Emission And ConcAerosol Emission and ConcentrationEmissions 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 the model. 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).
2D emissions: 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 the model (near-surface emissions). Anthropogenic emissions for biomass-burning aerosol are the sum of IPCC AR5 emissions for black and organic carbon from biomass-burning emissions. Grass fire emissions are assumed to be surface emissions, while forest fire emissions are distributed homogeneously across the boundary layer. Emissions based on interactive schemes: Sea-salt and mineral dust aerosol emissions are computed interactively depending on modelled near-surface wind speeds and soil properties (Jones et al., 2001; Woodward, 2001).
The only 3D aerosol-related emissions used in the model are natural emissions of sulphur dioxide from background volcanoes (Andres and Kasgnoc, 1998). Aircraft emissions of aerosol precursors or primary [aerosols] are not included in the model.2D-Emissions2D-EmissionsMethodMethodinteractiveotherSourceTypesSourceTypesanthropogenicbare groundothersea surfaceInteractivEmittedSpeciesInteractivEmittedSpeciesmineral dust, sea-salt, ocean-based DMSMethodCharacteristicsMethodCharacteristicsCMIP5 emission timeseries (monthly from linear interpolation of decadal means)EmittedSpeciesEmittedSpeciessulphur dioxide, ammonia, fossil-fuel black carbon, fossil-fuel organic carbon, biomass-burningother sourcesother sourcesnatural emissions from land surface of DMS and vegetation emissions3D-Emissions3D-EmissionsMethodMethodprescribed (climatology)SourceTypesSourceTypesothervolcanoesClimatologyTypeClimatologyTypemonthlyClimEmittedSpeciesClimEmittedSpeciessulphur dioxide from degassing volcanoes, secondary organic aerosolConcentrationsConcentrationsPrescribedLowerBoundaryPrescribedLowerBoundaryN/APrescribedUpperBoundaryPrescribedUpperBoundaryN/APrescribedWithinAtmosPrescribedWithinAtmosbiogenic aerosolChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCNicolas BellouinMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/nicolas-bellouinNicolas BellouinUK Met Office Hadley CentreMOHCAndres 1998Andres, R.J. and Kasgnoc, A.D. (1998) A time-averaged inventory of subaerial volcanic sulfur emissions. J. Geophys. Res., 103, 25251-25261, 1998. Bellouin et al. 2007http://www.metoffice.gov.uk/publications/HCTN/HCTN_73.pdfBellouin 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 2007Derwent 2003Derwent, 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.Jones 2001Jones 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. Lamarque 2009Lamarque, J.F. et al. (2009) Gridded emissions in support of IPCC AR5.. IGACtivities 41, 12-18, May 2009. Moss 2010Moss, R.H., et al. (2010) The next generation of scenarios for climate change research and assessment. Nature, 463, 747-756, doi:10.1038/nature08823Spiro 1992Spiro, 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. Woodward 2001Woodward 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. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30fcfc22-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:42.696910Aerosol ModelAerosol ModelThe 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 the interactive tropospheric chemistry scheme and depleted oxidants are fed back to the chemistry (alternatively, oxidant concentrations can be prescribed). Emissions of dimethylsulphide from the ocean is provided by the ocean biogeochemistry scheme. The sea salt scheme is a simple diagnostic scheme depending on wind speed and height above the surface to determine the number concentration of sea salt particles in two size modes (Jones et al., 2001). Schemes for black carbon from fossil-fuel emissions (Roberts and Jones, 2004), biomass-burning, and organic carbon from fossil-fuel emissions (Collins et al, 2008) include modes for freshly emitted particles that gradually age into another, more hygroscopic mode; there is also a mode for aerosols that have become incorporated into cloud droplets. Black carbon is considered to be slightly hygroscopic, only becoming incorporated into cloud droplets by diffusion, whereas organic carbon and biomass-burning aerosols are considered to act as cloud condensation nuclei. The mineral dust scheme is based on Woodward (2001) with further improvements made to the dust emission scheme (described in Collins et al, 2008): changes to values of the impact threshold friction velocity and parameterisation of the effect of soil moisture. The modelled horizontal flux includes a wide size range of particles from .06 to 2000 microns in 9 bins. Vertical flux is calculated for particles up to 60 microns in 6 bins, the size distribution following that of the horizontal flux in this range.ProcessesProcessesadvection (horizontal)advection (vertical)ageingcoagulationcondensationdry depositionoxidation (gas phase)oxidation (in cloud)sedimentationwet deposition (impaction scavenging)wet deposition (nucleation scavenging)CouplingWithCouplingWithCloudsLandSurfaceotherRadiationGasPhasePrecursorsGasPhasePrecursorsammoniaDMSSO2vegetation model couplingvegetation model couplingbare soil fraction for mineral dust emissionsocean biogeochemical couplingocean biogeochemical couplingprovides ocean-based DMS emissions, and is fertilised by mineral dust depositionAerosolSchemeAerosolSchemeSchemeTypeSchemeTypebulkBulkSpeciesBulkSpeciesBC (black carbon / soot)dustnitratePOM (particulate organic matter)sea saltSOA (secondary organic aerosols)sulphateChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCNicolas BellouinMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/nicolas-bellouinNicolas BellouinUK Met Office Hadley CentreMOHCBellouin et al. 2007http://www.metoffice.gov.uk/publications/HCTN/HCTN_73.pdfBellouin 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 2007Collins et al. 2008http://www.metoffice.gov.uk/publications/HCTN/HCTN_74.pdfCollins 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 74Jones 2001Jones 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. Roberts & Jones 2004doi: 10.1029/2004JD004676. Roberts D.L., and A. Jones (2004) Climate sensitivity to black carbon aerosol from fossil fuel combustion. J. Geophys. Resr., 109, Woodward 2001Woodward 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. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk31536f94-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:42.779208Aerosol TransportAerosol TransportAerosol transport is done by the HadGEM2-ES tracer advection scheme, which includes large-scale advection (Davies et al. 2005), convective transport (Gregory and Rowntree, 1990), and boundary layer mixing (Lock et al., 2000). MethodMethoduses AtmosphericChemistry transport schemeTurbulenceTurbulenceMethodMethoduse same turbulence scheme as AtmosphericChemistryChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCNicolas BellouinMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/nicolas-bellouinNicolas BellouinUK Met Office Hadley CentreMOHCDavies 2005Davies T., M. J. P. Cullen, A. J. Malcolm, M. H. Mawson, A. Staniforth, A. A. White, and N. Wood (2005) A new dynamical core for the Met Office's global and regional modelling of the atmosphere.. Quarterly Journal Royal Meteorology Society, 131, 1759-1782. Gregory 1990Gregory J., and P.R. Rowntree (1990) A mass flux convection scheme with representation of cloud ensemble characteristics and stability - dependent closure.. Monthly Weather Review, 118, 1483-1506. Lock 2000Lock A.P., A.R. Brown, M.R. Bush, G.M. Martin, R.N.B. Smith et al. (2000) A new boundary layer mixing scheme. Part I: scheme description and single column model tests.. Monthly Weather Review, American Meteorological Society, 128, 3187-3199. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30e4b5b8-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:42.811626metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDRS_CMIP5_componentTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30ba0df4-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:42.811727AtmosphereAtmosphereThe 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). Atmos Key PropertiesAtmosphere Top Of Atmos InsolationTop of Atmosphere InsolationImpactOnOzoneImpactOnOzonenoSolarConstantSolarConstantTypeTypetransientCharacteristicsCharacteristicsnormalised to give a mean solar constant of 1365 Wm-2 over the 2 solar cycles 1860-1881.OrbitalParametersOrbitalParametersTypeTypefixedComputationMethodComputationMethodBerger 1978ReferenceDateReferenceDate2000ModelFamilyModelFamilyAGCMBasicApproximationsBasicApproximationsnon-hydrostaticVolcanoesImplementationVolcanoesImplementationvia stratospheric aerosols optical thicknessVolcanoesImplementationMethodVolcanoesImplementationMethodmonthly stratospheric optical depths, at 550nm, prescribed for quarter-spheres (90S-30S, 30S-0, 0-30N, 30N-90N)OrographyOrographyOrographyTypeOrographyTypepresent-dayanthro_SO2_aerosolanthro_SO2_aerosolAnthropogenic sulphur dioxide emissions injected at the surface, except for energy emissions and half of industrial emissions which are injected at 0.5 km to represent chimney-level emissions. unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkbiogenic_emission_aerosobiogenic_emission_aeroso3D concentrations of organic aerosols from biogenic emissions. [CHECK cf name and short name]unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkland DMS emissionsland DMS emissionsConstant for land-based emissions amounting to 0.86 Tg/yr from Spiro et al., 1992)unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkocean_DMS_emissionsocean_DMS_emissionsOcean dimethyl sulphide emissionsunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksolar irradiancesolar irradianceAnnual mean total solar radianceunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkvolcanic aerosolvolcanic aerosolStratospheric aerosol concentrations due to volcanic eruptions represented as optical thickness at 550nmunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkvolcanic SO2 emissionsvolcanic SO2 emissions3D background emissions of sulphur dioxide from degassing volcanoes taken from Andres and Kasgnoc (1998). [This does not include SO2 emissions from biomass burning)unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gas_CFC-12well_mixed_gas_CFC-12Halocarbons (CFCs and related gases) are supplied as equivalent concentrations of CFC-12 and HFC-134a made available from the CMIP5 database, expressed as a mass mixing ratio (kg/kg). These species represent the total radiative forcing from 27 halocarbon species. unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gas_CH4well_mixed_gas_CH4Surface methane concentrations prescribed as a single global constant provided as an annual number but added as a 2D surface and interpolated in the model at each timestep. unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gas_CO2well_mixed_gas_CO2CO2 concentrations prescribed as a single global constant provided as an annual number but interpolated in the model at each timestep. Provided as a mass mixing ratio with units of kg/kg. CO2 concentrations are passed to the model's radiation scheme, terrestrial carbon cycle and ocean carbon cycle.unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gas_HFC-134awell_mixed_gas_HFC-134aHalocarbons (CFCs and related gases) are supplied as equivalent concentrations of CFC-12 and HFC-134a made available from the CMIP5 database, expressed as a mass mixing ratio (kg/kg). These species represent the total radiative forcing from 27 halocarbon species.
CF: mass_fraction_of_hfc134a_in_air (awaiting entry into CF-names)unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gas_N2Owell_mixed_gas_N2ON2O concentrations prescribed as a time series of annual global mean concentrations in all CMIP5 simulations. Concentrations used were interpolated from the annual concentrations every time step and passed to the models radiation scheme. unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gas_Ozonewell_mixed_gas_OzoneStratospheric Ozone prescribed as monthly 3D field derived from the CMIP5 recommended AC&C/SPARC ozone databaseunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHC2010Davies 2005Davies T., M. J. P. Cullen, A. J. Malcolm, M. H. Mawson, A. Staniforth, A. A. White, and N. Wood (2005) A new dynamical core for the Met Office's global and regional modelling of the atmosphere.. Quarterly Journal Royal Meteorology Society, 131, 1759-1782. Atmos Convect Turbul CloudAtmospheric Convective Turbulent CloudThe convection scheme is based on the mass flux scheme of Gregory and Rowntree (1990) but with major modifications. The scheme is explicitly coupled to the boundary layer scheme, and cumulus convection is similarly diagnosed using the mean humidity profile. If cumulus convection is diagnosed, then the boundary layer scheme is capped at the convective cloud base. The convection scheme is then triggered from the lifting condensation level in order to parameterize transports from cloud base upward. Deep and shallow convection are diagnosed separately and different thermodynamic closures are applied. In shallow convection the closure is based on Grant (2001); for deep convection a CAPE closure is used, based on Fritsch and Chappell (1980). A convective momentum transport (CMT) parameterization is used for both deep and shallow convection, based on a flux-gradient relationship obtained from the stress budget. A cloud-base closure for CMT is used, based on the assumption that large-scale horizontal pressure gradients should be continuous across cloud base. Entrainment and detrainment rates for shallow convection are parameterized as in Grant and Brown (1999). The radiative effects of convective anvils are represented by specifying a vertically varying convective cloud amount (Gregory 1999). The model includes adaptive detrainment parametrization to produce smoother mass-flux profiles and more realistic diabatic heating profiles. In addition the depth criterion for shallow convection has been removed to allow shallower clouds to rain provided their water content is sufficiently high. BoundaryLayerTurbulenceBoundaryLayerTurbulenceSchemeNameSchemeNameotherSchemeTypeSchemeTypevertical profile of KzCounterGradientCounterGradientyesDeepConvectionDeepConvectionSchemeNameSchemeNameGregory and RowntreeSchemeTypeSchemeTypemass-fluxProcessesProcessesconvective momentum transport (CMT)detrainmententrainmentradiative effects of anvilsupdrafts and downdraftsSchemeMethodSchemeMethodCAPEShallowConvectionShallowConvectionMethodMethodsame as deep (unified)OtherConvectionOtherConvectionSchemeNameSchemeNameMid-Level ConvectionSchemeTypeSchemeTypemass-fluxLargeScalePrecipitationLargeScalePrecipitationSchemeNameSchemeNameWilson and Ballard (1999; updated)PrecipitatingHydrometeorsPrecipitatingHydrometeorsgraupelhailliquid rainsnowMicrophysicsMicrophysicsSchemeNameSchemeNameSmith (1990) for cloud amount and cloud water content; Wilson and Ballard (1999, updated) for cloud microphysicsProcessesProcessescloud dropletscloud iceeffect of graupeleffect of raindropseffect of snowice nucleationmixed phasewater vapour depositionChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCDerbyshire 2010Derbyshire S.H., A. V. Maidens, S. F. Milton, R. A. Stratton and M. R. Willett (2010) Adaptive detrainment in a convective parametrization. Submitted to Q.J. Royal Meteorol. Soc. Fritsch 1980 Fritsch J. M., and C. F. Chappell (1980) Numerical prediction of convectively driven mesoscale pressure systems - Part I: Convective parameterization.. Journal of Atmospheric Sciences, 37, 1722-1733. Grant 1999Grant A.L.M., and A. R. Brown, (1999) A similarity hypothesis for shallow cumulus transports.. Quarterly Journal of Royal Meteorological Society, 125, 1913-1936. Grant 2001Grant A.L.M., (2001) Cloud base fluxes in the cumulus-capped boundary layer.. Quarterly Journal of Royal Meteorological Society, 127: 407-421. Gregory 1990Gregory J., and P.R. Rowntree (1990) A mass flux convection scheme with representation of cloud ensemble characteristics and stability - dependent closure.. Monthly Weather Review, 118, 1483-1506. Gregory 1999Gregory J., (1999) Representation of the radiative effects of convective anvils.. Hadley Centre Technical Note 7., Met. Office, Exeter Lock 2000Lock A.P., A.R. Brown, M.R. Bush, G.M. Martin, R.N.B. Smith et al. (2000) A new boundary layer mixing scheme. Part I: scheme description and single column model tests.. Monthly Weather Review, American Meteorological Society, 128, 3187-3199. Smith 1990Smith R. N. B., (1990) A scheme for predicting layer clouds and their water content in a general circulation model. Quarterly Journal of Royal Meteorological Society, 116, 435-460. Wilson 1999Wilson D. R., and S. P. Ballard (1999) A microphysically based precipitation scheme for the Met Office Unified Model.. Quarterly Journal of Royal Meteorological Society, 125, 1607-1636. Atmos Cloud SchemeAtmospheric Cloud SchemeThe 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. CloudSchemeAttributesCloudSchemeAttributesSeparatedCloudTreatmentSeparatedCloudTreatmentyesCloudOverlapCloudOverlapotherProcessesProcessesarea cloud fraction, diagnostic RH_critCloudOverlapSchemeCloudOverlapSchemeMaximum-random overlapSubGridScaleWaterDistributionSubGridScaleWaterDistributionTypeTypediagnosticFunctionNameFunctionNamesymmetric triangular distributionFunctionOrderFunctionOrderone momentCouplingWithConvectionCouplingWithConvectioncoupled with deep and shallowChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCSmith 1990Smith R. N. B., (1990) A scheme for predicting layer clouds and their water content in a general circulation model. Quarterly Journal of Royal Meteorological Society, 116, 435-460. Wilson 1999Wilson D. R., and S. P. Ballard (1999) A microphysically based precipitation scheme for the Met Office Unified Model.. Quarterly Journal of Royal Meteorological Society, 125, 1607-1636. