UKESM1-0-LL
Name: UKESM1-0-LL
Long name: UKESM1.0-N96ORCA1
Coupled model type(s): GCM
Version: 3.1
Top level description
- aerosol: UKCA-GLOMAP-mode,
- atmos: MetUM-HadGEM3-GA7.1 (N96;192 x 144 longitude/latitude; 85 levels; top level 85km),
- atmosChem: UKCA-StratTrop,
- land: JULES-ES-1.0,
- landIce:none,
- ocean:NEMO-HadGEM3-GO6.0 (eORCA1 tripolar primarily 1 deg latitude/longitude with meridional refinement down to 1/3 deg in tropics; 360 x 180 longitude/latitude; 75 levels; top grid cell 0-1m),
- ocnBgchem: MEDUSA2,
- seaIce:CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 180 longitude/latitude)
Coupler: OASIS3-MCT
Activity Properties
Radiative forcings
Description:Describes forcings related to aerosols, greenhouse gases and other – land use forcing and solar forcing.
Overview:Radiative forcings of the model for historical and scenario (aka Table 12.1 IPCC AR5)
Name: CMIP v6.2.0
Overview: SEE INFORMATION UNDER AEROSOLS, GREENHOUSE GASES and OTHER – LAND USE FORCING AND SOLAR FORCING
Scientific topic: Greenhouse gases Overview: Greenhouse gas forcing agents
Description:In concentration-driven runs, CO2 is prescribed as a spatially-constant scalar; in emission-driven runs CO2 is an interactive 3D tracer coupled to natural fluxes and anthropogenic emissiosn. In all runs, CFC-12 (equivalent) and HFC134 (equivalent) are prescribed as spatially constant scalars for the radiation scheme. The chemistry module has interactive CFC and HFC tracers forced by surface concentrations and emissions, but these are not coupled to radiation. In all runs the radiation uses 3D tracers of O3, CH4 and N2O, which are interactively simulated by the chemistry module. CH4 and N2O are constrained by prescribed surface concentrations, while O3 is forced by emissions & surface concentrations of precursors and depleting substances. All prescribed GHG concentrations are taken from the CMIP6 dataset of Meinshausen et al. (2017).
Citations:
Description:In concentration-driven runs, CO2 is prescribed as a spatially-constant scalar; in emission-driven runs CO2 is an interactive 3D tracer coupled to natural fluxes and anthropogenic emissiosn. In all runs, CFC-12 (equivalent) and HFC134 (equivalent) are prescribed as spatially constant scalars for the radiation scheme. The chemistry module has interactive CFC and HFC tracers forced by surface concentrations and emissions, but these are not coupled to radiation. In all runs the radiation uses 3D tracers of O3, CH4 and N2O, which are interactively simulated by the chemistry module. CH4 and N2O are constrained by prescribed surface concentrations, while O3 is forced by emissions & surface concentrations of precursors and depleting substances. All prescribed GHG concentrations are taken from the CMIP6 dataset of Meinshausen et al. (2017).
Citations:
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O’Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J. and Weiss, R. Historical greenhouse gas concentrations for climate modelling (CMIP6) Geosci. Model Dev., 10, 2057-2116 https://doi.org/10.5194/gmd-10-2057-2017
Hegglin, M. I., Kinnison, D., Plummer, D., et al., Historical and future ozone database (1850-2100) in support of CMIP6 GMD, in preparation. n/a
Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J. and Weiss, R. Historical greenhouse gas concentrations for climate modelling (CMIP6) Geosci. Model Dev., 10, 2057-2116 https://doi.org/10.5194/gmd-10-2057-2017
Properties:
Description: Ozone-depleting and non-ozone-depleting fluorinated gases forcingProvision: Y
Equivalence concentration: Option 3
Additional information: For radiative purposes, equivalent concentrations of CFC-12 and HFC-134a, as provided by Meinshausen et al. (2017), are used to represent the radiative forcing of all fluorinated gases. Concentration is treated as spatially constant, using the global mean data of Meinshausen et al. (2017). The chemistry module also simulates CFC and HFC concentrations interactively, constrained by surface concentrations. While these tracers are not used by the radiation scheme, their concentrations influence the interactive ozone, which is.
Description: Methane forcingProvision: ES
Additional information: CH4 is interactively simulated by chemistry module as a 3D tracer. Surface concentration is prescribed, using the global mean data of Meinshausen et al. (2017),
Description: Carbon dioxide forcingProvision: Y
Additional information: In concentration-driven experiments, concentration is treated as spatially constant, using the global mean data of Meinshausen et al. (2017). In emission-driven experiments (e.g. esm-piControl) CO2 is a in interactive 3D tracer coupled to terrestrial and marine fluxes and anthropogenic emissions.
Description: Nitrous oxide forcingProvision: ES
Additional information: N2O is interactively simulated by chemistry module as a 3D tracer. Surface concentration is prescribed, using the global mean data of Meinshausen et al. (2017),
Description: Stratospheric ozone forcingProvision: E
Additional information: 3D concentration of ozone is calculated interactively by chemistry module. Input forcing data are emissions of ozone precursors and surface concentrations of ozone-depleting substances.
Description: Troposheric ozone forcingProvision: ES
Additional information: 3D concentration of ozone is calculated interactively by chemistry module. Input forcing data are emissions of ozone precursors and surface concentrations of ozone-depleting substances.
Scientific topic: Aerosols Overview: Aerosol forcing agents
Description:The following aerosol species are simulated interactively: sulphate, black carbon (BC), organic carbon (OC), sea salt, mineral dust. Emissions of sea salt and dust are calculated by the model, while the other species are driven by prescribed emissions of SO2, BC, OC and monoterpene.
Citations:
Description:The following aerosol species are simulated interactively: sulphate, black carbon (BC), organic carbon (OC), sea salt, mineral dust. Emissions of sea salt and dust are calculated by the model, while the other species are driven by prescribed emissions of SO2, BC, OC and monoterpene.
Citations:
van Marle, M. J. E., Kloster, S., Magi, B. I., Marlon, J. R., Daniau, A-L., Field, R. D., Arneth, A., Forrest, M., Hantson, S., Kehrwald, N. M., Knorr, W., Lasslop, G., Li, F., Mangeon, S., Yue, C., Kaiser, J. W. and van der Werf, G. R. Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750-2015) Geosci. Model Dev., 10, 3329-3357 https://doi.org/10.5194/gmd-10-3329-2017
Liss P.S., and L. Merlivat Air-Sea Gas Exchange Rates: Introduction and Synthesis. In: Buat-Ménard P. (eds) The Role of Air-Sea Exchange in Geochemical Cycling. NATO ASI Series (Series C: Mathematical and Physical Sciences), vol 185. Springer, Dordrecht. n/a
Sindelarova, K., Granier, C., Bouarar, I., Guenther, A., Tilmes, S., Stavrakou, T., Müller, J.-F., Kuhn, U., Stefani, P. and Knorr, W. Global dataset of biogenic VOC emissions calculated by the MEGAN model over the last 30 years Atmos. Chem. Phys. 14, 10725-10788 doi:10.5194/acp-14-9317-2014
Lana, A., Bell, T. G., Simo, R., Vallina, S. M., Ballabrera-Poy, J., Kettle, A. J., Dachs, J., Bopp, L., Saltzman, E. S., Stefels, J., Johnson, J. E., Liss, P. S. An updated climatology of surface dimethlysulfide concentrations and emission fluxes in the global ocean Global Biogeochemical Cycles, 25(1):GB1004 doi:10.1029/2010GB003850
Gong, S. L. A parametrization of sea-salt aerosol source function for sub- and super-micron particles Global Biogeochemical Cycles, 17, 4, 1097 doi:10.1029/2003GB002079
Dentener, F., Kinne, S., Bond, T., Boucher, O., Cofala, J., Generoso, S., Ginoux, P., Gong, S., Hoelzemann, J. J., Ito, A., Marelli, L., Penner, J. E., Putaud, J. P., Textor, C., Schulz, M., Van Der Werf, G. R. and J. Wilson Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom Atmos. Chem. Phys., 6, 4321-4344 10.5194/acp-6-4321-2006
Spiro, P.A., Jacob, D.J., and Logan, J.A. (1992) Global inventory of sulfur emissions with 1×1 resolution. J. Geophys. Res., 97, 6023-6036, 1992. doi:10.1029/91JD03139
West R.E.L, Stier P., Jones, A., Johnson, C. E., Mann, G. W., Bellouin, N., Partridge, D. G., and Z. Kipling The importance of vertical velocity variability for estimates of the indirect aerosol effects Atmospheric Chemistry and Physics, 14, 6369-6393 doi:10.5194/acp-14-6369-2014, https://www.atm
Woodward, S. Mineral dust in HadGEM2 Tech. Rep. 87, Hadley Centre, Met Office, Exeter, UK n/a
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J. Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J-i., Li, M. Liu, L., Lu, Z., Moura, M. C. P., O’Rourke, P. R. and Zhang, Q. Historical (1750-2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS) Geosci. Model Dev., 11, 369-408 https://doi.org/10.5194/gmd-11-369-2018
Properties:
Description: SO4 aerosol forcingProvision: E
Additional information: H2SO4 is formed by the gas-phase and aqueous oxidation of precursor gases SO2 and DMS. Emissions of SO2 are taken from anthropogenic sources (Hoesly et al., 2018) and from continuously degassing volcanoes (Dentener et al., 2006). We use the terrestrial biogenic DMS emission dataset of Spiro et al. (1992), and an interactive marine DMS emission calculated using the flux parameterisation of Liss & Merlivat (1986) with DMS sea water concentration taken from the model’s ocean biogeochemistry component.
Description: Black carbon aerosol forcingProvision: E
Additional information: The model uses primary emissions of black carbon aerosol from biomass burning (van Marle et al., 2017) and anthropogenic (Hoesly et al., 2018) sources. Biomass burning emissions are scaled by a factor of 2 in order to achieve reasonable agreement with observed AOD in present-day simulations.
Description: Cloud albedo effect forcing (RFaci)Provision: E
Aerosol effect on ice clouds: false
Additional information: Cloud droplet number concentration is diagnosed from CCN and the variance of updraft velocity using the scheme of West et al. (2014).
Description: Cloud lifetime effect forcing (ERFaci)Provision: E
Aerosol effect on ice clouds: false
Rfaci from sulfate only: false
Additional information: nil:inapplicable
Description: Dust forcingProvision: M
Additional information: Dust emissions are calculated online using wind speed, soil moisture, bare soil fraction and soil properties, using the scheme of Woodward (2011). Bare soil fraction is prognostic in UKESM1, simulated by the dynamic vegetation scheme.
Description: Nitrate forcingProvision: N/A
Additional information: nil:inapplicable
Description: Organic carbon aerosol forcingProvision: E
Additional information: The model uses primary emissions of organic carbon aerosol from biomass burning (van Marle et al., 2017) and anthropogenic (Hoesly et al., 2018) sources. Biomass burning primary emissions are scaled by a factor of 2 in order to achieve reasonable agreement with observed AOD in present-day simulations. Additionally, UKESM1 has interactive emissions of primary marine organic aerosol, coupled to the surface chlorophyll concentration in the ocean biogeochemistry component. It also simulates the formation of secondary organic aerosol (SOA) through the oxidation of terpenes. Biogenic terpene emissions of are calculated interactively by the land surface model.
Description: Sea salt forcingProvision: M
Additional information: Primary emissions of sea salt aerosol are calculated online using instantaneous model wind speed with the scheme of Gong (2003).