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk32861768-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.129805Cloud SimulatorCloud Observation Feedback PackageCOSP is a flexible software tool that enables the simulation of data from several satellite-borne sensors from model variables. It facilitates the use of satellite data to evaluate models in a process-oriented and consistent way. The flexibility of COSP makes it suitable to be used in any type of numerical model, from high-resolution cloud-resolving models to coarse-resolution models like the GCMs used in climate modeling, and the scales in between used in weather forecast models. The fact that COSP includes several simulators under the same interface facilitates the implementation of a range of simulators in models. A general description of COSP is given in Bodas-Salcedo et al. (2011). The following instrument instrument simulators are included:CloudSat (Haynes et al., 2007), CALIPSO (Chepfer et al., 2008), ISCCP (Klein and Jakob, 1999; Webb et al., 2001), MISR (Marchand and Ackerman, 2010), and MODIS.COSPAttributesCOSPAttributesCOSPRunConfigurationCOSPRunConfigurationinlineNumberOfGridpointsNumberOfGridpointsAllNumberOfColumnsNumberOfColumns100NumberOfLevelsNumberOfLevels38InputsRadarInputsRadarRadarFrequencyRadarFrequency94GhzRadarTypeRadarTypespaceborneUseGasAbsorptionUseGasAbsorptionyesUseEffectiveRadiusUseEffectiveRadiusyesInputsLidarInputsLidarLidarIceTypeLidarIceTypeIce spheresOverlapOverlapmax / randomISSCPAttributesISSCPAttributesTopHeightTopHeightIR brightness and visible optical depthTopHeightDirectionTopHeightDirectionhighest altitude levelChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCAlejandro Bodas-SalcedoMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBalejandro.bodas@metoffice.gov.ukAlejandro Bodas-SalcedoUK Met Office Hadley CentreMOHCBodas-Salcedo (2008)A. Bodas-Salcedo et al. (2008) Evaluating cloud systems in the Met Office global forecast model using simulated CloudSat radar reflectivities. J. Geophys. Res., 113, D00A13, 2008. doi:10.1029/2007JD009620.Bodas-Salcedo (2011)A. Bodas-Salcedo et al. (2011) COSP: satellite simulation software for model assessment. Bull. Am. Meteorol. Soc. submitted, 2011.Chepfer 2008H. Chepfer et al. (2008) Use of CALIPSO lidar observations to evaluate the cloudiness simulated by a climate model. Geophys. Res. Lett., 35, L15 704, 2008. doi:10.1029/2008GL034207.Haynes 2007J. M. Haynes (2007) A multipurpose radar simulation package: Quickbeam. Bull. Am. Meteorol. Soc., 88 (11), 1723-1727, doi:10.1175/BAMS-88-11-1723.Klein & Jacob 1999Klein, S.A., and C. Jakob (1999) Validation and sensitivities of frontal clouds simulated by the ECMWF model. Mon. Weather Rev., 127 (10), 2514-2531.Marchand & Ackerman 2010Marchand, R. and T. Ackerman (2010) An analysis of cloud cover in multiscale modeling framework global climate model simulations using 4 and 1 km horizontal grids. J. Geophys. Res., 115, D16 207, doi:10.1029/2009JD013423.Webb 2001Webb, M. et al., (2001) Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Clim. Dyn., 17, 905-922metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk32a2c82c-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.218706metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk32840180-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.218789Atmos Dynamical CoreAtmospheric Dynamical CoreThe 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. ListOfPrognosticVariablesListOfPrognosticVariablescloudspotential temperaturevapour/solid/liquidwind componentsTopBoundaryConditionTopBoundaryConditionradiation boundary conditionHeatTreatmentAtTopHeatTreatmentAtTopN/AWindTreatmentAtTopWindTreatmentAtTopN/ATimeSteppingFrameworkTimeSteppingFrameworkSchemeTypeSchemeTypesemi-ImplicitTimeStepTimeStep30 minutesHorizontalDiscretizationHorizontalDiscretizationSchemeTypeSchemeTypefixed gridPoleSingularityTreatmentPoleSingularityTreatmentotherSchemeMethodSchemeMethodcentered finite differencesSchemeOrderSchemeOrdersecond orderHorizontalDiffusionHorizontalDiffusionSchemeNameSchemeNamehorizontal diffusion schemeSchemeMethodSchemeMethoditerated LaplacianChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCDavies 2005Davies T., M. J. P. Cullen, A. J. Malcolm, M. H. Mawson, A. Staniforth, A. A. White, and N. Wood (2005) A new dynamical core for the Met Office's global and regional modelling of the atmosphere.. Quarterly Journal Royal Meteorology Society, 131, 1759-1782. Atmos AdvectionAtmospheric AdvectionA semi-lagrangian advection scheme is used. The advection of potential temperature, moisture, density and winds are treated separately. Moisture is conserved using a non-hydrostatic scheme. TracersTracersSchemeNameSchemeNameotherSchemeCharacteristicsSchemeCharacteristicscubic semi-Lagrangianquintic semi-LagrangianConservedQuantitiesConservedQuantitiesTracer mass (all tracers)ConservationMethodConservationMethodconservation fixerMomentumMomentumSchemeNameSchemeNameotherSchemeCharacteristicsSchemeCharacteristicsstaggered gridConservedQuantitiesConservedQuantitiesTotal energyConservationMethodConservationMethodconservation fixerStaggeringTypeStaggeringTypeArakawa C-gridSchemeNameDetailSchemeNameDetailQuasi-cubicChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCDavies 2005Davies T., M. J. P. Cullen, A. J. Malcolm, M. H. Mawson, A. Staniforth, A. A. White, and N. Wood (2005) A new dynamical core for the Met Office's global and regional modelling of the atmosphere.. Quarterly Journal Royal Meteorology Society, 131, 1759-1782. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk31ca2422-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.374493metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk31c8516a-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.374556Atmos Orography And WavesAtmosphere Orography And WavesThe gravity wave drag (GWD) scheme is that of Webster et al. (2003) and includes low-level flow blocking. The actual gravity wave drag is that due to air flowing over orography; it is deposited where wave breaking is diagnosed (typically in the lower stratosphere). The remaining drag (about 80 per cent of the total) is attributed to flow around the orography and is deposited uniformly between the surface and the subgridscale orographic height. SubGridScaleOrographySubGridScaleOrographyeffect on dragOrographicGravityWavesOrographicGravityWavesSourceMechanismsSourceMechanismslinear mountain wavesotherCalculationMethodCalculationMethodotherPropagationSchemePropagationSchemelinear theoryDissipationSchemeDissipationSchemesingle waveCalculationMethodDetailCalculationMethodDetailAccounts for the anisotropy of the sub-grid orography in calculating the surface stress.Non-OrographicGravityWavesNon-OrographicGravityWavesSourceMechanismsSourceMechanismsbackground spectrumCalculationMethodCalculationMethodspatially dependenttemporally dependentPropagationSchemePropagationSchemenon-linear theoryDissipationSchemeDissipationSchemespectralChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCWebster 2003Webster S., A.R. Brown, D.R. Cameron and C.P. Jones (2003) Improvements to the Representation of Orography in the Met Office Unified Model. Quarterly Journal of Royal Meteorological Society, 129 (591), 1989-2010 Part B.metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk331b3474-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.471227Atmos RadiationAtmospheric RadiationThe radiation code is the solution to the two-stream equations by Edwards and Slingo (1996), with some developments. It includes absorption by CO2, H2O, O3, O2, N2O, CH4 and CFCs. The longwave band from 1200 to 1500 cm-1 has been split at 1330 cm-1 in order to better represent the overlap between CH4 and N2O. Gaseous absorption is based on the updated High-Resolution Transmission (HITRAN) 2000 database (Rothman et al., 2003). The water vapour continuum is version 2.4 of the Clough-Kneizys-Davies (CKD) formulation (Clough et al., 1992) and has been included in the shortwave region. Treatment of the effects of non-spherical ice cloud particles are determined using the parameterization by KristjA?nsson et al. (2000). The sea surface albedo is based on the functional form of Barker and Li (1995), modified in the light of aircraft data, and the land-surface albedo is described by Essery et al. (2003). The direct (scattering and absorption of radiation) and indirect radiative effects of aerosols is included. TimeStepTimeStep3 hoursAerosolTypesAerosolTypesBC (black carbon / soot)dustnitratePOM (particulate organic matter)sea saltSOA (secondary organic aerosols)sulphateGHG-TypesGHG-TypesCFCCH4CO2H2ON2OO3LongwaveLongwaveSchemeTypeSchemeTypeK-correlatedSchemeMethodSchemeMethodtwo-streamNumberOfSpectralIntervalsNumberOfSpectralIntervals9ShortwaveShortwaveSchemeTypeSchemeTypeotherNumberOfSpectralIntervalsNumberOfSpectralIntervals6SchemeTypeDetailSchemeTypeDetailK-correlatedCloudRadiativePropertiesCloudRadiativePropertiesiceiceParameterised as function of ice mass mixing ratio and effective dimension.liquidliquidParameterised as function of liquid mass mixing ratio and effective radius.Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCBarker 1995Barker, H.W. and Z. Li (1995) Improved simulation of clear-sky shortwave radiative transfer in the CCC-GCM J. Climate, 8, 2213-2223 Clough 1992Clough, S.A, M.J. Iacono, and J. L. Moncet (1992) Line-by-line calculations of atmospheric fluxes and cooling rates: application to water vapour. J. Geophys. Res., 97(D14), 15671-15785Edwards 1996Edwards, J.M. and A. Slingo (1996) Studies with a flexible new radiation code. I: choosing a configuration for a large-scale model Q. J. R. Meteorol. Soc., 122, 689-720 Essery 2003Essery, R. L. H., Best, M. J., Betts, R. A., Cox, P. M., and Taylor, C. M. (2003) Explicit representation of subgrid heterogeneity in a GCM land-surface scheme J. Hydrometeorol., 43, 530-543. Kristjansson 2000Kristjansson, J.E., J.M. Edwards, and D.L. Mitchell (2000) Impact of a new scheme for optical properties of ice crystals on climates of two GCM's J. Geophys. Res., 105(D8), 10063-10079 Rothman 2003DOI: 10.1016/S0022-4073(03)00146-8Rothman, L. S., et al. (2003) The HITRAN molecular spectroscopic database: edition of 2000 including updates through 2001. J. Quant. Spectrosc. Radiat. Transfer, 82, 5-44 metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk32423fc0-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.551644metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDRS_CMIP5_componentTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk317f51b8-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.551746HADAM1Atmospheric ChemistryAtmospheric ChemistryThe 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. Atm Chem Key PropertiesAtmospheric ChemistryChemSchemeScopeChemSchemeScopetroposphereBasicApproximationsBasicApproximationssee component descriptionListOfPrognosticVariablesListOfPrognosticVariables3D mass/mixing ratio for gasNumberOfTracersNumberOfTracers25FamilyApproachFamilyApproachnoCouplingWithChemicalReactivityCouplingWithChemicalReactivitynoTimeSteppingFrameworkTimeSteppingFrameworkMethodMethodotheracetaldehyde_emissionsacetaldehyde_emissionsSurface emissions of acetaldehyde, prescribed as annual quantities on the model gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkacetone_emissionsacetone_emissionsSurface emissions of acetone, prescribed as annual quantities on the model gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkaircraft_NOx_emissionsaircraft_NOx_emissions3D emissions of nitrogen oxides from aircraft, prescribed as monthly quantities on the 3D model grid.unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcarbon_monoxide_emissioncarbon_monoxide_emissionSurface emissions of Carbon Monoxide, prescribed as annual quantities on the model gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkethane_emissionsethane_emissionsSurface emissions of ethane (C2H6), prescribed as annual quantities on the model gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkformaldehyde_emissionsformaldehyde_emissionsSurface emissions of formaldehyde, prescribed as annual quantities on the model gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkpropane_emissionspropane_emissionsSurface emissions of propane (C3H8), prescribed as annual quantities on the model gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksurface_NOx_emissionssurface_NOx_emissionsSurface emissions of nitrogen oxides, prescribed as annual quantities on the model gridunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gases_CH4well_mixed_gases_CH4Surface methane concentrations prescribed as a single global constant provided as an annual number but added as a 2D surface and interpolated in the model at each timestep. unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gases_Ozonewell_mixed_gases_OzoneStratospheric Ozone is prescribed as monthly 3D field derived from the CMIP5 recommended AC&C/SPARC ozone databaseunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCFiona O'ConnorMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/fiona-oconnorFiona O'ConnorUK Met Office Hadley CentreMOHCO'Connor 2009doi:10.1029/2009GL039152,2009.O'Connor, F.M., C.E. Johnson, O. Morgenstern, and W.J. Collins (2009) Interactions between tropospheric chemistry and climate model temperature and humidity biases. Geophys. Res. Lett., 36, L16801,O'Connor 2010O'Connor, F. M., C.E. Johnson, O. Morgenstern, M.G. Sanderson, P. Young, G. Zeng, W.J. Collins, and J.A. Pyle (2010) Evaluation of the new UKCA climate-composition model. Part II. The troposphere Geosci. Model Dev. Disc., In preparation, 2010. Atm Chem Emission And ConcAtmospheric Chemistry Emission and ConcentrationThe 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 (either fixed or varying in time). The interactive chemistry does not consider heterogeneous chemistry in the stratosphere. For this reason, stratospheric ozone is prescribed 3-5 km above the tropopause using a time-varying or time-invariant field. 2D-Emissions2D-EmissionsMethodMethodotherprescribed (climatology)SourceTypesSourceTypesanthropogenicbare groundothersea surfacevegetationClimatologyTypeClimatologyTypemonthlyClimEmittedSpeciesClimEmittedSpeciesCO, Me2COMethodCharacteristicsMethodCharacteristicsPrescribed monthly mean emissions (spatially non-unifoem) linearly interpolated from CMIP5 emissions provided as decadal means.EmittedSpeciesEmittedSpeciesC2H6 ethane, C3H8 propane, CO carbon monoxide, HCHO formaldehyde, MeCHO acetaldehyde, Me2CO acetone, and NOx nitrogen oxides3D-Emissions3D-EmissionsMethodMethodinteractiveotherSourceTypesSourceTypesaircraftlightningInteractivEmittedSpeciesInteractivEmittedSpeciesNOx (nitrogen oxides)MethodCharacteristicsMethodCharacteristicsPrescribed monthly mean emissions (spatially non-uniform) linearly interpolated from CMIP5 emissions provided as decadal meansEmittedSpeciesEmittedSpeciesNOxConcentrationsConcentrationsPrescribedLowerBoundaryPrescribedLowerBoundaryCH4 (methane)PrescribedUpperBoundaryPrescribedUpperBoundaryO3 (ozone)Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCFiona O'ConnorMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/fiona-oconnorFiona O'ConnorUK Met Office Hadley CentreMOHCGedney 2003Gedney, 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 Lock 2000Lock A.P., A.R. Brown, M.R. Bush, G.M. Martin, R.N.B. Smith et al. (2000) A new boundary layer mixing scheme. Part I: scheme description and single column model tests.. Monthly Weather Review, American Meteorological Society, 128, 3187-3199. Price 1994Price, C. and Rind, D. (1994) Modelling global lightning distributions in a general circulation model. Mon. Weath. Rev., 122, 1930-1939, 1994. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk33825e60-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.768002Atm Chem Gas Phase ChemistryAtmospheric Gas Phase Chemistrysee description for "Atmospheric Chemistry" componentAtmGasPhaseChemistryAttributesAtmGasPhaseChemistryAttributesSpeciesSpeciesHOxNOyOxVOCsProcessesProcessesDryDepositionDryDepositioninteractiveWetDepositionWetDepositionyesOxidationOxidationyesNumOfReactionsAndSpeciesNumOfReactionsAndSpeciesNumberOfBimolecularReactionsNumberOfBimolecularReactions83NumberOfTermolecularReactionsNumberOfTermolecularReactions13NumberOfAdvectedSpeciesNumberOfAdvectedSpecies25NumberOfSteadyStateSpeciesNumberOfSteadyStateSpecies9Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCFiona O'ConnorMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/fiona-oconnorFiona O'ConnorUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk33de0cc4-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.841013Atm Chem Heterogen ChemistryAtmospheric Chemistry Heterogenous ChemistryThe atmospheric chemistry component of HadGEM2-ES does not include either tropospheric or stratospheric heterogeneous reactionsChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCFiona O'ConnorMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/fiona-oconnorFiona O'ConnorUK Met Office Hadley CentreMOHCStratospheric Heter ChemStratospheric Heterogeneous ChemistryProcessesProcessesSedimentationSedimentationnoCoagulationCoagulationnoNumOfReactionsAndSpeciesNumOfReactionsAndSpeciesNumberOfReactionsNumberOfReactionsN/ANumberOfAdvectedSpeciesNumberOfAdvectedSpeciesN/ANumberOfSteadyStateSpeciesNumberOfSteadyStateSpeciesN/AChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCFiona O'ConnorMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/fiona-oconnorFiona O'ConnorUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk34051648-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:43.920363Tropospheric Heter ChemTropospheric Heterogeneous Chemistry<needs a bit more description here>SpeciesSpeciesGasPhaseGasPhaseN/AProcessesProcessesDryDepositionDryDepositionInteractiveWetDepositionWetDepositionyesCoagulationCoagulationnoNumOfReactionsAndSpeciesNumOfReactionsAndSpeciesNumberOfReactionsNumberOfReactionsN/ANumberOfAdvectedSpeciesNumberOfAdvectedSpeciesN/ANumberOfSteadyStateSpeciesNumberOfSteadyStateSpeciesN/AChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCFiona O'ConnorMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/fiona-oconnorFiona O'ConnorUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk34288ab0-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.032113metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk340345e8-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.032210Atm Chem Photo ChemistryAtmospheric PhotoChemistryThe 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. PhotolysisPhotolysisMethodMethodoffline (with clouds)ReactionDataReactionDataupdated reaction absorption cross sectionsupdated reaction quantum yieldsNumOfReactionsAndSpeciesNumOfReactionsAndSpeciesNumberOfReactionsNumberOfReactions25NumberOfSpeciesNumberOfSpecies18Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCFiona O'ConnorMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/fiona-oconnorFiona O'ConnorUK Met Office Hadley CentreMOHCHough 1998Hough, A. M. (1998) The calculation of photolysis rates for use in global tropospheric modelling studies. AERE Report, 13259, At. Energy Res. Estab., Harwell, U.K., 1988 Law 1993Law, K. S. and Pyle, J. A. (1993) Modelling trace gas budgets in the troposphere. 1. ozone and odd nitrogen J. Geophys. Res., 98, 18377-18400, 1993. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk345ce4ea-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.074360Atm Chem TransportAtmospheric Chemistry TransportThe 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). SchemeTypeSchemeTypeSemi-LagrangianMassConservationMassConservationotherConvectionConvectionconvective fluxes connected to tracersDryMassConservationDryMassConservationformally conservedTracerAndMoistureConservationTracerAndMoistureConservationconcentrations positivity and local adjustment, reset conservatively if necessaryTurbulenceTurbulenceTypeType3DCouplingWithChemicalReactivityCouplingWithChemicalReactivitynoChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCFiona O'ConnorMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/fiona-oconnorFiona O'ConnorUK Met Office Hadley CentreMOHCDavies 2005Davies T., M. J. P. Cullen, A. J. Malcolm, M. H. Mawson, A. Staniforth, A. A. White, and N. Wood (2005) A new dynamical core for the Met Office's global and regional modelling of the atmosphere.. Quarterly Journal Royal Meteorology Society, 131, 1759-1782. Gregory 1990Gregory J., and P.R. Rowntree (1990) A mass flux convection scheme with representation of cloud ensemble characteristics and stability - dependent closure.. Monthly Weather Review, 118, 1483-1506. Lock 2000Lock A.P., A.R. Brown, M.R. Bush, G.M. Martin, R.N.B. Smith et al. (2000) A new boundary layer mixing scheme. Part I: scheme description and single column model tests.. Monthly Weather Review, American Meteorological Society, 128, 3187-3199. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk336c7f00-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.133169metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDRS_CMIP5_componentTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk334a9872-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.133295Land IceLand IceThe 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. Land Ice Key PropertiesLand IceLandIceAlbedoLandIceAlbedoprescribedChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCJeff RidleyMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/cryosphere-oceans/jeff-ridleyJeff RidleyUK Met Office Hadley CentreMOHCJohns_2006Johns 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. Land Ice SheetLand Ice SheetMassBalanceMassBalanceDownscalingTechniqueDownscalingTechniqueN/AChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCJeff RidleyMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/cryosphere-oceans/jeff-ridleyJeff RidleyUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk34ae695a-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.200826metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDRS_CMIP5_componentTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk347b4c64-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.200914Land SurfaceLand SurfaceThe 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. Land Surface Key PropertiesLand SurfaceBasicApproximationsBasicApproximationsLinearisation of the surface energy balance equationsGenealogyGenealogyotherCouplingWithAtmosphereCouplingWithAtmosphereimplicitLandCoverTypesLandCoverTypesbare soiliceurbanvegetatedListOfPrognosticVariablesListOfPrognosticVariablescanopy heat contentcanopy skin temperaturecanopy snow contentcanopy water contentsnow albedosnow masssoil heat contentsoil ice contentsoil moisturesoil temperaturesurface skin temperatureTilingTilingcommon to all LS subcomponentsTilingMethodTilingMethoddynamicConservationOfPropertiesConservationOfPropertiesWaterTreatmentWaterTreatmentAll water sent to ocean (with a lag)LagOfWaterDischargeLagOfWaterDischargesimulated by river flow modelTimeSteppingFrameworkTimeSteppingFrameworkMethodMethoduse Atmosphere time stepchanging_anthro_land_usechanging_anthro_land_useTime varying fractional mask of anthropogenic disturbance.unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkinitial_land_useinitial_land_usePrescribed fractions of urban areas, lakes, ice, broadleaf tree, needleleaf tree, C3 grass, C4 grass, shrub and bare soilunitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkwell_mixed_gas_CO2well_mixed_gas_CO2CO2 concentrations prescribed as a single global constant provided as an annual number but interpolated in the model at each timestep. Provided as a mass mixing ratio with units of kg/kg. CO2 concentrations are passed to the model's radiation scheme, terrestrial carbon cycle and ocean carbon cycle.unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCCox 1999Cox 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. Essery 2003Essery, R. L. H., Best, M. J., Betts, R. A., Cox, P. M., and Taylor, C. M. (2003) Explicit representation of subgrid heterogeneity in a GCM land-surface scheme J. Hydrometeorol., 43, 530-543. Land Surface AlbedoLand Surface AlbedoA 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). SpecificTilingSpecificTilingyesSnowFreeAlbedoSnowFreeAlbedoTypeTypeprognosticFunctionOfFunctionOfvegetation statevegetation typeDirect-DiffuseDirect-Diffuseno distinction between direct and diffuse albedoNumberOfWavelenghBandsNumberOfWavelenghBands1SnowAlbedoSnowAlbedoTypeTypeprognosticFunctionOfFunctionOfvegetation typeChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCEssery 2001http://www.metoffice.gov.uk/publications/HCTN/HCTN_30.pdfEssery R., M. Best, and P. Cox (2001) MOSES 2.2 technical documentation.. Hadley Centre Technical Note 30, 30 pp. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk367d7b36-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.362063Land Surface Carbon CycleLand Surface Carbon CycleThe 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). SoilSoilMethodMethodheterotrophic respirationNumberOfCarbonPoolsNumberOfCarbonPools4ListOfCarbonPoolsListOfCarbonPoolsDPM, RPM, BIO, HUMPermafrostPermafrostListOfGasesListOfGasesN/AChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCColeman 1999Coleman K, Jenkinson D. S (1999) RothC-26.3, A Model for the Turnover of Carbon in Soil: Model Description and User's Guide Lawes Agricultural Trust, Harpenden, UKCox 2001http://www.metoffice.gov.uk/publications/HCTN/HCTN_24.pdfCox, P.M. (2001) Description of the TRIFFID dynamic global vegetation model.. Hadley Centre Technical Note 24, Hadley Centre, Met Office, UK. Vegetation Carbon CycleVegetation Carbon CycleNumberOfCarbonPoolsNumberOfCarbonPools3ListOfCarbonPoolsListOfCarbonPoolsleaf, wood, root carbon. [These are diagnosed from the canopy height and LAI of the vegetation]PhotosynthesisPhotosynthesisMethodMethodcarbon assimilation approachAutotrophicRespirationAutotrophicRespirationMethodMethodparametrizedMaintenanceRespirationMaintenanceRespirationwhole plant (no distinction)AllocationAllocationAllocationBinsAllocationBinsleaves + stems + rootsAllocationFractionsAllocationFractionsfunction of vegetation typePhenologyPhenologyMethodMethodparametrizedChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk36abb9e2-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.474927metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk36a975d8-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.474992Land Surface Energy BalanceLand Surface Energy BalanceThe 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). SpecificTilingSpecificTilingyesNumberOfSurfaceTemperaturesNumberOfSurfaceTemperatures9SubsurfaceTilingSubsurfaceTilingnoSchemeMethodSchemeMethodTypeOfEvaporationFormulationTypeOfEvaporationFormulationcombinedProcessesProcessestranspirationChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCBest 2004Best, 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 Essery 2001http://www.metoffice.gov.uk/publications/HCTN/HCTN_30.pdfEssery R., M. Best, and P. Cox (2001) MOSES 2.2 technical documentation.. Hadley Centre Technical Note 30, 30 pp. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk36676918-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.526771Land Surface LakesLand Surface LakesLakes 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. CouplingWithRiversCouplingWithRiversnoSchemeMethodSchemeMethodIceTreatmentIceTreatmentnoLakesAlbedoLakesAlbedootherLakesDynamicsLakesDynamicsnoneDynamicLakesExtentDynamicLakesExtentnoEndorheicBasinsEndorheicBasinsnoChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk37050b1e-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.571582Land Surface SnowLand Surface SnowSnow 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). SpecificTilingSpecificTilingyesNumberOfSnowLayersNumberOfSnowLayers1SchemeMethodSchemeMethodSnowAlbedoSnowAlbedodiagnosticSnowDensitySnowDensityconstantSnowWaterEquivalentSnowWaterEquivalentprognosticSnowHeatContentSnowHeatContentotherSnowTemperatureSnowTemperatureprognosticSnowCoverFractionsSnowCoverFractionsground snow fractionvegetation snow fractionProcessesProcessessnow interceptionsnow meltingChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCEssery 2001http://www.metoffice.gov.uk/publications/HCTN/HCTN_30.pdfEssery R., M. Best, and P. Cox (2001) MOSES 2.2 technical documentation.. Hadley Centre Technical Note 30, 30 pp. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk362545e2-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.639017Land Surface SoilLand Surface SoilSoilMapSoilMapTextureTextureSoil properties are derived from fractions of clay, sand and silt defined in the datasets available from the IGBP DISStructureStructureThe 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 and Cox, 2003)AlbedoAlbedoDerived from MODIS data as defined in Houldcroft et al. (2008)WaterTableWaterTableAs described in Gedney and Cox (2003)Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCGedney 2003Gedney, 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 Houldcroft et al 2008Houldcroft C., W. Grey, M. Barnsley, C. Taylor, S. Los and P. North (2008) New vegetation albedo parameters and global fields of background albedo derived from MODIS for use in a climate model. J. Hydrometeorology, Vol 10, No. 1, pp 183-198, doi:10.1175/2008JHM1021.1Land Surf Soil Heat TreatmentLand Surface Soil Heat TreatmentSoilHeatTreatmentAttributesSoilHeatTreatmentAttributesSpecificTilingSpecificTilingnoNumberOfGroundHeatLayersNumberOfGroundHeatLayers4MethodMethodHeatStorageHeatStorageExplicit diffusionProcessesProcessessoil moisture freeze-thawChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk35ebc77c-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.727182Land Surf Soil HydrologyLand Surface Soil HydrologyThe 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. SoilHydrologyAttributesSoilHydrologyAttributesSpecificTilingSpecificTilingnoNumberOfGroundWaterLayersNumberOfGroundWaterLayers4WaterStorageMethodWaterStorageMethodExplicit diffusionSoilMoistureFreezingSoilMoistureFreezingNumberOfGroundIceLayersNumberOfGroundIceLayers4IceStorageMethodIceStorageMethodPrognostic frozen fraction of saturationPermafrostPermafrostotherRunoff-DrainageRunoff-DrainageMethodMethoddifferentiated drainage and runoffProcessesProcessesdeep drainageinfiltration excess runoffChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCClark 2008Clark, 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. Gedney 2003Gedney, 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 metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk35cba370-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.806486metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk35c9d842-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.806558Land Surface VegetationLand Surface VegetationThe 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). SpecificTilingSpecificTilingyesVegetationRepresentationVegetationRepresentationvegetation typesVegetationTimeVariationVegetationTimeVariationdynamical (varying from simulation)InterceptionInterceptionyesVegetationTypesVegetationTypesbroadleaf treeC3 grassC4 grassneedleleaf treeotherSchemeMethodSchemeMethodPhenologyPhenologyprognosticLAILAIprognosticBiomassBiomassdiagnosticBioGeographyBioGeographyprognosticStomatalResistanceFunctionOfStomatalResistanceFunctionOfCO2lighttemperaturewater availabilityChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCClark 2008Clark, 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. Collatz 1991Collatz, 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. Collatz 1992Collatz, 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. Cox 1999Cox 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. Cox 2001http://www.metoffice.gov.uk/publications/HCTN/HCTN_24.pdfCox, P.M. (2001) Description of the TRIFFID dynamic global vegetation model.. Hadley Centre Technical Note 24, Hadley Centre, Met Office, UK. Gedney 2003Gedney, 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 Mercado 2007Mercado, 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. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3643d8cc-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:44.890814River RoutingLand Surface River RoutingRealistic 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. SpecificTilingSpecificTilingyesResolutionResolutionindependentNumberOfReservoirsNumberOfReservoirs1ListOfPrognosticVariablesListOfPrognosticVariableswaterCouplingWithAtmosphereCouplingWithAtmosphereyesDrainageMapDrainageMappresent-dayQuantitiesExchangedWithAtmosphereQuantitiesExchangedWithAtmospherewaterOceanicDischargeOceanicDischargeTypeTypedirect (large rivers)QuantitiesTransportedQuantitiesTransportedwaterChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCOki 1998Oki T., and Y.C. Sud (1998) Design of the Total Runoff Integrating Pathways [TRIP] - A global river channel network.. Earth Interactions, 2. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk36e4d470-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.016149metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDRS_CMIP5_componentTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk359a10f8-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.016310OceanOceanThe 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. Ocean Key PropertiesOceanThe sea water formulation of the equation of state is following that of UNESCO.ModelFamilyModelFamilyOGCMBasicApproximationsBasicApproximationsBoussinesqnon-hydrostaticListOfPrognosticVariablesListOfPrognosticVariablespotential temperaturesalinitySSHU-velocityV-velocitySeaWaterSeaWaterEquationOfStateEquationOfStateotherFreezingPointFreezingPointfixedSpecificHeatSpecificHeatfixedFreezingPointValueFreezingPointValue-1.8SpecificHeatValueSpecificHeatValue3988.0Non-OceanicWaterNon-OceanicWaterRiverMouthMixingRiverMouthMixingAddition of surface freshwater at river mouthIsolatedSeasMixingIsolatedSeasMixingyesBathymetryBathymetryBathymetryTypeBathymetryTypefixedReferenceDateReferenceDatepresent-dayHorizontalDiscretizationHorizontalDiscretizationSchemeMethodSchemeMethodfinite differencesPoleSingularityTreatmentPoleSingularityTreatmentartificial islandStaggeringStaggeringArakawa B-gridTimeSteppingFrameworkTimeSteppingFrameworkTracersTracersLeap-frog + Asselin filterBarotropicSolverBarotropicSolverLeap-frog + Asselin filterBaroclinicMomentumBaroclinicMomentumLeap-frog + Asselin filterTimeStepTimeStep3600well_mixed_gas_CO2well_mixed_gas_CO2CO2 concentrations prescribed as a single global constant provided as an annual number but interpolated in the model at each timestep. Provided as a mass mixing ratio with units of kg/kg. CO2 concentrations are passed to the model's ocean carbon cycle.unitshttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkcfNamehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCBryan 1969Bryan K., (1969) A numerical method for the study of the circulation of the world ocean.. Journal of Computational Physics, 4, 347-376Cox 1984Cox M.D., (1984) A primitive equation, three dimensional model of the ocean.. Ocean Group Technical Report 1, GFDL, Princeton.Johns_2006Johns 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. Ocean AdvectionOcean AdvectionA 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. MomentumMomentumSchemeNameSchemeNameSecond order centred, leapfrogSchemeTypeSchemeTypeFlux formLateralTracersLateralTracersSchemeTypeSchemeTypeCentred 4th orderMonotonicFluxLimiterMonotonicFluxLimiternoVerticalTracersVerticalTracersSchemeTypeSchemeTypeCentred 2nd orderMonotonicFluxLimiterMonotonicFluxLimiternoChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCPacanowski 1998Pacanowski R. C., and S. M. Griffies (1998) MOM 3.0 manual.. NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, 692 pp. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk38e441fc-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.212737Ocean Boundary ForcingOcean Boundary ForcingScheme described in Ocean component.MomentumMomentumBottomFrictionBottomFrictionnon-linearLateralFrictionLateralFrictionno-slipSurfaceFluxCorrectionSurfaceFluxCorrectionnoChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCOcean Bound Forcing TracersOcean Boundary Forcing TracersA two band scheme for sunlight penetration is used (one more penetrative) from Paulson and Simpson (1977), assuming pure water type 1B with coefficients adjusted .
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. SunlightPenetrationSunlightPenetrationSchemeTypeSchemeType2 extinction depthsOceanColorDependentOceanColorDependentnoSurfaceSalinitySurfaceSalinityFromAtmosphereFromAtmospherefreshwater fluxFromSeaIceFromSeaIcefreshwater fluxFromRiverFromRiverfreshwater fluxChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCPaulson 1977Paulson C. A., and J. J. Simpson (1977) Irradiance Measurements in the Upper Ocean.. Journal of Physical Oceanography, 7, 952-956. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk39da4cc8-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.298104metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk39d835b4-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.298232Ocean Lateral PhysicsOcean Lateral PhysicsIsopycnal 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.Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCGriffies 1998Griffies S. M., (1998) The Gent-McWilliams skew flux.. Journal of Physical Oceanography, 28, 831-841. Griffies et al. 1998Griffies S. M., A. Gnanadesikan, R. C. Pacanowski, V. D. Larichev, J. K. Dukowicz, and R. D. Smith (1998) Isoneutral diffusion in a z-coordinate ocean model.. Journal of Physical Oceanography, 28, 805-830. Roberts 1998Roberts M. J., and D. Marshall (1998) Do we require adiabatic dissipation schemes in eddy-resolving ocean models?. Journal of Physical Oceanography, 28, 2050-2063. Visbeck 1997Visbeck M., J. Marshall, T. Haine, and M. Spall (1997) Specification of eddy transfer coefficients in coarse-resolution ocean circulation models. Journal of Physical Oceanography, 27, 381-402. Ocean Lateral Phys MomentumOcean Lateral Physics MomentumOperatorOperatorDirectionDirectiongeopotentialOrderOrderbi-harmonic (fourth order)DiscretizationDiscretizationsecond orderEddyViscosityCoefficientEddyViscosityCoefficientCoefficientTypeCoefficientTypespace varyingMinimalBackgroundValueMinimalBackgroundValue0SpatialVariationSpatialVariationlatitudeChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCDukowicz 1994Dukowicz J. K., and R. D. Smith (1994) Implicit free surface method for the Bryan-Cox-Semtner ocean model.. Journal of Geophysical Research, C4, 7991-8014. metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk391272de-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.380487Ocean Lateral Phys TracersOcean Lateral Physics TracersThe active tracers (temperature and salinity) are advected using a fourth-order scheme. The operator order is a combination of harmonic and bi-harmonic MesoscaleClosureMesoscaleClosureyesOperatorOperatorDirectionDirectionisopycnalOrderOrderotherDiscretizationDiscretizationsecond orderEddyViscosityCoefficientEddyViscosityCoefficientCoefficientTypeCoefficientTypeconstantBackgroundValueBackgroundValue0CoefficientValueCoefficientValue500Eddy-inducedVelocityEddy-inducedVelocitySchemeTypeSchemeTypeGM schemeFluxTypeFluxTypeskew fluxAddedDiffusivityAddedDiffusivityconstantCoefficientTypeCoefficientTypediagnosticChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk392cf2bc-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.472295Ocean StraitsOcean StraitsThere is a parameterisation of flow into three marginal seas where the passages are not resolved by the model grid. Mediterranean water is partially mixed with Atlantic water across the Strait of Gibraltar (constant flux of 0.4Sv over the top 80m and out at 600m). The Red Sea has 0.2Sv fluxed in over the top 20m and out at 40-60m. The Persian Gulf has 0.1Sv fluxed in over the top 20m and out at 40-60m. The flux volumes used are based on observed values, although the Mediterranean value was reduced because the model does not represent many of the mixing processes that would modulate the water as it flows over the sill. Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCsubmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk482e5488-19b1-11e0-ba3b-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.487302metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk391033ac-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.487375Ocean Up And Low BoundariesOcean BoundariesFreeSurfaceFreeSurfaceTypeTypelinear implicitChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk39c10718-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.843574Ocean Vertical PhysicsOcean Vertical PhysicsConvective 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. ConvectionConvectionnon-penetrative convective adjustmentChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCMoum 1986Moum J.N., and T.R. Osborn (1986) Mixing in the main thermocline. Journal of Physical Oceanography, Vol 16, Issue 7, pp1250-1259. Rahmstorf 1993Rahmstorf S., (1993) A fast and complete convection scheme for ocean models. Ocean Modelling, 101, 9-11. Roether 1994Roether W., V. M. Roussenov and R. Well (1994) A trace study of the thermohaline circulation of the eastern Mediterranean.. In: Malanotte-Rizzoli P, Robinson AR (eds) Ocean Processes in climate dynamics, global and Mediterranean example, Kluwer Academic Press, Dordrecht, pp 371-394. Ocean Interior MixingOcean Interior MixingScheme described in Ocean Mixed Layer ComponentTracersTracersSchemeTypeSchemeTypeotherBackgroundTypeBackgroundTypevertical profileMomentumMomentumSchemeTypeSchemeTypeotherBackgroundTypeBackgroundTypeconstant valueBackgroundCoefficientBackgroundCoefficient0.00002Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCmetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3981bb62-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.929021Ocean Mixed LayerOcean Mixed LayerThe 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. TracersTracersSchemeTypeSchemeTypeotherBackgroundCoefficientBackgroundCoefficient0.00001MomentumMomentumSchemeTypeSchemeTypeotherBackgroundValueBackgroundValue0.00002Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCMalcolm RobertsMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/understanding-climate/malcolm-robertsMalcolm RobertsUK Met Office Hadley CentreMOHCKraus 1967Kraus E. B., and J. S. Turner (1967) A one-dimensional model of the seasonal thermocline, Part II.. Tellus, 19, 98-105. Large 1994Large W. G., J. C. McWilliams and S.C. Doney (1994) Ocean vertical mixing: A review and a non-local boundary layer parameterization. Reviews of Geophysics, 32, 363-403.Peters 1988Peters H., M. C. Gregg, and J. M. Toole (1988) On the parameterization of equatorial turbulence. Journal of Geophysical Research, 93, 1199-1218.metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk39603ca8-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.980554metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk395e3c64-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.980655metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDRS_CMIP5_componentTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3829e988-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:45.980829Ocean Biogeo ChemistryOcean Biogeo ChemistryThere 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. Ocean Bio Key PropertiesOcean Biogeo ChemistryOcean Bio Time Step FrameworkOcean Bio Time Step FrameworkPassiveTracersPassiveTracersMethodMethoduse Ocean transport time stepBiologyBiologyMethodMethoduse ocean transport time stepBasicApproximationsBasicApproximationsEulerian model, N3 P2 Z1 D1 ecosystem; no diel cycle, constant detrital sinking rate, constant (carbonate) rain ratioListOfPrognosticVariablesListOfPrognosticVariablesDissolved inorganic nitrogen (nitrate+ammonia); dissolved silicate; dissolved iron; diatoms; other phytoplankton; zooplankton; diatom silicate; detrital nitrogen; detrital carbon; detrital silicate; dissolved inorganic carbon; total alkalinity; dissolved oxygen.BioGeoTracersDampingBioGeoTracersDampingListOfTracersListOfTracersNoneLatMinLatMinn/aLatMaxLatMaxn/aLonMinLonMinn/aLonMaxLonMaxn/aUpperLevelUpperLeveln/aLowerLevelLowerLeveln/aTransportTransportMethodMethodonline, different from Ocean TracersMethodCharacteristicsMethodCharacteristicsUTOPIA with flux-limiterChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCIan Totterdell Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/cryosphere-oceans/ian-totterdellIan Totterdell UK Met Office Hadley CentreMOHC2009Ocean Bio Boundary ForcingOcean Biogeo Chemistry Boundary ForcingThere 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, which is called every 24 hours. AtmosphericDepositionAtmosphericDepositionotherChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCIan Totterdell Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/cryosphere-oceans/ian-totterdellIan Totterdell UK Met Office Hadley CentreMOHCGarcia 1992Garcia, H.E. & Gordon, L.I. (1992) Oxygen solubility in seawater: Better fitting equations. Limnol. Oceanogr., 37, 1307-1312 metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk376ab82e-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.124948Ocean Bio ChemistryOcean Bio ChemistryAs well as the ocean carbon chemistry (described in the Ocean Bio Gas Exchange component), calcium carbonate is formed in proportion to the growth of the other non-diatom phytoplankton The total calcium carbonate formed in a water-column in a time-step is instantly re-dissolved with a constant depth profile in the level containing the 2300 m depth contour and in all levels below that but above the sea-floor (no calcium carbonate is formed in water-columns that are shallower than 2300 m).CarbonChemistryCarbonChemistrypH-scalepH-scalesea waterCarbonChemConstantsCarbonChemConstantsDOE(1994) (for K1, K2, Kw, and Kb)Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCIan Totterdell Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/cryosphere-oceans/ian-totterdellIan Totterdell UK Met Office Hadley CentreMOHCDoE 1994US 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 metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3813d6b6-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.151780Ocean Bio Gas ExchangeOcean Bio Gas ExchangeThe 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(-)] + [OH(-)] [H(+)], and so the calculation of [H(+)] and then [H2CO3] requires the constants K1, K2, Kb and Kw. The formulae for all these constants can be found in DOE (1994), with the K1 and K2 constants coming originally from Roy et al. (1993) and the boric acid dissociation constant Kb from Dickson (1990) The total boron concentration is linked to salinity as in Peng et al. (1987). [H(+)] is found using the iterative secant method of similar triangles following Bacastow (1981). The Schmidt number for CO2 is calculated following Table A1 in Wanninkhof (1992), which itself uses experimental results from Jahne et al. (1987). The wind-speed dependence of the piston velocity follows Wanninkhof (1992) and uses the 0.31 coefficient value. CO2CO2PresentPresentyesSchemeTypeSchemeTypeWanninkhofO2O2PresentPresentyesSchemeTypeSchemeTypeWanninkhofDMSDMSPresentPresentyesSchemeTypeSchemeTypeWanninkhofN2N2PresentPresentnoN2ON2OPresentPresentnoCOCOPresentPresentnoChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCIan Totterdell Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/cryosphere-oceans/ian-totterdellIan Totterdell UK Met Office Hadley CentreMOHCAranami 2004doi:10.1029/2003JD004288 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,Bacastow 1981Bacastow, R. (1981) Numerical evaluation of the evasion factor, pp95-101 in: Scope 16: Carbon Cycle Modelling Bolin, B., editor, John Wiley, New York Dickson 1990Dickson, 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 DoE 1994US 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 Jahne 1987Jahne, 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 Peng 1987Peng, 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 Roy 1993Roy, 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 Saltzman 1993Saltzman, 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 Simo 2002doi:10.1029/2001GB001829Simo, R. & Dachs, J. (2002) Global ocean emission of dimethylsulfide predicted from biogeophysical data, Global Biogeochem. Cycles, 16(4), 1018Wanninkhof 1992Wanninkhof, R. (1992) Relationship between wind speed and gas exchange over the ocean. J. Geophys. Res., 97C, 7373-7382Weiss 1974Weiss, R.F. (1974) Carbon dioxide in water and seawater: The solubility of a non-ideal gas. Mar. Chem., 2, 203-215 metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3779dc78-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.254685Ocean Bio TracersOcean Bio TracersThe 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. SulfurCycleSulfurCyclenoNutrientsNutrientsListOfSpeciesListOfSpeciesIron (Fe)Nitrogen (N)Silicium (Si)DisolvedOrganicMatterDisolvedOrganicMatterLabilityLabilitynoBacteriaRepresentationBacteriaRepresentationnoParticulesParticulesMethodMethodprognosticTypesOfParticulesTypesOfParticulesBSiPIC (calcite)POCSizeSpectrumSizeSpectrumnoSinkingSpeedSinkingSpeedotherChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCIan Totterdell Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/cryosphere-oceans/ian-totterdellIan Totterdell UK Met Office Hadley CentreMOHCGoldman 1980Goldman, J.C. & Brewer, P.G. (1980) Effect of nitrogen source and growth rate on phytoplankton-mediated changes in alkalinity Limnol. Oceanogr., 25, 352-357 Ocean Bio Tracers EcosystemOcean Bio Tracers EcosystemThe 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 ratio where iron is a limiting nutrient.
- diatom silicate: because the Si:N uptake ratio varies, the Si:N ratio in diatoms also varies so this has to be a separate prognostic variable. Its source is the uptake of dissolved silicate during diatom growth, and it become detrital silicate when the diatom dies by predation or natural mortality. It sinks at 1 m/day, like the diatoms. Units are mMoles-Si/m^3.
- other non-diatom phytoplankton: also described in terms of their nitrogen content (units: mMoles-N/m^3). They represent all phytoplankton except those that are diatoms. Their growth is limited by [DIN] and light. They are subject to predation by zooplankton and to natural mortality. They do not sink. They have a lower maximum growth rate than diatoms, but it is reduced less by iron limitation. Calcium carbonate is formed in proportion to the growth rate of this compartment (it is recognised that not all non-diatom phytoplankton calcify, and this is accounted for in the proportionality).
- zooplankton: are described in terms of their nitrogen content (units: mMoles-N/m^3). They feed on diatoms, other non-diatom phytoplankton and detritus (detrital nitrogen and detrital carbon). They have dynamic feeding preferences which depend on the relative concentrations of the prey following Fasham et al. (1990). The base preference for diatoms varies with the degree of iron limitation, to represent the observed effect that iron-limited diatoms are more heavily silicified and so less appetising to predators. The rate of feeding depends on the absolute prey concentration, weighted by preference. The zooplankton respire (with a corresponding excretion of nitrogen to balance their carbon:nitrogen ratio) and suffer natural mortality, the latter term implicitly including the effects of higher trophic levels.
c) Other particles:
- detrital carbon, detrital nitrogen: are described in terms of their carbon and nitrogen contents respectively (units: mMoles-C/m^3, mMoles-N/m^3), and represent the elemental fractions of detrital particles. Their sources are (fractions of) the natural mortalities of diatoms, other non-diatom phytoplankton and zooplankton, and messy feeding and egestion of un-assimilated food by zooplankton. They sink at a constant speed, 10 m/day. They are remineralised to DIC or DIN at a specific rate that is inversely proportional to depth (up to an absolute maximum specific rate). If they sink to the sea-floor they are instantly remineralised and the products evenly spread over the bottom three levels of the water-column.
- detrital silicate: its source is the natural mortality of diatoms and their predation by zooplankton. It sinks at a constant speed of 10 m/day, and returns to dissolved silicate at a constant specific rate (which is depth-independent). Any that reaches the sea-floor is instantly remineralised and the resulting dissolved silicate spread over the bottom three levels of the water-column. Units are mMoles-Si/m^3. UpperTrophicLevelsUpperTrophicLevelsnoPhytoplanctonPhytoplanctonTypeTypegenericZooplanctonZooplanctonTypeTypegenericChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCIan Totterdell Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/our-scientists/cryosphere-oceans/ian-totterdellIan Totterdell UK Met Office Hadley CentreMOHCFasham 1990Fasham, 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 metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk37b55532-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.369473metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk37b3cbea-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.369536metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDRS_CMIP5_componentTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3721c8ee-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.369641Sea IceSeaIceThe 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 modeled whilst only coupling between 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. Sea Ice Key PropertiesSea IceBasicApproximationsBasicApproximationsMultiple ice thickness categories (5 + open water); zero layer thermodynamics; EVP dynamics and ridging schemeListOfPrognosticVariablesListOfPrognosticVariablesIce concentration (per thickness category), grid box mean ice thickness (per thickness category), grid box mean snow thickness (per thickness category), surface snow or ice temperature (per thickness category), ice velocities, internal ice stress tensorsSeaIceRepresentationSeaIceRepresentationSchemeTypeSchemeTypeotherTimeSteppingFrameworkTimeSteppingFrameworkMethodMethoduse Ocean time stepChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCHelene HewittMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/out-scientists/cryosphere-oceans/helene-hewittHelene HewittUK Met Office Hadley CentreMOHCMcLaren 2006doi:10.1029/2005JC003033. McLaren A.J., H. T. Banks, C. F. Durman, J. M. Gregory, T. C. Johns, A. B. Keen, J. K. Ridley, M. J. Roberts, W. H. Lipscomb, W. M. Connolley and S. W. Laxon (2006) Evaluation of the sea ice simulation in a new coupled atmosphere-ocean climate model. Journal of Geophysical Research - Oceans, American Geophysical Union, Vol. 111, C12014,Thorndike 1975Thorndike, 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. Sea Ice AlbedoSea Ice AlbedoThe 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. Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCHelene HewittMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/out-scientists/cryosphere-oceans/helene-hewittHelene HewittUK Met Office Hadley CentreMOHCEbert 1993Ebert E. E., and J. A. Curry (1993) An intermediate one-dimensional thermodynamic sea ice model for investigating ice-atmosphere interactions. Journal of Geophysical Research, 98, 10085-10109. Semtner 1987Semtner A., (1987) A numerical study of sea ice and ocean circulation in the Arctic.. Journal of Physical Oceanography, 17, 1077-1099submetaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkdabbdede-18c5-11e0-a036-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.450588Sea Ice DynamicsSea Ice DynamicsThe 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. RheologyRheologyEVPAdvectionAdvectionotherHorizontalDiscretizationGridHorizontalDiscretizationGridOcean gridAdvectionTypeAdvectionTypeFirst-order upwindRedistributionRedistributionTypeTyperidgingIceStrengthFormulationIceStrengthFormulationHibler(1979). P* =20,000Nm-2 and c=20Chris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCHelene HewittMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/out-scientists/cryosphere-oceans/helene-hewittHelene HewittUK Met Office Hadley CentreMOHCHibler 1979Hibler, W. D. (1979) A dynamic-thermodynamic sea ice model. Journal of Physical Oceanography, 13, 1093-1104.
Hunke 1997Hunke E., and J. Dukowicz (1997) An elastic-viscous-plastic model for sea-ice dynamics. Journal of Physical Oceanography, 27, 1849-1867. Hunke 2004Hunke 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.metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3a5eaf36-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.495163Sea Ice ThermodynamicsSea Ice ThermodynamicsThe 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 (1992) scheme that uses both the ocean-ice temperature difference and the friction velocity in the flux parameterisation. 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. WaterPondsWaterPondsnoSurfaceAlbedoSurfaceAlbedoCurry et al. (2001) parameterization, with adjustment of Semtner (1987) to compensate for zero layer thermodynamics. Also, thin and partial snow cover scheme for snow albedo (Cox et al, 1999). Albedo parameters: bare ice = 0.61; melting deep snow on seaice = 0.65; cold deep snow on seaice = 0.8. NewIceFormationNewIceFormationFrazil ice forms with a thickness of 5cm when the temperature of the top ocean layer falls below freezing. The volume of new ice is determined by the heat required to bring the ocean surface temperature back to freezing. SnowSnowHeatDiffusionHeatDiffusionone layerSchemeTypeSchemeTypeothersnow-iceSnowSchemeSnowSchemeincludes sublimationIceIceVerticalHeatDiffusionVerticalHeatDiffusionone layerOceanToIceBasalHeatFluxOceanToIceBasalHeatFluxparametrized (calculated in SeaIce)BrineInclusionsBrineInclusionsnoneProcessesProcessesotherSurface sublimationTransportInThicknessSpaceTransportInThicknessSpacelinear remappingChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCHelene HewittMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBhttp://www.metoffice.gov.uk/research/out-scientists/cryosphere-oceans/helene-hewittHelene HewittUK Met Office Hadley CentreMOHCCox 1999Cox 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. Curry 2001Curry, J., J. Schramm, D. Perovich and J. Pinto, 2001. Applications of SHEBA/FIRE data to evaluation of snow/ice albedo parameterizations. J. Geophys. Res., 106, 15345-15355.
Hibler 1979Hibler, W. D. (1979) A dynamic-thermodynamic sea ice model. Journal of Physical Oceanography, 13, 1093-1104.
Lipscomb 2001Lipscomb W., (2001) Remapping the thickness distribution in sea ice models.. Journal of Geophysical Research, 106, 13989-14000 McPhee 1992McPhee 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. Semtner 1976Semtner A., (1976) A model for the thermodynamic growth of sea ice in numerical investigations of climate.. Journal of Physical Oceanography, 6, 379-389 metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3a3b145e-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.575658metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDRS_CMIP5_componentTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk3a0e59f0-e2b3-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:46.575745metaforhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk309f6a26-e2b3-11df-bf17-00163e9152a52Metafor Questionnaire2012-04-23T15:26:46.575892The 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.HadGEM2-AOGareth JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBgareth.jones@metoffice.gov.ukGareth JonesChris JonesMet Office Hadley Centre, Fitzroy Road, Exeter, Devon, UK, EX1 3PBchris.jones@metoffice.gov.ukhttp://www.metoffice.gov.uk/research/our-scientists/climate-chemistry-ecosystems/chris-jonesChris JonesUK Met Office Hadley CentreMOHCUK Met Office Hadley CentreMOHCprojecthttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkhistoricalExt3.2 Historical Extension (2005-2019)An extension to the historical ensemble for elements r2, r3, and r4. Impose changing conditions (consistent with observations), which include: atmospheric composition (including CO2) changes due to both anthropogenic and volcanic influences; solar forcing; emissions or concentrations of short-lived species and natural and anthropogenic aerosols or their precursors; and land use. For the time period beyond 2005 the RCP85 forcings are used.76f85a8a-4830-11e1-8ba0-00163e9152a5historicalExtexperiment1Reference to an Experiment called historicalExt with experimentNumber 7.4Annual CO2 concentrations were provided by CMIP5 in units of parts per million by volume (ppmv) whereas HadGEM2-ES requires atmospheric concentrations of CO2 in units of mass mixing ratio (mmr). A conversion factor of (44.0/28.964e6) was used to convert units.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunka31d55c4-4bc0-11e0-a872-00163e9152a5well_mixed_gas_CO2dataObject1Reference to a dataObject called well_mixed_gas_CO2317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmospherea31d55c4-4bc0-11e0-a872-00163e9152a5CO2_concentration_mmrfileVariable1Reference to a fileVariable called CO2_concentration_mmr in a dataObject called well_mixed_gas_CO2317f51b8-e2b3-11df-bf17-00163e9152a5well_mixed_gas_CO2componentProperty1Reference to a componentProperty called well_mixed_gas_CO2 in a modelComponent called AtmosphereIn the model, only the surface CH4 concentration were forced to follow the prescribed trajectory, but CH4 concentrations above the surface were calculated interactively, and the full 3D field was then passed to the model's radiation scheme. As CH4 concentrations were only prescribed at the surface, CH4 in HadGEM2-ES above the surface is free to evolve a non-uniform structure and may differ from the prescribed, well-mixed historical concentrations. The impact of passing a full 3D CH4 field from UKCA to the radiation scheme rather than passing a uniform concentration everywhere was evaluated in a present-day atmosphere-only configuration of the HadGEM1 model (Johns et al., 2006; Martin et al., 2006). It was found to cool the extra-tropical stratosphere by 0.5-1.0 K, thereby reducing the warm temperature biases in the model (O'Connor et al., 2009).CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunke8c12182-4bc0-11e0-9b89-00163e9152a5well_mixed_gas_CH4dataObject1Reference to a dataObject called well_mixed_gas_CH4317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmospheree8c12182-4bc0-11e0-9b89-00163e9152a5CH4_concentration_mmrfileVariable1Reference to a fileVariable called CH4_concentration_mmr in a dataObject called well_mixed_gas_CH4317f51b8-e2b3-11df-bf17-00163e9152a5well_mixed_gas_CH4componentProperty1Reference to a componentProperty called well_mixed_gas_CH4 in a modelComponent called AtmosphereThe N2O concentrations used were taken from the recommended CMIP5 dataset. HadGEM2-ES requires atmospheric concentrations of N2O in units of mass mixing ratio (mmr). A conversion factor of 44.013/(28.964e9) was used to convert units from values supplied in ppbv.