Description: Stratospheric volcanic forcingProvision: Y
Historical explosive volcanic aerosol implementation: nil:withheld
Future explosive volcanic aerosol implementation: Type B
Additional information: Stratospheric aerosol is not simulated interactively. Volcanic direct forcing is imposed on the model’s radiation scheme using zonal mean fields of extinction, single scattering albedo and asymmetry parameter, using the CMIP6 dataset. Additionally, the heterogeneous chemistry uses prescribed aerosol surface area density, also taken from the CMIP6 forcing dataset.
Description: Tropospheric volcanic forcingProvision: E
Historical explosive volcanic aerosol implementation: Type E
Future explosive volcanic aerosol implementation: Type E
Additional information: A constant background 3D emission of SO2 is used to represent the tropospheric source from both continuously degassing and explosive volcanoes, using the dataset of Dentener et al. (2006). This SO2 feeds into the interactive tropospheric aerosol simulation (see aerosol component description).
Scientific topic: Other Overview: Miscellaneous forcing agents
Description:Land use change is imposed via prescribed agricultural fractions which constraint the area available for dynamic natural vegetation. Solar forcing is imposed via total and spectral solar irradiance.
Citations:
Description:Land use change is imposed via prescribed agricultural fractions which constraint the area available for dynamic natural vegetation. Solar forcing is imposed via total and spectral solar irradiance.
Citations:
Hurtt, G., Chini, L., Sahajpal, R., Frolking, S., et al., Harmonization of global land-use change and management for the period 850-2100 Geoscientific Model Development (In prep). n/a
Global Soil Data Task Global soil data products CD-ROM (IGBP-DIS) International Geosphere-Biosphere Programme, Data and Information System, Potsdam, Germany n/a
Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretzschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A. C., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and Versick, S. Solar forcing for CMIP6 (v3.2) Geosci. Model Dev., 10, 2247-2302 https://doi.org/10.5194/gmd-10-2247-2017
Properties:
Description: Land use forcingProvision: Y
Crop change only: false
Additional information: The model has dynamic vegetation fractions, with 9 natural plant functional types (PFTs), 2 crop PFTs (C3 & C4 grass) and 2 pasture PFTs (C3 & C4 grass). Time-varying crop and pasture fractions on each gridbox are prescribed using the land use data of Hurtt et al (in prep). Rangeland is not taken into account. With the crop fraction, only the two crop PFTs are allowed to grow. If these crop PFTs are not viable, bare soil will result. Similarly for the pasture fraction and pasture PFTs. Natural vegetation PFT are only allowed to grow in the remainder of each grid box.
Description: Solar forcingProvision: irradiance
Additional information: Total and spectral solar irradiance are specified using the CMIP6 dataset of Matthes et al. (2017). The upper and lower limits of the model spectral bands are 200 nm and 10,000 nm; the CMIP6 SSI from 10 nm to 200 nm is included in the first model spectral band (200 – 220 nm), and the CMIP6 SSI from 10,000nm to 100,000 nm is included in the last model spectral band (2,380 – 10,000 nm).
Key properties
Scientific topic: Key properties Overview: Key properties of the model
Description: Describes summary properties, genealogy and history of the model, software properties, conservation, coupling and tuning.
Properties:
Description: Describes summary properties, genealogy and history of the model, software properties, conservation, coupling and tuning.
Properties:
Description: Flux correction properties of the modelDetails: No flux correction is used.
Description: Genealogy and history of the modelCmip5 differences: Ocean and sea-ice component models have been completely replaced since HadGEM2-ES, by NEMO and CICE respectively. Vertical resolution of the ocean has increased to 75 levels, with 1m resolution at the surface. The number of atmospheric vertical levels has increased to 85, and the stratosphere is now well-resolved with an 85km top. The model has a new dynamical core, and key physics developments include prognostic cloud, condensate and rain, a 2-moment aerosol scheme, and improvements to liquid and mixed-phase cloud microphysics. Key land surface developments since HadGEM2 include a multi-layer snow scheme and improved canopy-radiation interaction. The key Earth system developments since HadGEM2-ES are: inclusion of stratospheric chemistry and tropospheric isoprene chemistry; a terrestrial nitrogen cycle, additional plant functional types and improved land use representation; a new ocean biogeochemistry model MEDUSA. UKESM1 also includes new couplings between Earth system compone
Year released: 2018
Cmip3 parent: HadGEM1
Cmip5 parent: HadGEM2-ES
Previous name: nil:inapplicable
Description: Software properties of modelRepository: Requires registration – available on request.
Code version: MetUM vn10.9, JULES vn5.0, NEMO vn3.6, CICE vn5.1.2, MEDUSA v2.1.
Code languages: Fortran90, c, python
Components structure: Atmospheric and land components are compiled as a single executable, coupled to an ocean and sea-ice executable via OASIS3-MCT.
Coupler: OASIS3-MCT
Subtopics:
Scientific topic: Coupling Overview: n/a
Description:The atmosphere uses the Unified Model and land surface uses JULES – these component models run on the same grid and as part of the same model executable so can be considered to be “tightly coupled”, passing data where necessary by sub-routine arguments or shared data arrays. Similarly the ocean (NEMO) and sea ice (CICE) models are compiled into a single executable and are “tightly coupled” on the same grid (with the caveat that CICE uses an Arakawa B grid placement of velocities in contrast to the C grid in NEMO). Coupling between the atmosphere and ocean is performed by OASIS3-MCT. For further information see Appendix A of Williams et al. (2017).
Citations:
Description:The atmosphere uses the Unified Model and land surface uses JULES – these component models run on the same grid and as part of the same model executable so can be considered to be “tightly coupled”, passing data where necessary by sub-routine arguments or shared data arrays. Similarly the ocean (NEMO) and sea ice (CICE) models are compiled into a single executable and are “tightly coupled” on the same grid (with the caveat that CICE uses an Arakawa B grid placement of velocities in contrast to the C grid in NEMO). Coupling between the atmosphere and ocean is performed by OASIS3-MCT. For further information see Appendix A of Williams et al. (2017).
Citations:
Williams, K., Copsey, D., Blockley, E., Bodas-Salcedo, A., Calvert, D., Comer, R., Davis, P., Graham, T., Hewitt, H., Hill, R., Hyder, P., Ineson, S., Johns, T., Keen, A., Lee, R., Megann, A., Milton, S., Rae, J., Roberts, M., Scaife, A., Schiemann, R., Storkey, D., Thorpe, L., Watterson, I., Walters, D., West, A., Wood, R., Woollings, T., and Xavier, P. The Met Office Global Coupled model 3.0 and 3.1 (GC3 and GC3.1) configurations, Journal of Advances in Modeling Earth Systems Journal of Advances in Modeling Earth Systems, 10, 357-380. https://doi.org/10.1002/2017MS001115
Scientific topic: Tuning applied Overview: Tuning methodology for model
Description:SEE INDIVIDUAL SCIENCE MODELS and model documentation, e.g. Williams et al. (2017).
Citations:
Description:SEE INDIVIDUAL SCIENCE MODELS and model documentation, e.g. Williams et al. (2017).
Citations:
Williams, K., Copsey, D., Blockley, E., Bodas-Salcedo, A., Calvert, D., Comer, R., Davis, P., Graham, T., Hewitt, H., Hill, R., Hyder, P., Ineson, S., Johns, T., Keen, A., Lee, R., Megann, A., Milton, S., Rae, J., Roberts, M., Scaife, A., Schiemann, R., Storkey, D., Thorpe, L., Watterson, I., Walters, D., West, A., Wood, R., Woollings, T., and Xavier, P. The Met Office Global Coupled model 3.0 and 3.1 (GC3 and GC3.1) configurations, Journal of Advances in Modeling Earth Systems Journal of Advances in Modeling Earth Systems, 10, 357-380. https://doi.org/10.1002/2017MS001115
Sellar et al UKESM1: Description and evaluation of the UK Earth System Model in prep n/a
Scientific topic: Conservation Overview: Global convervation properties of the model
Description:Water is conserved to within 10mSv (107 Kg s-1). Total energy is conserved to within 0.001 Wm-2. Carbon conservation is currently under assessment for the emission-driven configuration of UKESM1.
Citations:
Description:Water is conserved to within 10mSv (107 Kg s-1). Total energy is conserved to within 0.001 Wm-2. Carbon conservation is currently under assessment for the emission-driven configuration of UKESM1.
Citations:
Oki T., and Y.C. Sud (1998) Design of the Total Runoff Integrating Pathways [TRIP] – A global river channel network.. Earth Interactions, 2. https://doi.org/10.1175/1087-3562(1998)002<00
Marsh, R., Ivchenko, V. O., Skliris, N., Alderson, S., Bigg, G. R., Madec, G., Blaker, A. T., Aksenov, Y., Sinha, B., Coward, A. C., Le Sommer, J., Merino, I., and Zalesny, V. NEMO-ICB (v1.0): interactive icebergs in the NEMO ocean model globally configured at eddy-permitting resolution Geoscientific Model Development, 8, 1547-1562 https://hal-insu.archives-ouvertes.fr/insu-01
West, A. E, McLaren, A. J., Hewitt, H. T. and Best, M. J. The location of the thermodynamic atmosphere-ice interface in fully coupled models – a case study using JULES and CICE Geosci. Mod. Dev., 9, 1125-1141 https://doi.org/10.5194/gmd-9-1125-2016
Properties:
Description: Global fresh water convervation properties of the modelGlobal: Atmospheric water is conserved globally in the dynamical core after using a corrector. Water is not conserved in some parameterizations. Global water non conservation in each of the atmosphere, ocean, soil moisture, river routing, land snow and sea ice sub-models is smaller than an acceptance criterion of 10 mSv (10,000,000 Kg s-1).
Atmos ocean interface: Water is not intrinsically conserved in the atmosphere/ocean coupling interface. Global non conservation of water is smaller than an acceptance criterion of 10 mSv (10,000,000 Kg s-1).
Atmos land interface: Water is conserved by ensuring that one of the terms in the surface water balance equation is determined as the residual of the other terms. The atmosphere and land models share a common grid, so there is no horizontal interpolation error.
Atmos sea-ice interface: Water is not intrinsically conserved in the atmosphere/sea-ice interface. The model contains an error in the implementation of the sublimation flux from sea ice to atmosphere. Global non conservation is however smaller than acceptance criterion of 10 mSv (10,000,000 Kg s-1).
Ocean seaice interface: Freshwater is conserved intrinsically between ice and ocean. Freshwater is passed from ice to ocean by means of a single flux, constructed during the sea ice mass balance calculations. It is incremented in proportion to the net decrease in combined ice and snow mass during a timestep, with the net sublimation component removed. In addition, it is incremented by the quantity of rain falling on the sea ice surface, which is assumed to drain immediately to the ocean.
Runoff: River water is routed conservatively using the total runoff integrating pathways (TRIP) model of Oki and Sud (1998) to outflow points over the ocean. The river outflow field is interpolated to the ocean grid the using 1st-order conservative remapping, and the result is added to the surface freshwater flux.
Iceberg calving: Icebergs are explicitly advected by the ocean model, supplied by a calving flux at the coast. The magnitude of this flux is set to balance snow surface mass balance (see snow accumulation property). The spatial distribution of the calving flux is taken from the dataset of Marsh et al. (2015), and is scaled independently for the northern and southern hemispheres.
Endoreic basins: For closed seas the volume of water within each basin is calculated. If the volume increases water is transported to a pre-defined runoff point in the open ocean. If the volume decreases then water is gathered from everywhere else on the globe to make up the short-fall. in this manner the water volume of closed seas lakes remains fixed.