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk04c2aa56-4bf6-11e0-9fc1-00163e9152a5well_mixed_gas_N2OdataObject1Reference to a dataObject called well_mixed_gas_N2O317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmosphere04c2aa56-4bf6-11e0-9fc1-00163e9152a5N2O_concentration_mmrfileVariable1Reference to a fileVariable called N2O_concentration_mmr in a dataObject called well_mixed_gas_N2O317f51b8-e2b3-11df-bf17-00163e9152a5well_mixed_gas_N2OcomponentProperty1Reference to a componentProperty called well_mixed_gas_N2O in a modelComponent called AtmosphereThe CMIP5 equivalent concentrations of CFC12 and HFC134a were derived by simply summing the radiative forcing of individual species and assuming linearity of both concentration and radiative forcing for a single species and of additivity of multiple species. CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkc0f481ea-4bf6-11e0-8b40-00163e9152a5well_mixed_gas_halocarbonsdataObject1Reference to a dataObject called well_mixed_gas_halocarbons317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmospherec0f481ea-4bf6-11e0-8b40-00163e9152a5CFC-12_concentration_mmrfileVariable1Reference to a fileVariable called CFC-12_concentration_mmr in a dataObject called well_mixed_gas_halocarbons317f51b8-e2b3-11df-bf17-00163e9152a5well_mixed_gas_CFC-12componentProperty1Reference to a componentProperty called well_mixed_gas_CFC-12 in a modelComponent called AtmosphereThe CMIP5 equivalent concentrations of CFC12 and HFC134a were derived by simply summing the radiative forcing of individual species and assuming linearity of both concentration and radiative forcing for a single species and of additivity of multiple species. CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkc0f481ea-4bf6-11e0-8b40-00163e9152a5well_mixed_gas_halocarbonsdataObject1Reference to a dataObject called well_mixed_gas_halocarbons317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmospherec0f481ea-4bf6-11e0-8b40-00163e9152a5HFC-134a_concentration_mmrfileVariable1Reference to a fileVariable called HFC-134a_concentration_mmr in a dataObject called well_mixed_gas_halocarbons317f51b8-e2b3-11df-bf17-00163e9152a5well_mixed_gas_HFC-134acomponentProperty1Reference to a componentProperty called well_mixed_gas_HFC-134a in a modelComponent called AtmosphereStratospheric ozone is prescribed as monthly zonal/height ancillary files taken from the CMIP5 recommended AC&C/SPARC ozone database. These data were horizontally interpolated onto the model N96 horizontal grid. Vertical interpolation was achieved by mapping the SPARC ozone data from pressure surfaces onto pressure surface equivalent levels corresponding to the models height-based grid. Near-surface missing data was replaced by overlying nearest neighbour non-missing data. Tropospheric ozone is simulated interactively by the UKCA atmospheric chemistry model using surface and aircraft emissions of tropospheric ozone precursors and reactive gases.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30non-conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk58472ef0-4e57-11e0-8b40-00163e9152a5well_mixed_gas_OzonedataObject1Reference to a dataObject called well_mixed_gas_Ozone317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmosphere58472ef0-4e57-11e0-8b40-00163e9152a5Oz_concentration_mmrfileVariable1Reference to a fileVariable called Oz_concentration_mmr in a dataObject called well_mixed_gas_Ozone317f51b8-e2b3-11df-bf17-00163e9152a5well_mixed_gas_OzonecomponentProperty1Reference to a componentProperty called well_mixed_gas_Ozone in a modelComponent called AtmosphereAnnual CO2 concentrations were provided by CMIP5 in units of parts per million by volume (ppmv) whereas HadGEm2-ES requires atmospheric concentrations of CO2 in units of mass mixing ratio (mmr). A conversion factor of (44.0/28.964e6) was used to convert units.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk30mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunka31d55c4-4bc0-11e0-a872-00163e9152a5well_mixed_gas_CO2dataObject1Reference to a dataObject called well_mixed_gas_CO23829e988-e2b3-11df-bf17-00163e9152a5OceanmodelComponent1Reference to a modelComponent called Oceana31d55c4-4bc0-11e0-a872-00163e9152a5CO2_concentration_mmrfileVariable1Reference to a fileVariable called CO2_concentration_mmr in a dataObject called well_mixed_gas_CO23829e988-e2b3-11df-bf17-00163e9152a5well_mixed_gas_CO2componentProperty1Reference to a componentProperty called well_mixed_gas_CO2 in a modelComponent called OceanStratospheric aerosol concentrations due to volcanic eruptions are varied across four equal area latitudinal zones on a monthly timescale. The aerosol is distributed vertically above the tropopause such that the mass mixing ratio is constant across the levels. In this version of the model, volcanic aerosol is not related to, and does not interact with, other simulated aerosol behaviour. The dataset used for the historic period was monthly stratospheric optical depths, at 550nm, from 1850 to 2000 (Sato et al., 1993).Background aerosols concentrations are covered in the sulphur_dioxide_emissions input. HadGEM2-ES does not treat any gases from volcanic sources as a climate forcing.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk1mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunke9c7b676-509e-11e0-b2eb-00163e9152a5volcanic_optical_thicknessdataObject1Reference to a dataObject called volcanic_optical_thickness317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmospheree9c7b676-509e-11e0-b2eb-00163e9152a5stratospheric_optical_thicknessfileVariable1Reference to a fileVariable called stratospheric_optical_thickness in a dataObject called volcanic_optical_thickness317f51b8-e2b3-11df-bf17-00163e9152a5volcanic aerosolcomponentProperty1Reference to a componentProperty called volcanic aerosol in a modelComponent called AtmosphereFor emissions of C2H6, all C2 species were combined (C2H6, ethene (C2H4), and ethyne (C2H2)) and treated as emissions of C2H6. These were each converted to kg(C2H6)/m2/s, added together, and then re-gridded onto the models N96 grid (1.75x1.25 degrees).CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf1ef9c22-50a0-11e0-9b89-00163e9152a5ethane_emissionsdataObject1Reference to a dataObject called ethane_emissions334a9872-e2b3-11df-bf17-00163e9152a5Atmospheric ChemistrymodelComponent1Reference to a modelComponent called Atmospheric Chemistryf1ef9c22-50a0-11e0-9b89-00163e9152a5ethane emissionsfileVariable1Reference to a fileVariable called ethane emissions in a dataObject called ethane_emissions334a9872-e2b3-11df-bf17-00163e9152a5ethane_emissionscomponentProperty1Reference to a componentProperty called ethane_emissions in a modelComponent called Atmospheric ChemistryFor surface emissions of C3H8, the C3 species (propane and propene (C3H6)) were combined and treated as emissions of C3H8. In each case a small adjustment was made after re-gridding onto the models N96 grid to ensure the global totals matched those of the original data. CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk1c155438-50a1-11e0-9b89-00163e9152a5propane_emissionsdataObject1Reference to a dataObject called propane_emissions334a9872-e2b3-11df-bf17-00163e9152a5Atmospheric ChemistrymodelComponent1Reference to a modelComponent called Atmospheric Chemistry1c155438-50a1-11e0-9b89-00163e9152a5propane_emissionsfileVariable1Reference to a fileVariable called propane_emissions in a dataObject called propane_emissions334a9872-e2b3-11df-bf17-00163e9152a5propane_emissionscomponentProperty1Reference to a componentProperty called propane_emissions in a modelComponent called Atmospheric ChemistryFor CO, emissions from land-based anthropogenic sources, biomass burning, and shipping were taken for the historical period from Lamarque et al. (2010a). These were added together and re-gridded on to an intermediate 1x1 degree grid in terms of kg(CO)/m2/s. Oceanic CO emissions were also added (45 Tg(CO)/year), and their spatial and temporal distribution were provided by the Global Emissions Inventory Activity (GEIA; http://www.geiacenter.org/inventories/present.html), based on distributions of oceanic VOC emissions from Guenther et al. (1995). In the absence of an isoprene (C5H8) oxidation mechanism in the UKCA tropospheric chemistry scheme used in HadGEM2-ES, an additional 354 Tg(CO)/year was added based on a global mean CO yield of 30 % from C5H8 from a study by Pfister et al. (2008) and a global C5H8 emission source of 506 TgC/year (Guenther et al., 1995). It is distributed spatially and temporally using C5H8 emissions from Guenther et al. (1995) and added to the other monthly mean emissions on the 1x1 degree grid. The total monthly mean emissions were then re-gridded on to the model?s N96 grid and a small adjustment applied to conserve the original global totals. CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk8fb6e3a2-50a1-11e0-bf90-00163e9152a5carbon_monoxide_emissionsdataObject1Reference to a dataObject called carbon_monoxide_emissions334a9872-e2b3-11df-bf17-00163e9152a5Atmospheric ChemistrymodelComponent1Reference to a modelComponent called Atmospheric Chemistry8fb6e3a2-50a1-11e0-bf90-00163e9152a5carbon_monoxide_emissionsfileVariable1Reference to a fileVariable called carbon_monoxide_emissions in a dataObject called carbon_monoxide_emissions334a9872-e2b3-11df-bf17-00163e9152a5carbon_monoxide_emissioncomponentProperty1Reference to a componentProperty called carbon_monoxide_emission in a modelComponent called Atmospheric ChemistryFor HCHO emissions, the monthly mean land-based anthropogenic sources were combined with monthly mean biomass burning emissions from Larmarque et al. (2010a) for the historical period and re-gridded on to the model's N96 grid. The emissions were then re-scaled to ensure that the global totals of the original emissions were maintained.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunke5d18b98-50a1-11e0-9b89-00163e9152a5formaldehyde_emissionsdataObject1Reference to a dataObject called formaldehyde_emissions334a9872-e2b3-11df-bf17-00163e9152a5Atmospheric ChemistrymodelComponent1Reference to a modelComponent called Atmospheric Chemistrye5d18b98-50a1-11e0-9b89-00163e9152a5formaldehyde_emissionsfileVariable1Reference to a fileVariable called formaldehyde_emissions in a dataObject called formaldehyde_emissions334a9872-e2b3-11df-bf17-00163e9152a5formaldehyde_emissionscomponentProperty1Reference to a componentProperty called formaldehyde_emissions in a modelComponent called Atmospheric ChemistryFor MeCHO, the monthly mean NMVOC biomass burning emissions from Lamarque et al. (2010a) for the historical period were used. Using different emission factors from Andreae and Merlet (2001) for grass fires, tropical forest fires, and extra-tropical forest fires, emissions of NMVOCs were converted into emissions of MeCHO (i.e. kg(MeCHO)/m2/s). They were then re-gridded on to the N96 grid of HadGEM2-ES and re-scaled to conserve the original global annual totals.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk1e916a66-50a2-11e0-b2eb-00163e9152a5acetaldehyde_emissionsdataObject1Reference to a dataObject called acetaldehyde_emissions334a9872-e2b3-11df-bf17-00163e9152a5Atmospheric ChemistrymodelComponent1Reference to a modelComponent called Atmospheric Chemistry1e916a66-50a2-11e0-b2eb-00163e9152a5acetaldehyde_emissionsfileVariable1Reference to a fileVariable called acetaldehyde_emissions in a dataObject called acetaldehyde_emissions334a9872-e2b3-11df-bf17-00163e9152a5acetaldehyde_emissionscomponentProperty1Reference to a componentProperty called acetaldehyde_emissions in a modelComponent called Atmospheric ChemistrySurface emissions of Me2CO were taken from land-based anthropogenic sources and biomass burning from Lamarque et al. (2010a, 2010b). These were added together and re-gridded on to an intermediate 1x1 degree grid in terms of kg(Me2CO)/m2/s. Then, the dominant source of Me2CO from vegetation was added, based on a global distribution from Guenther et al. (1995) and scaled to give a global annual total of 40.0 Tg(Me2CO)/year. The total monthly mean emissions were then re-gridded on to the model?s N96 and a small re-adjustment applied to conserve the original global annual totals. CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5662e820-50a2-11e0-9b89-00163e9152a5acetone_emissionsdataObject1Reference to a dataObject called acetone_emissions334a9872-e2b3-11df-bf17-00163e9152a5Atmospheric ChemistrymodelComponent1Reference to a modelComponent called Atmospheric Chemistry5662e820-50a2-11e0-9b89-00163e9152a5acetone_emissionsfileVariable1Reference to a fileVariable called acetone_emissions in a dataObject called acetone_emissions334a9872-e2b3-11df-bf17-00163e9152a5acetone_emissionscomponentProperty1Reference to a componentProperty called acetone_emissions in a modelComponent called Atmospheric ChemistryFor NOx surface emissions, contributions from land-based anthropogenic sources, biomass burning, and shipping from Larmarque et al. (2010a) were added together and re-gridded on to an intermediate 1x1 degree grid in terms of kg(NO)/m2/s. Added to these were a contribution from natural soil emissions, based on a global and monthly distribution provided by GEIA on a 1x1 degree grid (http://www.geiacenter.org/inventories/present.html), and based on the global empirical model of soil-biogenic emissions from Yienger and Levy II (1995). These were scaled to contribute an additional 12 Tg(NO)/year. The total emissions were then re-gridded on to the model?s N96 grid and a small adjustment applied to conserve the original global totals. CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkaadca97c-50a2-11e0-bf90-00163e9152a5nitrogen_oxide_emissionsdataObject1Reference to a dataObject called nitrogen_oxide_emissions334a9872-e2b3-11df-bf17-00163e9152a5Atmospheric ChemistrymodelComponent1Reference to a modelComponent called Atmospheric Chemistryaadca97c-50a2-11e0-bf90-00163e9152a5nitrogen_oxide_emissionsfileVariable1Reference to a fileVariable called nitrogen_oxide_emissions in a dataObject called nitrogen_oxide_emissions334a9872-e2b3-11df-bf17-00163e9152a5surface_NOx_emissionscomponentProperty1Reference to a componentProperty called surface_NOx_emissions in a modelComponent called Atmospheric ChemistryIn the case of NOx emissions, 3D emissions from aircraft were also considered. These were supplied as monthly mean fields on a 25 level (L25) 0.5x0.5 grid by Lamarque et al. (2010a) for the historical period. They were first re-gridded on to an N96xL25 grid and then projected on to the model?s N96xL38 grid, ensuring that the global annual total emissions were conserved. CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkecb81520-50a2-11e0-9b89-00163e9152a5aircraft_emissionsdataObject1Reference to a dataObject called aircraft_emissions334a9872-e2b3-11df-bf17-00163e9152a5Atmospheric ChemistrymodelComponent1Reference to a modelComponent called Atmospheric Chemistryecb81520-50a2-11e0-9b89-00163e9152a5nitrogen_oxide_emissionsfileVariable1Reference to a fileVariable called nitrogen_oxide_emissions in a dataObject called aircraft_emissions334a9872-e2b3-11df-bf17-00163e9152a5aircraft_NOx_emissionscomponentProperty1Reference to a componentProperty called aircraft_NOx_emissions in a modelComponent called Atmospheric ChemistryDataset is derived from the historical time series prepared for CMIP5. This input field is interpolated by the model every 5 simulated days from the prescribed monthly mean field.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk465110ea-5176-11e0-9b89-00163e9152a5fossil_fuel_black_carbondataObject1Reference to a dataObject called fossil_fuel_black_carbon30ba0df4-e2b3-11df-bf17-00163e9152a5AerosolsmodelComponent1Reference to a modelComponent called Aerosols465110ea-5176-11e0-9b89-00163e9152a5fossil_fuel_black_carbonfileVariable1Reference to a fileVariable called fossil_fuel_black_carbon in a dataObject called fossil_fuel_black_carbon30ba0df4-e2b3-11df-bf17-00163e9152a5fossil_fuel_black_carboncomponentProperty1Reference to a componentProperty called fossil_fuel_black_carbon in a modelComponent called AerosolsDataset is derived from the historical time series prepared for CMIP5. This input field is interpolated by the model every 5 simulated days from the prescribed monthly mean field.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk8e92715a-5176-11e0-9919-00163e9152a5fossil_fuel_organic_carbondataObject1Reference to a dataObject called fossil_fuel_organic_carbon30ba0df4-e2b3-11df-bf17-00163e9152a5AerosolsmodelComponent1Reference to a modelComponent called Aerosols8e92715a-5176-11e0-9919-00163e9152a5fossil_fuel_organic_carbonfileVariable1Reference to a fileVariable called fossil_fuel_organic_carbon in a dataObject called fossil_fuel_organic_carbon30ba0df4-e2b3-11df-bf17-00163e9152a5fossil_fuel_organic_carbcomponentProperty1Reference to a componentProperty called fossil_fuel_organic_carb in a modelComponent called AerosolsDataset is derived from the historical time series prepared for CMIP5. These input fields are interpolated by the model every 5 simulated days from the prescribed monthly mean field.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkbd51f29a-5176-11e0-94a5-00163e9152a5biomass_burningdataObject1Reference to a dataObject called biomass_burning30ba0df4-e2b3-11df-bf17-00163e9152a5AerosolsmodelComponent1Reference to a modelComponent called Aerosolsbd51f29a-5176-11e0-94a5-00163e9152a5grass fire emissionsfileVariable1Reference to a fileVariable called grass fire emissions in a dataObject called biomass_burning30ba0df4-e2b3-11df-bf17-00163e9152a5biomass_burningcomponentProperty1Reference to a componentProperty called biomass_burning in a modelComponent called AerosolsDataset is derived from the historical time series prepared for CMIP5. These input fields are interpolated by the model every 5 simulated days from the prescribed monthly mean field.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkbd51f29a-5176-11e0-94a5-00163e9152a5biomass_burningdataObject1Reference to a dataObject called biomass_burning30ba0df4-e2b3-11df-bf17-00163e9152a5AerosolsmodelComponent1Reference to a modelComponent called Aerosolsbd51f29a-5176-11e0-94a5-00163e9152a5forest fire emissionsfileVariable1Reference to a fileVariable called forest fire emissions in a dataObject called biomass_burning30ba0df4-e2b3-11df-bf17-00163e9152a5biomass_burningcomponentProperty1Reference to a componentProperty called biomass_burning in a modelComponent called AerosolsDataset is derived from Andres and Kasgnoc (1998). The total emissions are presented as annual values with the emissions constant at 0.62 Tg[S]/yr). The distribution of emissions varies from year to year, both horizontally and vertically.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk19a1da9a-5179-11e0-aa5f-00163e9152a5sulphur_dioxide_emissionsdataObject1Reference to a dataObject called sulphur_dioxide_emissions317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmosphere19a1da9a-5179-11e0-aa5f-00163e9152a5sulphur dioxidefileVariable1Reference to a fileVariable called sulphur dioxide in a dataObject called sulphur_dioxide_emissions317f51b8-e2b3-11df-bf17-00163e9152a5volcanic SO2 emissionscomponentProperty1Reference to a componentProperty called volcanic SO2 emissions in a modelComponent called AtmosphereDataset is derived from Spiro et al. (1992) and has a constant annual rate of 0.86 Tg[S]/yr. The emissions are presented monthly and vary horizontally and by month to account for seasonal effects.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk4693d238-5179-11e0-aa5f-00163e9152a5DMS_emissionsdataObject1Reference to a dataObject called DMS_emissions317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmosphere4693d238-5179-11e0-aa5f-00163e9152a5DMS_emissionsfileVariable1Reference to a fileVariable called DMS_emissions in a dataObject called DMS_emissions317f51b8-e2b3-11df-bf17-00163e9152a5land DMS emissionscomponentProperty1Reference to a componentProperty called land DMS emissions in a modelComponent called AtmosphereDataset is derived from annual sector based emissions. Data is presented on N96 grid.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk9f025ae4-53b2-11e0-a555-00163e9152a5anthropogenic_emissions_SO2dataObject1Reference to a dataObject called anthropogenic_emissions_SO2317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmosphere9f025ae4-53b2-11e0-a555-00163e9152a5SO2_emissionsfileVariable1Reference to a fileVariable called SO2_emissions in a dataObject called anthropogenic_emissions_SO2317f51b8-e2b3-11df-bf17-00163e9152a5anthro_SO2_aerosolcomponentProperty1Reference to a componentProperty called anthro_SO2_aerosol in a modelComponent called AtmosphereAnnual mean variations in total solar irradiance (TSI) passed to the model are partitioned across six shortwave spectral bands (0.2-10um) to estimate the associated spectral changes with TSI variations (Lean et al., 1995). With the changes across the spectral bands the Rayleigh scattering and ozone absorption properties are also varied in the model. The TSI data used for the historic period were recommended by CMIP5 (Lean et al., SOLARIS 2009) and are created from reconstructions of solar cycle and background variations in TSI. The annual mean TSI was processed to force the mean of the 1700-2004 period to be the same as the model control solar constant value (1365 Wm-2). CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5mappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk753a78ee-e2ac-11df-b3ef-00163e9152a5solardataObject1Reference to a dataObject called solar317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmosphere753a78ee-e2ac-11df-b3ef-00163e9152a5Total Solar IrradiancefileVariable1Reference to a fileVariable called Total Solar Irradiance in a dataObject called solar317f51b8-e2b3-11df-bf17-00163e9152a5solar irradiancecomponentProperty1Reference to a componentProperty called solar irradiance in a modelComponent called AtmosphereThe summed fractional coverage of crop and pasture is provided as a time-varying input on an annual basis. These data are interpolated at intervals of 10 days within the model. Other land use fractions are simulated by the models vegetation dynamics. CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk10conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk50d396d6-53cf-11e0-ad0a-00163e9152a5crop_pasturedataObject1Reference to a dataObject called crop_pasture359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surface50d396d6-53cf-11e0-ad0a-00163e9152a5fractional_cover_crop_pasturefileVariable1Reference to a fileVariable called fractional_cover_crop_pasture in a dataObject called crop_pasture359a10f8-e2b3-11df-bf17-00163e9152a5changing_anthro_land_usecomponentProperty1Reference to a componentProperty called changing_anthro_land_use in a modelComponent called Land SurfaceSecondary organic aerosols from biogenic emissions are represented by monthly distributions of three-dimensional mass-mixing ratios obtained from the chemistry transport model (Derwent et al., 2003). These distributions are presented as monthly 3D profiles that are constant for all simulated years.CouplingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk5conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunke5d7f29a-5474-11e0-a872-00163e9152a5biogenic_emission_aerosolsdataObject1Reference to a dataObject called biogenic_emission_aerosols317f51b8-e2b3-11df-bf17-00163e9152a5AtmospheremodelComponent1Reference to a modelComponent called Atmosphere317f51b8-e2b3-11df-bf17-00163e9152a5biogenic_emission_aerosocomponentProperty1Reference to a componentProperty called biogenic_emission_aeroso in a modelComponent called AtmosphereThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_baresoilfileVariable1Reference to a fileVariable called fractional_cover_baresoil in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_broadleaf_treefileVariable1Reference to a fileVariable called fractional_cover_broadleaf_tree in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_C3_grassfileVariable1Reference to a fileVariable called fractional_cover_C3_grass in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_C4_grassfileVariable1Reference to a fileVariable called fractional_cover_C4_grass in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_icefileVariable1Reference to a fileVariable called fractional_cover_ice in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_lakefileVariable1Reference to a fileVariable called fractional_cover_lake in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_needleleaf_treefileVariable1Reference to a fileVariable called fractional_cover_needleleaf_tree in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_shrubfileVariable1Reference to a fileVariable called fractional_cover_shrub in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceThe historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.conservativemappingTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a5land_usedataObject1Reference to a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5Land SurfacemodelComponent1Reference to a modelComponent called Land Surfacef59b8360-53cd-11e0-ad0a-00163e9152a5fractional_cover_urbanfileVariable1Reference to a fileVariable called fractional_cover_urban in a dataObject called land_use359a10f8-e2b3-11df-bf17-00163e9152a5initial_land_usecomponentProperty1Reference to a componentProperty called initial_land_use in a modelComponent called Land SurfaceC. Jones, J. Hughes, G. Jones, N. Christidis, F. Lott, A .Sellar, M. Webb, A. Bodas-Salcedo, Y. Tsushima, G. Martin76f85a8a-4830-11e1-8ba0-00163e9152a5ic.102NumericalRequirement1Reference to a NumericalRequirement called ic.102 in a experiment called 7.4 historicalExtExtends historical ensemble from 2006 to 2019.76f85a8a-4830-11e1-8ba0-00163e9152a5stc.040NumericalRequirement1Reference to a NumericalRequirement called stc.040 in a experiment called 7.4 historicalExtThe forcing beyond 2006 was as provided for the rcp85 simulation.76f85a8a-4830-11e1-8ba0-00163e9152a5bc.103NumericalRequirement1Reference to a NumericalRequirement called bc.103 in a experiment called 7.4 historicalExtThe resources(deployment) on which this simulation ranb765775a-e2ac-11df-9efb-00163e9152a5IBM Power 6platform1Reference to a platform called IBM Power 6P14Y2005-12-01T00:00:00Z309f6a26-e2b3-11df-bf17-00163e9152a5HadGEM2-ESmodelComponent2Reference to a modelComponent called HadGEM2-ES84d52fd8-2c8e-11e1-a4f1-00163e9152a54QN_DRS
The QN_DRS value allows mapping from data files to metadata
being exported from the metadata questionnaire, and contains
the institution name, the model name on which the simulation
was run, the experiment name to which the simulation
conforms, the simulation level base rip value, and finally
the given start year for the simulation. The format of the string will thus be:
institute_model_experiment_rip_startyear. Also note, that in particular cases,
i.e. decadal and noVolc exps, the start date and expdate
may differ - this will occur in those cases where the simulation
start date is 1st january but still refers to an experiment
for the year before. - (see cmip5 experiment design document)
DRS_CMIP5_ensembleTypeMetafor Questionnaire2012-04-23T15:26:46.983209parent branch date is 2005-12-01b83aceb2-e349-11df-b73d-00163e9152a5historicalsimulation4Reference to a simulation called historicalUK Met Office Hadley CentreMOHChistoricalExt3.2 Historical Extension (2005-2019)Extends three of the four elements of the historical ensemble (elements r2, r3, and r4) - runs initialised using dump files from the end of the relevant element in the historical ensemble.76f85a8a-4830-11e1-8ba0-00163e9152a57.4 historicalExtexperiment1Reference to a experiment called 7.4 historicalExtensembleTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk84d52fd8-2c8e-11e1-a4f1-00163e9152a5historicalExtsimulation4Reference to a simulation called historicalExtDRS_CMIP5_ensembleTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk84d52fd8-2c8e-11e1-a4f1-00163e9152a5historicalExtsimulation4Reference to a simulation called historicalExtDRS_CMIP5_ensembleType84d52fd8-2c8e-11e1-a4f1-00163e9152a5historicalExtsimulation4Reference to a simulation called historicalExtDRS_CMIP5_ensembleType317d1bc8-4671-11e1-b757-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.301476Climate change detection/attribution study and evaluation of model performance against present climate and observed climate change.historicalExtHistorical ExtensionExtend the CMIP5 historical runs to the near-present (as we have for AMIP), rather than ending them in 2005.
Simulations extended to at least the end of 2012 using some estimate of recent and future forcing.
Groups are free to use whatever concentrations, solar forcing, SO2 emissions etc. they want to use in extending these runs.
It is also o.k. for detection/attribution studies to simply splice one of the RCP runs to the end of the historical simulations.
It is recommended that if an ensemble of "all-forcings" historical simulations have been run, then *each* member of the ensemble should be carried to the end of 2012.
For all-forcing (anthro + natural) historical runs, the extended portions of these runs should be treated as a new runs spawned from the parent historical runs at
the end of year 2005. If this run is forced by an RCP that extends at least to the end of the 21st century, then nothing special needs to be done.
If, however, some other forcing is used or if the run is an RCP run that is truncated after a few years (say ending in 2012), then the run should be considered a
"historical extension" experiment with its output placed in a directory named historicalExt. The "forcing" attribute (a netCDF global attribute) should describe what
forcing is used to extend the run, and this information will also need to be recorded here in the questionnaire.
For these historicalExt experiments, the ensemble member (designated by the "rip" value appearing in the filename and recorded as netCDF global attributes)
will be identical to the historical run it extends.