Snow accumulation: Snow is allowed to accumulate on land and sea-ice with no removal. This accumulated snow is available as a source of melt in long climate runs. In order to avoid drift in the ocean fresh water mass, an iceberg calving flux is used, the magnitude of which is calibrated using the net surface mass balance (=snowfall – sublimation – runoff) over regions of permanent snow cover, diagnosed from the end portion of the piControl-spinup.
Description: Global heat convervation properties of the modelGlobal: Atmosphere model is not formulated to conserve atmospheric energy. It uses instead an energy correction, calculated daily as an energy residual and applied on each timestep as a uniform temperature increment. Global energy non conservation is two orders of magnitude smaller than an acceptance criterion of 0.1 W m-2.
Atmos ocean interface: Heat is not intrinsically conserved in the atmosphere/ocean coupling interface. Global energy non conservation in the interface is three orders of magnitude smaller than acceptance criterion of 0.1 W m-2.
Atmos land interface: Energy is conserved by ensuring that one of the terms in the surface energy balance equation is determined as the residual of the other terms. The atmosphere and land models share a common grid, so there is no horizontal interpolation error.
Atmos sea-ice interface: The atmosphere/sea-ice coupling interface is located immediately below the sea ice surface, as described in West et al (2016). Heat is exchanged between the models by means of three fluxes: downwards conduction, top melt and net sublimation. To enable fluxes to be roughly proportionate to underlying ice area, they are passed as local values in which the gridbox mean flux calculated in the atmosphere is divided by the ice fraction field used for the ensuing coupling period. This method has been shown to conserve energy perfectly in theory, but there is an implementation error in the sublimation flux which leads to a loss of conservation. Despite this error, heat is conserved to within an average of 10e-5 Wm-2 in practice.
Ocean seaice interface: Heat is intrinsically conserved between ice and ocean. At the beginning of the ocean timestep, freezing potential is calculated, passed to the sea ice model in order to grow new ice, and the ocean non-solar heat flux is incremented by this amount. The sea ice model constructs an ice-ocean heat flux during the thermodynamics calculations. An initial value (<=0) is calculated based on the extent to which sea surface temperature is greater than ice base temperature. This is then incremented by the energy used to melt ice. At the end of the timestep, the flux is passed to the ocean model, and is used to increment the ocean non-solar heat flux during the following timestep.
Land ocean interface: No heat is exchanged between the land and ocean.
Description: Global momentum convervation properties of the modelDetails: The momentum conservation properties of the ocean and atmosphere have not been explicitly diagnosed. Wind stress is regridded from the atmosphere to ocean grid using non-conservative bilinear interpolation.
Description: Global salt convervation properties of the modelOcean seaice interface: Salt is conserved intrinsically between ice and ocean. Salt is passed from ice to ocean by means of a single flux, constructed during the sea ice mass balance calculations. It is incremented in proportion to the net decrease in combined ice and snow mass during a timestep, with the net sublimation component removed. For the purposes of these calculations, sea ice is assumed to have a uniform salinity of 8.
Realms
Canonical name: atmoschem
Short name:
Description: Atmospheric Chemistry Realm
Overview: Atmospheric Chemistry Realm
Grid
Scientific topic: Grid Overview: Atmospheric chemistry grid
Description: Same as Atmospheric model : 192×144 grid cells in horizontal with resolution of 1.875 x 1.25 degrees respectively, translating to approx 110km in mid-latitudes. 85 Hybrid Levels in the vertical extending upto 85.0 km.
Subtopics:
Description: Same as Atmospheric model : 192×144 grid cells in horizontal with resolution of 1.875 x 1.25 degrees respectively, translating to approx 110km in mid-latitudes. 85 Hybrid Levels in the vertical extending upto 85.0 km.
Subtopics:
Scientific topic: Resolution Overview: Resolution in the atmospheric chemistry grid
Description:Horizontal resolution of 1.875 x 1.25 degrees, translating to approx 110 km in mid-latitudes.
Description:Horizontal resolution of 1.875 x 1.25 degrees, translating to approx 110 km in mid-latitudes.
Realm’s Key Properties
Scientific topic: Key properties Overview: Key properties of the atmospheric chemistry
Description: Key properties cover an overview of the main properties, software properties, timestep framework and tuning applied to the model.
Properties:
Description: Key properties cover an overview of the main properties, software properties, timestep framework and tuning applied to the model.
Properties:
Description: Software properties of aerosol codeRepository: https://code.metoffice.co.uk/trac/um
Code version: UM11.0
Code languages: Fortran 77/90/2003
Subtopics:
Scientific topic: Timestep framework Overview: Timestepping in the atmospheric chemistry model
Description:Processing of emissions and tracer transport (large-scale advection, convection, boundary layer mixing) occurs on each atmospheric model timestep (1200s). The photolysis, main chemical solver and deposition processes occur every 3600s i.e. every 3rd atmospheric timestep.
Properties:
Description:Processing of emissions and tracer transport (large-scale advection, convection, boundary layer mixing) occurs on each atmospheric model timestep (1200s). The photolysis, main chemical solver and deposition processes occur every 3600s i.e. every 3rd atmospheric timestep.
Properties:
Description: n/aTurbulence: 4
Convection: 2
Precipitation: 1
Emissions: 3
Deposition: 6
Gas phase chemistry: 6
Tropospheric heterogeneous phase chemistry: nil:inapplicable
Stratospheric heterogeneous phase chemistry: nil:inapplicable
Photo chemistry: 5
Aerosols: 2
Scientific topic: Tuning applied Overview: Tuning methodology for atmospheric chemistry component
Description:Improvement of tropospheric ozone burden by tuning the lightning NOx parameterisation. Climatological metrics were used for overall O3 burden, while process-based metrics like flash rate and NOx vertical distribution based on observations were used to improve the lightning NOx parameterisation.
Description:Improvement of tropospheric ozone burden by tuning the lightning NOx parameterisation. Climatological metrics were used for overall O3 burden, while process-based metrics like flash rate and NOx vertical distribution based on observations were used to improve the lightning NOx parameterisation.
Realm’s Processes
Scientific topic: Transport Overview: Atmospheric chemistry transport
Description: Tracers are transported in the atmospheric model using a monotonous semi-Langragian advection scheme involving a high-order interpolation and a modified Priestley conservation scheme.
Description: Tracers are transported in the atmospheric model using a monotonous semi-Langragian advection scheme involving a high-order interpolation and a modified Priestley conservation scheme.
Scientific topic: Emissions concentrations Overview: Atmospheric chemistry emissions
Description: The scheme uses prescribed emissions for NO, CO, HCHO, C2H6, C3H8, Me2CO, MeCHO, NVOC(MeOH), SO2, land-DMS and NH3, along with interactive emissions for Lightning NOx (online in UKCA), terrestrial monoterpene and Isoprene (from JULES), and oceanic-DMS (based on surface concentration from MEDUSA). Concentrations of CH4, N2O, and CFCs are prescribed at the surface.
Subtopics:
Description: The scheme uses prescribed emissions for NO, CO, HCHO, C2H6, C3H8, Me2CO, MeCHO, NVOC(MeOH), SO2, land-DMS and NH3, along with interactive emissions for Lightning NOx (online in UKCA), terrestrial monoterpene and Isoprene (from JULES), and oceanic-DMS (based on surface concentration from MEDUSA). Concentrations of CH4, N2O, and CFCs are prescribed at the surface.
Subtopics:
Scientific topic: Surface emissions Overview: n/a
Description:Surface emissions: NO, CO, HCHO, C2H6, C3H8, Me2CO, MeCHO, NVOC(MeOH), SO2, land-DMS and NH3, along with interactive emissions for Monoterpene and Isoprene (from JULES), and oceanic-DMS (calculated using surface DMS concentrations from MEDUSA).
Description:Surface emissions: NO, CO, HCHO, C2H6, C3H8, Me2CO, MeCHO, NVOC(MeOH), SO2, land-DMS and NH3, along with interactive emissions for Monoterpene and Isoprene (from JULES), and oceanic-DMS (calculated using surface DMS concentrations from MEDUSA).
Scientific topic: Atmospheric emissions Overview: TO DO
Description:Emissions from aircraft, lightning, volcanoes, forest fires and industrial sources are emitted into higher levels.
Description:Emissions from aircraft, lightning, volcanoes, forest fires and industrial sources are emitted into higher levels.
Scientific topic: Concentrations Overview: TO DO
Description:Prescribed concentrations of CH4, CO2, N2O, MeBr, MeCl, CH2Br2, CFC115, CCl4, MeCCl3, HCFC141b, HCFC142b, H1211, H1202, H1301, and H2402 are read in from files generated from CMIP6 forcing data. N2, H2, are specified via namelist and COS is specified in code.
Description:Prescribed concentrations of CH4, CO2, N2O, MeBr, MeCl, CH2Br2, CFC115, CCl4, MeCCl3, HCFC141b, HCFC142b, H1211, H1202, H1301, and H2402 are read in from files generated from CMIP6 forcing data. N2, H2, are specified via namelist and COS is specified in code.
Scientific topic: Gas phase chemistry Overview: Atmospheric gas phase chemistry transport
Description: UKCA Strat-trop (Stratospheric + Tropospheric) or CheST (Chemistry of the Stratosphere and Troposphere). Gas phase chemistry is handled by the atmospheric component. Semi-Langragian advection with Preistley conservation.
Description: UKCA Strat-trop (Stratospheric + Tropospheric) or CheST (Chemistry of the Stratosphere and Troposphere). Gas phase chemistry is handled by the atmospheric component. Semi-Langragian advection with Preistley conservation.
Scientific topic: Stratospheric heterogeneous chemistry Overview: Atmospheric chemistry startospheric heterogeneous chemistry
Description: Stratospheric heterogeneous chemistry involving chlorine and dinitrogen pentoxide is included in the model following Chipperfield (1999). These reactions occur on nitric acid trihydrate (NAT) and mixed NAT/ice polar stratospheric clouds calculated following Chipperfield (1999) as well as on the prescribed surface area of volcanic aerosol.
Citations:
Description: Stratospheric heterogeneous chemistry involving chlorine and dinitrogen pentoxide is included in the model following Chipperfield (1999). These reactions occur on nitric acid trihydrate (NAT) and mixed NAT/ice polar stratospheric clouds calculated following Chipperfield (1999) as well as on the prescribed surface area of volcanic aerosol.
Citations:
Chipperfield, M. P. Multiannual simulations with a three-dimensional chemical transport model J. Geophys. Res., 104(D1) , 1781-1805 doi:10.1029/98JD02597
Scientific topic: Tropospheric heterogeneous chemistry Overview: Atmospheric chemistry tropospheric heterogeneous chemistry
Description: This component is not applicable to the model.
Description: This component is not applicable to the model.
Scientific topic: Photo chemistry Overview: Atmospheric chemistry photo chemistry
Description: The model uses the interactive photolysis scheme Fast-JX with 18 wavelength bands but above a pressure level of 20 Pa, tabulated photolysis rates are used.
Subtopics:
Description: The model uses the interactive photolysis scheme Fast-JX with 18 wavelength bands but above a pressure level of 20 Pa, tabulated photolysis rates are used.
Subtopics:
Scientific topic: Photolysis Overview: Photolysis scheme
Description:Fast-JX (Telford et al 2013) is a development of the Fast-J scheme of Wild et al. (2000), a flexible and accurate photolysis scheme, which calculates photolysis rates in the presence of an arbitrary mix of cloud and aerosol layers. The scheme has a 18-bin quadrature covering wavelengths from 177 to 850 nm. The lower wavelength limit of 177nm does not cover all the reactions in upper parts of the atmosphere. To cope with this, above a cut-off pressure level of typically 20 Pa, stratospheric photolysis rates based on the lookup table approach of Lary and Pyle (1991).