If one chooses to do historical runs with only a subset of forcing (e.g., GHG only, natural forcing only, single-forcing experiments, etc.), then all the data for
the complete historical period and in the extended portion (from 2006-2012) would be kept together, no matter what forcing was used (in the historicalNat, historicalGHG,
or historicalMisc directories).7.4ic.1027.4.icInitial conditions are from the historical experiment, number 3.27.4.bc.historicalForcingExtensionForcing applied to the historical extension simulationbc.1037.4.bc.RCPTruncated RCP forcingbc.1047.4.bc.otherForcingOther forcing agentsstc.0407.4.stc.2005_7yrBegin near the end of 2005 and run for 7 yearsP7Y2012-12-31T00:00:00Z2005-12-31T00:00:00Z76f85a8a-4830-11e1-8ba0-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.312062IBM Power 6_OtherMachine IBM Power 6 and compiler OtherUK Met Office Hadley CentreMOHCIBM Power 6ParallelmachineOperatingSystemhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkmachineVendorhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkmachineInterconnecthttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk232machineProcessorTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkOther12.1.0.0b765775a-e2ac-11df-9efb-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.312262
well_mixed_gas_CO2
Atmospheric concentrations of CO2 expressed in units of mass mixing ratio (mmr) with units of kg/kg. The factor used to convert concentrations provided by CMIP5 in ppmv to mmr units was (44.0/28.964e6)dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkCO2 concentrationdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkCO2_concentration_mmrCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunka31d55c4-4bc0-11e0-a872-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.403839
well_mixed_gas_CH4
Surface concentrations of CH4 expressed in units of mass mixing ratio (mmr) with units of kg/kg. The factor used to convert concentrations provided by CMIP5 in ppbv to mmr units was (16.04/28.964e9).dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkMethane concentrationdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkO'Connor 2009doi:10.1029/2009GL039152,2009.O'Connor, F.M., C.E. Johnson, O. Morgenstern, and W.J. Collins (2009) Interactions between tropospheric chemistry and climate model temperature and humidity biases. Geophys. Res. Lett., 36, L16801,CH4_concentration_mmrCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunke8c12182-4bc0-11e0-9b89-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.408846
well_mixed_gas_N2O
Atmospheric concentrations of N2O expressed in units of mass mixing ratio (mmr) with units of kg/kg. The factor used to convert concentrations provided by CMIP5 in ppbv to mmr units was (44.013/(28.964e9).dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkN2O concentrationdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkN2O_concentration_mmrCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk04c2aa56-4bf6-11e0-9fc1-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.412090
well_mixed_gas_halocarbons
Atmopheric concentrations of CFC-12 and HFC-134a expressed in terms of mass mixing ratio (mmr) with units of kg/kg.dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkhalocarbon concentrationsdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkCFC-12_concentration_mmrCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkHFC-134a_concentration_mmrmass_fraction_of_cfc134a_in_air (awaiting entry in CF names table)c0f481ea-4bf6-11e0-8b40-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.416196
well_mixed_gas_Ozone
3D gridded data of stratospheric ozone interpolated to the grids of the model using the file (17 levels for HadCM3).dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkOzone concentrations in the stratospheredataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkOz_concentration_mmrCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk58472ef0-4e57-11e0-8b40-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.419649
volcanic_optical_thickness
Vertical profiles of optical thickness for four equal area latitudinal zones on a monthly timestep. Derived from http://data.giss.nasa.gov/modelforce/strataer/dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkOptical thickness in stratosphere due to volcanic aerosolsdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkstratospheric_optical_thicknessCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunke9c7b676-509e-11e0-b2eb-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.423035
ethane_emissions
2D gridded annual surface emissions of ethanedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksurface emissions of ethanedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkethane emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf1ef9c22-50a0-11e0-9b89-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.426295
propane_emissions
2D gridded annual surface emissions of propanedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksurface emissions of propanedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkpropane_emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk1c155438-50a1-11e0-9b89-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.429529
carbon_monoxide_emissions
2D gridded annual surface emissions of Carbon MonoxidedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksurface emissions of carbon monoxidedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkLamarque et al. 2010aLamarque, J.-F., T. C. Bond, V. Eyring, C. Granier, A. Heil, Z. Klimont, D. Lee, C. Liousse, A. Mieville, B. Owen, M. G. Schultz, D. Shindell, S. J. Smith, E. Stehfest, J. Van Aardenne, O. R. Cooper, M. Kainuma, N. Mahowald, J. R. McConnell, V. Naik, K. Riahi, and D. P. van Vuuren (2010) Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos. Chem. Phys., 10, 7017-7039 carbon_monoxide_emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk8fb6e3a2-50a1-11e0-bf90-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.434802
formaldehyde_emissions
2D gridded annual surface emissions of formaldehydedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksurface emissions of formaldehydedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkLamarque et al. 2010aLamarque, J.-F., T. C. Bond, V. Eyring, C. Granier, A. Heil, Z. Klimont, D. Lee, C. Liousse, A. Mieville, B. Owen, M. G. Schultz, D. Shindell, S. J. Smith, E. Stehfest, J. Van Aardenne, O. R. Cooper, M. Kainuma, N. Mahowald, J. R. McConnell, V. Naik, K. Riahi, and D. P. van Vuuren (2010) Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos. Chem. Phys., 10, 7017-7039 formaldehyde_emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunke5d18b98-50a1-11e0-9b89-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.439846
acetaldehyde_emissions
2D gridded annual surface emissions of acetaldehydedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksurface emissions of acetaldehydedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkAndreae 2001Andreae, M.O., and P. Merlet (2001) Emission of Trace Gases and Aerosols From Biomass Burning Global Biogeochem. Cy., 15(4), 955-966 acetaldehyde_emissionswaiting for cf_name: tendency_of_atmosphere_mass_content_of_acetaldehyde_due_to_emission1e916a66-50a2-11e0-b2eb-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.443995
acetone_emissions
2D gridded annual surface emissions of acetonedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksurface emissions of acetonedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkLamarque et al. 2010aLamarque, J.-F., T. C. Bond, V. Eyring, C. Granier, A. Heil, Z. Klimont, D. Lee, C. Liousse, A. Mieville, B. Owen, M. G. Schultz, D. Shindell, S. J. Smith, E. Stehfest, J. Van Aardenne, O. R. Cooper, M. Kainuma, N. Mahowald, J. R. McConnell, V. Naik, K. Riahi, and D. P. van Vuuren (2010) Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos. Chem. Phys., 10, 7017-7039 acetone_emissionswaiting for cf_name: tendency_of_atmosphere_mass_content_of_acetone_due_to_emission5662e820-50a2-11e0-9b89-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.448062
nitrogen_oxide_emissions
2D gridded annual surface emissions of nitrogen oxidesdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunksurface emissions of nitrogen oxidesdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkLamarque et al. 2010aLamarque, J.-F., T. C. Bond, V. Eyring, C. Granier, A. Heil, Z. Klimont, D. Lee, C. Liousse, A. Mieville, B. Owen, M. G. Schultz, D. Shindell, S. J. Smith, E. Stehfest, J. Van Aardenne, O. R. Cooper, M. Kainuma, N. Mahowald, J. R. McConnell, V. Naik, K. Riahi, and D. P. van Vuuren (2010) Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos. Chem. Phys., 10, 7017-7039 nitrogen_oxide_emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkaadca97c-50a2-11e0-bf90-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.453344
aircraft_emissions
3D gridded monthly surface emissions of nitrogen oxides from aircraftdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkaircraft emissions of nitrogen oxidesdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkLamarque et al. 2010aLamarque, J.-F., T. C. Bond, V. Eyring, C. Granier, A. Heil, Z. Klimont, D. Lee, C. Liousse, A. Mieville, B. Owen, M. G. Schultz, D. Shindell, S. J. Smith, E. Stehfest, J. Van Aardenne, O. R. Cooper, M. Kainuma, N. Mahowald, J. R. McConnell, V. Naik, K. Riahi, and D. P. van Vuuren (2010) Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos. Chem. Phys., 10, 7017-7039 nitrogen_oxide_emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkecb81520-50a2-11e0-9b89-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.458912
fossil_fuel_black_carbon
2D gridded monthly-mean fields of black carbon emissions from fossil fuel burningdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkemissions of black carbon from fossil fuel buringdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfossil_fuel_black_carbonCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk465110ea-5176-11e0-9b89-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.462189
fossil_fuel_organic_carbon
2D gridded monthly-mean fields of organic carbon emissions from fossil fuel burningdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkemissions of organic carbon from fossil fuel burningdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfossil_fuel_organic_carbonmissing CF name: tendency_of_atmosphere_mass_content_of_carbon_dioxide_expressed_as_carbon_due_to_emission_from_fossil_fuel_combustion8e92715a-5176-11e0-9919-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.464283
biomass_burning
2D gridded monthly-mean fields of grass fire and forest fire combined emissions of black carbon and organic carbon from biomass burning. dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkemissions from biomass burningdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkforest fire emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkgrass fire emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkbd51f29a-5176-11e0-94a5-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.468268
sulphur_dioxide_emissions
dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkemissions of sulphur dioxidedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkAndres 1998Andres, R.J. and Kasgnoc, A.D. (1998) A time-averaged inventory of subaerial volcanic sulfur emissions. J. Geophys. Res., 103, 25251-25261, 1998. sulphur dioxideCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk19a1da9a-5179-11e0-aa5f-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.473157
DMS_emissions
land based DMS emissionsdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkemissions of dimethyl sulfidedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkSpiro 1992Spiro, 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. DMS_emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk4693d238-5179-11e0-aa5f-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.478273
anthropogenic_emissions_SO2
Dataset is derived from annual sector based emissions. Data is presented on N96 griddataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkAnthropogenic emissions of sulphur dioxidedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkSO2_emissionsCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk9f025ae4-53b2-11e0-a555-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.481327
solar
Annual mean variations in total solar irradiance (TSI) are partitioned across six shortwave spectral bands (0.2-10μm) to estimate the associated spectral changes with TSI variations (Lean et al., 1995). With the changes across the spectral bands the Rayleigh scattering and ozone absorption properties are also varied. The TSI data used for the historic period were recommended by CMIP5 (Lean et al., 2009 -L09; SOLARIS 2009) and are created from reconstructions of solar cycle and background variations in TSI. The annual mean TSI was processed to force the mean of the 1700-2004 period to be the same as the model control solar constant value (1365 Wm-2). dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkSolar IrradiancedataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkSOLARIS 2009http://www.geo.fu-berlin.de/en/met/ag/strat/forschung/SOLARIS/Input_data/CMIP5_solar_irradiance.htmlCMIP5 solar irradianceTotal Solar IrradianceCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkTotal solar irradiance in Wm-2753a78ee-e2ac-11df-b3ef-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.486407
crop_pasture
Annual fractional cover of crop/pasture. The historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution with annual increments. The disturbed fraction is re-gridded onto the N96 grid using area average re-griddingdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfraction of anthropogenic disturbed landdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkHurtt et al. 2010Hurtt, G. C. , L. P. Chini, S. Frolking, R. Betts, J. Feddema, G. Fischer, J. P. Fisk, K. Hibbard, R. A. Houghton, A. Janetos, C. Jones, G. Kindermann, T. Kinoshita, K. Klein Goldewijk, K. Riahi, E. Shevliakova, S. Smith, E. Stehfest, A. Thomson, P. Thornton, D. P. van Vuuren, Y. Wang (2010) Harmonization of Land-Use Scenarios for the Period 1500-2100: 600 Years of Global Gridded Annual Land-Use Transitions, Wood Harvest, and Resulting Secondary Lands. Climatic Change, submittedfractional_cover_crop_pastureCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunk50d396d6-53cf-11e0-ad0a-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.491552
biogenic_emission_aerosols
These biogenic emissions (represented as concentrations) are obtained from an external chemistry transport model (Derwent et al., 2003) , and are presented as monthly 3D profiles that are constant for all simulated years.dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkSecondary organic aerosols from biogenic emissionsdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkDerwent 2003Derwent, 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.biogenic emission concentrationCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkCHECK cf namee5d7f29a-5474-11e0-a872-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.496626
land_use
The historical land use data is based on the HYDE database v3.1 (Klein Goldewijk et al., 2010a; Klein Goldewijk et al., 2010b) as processed for CMIP5 by Hurtt et al (2010), and made available at 0.5 x 0.5 degree resolution. These fractions are mapped on to the N96 grid using area average re-gridding.dataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkhttp://cmip-pcmdi.llnl.gov/cmip5/forcing.html#land-use_dataland use fractionsdataFormatTypehttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkHurtt et al. 2010Hurtt, G. C. , L. P. Chini, S. Frolking, R. Betts, J. Feddema, G. Fischer, J. P. Fisk, K. Hibbard, R. A. Houghton, A. Janetos, C. Jones, G. Kindermann, T. Kinoshita, K. Klein Goldewijk, K. Riahi, E. Shevliakova, S. Smith, E. Stehfest, A. Thomson, P. Thornton, D. P. van Vuuren, Y. Wang (2010) Harmonization of Land-Use Scenarios for the Period 1500-2100: 600 Years of Global Gridded Annual Land-Use Transitions, Wood Harvest, and Resulting Secondary Lands. Climatic Change, submittedfractional_cover_baresoilCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfractional_cover_broadleaf_treeCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfractional_cover_C3_grassCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfractional_cover_C4_grassCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfractional_cover_iceCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfractional_cover_lakeCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfractional_cover_needleleaf_treeCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfractional_cover_shrubCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkfractional_cover_urbanCFhttp://proj.badc.rl.ac.uk/svn/metafor/cmip5q/trunkf59b8360-53cd-11e0-ad0a-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.509435UM N96L38 ATM Grid SystemMet Office Unified Model 192-column 38-level Atmosphere Grid SystemSpecification of the atmosphere grid configuration utilised in the Met Office Hadley Centre's HadGEM1 and HadGEM2 climate models.
The key features of the N96L38 grid configuration, which is utilised by the Met Office Hadley Centre HadGAM1 and HadGAM2 atmosphere models, are as follows.
The grid is logically rectangular and dimensioned (i=192, j=145, k=38), where i = longitude, j = latitude, k = level. Horizontal grid cell size is 1.875 degrees in longitude by 1.25 degrees in latitude. Vertical levels are terrain-following for levels up to k=29 and constant thickness above that level. Grid staggering (i.e. between the sub-grids used by scalar (physics) and vector quantities) is based upon the Arakawa-C grid configuration.
Array indexing in the latitude direction starts at the south pole. For an unrotated grid mesh, longitude (i=0.5) corresponds to Greenwich meridian.
In the Unified Model, the north and south poles coincide with the bounding half-integer j planes, i.e. j=0.5 and j=M-0.5. P-points and u-points exist at the poles, but not v-points. At the poles all values of P variables are set equal. Likewise for scalar variables rho, theta, m, w.Johns_2005Johns T.C., et al. (2005). "HadGEM1 - Model description and analysis of preliminary experiments for the IPCC Fourth Assessment Report". Hadley Centre Technical Note 55, Met, Office, Exeter 74pp. Martin 2006Martin G.M., M.A. Ringer, V.D. Pope, A. Jones, C. Dearden and T.J. Hinton (2006) The physical properties of the atmosphere in the new Hadley Centre Global Environmental Model, HadGEM1 - Part 1: Model description and global climatology. Journal of Climate, American Meteorological Society, Vol. 19, No.7, pages 1274-1301. Horizontal properties: The N96 Grid represents the 192-column horizontal coordinate system utilised within the Met Office Hadley Centre HadGAM1 and HadGAM2 atmosphere models. This grid defines the horizontal locations of the physics (P) variables computed by these atmosphere models. The locations of U variables are offset by one-half of a grid cell to the east of P grid locations. The locations of V variables are offset by one-half of a grid cell to the north of P grid locations. Vertical properties: Vertical levels are terrain-following for levels up to k=29 and constant thickness above that level.-90900360145NumberOfLatitudinalGridCells192NumberOfLongitudinalGridCells39254.8TopModelLeveln/aNumberOfLevelsBelow850hPan/aNumberOfLevelsAbove200hPa38NumberOfLevelsHybrid height, terrain-following near bottom boundaryHybridizationN9656259768-e2b1-11df-aab5-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.803479UM N180L40 OCN Grid SystemMet Office Unified Model 360-column 40-level Ocean Grid SystemSpecification of the ocean grid configuration utilised in the Met Office Hadley Centre's HadGEM1 and HadGEM2 climate models.
The key features of the N180L40 grid, which is utilised within the Met Office Hadley Centre HadGOM1 and HadGOM2 ocean models, are as follows:
The grid is logically rectangular and dimensioned (i=360, j=216, k=40), where i = longitude, j = latitude, k = depth. The grid is characterised as regular rather than uniform since the Y dimension (latitude) is specified via a 1D vector rather than a constant scalar offset.
Between the poles and 30 degrees N and S the horizontal grid cell size is 1.0 degree by 1.0 degree. In the tropical region, however, the grid cell size in the Y/latitude directon decreases (and resolution increases) smoothly from 1 degree at 30 N/S to approximately 1/3 degree at the equator.
Grid staggering in the HadGOM1/HadGOM2 ocean grid is based upon the Arakawa-B grid scheme. In this scheme, u and v variables are co-located at the corners points of the grid cells. T and w variables coincide in the horizontal (at the grid cell centres) but are offset from each other by one-half a grid cell in the vertical. In physical space, T/w points are exactly halfway in latitude between u/v points, but the converse does not hold true. In the vertical, T points are exactly halfway in depth between w points, but again the converse does not hold true.Johns_2005Johns T.C., et al. (2005). "HadGEM1 - Model description and analysis of preliminary experiments for the IPCC Fourth Assessment Report". Hadley Centre Technical Note 55, Met, Office, Exeter 74pp. Johns_2006Johns 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. Horizontal properties: Between the poles and 30 degrees N and S the horizontal grid cell size is 1.0 degree by 1.0 degree. In the tropical region, however, the grid cell size in the Y/latitude direction decreases (and resolution increases) smoothly from 1 degree at 30 N/S to approximately 1/3 degree at the equator. Vertical properties: Layer thickness increases from 10 m at the surface to 345 m at maximum depth-90900360216NumberOfLatitudinalGridCells360NumberOfLongitudinalGridCells10NumberOfLevelsInUpper100m5.0UpperLevel5327.5LowerLevel40NumberOfLevelsN1809cef52e4-e2af-11df-bf17-00163e9152a51Metafor Questionnaire2012-04-23T15:26:47.926211