Citations:
Description:Fast-JX (Telford et al 2013) is a development of the Fast-J scheme of Wild et al. (2000), a flexible and accurate photolysis scheme, which calculates photolysis rates in the presence of an arbitrary mix of cloud and aerosol layers. The scheme has a 18-bin quadrature covering wavelengths from 177 to 850 nm. The lower wavelength limit of 177nm does not cover all the reactions in upper parts of the atmosphere. To cope with this, above a cut-off pressure level of typically 20 Pa, stratospheric photolysis rates based on the lookup table approach of Lary and Pyle (1991).
Citations:
Telford, P. J., Abraham, N. L., Archibald, A. T., Braesicke, P., Dalvi, M., Morgenstern, O>, O’Connor, F. M., Richards, N. A. D. and J. A. Pyle Implementation of the Fast-JX Photolysis scheme (v6.4) into the UKCA component of the MetUM chemistry-climate model (v7.3) Geoscientific Model Development, 6, 161-177 n/a
Lary, D. J. and J. A. Pyle Diffuse radiation, twilight, and photochemistry. I, II Journal of Atmospheric Chemistry, 13, 4, 373-406 10.1007/BF00057753
Canonical name: ocnbgchem
Short name:
Description: Ocean Biogeochemistry Realm
Overview: Ocean Biogeochemistry Realm
Realm’s Key Properties
Scientific topic: Key properties Overview: Ocean Biogeochemistry key properties
Description: The key properties of MEDUSA2 include model type, stoichiometry, tracers, boundary forcing, carbon chemistry, gas exchange, timestepping framework, and the transport scheme.
Citations:
Description: The key properties of MEDUSA2 include model type, stoichiometry, tracers, boundary forcing, carbon chemistry, gas exchange, timestepping framework, and the transport scheme.
Citations:
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies Geosci. Model Dev., 6, 1767-1811, https://doi.org/10.5194/gmd-6-1767-2013
Yool, A., Popova, E. E., and Anderson, T. R Medusa-1.0: a new intermediate complexity plankton ecosystem model for the global domain Geosci. Model Dev., 4, 381-417 https://doi.org/10.5194/gmd-4-381-2011
Yool, A., E. E. Popova, and A. C. Coward Future change in ocean productivity: Is the Arctic the new Atlantic? J. Geophys. Res. Oceans, 120, 7771-7790 doi:10.1002/2015JC011167
Subtopics:
Scientific topic: Time stepping framework Overview: Time stepping framework for ocean biogeochemistry
Description:MEDUSA timesteps forward in lockstep with its underlying ocean physics model, NEMO, i.e. leapfrog. MEDUSA uses NEMO’s native TOP framework for handling biogeochemical sinks and sources.
Properties:
Description:MEDUSA timesteps forward in lockstep with its underlying ocean physics model, NEMO, i.e. leapfrog. MEDUSA uses NEMO’s native TOP framework for handling biogeochemical sinks and sources.
Properties:
Description: Time stepping framework for biology sources and sinks in ocean biogeochemistryMethod: use ocean model transport time step
Timestep if not from ocean: nil:inapplicable
Description: Time stepping method for passive tracers transport in ocean biogeochemistryMethod: use ocean model transport time step
Timestep if not from ocean: nil:inapplicable
Scientific topic: Transport scheme Overview: Transport scheme in ocean biogeochemistry
Description: MEDUSA-2 uses online passive tracers that are transported using a different scheme (MUSCL) to that of the ocean’s active tracers (TVD).
Description: MEDUSA-2 uses online passive tracers that are transported using a different scheme (MUSCL) to that of the ocean’s active tracers (TVD).
Scientific topic: Boundary forcing Overview: Properties of biogeochemistry boundary forcing
Description:Components of MEDUSA experience boundaries at the air-sea interface and at the ocean-seafloor interface. The model includes gas transfer of some species (C and O2), sea surface deposition of one species (Fe) and seafloor inputs of one species (Fe). There are no riverine sources of input (except freshwater itself). The model is conservative for N, Si and ALK, has air-sea exchange for C and O2 and is non-conservative for Fe (which is added and removed from the ocean model).
Citations:
Description:Components of MEDUSA experience boundaries at the air-sea interface and at the ocean-seafloor interface. The model includes gas transfer of some species (C and O2), sea surface deposition of one species (Fe) and seafloor inputs of one species (Fe). There are no riverine sources of input (except freshwater itself). The model is conservative for N, Si and ALK, has air-sea exchange for C and O2 and is non-conservative for Fe (which is added and removed from the ocean model).
Citations:
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies Geosci. Model Dev., 6, 1767-1811, https://doi.org/10.5194/gmd-6-1767-2013
Scientific topic: Gas exchange Overview: Properties of gas exchange in ocean biogeochemistry
Description:Air-sea exchange of CO2, O2, DMS, CFC-11, CFC-12, SF6 and primary marine organic carbon (PMOC) is parameterised in MEDUSA. MEDUSA-2 uses the Wanninkhof (2014) modification to the Wanninkhof (1992) scheme, as specified by the OMIP protocol for CO2, O2 and CFC fluxes; DMS fluxes utilise the Liss and Merlivat (1986) scheme, and are calculated by the atmospheric chemistry submodel, UKCA, rather than MEDUSA-2; 13CO2 and 14CO2 are not represented. While not a gas exchange, primary marine organic aerosols are emitted into the atmosphere, using MEDUSA’s surface chlorophyll distribution.
Citations:
Description:Air-sea exchange of CO2, O2, DMS, CFC-11, CFC-12, SF6 and primary marine organic carbon (PMOC) is parameterised in MEDUSA. MEDUSA-2 uses the Wanninkhof (2014) modification to the Wanninkhof (1992) scheme, as specified by the OMIP protocol for CO2, O2 and CFC fluxes; DMS fluxes utilise the Liss and Merlivat (1986) scheme, and are calculated by the atmospheric chemistry submodel, UKCA, rather than MEDUSA-2; 13CO2 and 14CO2 are not represented. While not a gas exchange, primary marine organic aerosols are emitted into the atmosphere, using MEDUSA’s surface chlorophyll distribution.
Citations:
Orr, J. C., Najjar, R. G., Aumont, O., Bopp, L., Bullister, J. L., Danabasoglu, G., Doney, S. C., Dunne, J. P., Dutay, J.-C., Graven, H., Griffies, S. M., John, J. G., Joos, F., Levin, I., Lindsay, K., Matear, R. J., McKinley, G. A., Mouchet, A., Oschlies, A., Romanou, A., Schlitzer, R., Tagliabue, A., Tanhua, T., and A. Yool Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP), Geosci. Model Dev., 10, 2169-2199 https://doi.org/10.5194/gmd-10-2169-2017,
Anderson, T. R., Spall, S. A., Yool, A., Cipollini, P., Challenor, P. G., and Fasham, M. J. R. Global fields of sea surface dimethylsulphide predicted from chlorophyll, nutrients and light, J. Mar. Syst., 30, 1-20, n/a
Wanninkhof, R. (1992) Relationship between wind speed and gas exchange over the ocean J. Geophys. Res., 97C, 7373-7382 n/a
Wanninkhof, R. Relationship between wind speed and gas exchange over the ocean revisited Limnol. Oceanogr. Methods, 12, doi:10.4319/lom.2014.12.351, 2014.
Liss P.S., and L. Merlivat Air-Sea Gas Exchange Rates: Introduction and Synthesis. In: Buat-Ménard P. (eds) The Role of Air-Sea Exchange in Geochemical Cycling. NATO ASI Series (Series C: Mathematical and Physical Sciences), vol 185. Springer, Dordrecht. n/a
Najjar, R. and J. C. Orr Biotic-HOWTO Internal OCMIP Report, LSCE/CEA Saclay, Gif-sur-Yvette, France, 15 pp. n/a
Gantt, B., Meskhidze, N., Facchini, M. C., Rinaldi, M., Ceburnis, D., and C. D. O’Dowd Wind speed dependent size-resolved parameterization for the organic mass fraction of sea spray aerosol Atmos. Chem. Phys., 11, 8777-8790 10.5194/acp-11-8777- 2011
Scientific topic: Carbon chemistry Overview: Properties of carbon chemistry biogeochemistry
Description:Carbon is modelled as an explicit dissolved property in MEDUSA (DIC), with both implicit and explicit (slow-sinking detritus) particulate reservoirs. It exchanges with the atmosphere, but is otherwise conservative within the model. Air-sea exchange is mediated via the MOCSY software (Orr and Epitalon, 2015).
Citations:
Description:Carbon is modelled as an explicit dissolved property in MEDUSA (DIC), with both implicit and explicit (slow-sinking detritus) particulate reservoirs. It exchanges with the atmosphere, but is otherwise conservative within the model. Air-sea exchange is mediated via the MOCSY software (Orr and Epitalon, 2015).
Citations:
Orr, J. C. and Epitalon, J.-M. Improved routines to model the ocean carbonate system: mocsy 2.0, Geosci. Model Dev., 8, 485-499, https://doi.org/10.5194/gmd-8-485-2015,
Scientific topic: Tuning applied Overview: Tuning methodology for ocean biogeochemistry component
Description:n/a
Description:n/a
Realm’s Processes
Scientific topic: Tracers Overview: Ocean biogeochemistry tracers
Description: MEDUSA-2 contains 15 passive tracers that represent the ocean’s biogeochemical cycles of nitrogen, silicon, iron, carbon, alkalinity and oxygen. See Yool et al., 2013 for a full overview.
Citations:
Description: MEDUSA-2 contains 15 passive tracers that represent the ocean’s biogeochemical cycles of nitrogen, silicon, iron, carbon, alkalinity and oxygen. See Yool et al., 2013 for a full overview.
Citations:
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies Geosci. Model Dev., 6, 1767-1811, https://doi.org/10.5194/gmd-6-1767-2013
Subtopics:
Scientific topic: Ecosystem Overview: Ecosystem properties in ocean biogeochemistry
Description:MEDUSA-2 represents primary producers and consumers at the base of the ocean’s food web; all explicitly modelled plankton components have a non-linear loss term that represents, in part, losses to unmodelled higher trophic levels. These are divided into two interlinked nutrient-phytoplankton-zooplankton-detritus (NPZD) food chains based on size.
Properties:
Description:MEDUSA-2 represents primary producers and consumers at the base of the ocean’s food web; all explicitly modelled plankton components have a non-linear loss term that represents, in part, losses to unmodelled higher trophic levels. These are divided into two interlinked nutrient-phytoplankton-zooplankton-detritus (NPZD) food chains based on size.
Properties:
Description: Phytoplankton properties in ocean biogeochemistryType: PFT including size based (specify both below)
Pft: Diatoms
Size classes: Microphytoplankton | Nanophytoplankton |
Description: Zooplankton properties in ocean biogeochemistryType: Size based (specify below)
Size classes: Microzooplankton | Mesozooplankton |
Scientific topic: Disolved organic matter Overview: Disolved organic matter properties in ocean biogeochemistry
Description:MEDUSA-2 has no representation of dissolved organic matter.
Description:MEDUSA-2 has no representation of dissolved organic matter.
Scientific topic: Particules Overview: Particulate carbon properties in ocean biogeochemistry
Description:MEDUSA-2 has two classes of sinking particles of organic matter: small, slow-sinking, and large, fast-sinking. The former are represented explicitly by two passive tracers (nitrogen and carbon; iron is implicit and slaved to nitrogen). The latter are represented implicitly by five components (organic nitrogen, iron and carbon and inorganic silicon and calcium carbonate) and are created and remineralised within the same model timestep. Small particles have a sinking rate, separate nitrogen and carbon remineralisation rates, and can be consumed by both microzooplankton and mesozooplankton down the water column. Large particles use the ballast model of Armstrong et al. (2002) to determine the fraction of sinking material that is “protected” by biominerals, and the fraction that is amenable to remineralisation. The latter remineralises down the water column using an e-folding length-scale. Both silicon and calcium carbonate biominerals dissolve similarly but with longer e-folding length-scales, and, in the case of CaCO3, only below the calcite carbonate compensation depth (CCD; this is calculated by MOCSY-2.0). Large particles are not consumed by zooplankton. In all cases, remineralising or dissolving particulate material is returned directly to dissolved components (e.g. nutrients, DIC, alkalinity).
Citations:
Description:MEDUSA-2 has two classes of sinking particles of organic matter: small, slow-sinking, and large, fast-sinking. The former are represented explicitly by two passive tracers (nitrogen and carbon; iron is implicit and slaved to nitrogen). The latter are represented implicitly by five components (organic nitrogen, iron and carbon and inorganic silicon and calcium carbonate) and are created and remineralised within the same model timestep. Small particles have a sinking rate, separate nitrogen and carbon remineralisation rates, and can be consumed by both microzooplankton and mesozooplankton down the water column. Large particles use the ballast model of Armstrong et al. (2002) to determine the fraction of sinking material that is “protected” by biominerals, and the fraction that is amenable to remineralisation. The latter remineralises down the water column using an e-folding length-scale. Both silicon and calcium carbonate biominerals dissolve similarly but with longer e-folding length-scales, and, in the case of CaCO3, only below the calcite carbonate compensation depth (CCD; this is calculated by MOCSY-2.0). Large particles are not consumed by zooplankton. In all cases, remineralising or dissolving particulate material is returned directly to dissolved components (e.g. nutrients, DIC, alkalinity).
Citations:
Armstrong, R. A., Lee, C., Hedges, J. I., Honjo, S., and S. G. Wakeham A new, mechanistic model for organic carbon fluxes in the ocean: based on the quantitative association of POC with ballast minerals, Deep-Sea Res. Pt. II, 49, 219-236 n/a
Scientific topic: Dic alkalinity Overview: DIC and alkalinity properties in ocean biogeochemistry
Description:In MEDUSA, both DIC and ALK are explicitly represented tracers that are transported by the ocean physics and which are modified by biological activity. MEDUSA-2 includes dissolved inorganic carbon and total alkalinity tracers. No additional isotopic or abiotic carbon / alkalinity tracers are included.
Description:In MEDUSA, both DIC and ALK are explicitly represented tracers that are transported by the ocean physics and which are modified by biological activity. MEDUSA-2 includes dissolved inorganic carbon and total alkalinity tracers. No additional isotopic or abiotic carbon / alkalinity tracers are included.
Canonical name: land
Short name:
Description: Land Realm
Overview: Land Realm
Grid
Scientific topic: Grid Overview: Land surface grid
Description: The land-surface grid maps to the atmospheric model grid.
Subtopics:
Description: The land-surface grid maps to the atmospheric model grid.
Subtopics:
Scientific topic: Horizontal Overview: The horizontal grid in the land surface
Description:Horizontal grid matches the atmospheric model grid.
Description:Horizontal grid matches the atmospheric model grid.
Scientific topic: Vertical Overview: The vertical grid in the soil
Description:The total depth of the soil is 3 m with the vertical grid structured as four layers for water and energy at 0.1, 0.25, 0.65 and 2.0 m.
Description:The total depth of the soil is 3 m with the vertical grid structured as four layers for water and energy at 0.1, 0.25, 0.65 and 2.0 m.
Realm’s Key Properties
Scientific topic: Key properties Overview: Land surface key properties
Description: Covers the key properties of the model including its details, processes modelled, flux exchanges, atmospheric coupling treatment, land cover types, tiling, conservation properties, software properties and timestepping framework.
Citations:
Description: Covers the key properties of the model including its details, processes modelled, flux exchanges, atmospheric coupling treatment, land cover types, tiling, conservation properties, software properties and timestepping framework.
Citations:
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Menard, C. B., Edwards, J. M., Hendry, M. A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and R. J. Harding (2011) The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes Geosci. Model Dev., 4, 677– 699 n/a
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M (2011) The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics Geosci. Model Dev., 4, 701-722 n/a
Subtopics:
Scientific topic: Conservation properties Overview: Conservation
Description:Energy and water conservation have been assessed for the coupled model as a whole – see top level conservation properties. Carbon conservation is still under assessment for emission-driven runs.
Description:Energy and water conservation have been assessed for the coupled model as a whole – see top level conservation properties. Carbon conservation is still under assessment for emission-driven runs.
Scientific topic: Timestepping framework Overview: Timestepping Framework
Description:Land-surface is called during each atmospheric timestep (1200s in GC3.1).
Description:Land-surface is called during each atmospheric timestep (1200s in GC3.1).
Scientific topic: Software properties Overview: Software properties of land surface code
Description:Details of the software properties for the model, including repository, version and coding language.
Description:Details of the software properties for the model, including repository, version and coding language.
Scientific topic: Tuning applied Overview: Tuning methodology for land component
Description:n/a
Description:n/a
Realm’s Processes
Scientific topic: Lakes Overview: Land surface lakes
Description: There is no lake module in UKESM wetlands are calculated using an implementation of the TOPMODEL
Subtopics:
Description: There is no lake module in UKESM wetlands are calculated using an implementation of the TOPMODEL
Subtopics:
Scientific topic: Wetlands Overview: Wetlands treatment
Description:Wetland fraction is calculated by an implementation of the TOPMODEL ground water scjheme
Description:Wetland fraction is calculated by an implementation of the TOPMODEL ground water scjheme
Scientific topic: Method Overview: Lakes treatment
Description:No lakes model is included
Description:No lakes model is included
Scientific topic: Nitrogen cycle Overview: Land surface nitrogen cycle
Description: JULES-CN refers to the coupled Carbon-Nitrogen configuration of JULES.
Description: JULES-CN refers to the coupled Carbon-Nitrogen configuration of JULES.
Scientific topic: River routing Overview: Land surface river routing
Description: The surface and sub-surface runoff fluxes are supplied to an implementation of the TRIP river routing model.
Citations:
Description: The surface and sub-surface runoff fluxes are supplied to an implementation of the TRIP river routing model.
Citations:
Oki T., and Y.C. Sud (1998) Design of the Total Runoff Integrating Pathways [TRIP] – A global river channel network.. Earth Interactions, 2. https://doi.org/10.1175/1087-3562(1998)002<00
Subtopics:
Scientific topic: Oceanic discharge Overview: Oceanic discharge treatment in river routing
Description:The river routing oceanic discharge is claculated by direct flow from major basins.
Description:The river routing oceanic discharge is claculated by direct flow from major basins.
Scientific topic: Energy balance Overview: Land surface energy balance
Description: Energy balance is resolved for each land-surface tile.
Description: Energy balance is resolved for each land-surface tile.
Scientific topic: Carbon cycle Overview: Land surface carbon cycle
Description: The carbon cycle is represented with the TRIFFID dynamic vegetation model and the JULES photsynthesis / veg respiration and soil respiration components
Subtopics:
Description: The carbon cycle is represented with the TRIFFID dynamic vegetation model and the JULES photsynthesis / veg respiration and soil respiration components
Subtopics:
Scientific topic: Permafrost carbon Overview: Permafrost carbon treatment in carbon cycle
Description:There is no representation of permafrost in UKESM beyond the fact that some soil layers may stay frozen year round.
Description:There is no representation of permafrost in UKESM beyond the fact that some soil layers may stay frozen year round.
Scientific topic: Soil Overview: Soil treatment in carbon cycle
Description:Soil carbon is dealt with with an implementation of the Roth C carbon model
Description:Soil carbon is dealt with with an implementation of the Roth C carbon model
Scientific topic: Vegetation Overview: Vegetation treatment in carbon cycle
Description:Vegetation competition is handled by the TRIFFID module
Properties:
Description:Vegetation competition is handled by the TRIFFID module
Properties:
Description: Allocation treatment in carbon cycleAllocation fractions: fixed
Method: The allocation scheme uses fixed allometric fractions
Allocation bins: leaves + stems + roots
Description: Autotrophic respiration treatment in carbon cycleMaintainance respiration: Maintenance respiration is a combination of soi moisture restricted canopy dark respiration and root and stem respiration (independent of soil moisture but with dependences in nitrogen content and temperature.
Growth respiration: Growth respiration is assumed to be a fixed fraction of net primary prodiuctivity
Description: Vegetation mortality treatment in carbon cycleMethod: Mortality is defined by a fixed turnover parameter
Description: Phenology treatment in carbon cycleMethod: Leaf penology are assumed to be a function of temperature increasing from a minimum as the temperature drops bellow a threshold temperature.
Description: Photosynthesis treatment in carbon cycleMethod: UKESM1 uses the C3 and C4 photosynthesis from Collatz 1991 and 1992 to determine leaf level photosynthesis. This is scaled up to canopy level photosynthesis across 10 canopy layers splitting the incoming PAR into direct and diffuse fractions
Scientific topic: Litter Overview: Litter treatment in Carbon Cycle
Description:Litter is split into a fast (DPM) and slow (RPM) fractions
Description:Litter is split into a fast (DPM) and slow (RPM) fractions
Scientific topic: Snow Overview: Land surface snow
Description: The snow module included is a layered snow module. A maximum number of layers is preset (10 in this configuration) but layers are only created when the snow depth requires it. In practice seasonally snow-covered grid boxes will only use 3 layers. Variable density allows compaction of the snow pack. For needleleaf trees snow is partitioned between canopy interception and through-fall, with canopy snow being stored in a single reservoir.
Citations:
Description: The snow module included is a layered snow module. A maximum number of layers is preset (10 in this configuration) but layers are only created when the snow depth requires it. In practice seasonally snow-covered grid boxes will only use 3 layers. Variable density allows compaction of the snow pack. For needleleaf trees snow is partitioned between canopy interception and through-fall, with canopy snow being stored in a single reservoir.
Citations:
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Menard, C. B., Edwards, J. M., Hendry, M. A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and R. J. Harding (2011) The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes Geosci. Model Dev., 4, 677– 699 n/a
Subtopics:
Scientific topic: Snow albedo Overview: Snow albedo
Description:n/a
Description:n/a
Scientific topic: Vegetation Overview: Land surface vegetation
Description: The vegetation coverage, LAI and height are calculated by the TRIFFID dynamic vegetation module
Citations:
Description: The vegetation coverage, LAI and height are calculated by the TRIFFID dynamic vegetation module
Citations:
Jacobs, C. M. J. Direct impact of atmospheric CO2 enrichment on regional transpiration PhD Thesis, Wageningen Agric. Univ., Wageningen, Netherlands n/a
Scientific topic: Soil Overview: Land surface soil
Description: The soil hydraulics in the model is an implementation of the Brooks Corey hydraulic properties. Brooks Corey 1964 Hydraulic properties in porous media. Colorado State University. Hydrology Papers 3
Citations:
Description: The soil hydraulics in the model is an implementation of the Brooks Corey hydraulic properties. Brooks Corey 1964 Hydraulic properties in porous media. Colorado State University. Hydrology Papers 3
Citations:
van Genuchten, M. Th (1980) A closed-form equation for predicting the hydraulic conductivity of unsaturated soils Soil Science Society of America Journal, 44:892–898 n/a
Subtopics:
Scientific topic: Hydrology Overview: Key properties of the soil hydrology
Description:Incoming precipitation is divided between canopy intercepted and throughfall. Throughfall at a rate lower than a (hydraulic conductivity based) threshold infiltrates the soil. Surplus is partitioned into surface runoff. Movement of moisture between soil layers is based on the hydraulic relationships of van Genuchten.
Properties:
Description:Incoming precipitation is divided between canopy intercepted and throughfall. Throughfall at a rate lower than a (hydraulic conductivity based) threshold infiltrates the soil. Surplus is partitioned into surface runoff. Movement of moisture between soil layers is based on the hydraulic relationships of van Genuchten.
Properties:
Description: Drainage treatment in the soilDescription: Incoming precipitation is divided between canopy intercepted and throughfall. Throughfall at a rate lower than a (hydraulic conductivity based) threshold infiltrates the soil. Surplus is partitioned into surface runoff. Movement of moisture between soil layers is based on the hydraulic relationships of van Genuchten.
Types: Horton mechanism | topmodel-based | Dunne mechanism |
Description: Frozen Soil TreatmentNumber of ground ice layers: 4
Ice storage method: Soil water may freeze with the amount dependent on the minimisation of Gibbs free energy.
Permafrost: nil:inapplicable
Scientific topic: Heat treatment Overview: Soil heat treatment
Description:Heat treatment within surface / soil is a simplified version of the scheme described in Johansen (1975) and is documented in Dharssi et al. (2009). Heat fluxes take into account frozen and unfrozen components of soil moisture.
Citations:
Description:Heat treatment within surface / soil is a simplified version of the scheme described in Johansen (1975) and is documented in Dharssi et al. (2009). Heat fluxes take into account frozen and unfrozen components of soil moisture.
Citations:
Scientific topic: Soil map Overview: Key properties of the land surface soil map
Description:The soil map is derived from the Harmonized World Soil Database (HWSD) and the hydraulic parameters are derived from the texture properties and equations from Brookes Corey. The hydraulic and thermal parameters are derived from the grid box mean ratios of sand, silt and clay.
Description:The soil map is derived from the Harmonized World Soil Database (HWSD) and the hydraulic parameters are derived from the texture properties and equations from Brookes Corey. The hydraulic and thermal parameters are derived from the grid box mean ratios of sand, silt and clay.
Scientific topic: Snow free albedo Overview: TODO
Description:Snow free albedo is calculated as the fraction area covered weight sum of individual tile albedos, with lake and urban albedo taking a globally prescribed value, soil albedo prescribed from a soil colour map (Best et al., 2011). Vegetated tile albedo are calculated based on radiative transfer through vegetation as described by Sellers (1985) and implemented by Essery et al. (2001). This scheme uses separate direct-beam and diffuse albedos in the visible and near-infrared for each vegetation type and requires four parameter values for leaf reflection and leaf scattering coefficients for both near-infrared and photosynthetically active radiation. Beams are intercepted/scattered through the canopy, where leaves are approximated as isotropic scattering elements. A fraction of both beams penetrate the canopy and is reflected by the bare soils prescribed albedo.
Citations:
Description:Snow free albedo is calculated as the fraction area covered weight sum of individual tile albedos, with lake and urban albedo taking a globally prescribed value, soil albedo prescribed from a soil colour map (Best et al., 2011). Vegetated tile albedo are calculated based on radiative transfer through vegetation as described by Sellers (1985) and implemented by Essery et al. (2001). This scheme uses separate direct-beam and diffuse albedos in the visible and near-infrared for each vegetation type and requires four parameter values for leaf reflection and leaf scattering coefficients for both near-infrared and photosynthetically active radiation. Beams are intercepted/scattered through the canopy, where leaves are approximated as isotropic scattering elements. A fraction of both beams penetrate the canopy and is reflected by the bare soils prescribed albedo.
Citations:
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Menard, C. B., Edwards, J. M., Hendry, M. A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and R. J. Harding (2011) The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes Geosci. Model Dev., 4, 677– 699 n/a
Essery R., M. Best, and P. Cox (2001) MOSES 2.2 technical documentation.. Hadley Centre Technical Note 30, 30 pp. n/a
Sellers, P. J. Canopy reflectance, photosynthesis and transpiration. International Journal of Remote Sensing, 6(8), pp.1335-1372. https://doi.org/10.1080/01431168508948283
Canonical name: aerosol
Short name:
Description: n/a
Overview: n/a
Grid
Scientific topic: Grid Overview: Aerosol grid
Description: The grid used for the aerosols model is the same as for the atmosphere model.
Subtopics:
Description: The grid used for the aerosols model is the same as for the atmosphere model.
Subtopics:
Scientific topic: Resolution Overview: Resolution in the atmospheric aerosol grid
Description:192×144 grid cells in horizontal with resolution of 1.875 x 1.25 degrees respectively, translating to approx 110 km in mid-latitudes. 85 hybrid levels in the vertical extending upto 85.0 km
Description:192×144 grid cells in horizontal with resolution of 1.875 x 1.25 degrees respectively, translating to approx 110 km in mid-latitudes. 85 hybrid levels in the vertical extending upto 85.0 km
Realm’s Key Properties
Scientific topic: Key properties Overview: Key properties of the aerosol model
Description: Multi-component and multi-modal aerosol model that transports aerosol particle number and component mass concentrations of sulfate, sea salt, black carbon and organic carbon in five internally mixed log-normal modes. Mineral dust is simulated separately using the 6-bin mass-based CLASSIC scheme.
Citations:
Description: Multi-component and multi-modal aerosol model that transports aerosol particle number and component mass concentrations of sulfate, sea salt, black carbon and organic carbon in five internally mixed log-normal modes. Mineral dust is simulated separately using the 6-bin mass-based CLASSIC scheme.
Citations:
Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J. and C. E. Johnson Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model, Geosci. Model Dev., 3, 519-551 https://doi.org/10.5194/gmd-3-519-2010
Mann, G. W., Carslaw, K. S., Ridley, D. A., Spracklen, D. V., Pringle, K. J., Merikanto, J., Korhonen, H., Schwarz, J. P., Lee, L. A., Manktelow, P. T., Woodhouse, M. T., Schmidt, A., Breider, T. J., Emmerson, K. M., Reddington, C. L., Chipperfield, M. P, and S. J. Pickering Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model Atmos. Chem. Phys., 12, 4449-4476 https://doi.org/10.5194/acp-12-4449-2012
Woodward S., (2001) Modelling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model.. J. Geophys. Res., 106, D16, 18,155-18,166, 2001. n/a
Mulcahy, J. P., Jones, C., Sellar, A., Johnson,B., Boutle, I., Jones, A., Andrews, T., Rumbold, S., Mollard, J., Bellouin, N., Johnson, C., Williams, K., Grosvenor, D. and D. T. McCoy Improved aerosol processes and effective radiative forcing in HadGEM3 and UKESM1 in prep 2018 n/a
Properties:
Description: Software properties of aerosol codeRepository: https://code.metoffice.co.uk/trac/um
Code version: UM11.0
Code languages: Fortran 90/2003
Subtopics:
Scientific topic: Timestep framework Overview: Physical properties of seawater in ocean
Description:Specific timestepping (operator splitting) performed with a timestep of 1200 seconds done in the atmosphere model for aerosol advection and a timestep of 3600 seconds for aerosol physics.
Description:Specific timestepping (operator splitting) performed with a timestep of 1200 seconds done in the atmosphere model for aerosol advection and a timestep of 3600 seconds for aerosol physics.
Scientific topic: Meteorological forcings Overview: n/a
Description:Information on 3D and 2D forcing variables and the frequency with which the forcings are applied.
Description:Information on 3D and 2D forcing variables and the frequency with which the forcings are applied.
Scientific topic: Resolution Overview: Resolution in the aerosol model grid
Description:192×144 grid cells in horizontal with resolution of 1.875 x 1.25 degrees respectively, translating to approx 110 km in mid-latitudes. 85 Hybrid Levels in the vertical extending upto 85.0 km.
Description:192×144 grid cells in horizontal with resolution of 1.875 x 1.25 degrees respectively, translating to approx 110 km in mid-latitudes. 85 Hybrid Levels in the vertical extending upto 85.0 km.
Scientific topic: Tuning applied Overview: Tuning methodology for aerosol model
Description:Mineral dust emissions have three tuning parameters described in Woodward (2001), these tune the global total emission, soil moisture dependence and threshold frictional velocity dependence. Tuned to give as good agreement as possible with observed dust surface concentration and optical depths. Biomass burning emissions of BC and OC are scaled to give improved AOD agreement in biomass burning regions following Johnson et al., 2016. SOA yield from Monoterpene has a scaling factor of 2.0. In-cloud oxidation of SO2 is reduced by 25% following Mulcahy et al., 2018 in prep.
Citations:
Description:Mineral dust emissions have three tuning parameters described in Woodward (2001), these tune the global total emission, soil moisture dependence and threshold frictional velocity dependence. Tuned to give as good agreement as possible with observed dust surface concentration and optical depths. Biomass burning emissions of BC and OC are scaled to give improved AOD agreement in biomass burning regions following Johnson et al., 2016. SOA yield from Monoterpene has a scaling factor of 2.0. In-cloud oxidation of SO2 is reduced by 25% following Mulcahy et al., 2018 in prep.
Citations:
Woodward S., (2001) Modelling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model.. J. Geophys. Res., 106, D16, 18,155-18,166, 2001. n/a
Johnson, B. T., Haywood, J. M., Langridge, J. M., Darbyshire, E., Morgan, W. T., Szpek, K., Brooke, J. K., Marenco, F., Coe, H., Artaxo, P., Longo, K. M., Mulcahy, J. P., Mann, G. W., Dalvi, M., and Bellouin, N. Evaluation of biomass burning aerosols in the HadGEM3 climate model with observations from the SAMBBA field campaign Atmos. Chem. Phys., 16, 14657-14685 https://doi.org/10.5194/acp-16-14657-2016
Mulcahy, J. P., Jones, C., Sellar, A., Johnson,B., Boutle, I., Jones, A., Andrews, T., Rumbold, S., Mollard, J., Bellouin, N., Johnson, C., Williams, K., Grosvenor, D. and D. T. McCoy Improved aerosol processes and effective radiative forcing in HadGEM3 and UKESM1 in prep 2018 n/a
Realm’s Processes
Scientific topic: Transport Overview: Aerosol transport
Description: Transport of aerosols and aerosol-chemistry tracers is handled by the atmospheric model.
Description: Transport of aerosols and aerosol-chemistry tracers is handled by the atmospheric model.
Scientific topic: Emissions Overview: Atmospheric aerosol emissions
Description: For HadGEM3/GC3.1 prescribed emissions of SO2, BC, OC, land and oceanic DMS, Isoprene and Monoterpene. Online emissions for sea-salt and dust.
Description: For HadGEM3/GC3.1 prescribed emissions of SO2, BC, OC, land and oceanic DMS, Isoprene and Monoterpene. Online emissions for sea-salt and dust.
Scientific topic: Concentrations Overview: Atmospheric aerosol concentrations
Description: For HadGEM3 the concentrations in the model are unknown with no species listed.
Description: For HadGEM3 the concentrations in the model are unknown with no species listed.
Scientific topic: Optical radiative properties Overview: Aerosol optical and radiative properties
Description: Aerosol direct and indirect effects included. Optical properties calculated from Mie theory assuming homogeneous spheres where all components present in a size mode are internally mixed. Mineral dust aerosol also modelled as spheres and externally mixed with the modal aerosol.
Subtopics:
Description: Aerosol direct and indirect effects included. Optical properties calculated from Mie theory assuming homogeneous spheres where all components present in a size mode are internally mixed. Mineral dust aerosol also modelled as spheres and externally mixed with the modal aerosol.
Subtopics:
Scientific topic: Absorption Overview: Absortion properties in aerosol scheme
Description:Information on absorption mass coefficients for black carbon, dust and organics.
Description:Information on absorption mass coefficients for black carbon, dust and organics.
Scientific topic: Mixtures Overview: n/a
Description:Information on internal and external mixing with respect to chemical composition.
Description:Information on internal and external mixing with respect to chemical composition.
Scientific topic: Impact of h2o Overview: n/a
Description:The impact of H2O on aerosols
Description:The impact of H2O on aerosols
Scientific topic: Radiative scheme Overview: Radiative scheme for aerosol
Description:Aerosol-radiation scheme RADAER is described in Bellouin et al., 2013. Optical properties for each aerosol mode vary interactively depending on modal radius and chemical composition (including any water).
Citations:
Description:Aerosol-radiation scheme RADAER is described in Bellouin et al., 2013. Optical properties for each aerosol mode vary interactively depending on modal radius and chemical composition (including any water).
Citations:
Bellouin, N., Mann, G. W., Woodhouse, M. T., Johnson, C., Carslaw, K. S. and M. Dalvi Impact of the modal aerosol scheme GLOMAP-mode on aerosol forcing in the Hadley Centre Global Environmental Model Atmos. Chem. Phys., 13, 3027-3044 doi:10.5194/acp-13-3027-2013
Scientific topic: Cloud interactions Overview: Aerosol-cloud interactions
Description:Aerosol activation of cloud droplets is simulated using the UKCA-ACTIVATE scheme (West et al., 2014), which implements the Abdul Razzak Ghan (2000) parameterisation. There is no minimum limit on CCN, but the activation scheme assumes a minimum CDNC of 5 cm-3 to avoid numerical failures.
Citations:
Description:Aerosol activation of cloud droplets is simulated using the UKCA-ACTIVATE scheme (West et al., 2014), which implements the Abdul Razzak Ghan (2000) parameterisation. There is no minimum limit on CCN, but the activation scheme assumes a minimum CDNC of 5 cm-3 to avoid numerical failures.
Citations:
West R.E.L, Stier P., Jones, A., Johnson, C. E., Mann, G. W., Bellouin, N., Partridge, D. G., and Z. Kipling The importance of vertical velocity variability for estimates of the indirect aerosol effects Atmospheric Chemistry and Physics, 14, 6369-6393 doi:10.5194/acp-14-6369-2014, https://www.atm
Abdul-Razzak, H. and S. J. Ghan A parameterization of aerosol activation: 2. Multiple aerosol types Journal of Geophysical Research:Atmospheres, 105, 6837-6844 doi:10.1029/1999JD901161, http://dx.doi.org/1
Scientific topic: Model Overview: Aerosol model
Description: UKCA-GLOMAP-mode (Mann et al., 2010, 2012) is a multi-component and multi-modal aerosol model representing microphysical processes in the form of size-resolved primary emissions, new particle formation, condensation, coagulation, cloud processing, dry deposition, sedimentation, nucleation scavenging and impaction scavenging. The model transports aerosol particle number and component mass concentrations of sulfate, sea salt, black carbon and organic carbon in five internally mixed log-normal modes. Mineral dust is simulated separately using the 6-bin emission scheme of Woodward (2001). This represents the direct interaction of dust with radiation, but not interactions with cloud microphysics. Dust does not mix internally with the aerosols represented by the modal scheme.
Citations:
Description: UKCA-GLOMAP-mode (Mann et al., 2010, 2012) is a multi-component and multi-modal aerosol model representing microphysical processes in the form of size-resolved primary emissions, new particle formation, condensation, coagulation, cloud processing, dry deposition, sedimentation, nucleation scavenging and impaction scavenging. The model transports aerosol particle number and component mass concentrations of sulfate, sea salt, black carbon and organic carbon in five internally mixed log-normal modes. Mineral dust is simulated separately using the 6-bin emission scheme of Woodward (2001). This represents the direct interaction of dust with radiation, but not interactions with cloud microphysics. Dust does not mix internally with the aerosols represented by the modal scheme.
Citations:
Woodward S., (2001) Modelling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model.. J. Geophys. Res., 106, D16, 18,155-18,166, 2001. n/a
Mann, G. W., Carslaw, K. S., Ridley, D. A., Spracklen, D. V., Pringle, K. J., Merikanto, J., Korhonen, H., Schwarz, J. P., Lee, L. A., Manktelow, P. T., Woodhouse, M. T., Schmidt, A., Breider, T. J., Emmerson, K. M., Reddington, C. L., Chipperfield, M. P, and S. J. Pickering Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model Atmos. Chem. Phys., 12, 4449-4476 https://doi.org/10.5194/acp-12-4449-2012
Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J. and C. E. Johnson Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model, Geosci. Model Dev., 3, 519-551 https://doi.org/10.5194/gmd-3-519-2010
Canonical name: atmos
Short name:
Description: Atmosphere Realm
Overview: Atmosphere Realm
Grid
Scientific topic: Grid Overview: Atmosphere grid
Description: Horizontal grid is 1.25 x 1.875 degrees lat-lon, denoted N96. Horizontal grid staggering uses an Arakawa C-grid. Vertical grid uses 85 levels with a Charney-Phillips staggering and terrain-following hybrid height coordinates.
Subtopics:
Description: Horizontal grid is 1.25 x 1.875 degrees lat-lon, denoted N96. Horizontal grid staggering uses an Arakawa C-grid. Vertical grid uses 85 levels with a Charney-Phillips staggering and terrain-following hybrid height coordinates.
Subtopics:
Scientific topic: Discretisation Overview: Atmosphere grid discretisation
Description:These prognostic fields are discretised horizontally onto a regular longitude/latitude grid with Arakawa C-grid staggering, whilst the vertical discretisation utilises a Charney-Phillips staggering using terrain-following hybrid height coordinates. The discretised equations are solved using a nested iterative approach centred about solving a linear Helmholtz equation.
Properties:
Description:These prognostic fields are discretised horizontally onto a regular longitude/latitude grid with Arakawa C-grid staggering, whilst the vertical discretisation utilises a Charney-Phillips staggering using terrain-following hybrid height coordinates. The discretised equations are solved using a nested iterative approach centred about solving a linear Helmholtz equation.
Properties:
Description: Atmosphere discretisation in the horizontalScheme type: fixed grid
Scheme method: finite difference
Scheme order: nil:inapplicable
Horizontal pole: filter
Grid type: Latitude-Longitude
Description: Atmosphere discretisation in the verticalCoordinate type: hybrid sigma-pressure
Realm’s Key Properties
Scientific topic: Key properties Overview: Atmosphere key properties
Description: A brief description of the key properties of the model, including type, basic approximations, orography, resolutions and timestepping.
Subtopics:
Description: A brief description of the key properties of the model, including type, basic approximations, orography, resolutions and timestepping.
Subtopics:
Scientific topic: Resolution Overview: Characteristics of the model resolution
Description:The horizontal resolution is 1.25 x 1.875 degrees lat-lon everywhere, giving approximately isotropic resolution of 130 km in mid-latitudes. In the vertical 85 levels are used, with 50 levels below 18 km, 35 levels above this and a fixed model lid 85 km above sea level.
Description:The horizontal resolution is 1.25 x 1.875 degrees lat-lon everywhere, giving approximately isotropic resolution of 130 km in mid-latitudes. In the vertical 85 levels are used, with 50 levels below 18 km, 35 levels above this and a fixed model lid 85 km above sea level.
Scientific topic: Timestepping Overview: Characteristics of the atmosphere model time stepping
Description:With ENDGame, the UM uses a nested iterative structure for each atmospheric timestep within which processes are split into an outer loop and an inner loop. The semi-Lagrangian departure point equations are solved within the outer loop using the latest estimates for the wind variables. Appropriate fields are then interpolated to the updated departure points. Within the inner loop, the Coriolis, orographic and non-linear terms are solved along with a linear Helmholtz problem to obtain the pressure increment. Latest estimates for all variables are then obtained from the pressure increment via a back-substitution process; see Wood et al. (2014) for details.
Citations:
Description:With ENDGame, the UM uses a nested iterative structure for each atmospheric timestep within which processes are split into an outer loop and an inner loop. The semi-Lagrangian departure point equations are solved within the outer loop using the latest estimates for the wind variables. Appropriate fields are then interpolated to the updated departure points. Within the inner loop, the Coriolis, orographic and non-linear terms are solved along with a linear Helmholtz problem to obtain the pressure increment. Latest estimates for all variables are then obtained from the pressure increment via a back-substitution process; see Wood et al. (2014) for details.
Citations:
Wood, N., Staniforth, A., White, A., Allen, T., Diamantakis, M., Gross, M., Melvin, T., Smith, C., Vosper, S., Zerroukat, M., and Thuburn, J. An inherently mass-conserving semi-implicit semi-Lagrangian discretization of the deep-atmosphere global non-hydrostatic equations Q. J. Roy. Meteorol. Soc., 140, 1505-1520 10.1002/qj.2235, 2014
Scientific topic: Orography Overview: Characteristics of the model orography
Description:The GLOBE dataset (GLOBE Task Team et al., 1999) is used, smoothed to avoid dynamical instabilities.
Citations:
Description:The GLOBE dataset (GLOBE Task Team et al., 1999) is used, smoothed to avoid dynamical instabilities.
Citations:
Hastings, D. A., Dunbar, P. K., Elphingstone, G. M., Bootz, M., Hiroshi Murakami, Hiroshi Maruyama, Hiroshi Masaharu, Holland, P., Payne, J., Bryant, N. A., Logan, T. L., Muller, J.-P., Schreier, G., and J. S. MacDonald), eds., The Global Land One-kilometer Base Elevation (GLOBE) Digital Elevation Model, Version 1.0. National Oceanic and Atmospheric Administration, National Geophysical Data Center, 325 Broadway, Boulder, Colorado 80305-3328, U.S.A. n/a
Scientific topic: Tuning applied Overview: Tuning methodology for atmospheric component
Description:n/a
Citations:
Description:n/a
Citations:
Walters, D., Baran, A., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and M. Zerroukat The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations Geosci. Model Dev. Discuss., in review, 2017. https://doi.org/10.5194/gmd-2017-291
Williams, K., Copsey, D., Blockley, E., Bodas-Salcedo, A., Calvert, D., Comer, R., Davis, P., Graham, T., Hewitt, H., Hill, R., Hyder, P., Ineson, S., Johns, T., Keen, A., Lee, R., Megann, A., Milton, S., Rae, J., Roberts, M., Scaife, A., Schiemann, R., Storkey, D., Thorpe, L., Watterson, I., Walters, D., West, A., Wood, R., Woollings, T., and Xavier, P. The Met Office Global Coupled model 3.0 and 3.1 (GC3.0 and GC3.1) configurations Journal of Advances in Modeling Earth Systems, 10, 357-380 https://doi.org/10.1002/2017MS001115
Mulcahy, J. P., Jones, C., Sellar, A., Johnson,B., Boutle, I., Jones, A., Andrews, T., Rumbold, S., Mollard, J., Bellouin, N., Johnson, C., Williams, K., Grosvenor, D. and D. T. McCoy Improved aerosol processes and effective radiative forcing in HadGEM3 and UKESM1 in prep 2018 n/a
Realm’s Processes
Scientific topic: Dynamical core Overview: Characteristics of the dynamical core
Description: Semi-implicit, semi-Lagrangian, using cubic interpolation.
Citations:
Description: Semi-implicit, semi-Lagrangian, using cubic interpolation.
Citations:
Walters, D., Baran, A., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and M. Zerroukat The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations Geosci. Model Dev. Discuss., in review, 2017. https://doi.org/10.5194/gmd-2017-291
Wood, N., Staniforth, A., White, A., Allen, T., Diamantakis, M., Gross, M., Melvin, T., Smith, C., Vosper, S., Zerroukat, M., and Thuburn, J. An inherently mass-conserving semi-implicit semi-Lagrangian discretization of the deep-atmosphere global non-hydrostatic equations Q. J. Roy. Meteorol. Soc., 140, 1505-1520 10.1002/qj.2235, 2014
Subtopics:
Scientific topic: Top boundary Overview: Type of boundary layer at the top of the model
Description:For wind, w=0 at the boundary, with w-damping in the top few layers.
Description:For wind, w=0 at the boundary, with w-damping in the top few layers.
Scientific topic: Lateral boundary Overview: Type of lateral boundary condition (if the model is a regional model)
Description:Not applicable for global models.
Description:Not applicable for global models.
Scientific topic: Diffusion horizontal Overview: Horizontal diffusion scheme
Description:A horizontal diffusion scheme is not applicable for the global models.
Description:A horizontal diffusion scheme is not applicable for the global models.
Scientific topic: Advection Overview: Dynamical core advection
Description:The UM’s ENDGame dynamical core uses a semi-implicit semi-Lagrangian formulation to solve the non-hydrostatic, fully-compressible deep-atmosphere equations of motion (Wood et al., 2014). The primary atmospheric prognostics are the three-dimensional wind components, virtual dry potential temperature, Exner pressure and dry density.
Citations:
Description:The UM’s ENDGame dynamical core uses a semi-implicit semi-Lagrangian formulation to solve the non-hydrostatic, fully-compressible deep-atmosphere equations of motion (Wood et al., 2014). The primary atmospheric prognostics are the three-dimensional wind components, virtual dry potential temperature, Exner pressure and dry density.
Citations:
Walters, D., Baran, A., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and M. Zerroukat The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations Geosci. Model Dev. Discuss., in review, 2017. https://doi.org/10.5194/gmd-2017-291
Properties:
Description: Momentum advection schemeScheme name: semi-Lagrangian
Scheme characteristics: staggered grid | 3rd order |
Scheme staggering type: Arakawa C-grid
Conserved quantities: nil:inapplicable
Conservation method: nil:inapplicable
Description: Tracer advection schemeScheme name: None
Scheme characteristics: cubic semi-Lagrangian
Conserved quantities: dry mass | tracer mass |
Conservation method: Priestley algorithm
Scientific topic: Radiation Overview: Characteristics of the atmosphere radiation process
Description: Solar radiation is treated in six SW bands and thermal radiation in nine LW bands. Gaseous absorption uses the correlated-k method with newly derived coefficients for all gases (except where indicated below) based on the HITRAN 2012 spectroscopic database (Rothman et al., 2013). Scaling of absorption coefficients uses a look-up table of 59 pressures with five temperatures per pressure level based around a mid-latitude summer profile. The method of equivalent extinction (Edwards, 1996; Amundsen et al., 2017) is used for minor gases in each band.
Citations:
Description: Solar radiation is treated in six SW bands and thermal radiation in nine LW bands. Gaseous absorption uses the correlated-k method with newly derived coefficients for all gases (except where indicated below) based on the HITRAN 2012 spectroscopic database (Rothman et al., 2013). Scaling of absorption coefficients uses a look-up table of 59 pressures with five temperatures per pressure level based around a mid-latitude summer profile. The method of equivalent extinction (Edwards, 1996; Amundsen et al., 2017) is used for minor gases in each band.
Citations:
Rothman, L. S., Gordon, I. E., Babikov, Y., Barbe, A., Chris Benner, D., Bernath, P. F., Birk, M., Bizzocchi, L., Boudon, V., Brown, L. R., Campargue, A., Chance, K., Cohen, E. A., Coudert, L. H., Devi, V. M., Drouin, B. J., Fayt, A., Flaud, J.-M., Gamache, R. R., Har- rison, J. J., Hartmann, J.-M., Hill, C., Hodges, J. T., Jacquemart, D., Jolly, A., Lamouroux, J., Le Roy, R. J., Li, G., Long, D. A., Lyulin, O. M., Mackie, C. J., Massie, S. T., Mikhailenko, S., Müller, H. S. P., Naumenko, O. The HITRAN2012 molecular spectroscopic database J. Quant. Spectrosc. Radiat. Transfer, 130, 4-50 https://doi.org/10.1016/j.jqsrt.2013.07.002
Edwards, J. M. Efficient calculation of infrared fluxes and cooling rates using the two-stream equations J. Atmos. Sci., 53, 1921-1932 https://doi.org/10.1175/1520-0469(1996)053<19
Amundsen, D. S., Tremblin, P., Manners, J., Baraffe, I., and N. J. Mayne Treatment of overlapping gaseous absorption with the correlated-k method in hot Jupiter and brown dwarf atmosphere models Astron. Astrophys., 598, A97, 10pp https://doi.org/10.1051/0004-6361/201629322
Edwards, 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 http://dx.doi.org/10.1002/qj.49712253107
Subtopics:
Scientific topic: Shortwave radiation Overview: Properties of the shortwave radiation scheme
Description:Gaseous absorption uses the correlated-k method, with 41 k-terms for the major gases in six SW bands. See Table 1 in Waters et al. (2017) for details.
Description:Gaseous absorption uses the correlated-k method, with 41 k-terms for the major gases in six SW bands. See Table 1 in Waters et al. (2017) for details.
Scientific topic: Shortwave ghg Overview: Representation of greenhouse gases in the shortwave radiation scheme
Description:Absorption by H2O, CO2, O3, O2, N2O and CH4 is included.
Description:Absorption by H2O, CO2, O3, O2, N2O and CH4 is included.
Scientific topic: Shortwave cloud ice Overview: Shortwave radiative properties of ice crystals in clouds
Description:The parametrisation of ice crystals is described in Baran et al. (2016). Full treatment of scattering is used in both the SW and LW.
Citations:
Description:The parametrisation of ice crystals is described in Baran et al. (2016). Full treatment of scattering is used in both the SW and LW.
Citations:
Baran, A. J., Hill, P., Walters, D., Hardman, S. C., Furtado, K., Field, P. R., and J. Manners The impact of two coupled cirrus microphysics-radiation parameterizations on the temperature and specific humidity biases in the tropical tropopause layer in a climate model J. Climate, 29, 5299-5316 https://doi.org/10.1175/JCLI-D-15-0821.1, 201
Scientific topic: Shortwave cloud liquid Overview: Shortwave radiative properties of liquid droplets in clouds
Description:The parametrisation of cloud droplets is described in Edwards and Slingo (1996) using the method of “thick averaging”. Pade fits are used for the variation with effective radius, which is computed from the number of cloud droplets. The parameterisation of Liu et al. (2008) is used to represent the effect of droplet size spectral dispersion.
Citations:
Description:The parametrisation of cloud droplets is described in Edwards and Slingo (1996) using the method of “thick averaging”. Pade fits are used for the variation with effective radius, which is computed from the number of cloud droplets. The parameterisation of Liu et al. (2008) is used to represent the effect of droplet size spectral dispersion.
Citations:
Edwards, 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 http://dx.doi.org/10.1002/qj.49712253107
Scientific topic: Shortwave cloud inhomogeneity Overview: Cloud inhomogeneity in the shortwave radiation scheme
Description:The subgrid cloud structure is represented using the Monte Carlo Independent Column Approximation (McICA) as described in Hill et al. (2011), with the parametrisation of subgrid-scale water content variability described in Hill et al. (2015b).
Citations:
Description:The subgrid cloud structure is represented using the Monte Carlo Independent Column Approximation (McICA) as described in Hill et al. (2011), with the parametrisation of subgrid-scale water content variability described in Hill et al. (2015b).
Citations:
Edwards, 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 http://dx.doi.org/10.1002/qj.49712253107
Hill, P. G., Manners, J., and J. C. Petch Reducing noise associated with the Monte Carlo Independent Column Approximation for weather forecasting models Q. J. R. Meteorol. Soc., 137, 219-228 https://doi.org/10.1002/qj.732, 2011.
Hill, P. G., Morcrette, C. J., and Boutle, I. A. A regime-dependent parametrization of subgrid-scale cloud water content variability Q. J. R. Meteorol. Soc., 141, 1975-1986 https://doi.org/10.1002/qj.2506
Scientific topic: Shortwave aerosols Overview: Shortwave radiative properties of aerosols
Description:The aerosol scattering and absorption coefficients and asymmetry parameters are pre-computed for a wide range of plausible Mie parameters and stored in look-up tables for use during run-time when the atmospheric chemical composition, including mean aerosol particle radius and water content, are known. As the aerosol species are internally mixed within the modal aerosol scheme, the refractive indices of each mode are calculated online as a volume weighted mean of the component species contributing to that mode. The component refractive indices are documented Bellouin et al. (2013).
Description:The aerosol scattering and absorption coefficients and asymmetry parameters are pre-computed for a wide range of plausible Mie parameters and stored in look-up tables for use during run-time when the atmospheric chemical composition, including mean aerosol particle radius and water content, are known. As the aerosol species are internally mixed within the modal aerosol scheme, the refractive indices of each mode are calculated online as a volume weighted mean of the component species contributing to that mode. The component refractive indices are documented Bellouin et al. (2013).
Scientific topic: Shortwave gases Overview: Shortwave radiative properties of gases
Description:Based on the HITRAN 2012 spectroscopic database. The water vapour continuum is represented using laboratory results from the CAVIAR project (Continuum Absorption at Visible and Infrared wavelengths and its Atmospheric Relevance) between 1 and 5 microns and version 2.5 of the Mlawer–Tobin_Clough–Kneizys–Davies (MT_CKD-2.5) model at other wavelengths.
Description:Based on the HITRAN 2012 spectroscopic database. The water vapour continuum is represented using laboratory results from the CAVIAR project (Continuum Absorption at Visible and Infrared wavelengths and its Atmospheric Relevance) between 1 and 5 microns and version 2.5 of the Mlawer–Tobin_Clough–Kneizys–Davies (MT_CKD-2.5) model at other wavelengths.
Scientific topic: Longwave radiation Overview: Properties of the longwave radiation scheme
Description:Gaseous absorption uses the correlated-k method, with 81 k-terms used for the major gases in nine LW bands. See Table 1 of Walters et al. (2017) for details.
Citations:
Description:Gaseous absorption uses the correlated-k method, with 81 k-terms used for the major gases in nine LW bands. See Table 1 of Walters et al. (2017) for details.
Citations:
Walters, D., Baran, A., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and M. Zerroukat The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations Geosci. Model Dev. Discuss., in review, 2017. https://doi.org/10.5194/gmd-2017-291
Scientific topic: Longwave ghg Overview: Representation of greenhouse gases in the longwave radiation scheme
Description:In the LW bands 81 k-terms are used for the major gases. Absorption by H2O, O3, CO2, CH4, N2O, CFC-12 (CCl2 F2) and HFC134a (CH2 FCF3) is included. The atmospheric concentrations of CFC-12 and HFC134a are adjusted to represent absorption by all the remaining trace halocarbons.
Description:In the LW bands 81 k-terms are used for the major gases. Absorption by H2O, O3, CO2, CH4, N2O, CFC-12 (CCl2 F2) and HFC134a (CH2 FCF3) is included. The atmospheric concentrations of CFC-12 and HFC134a are adjusted to represent absorption by all the remaining trace halocarbons.
Scientific topic: Longwave cloud ice Overview: Longwave radiative properties of ice crystals in clouds
Description:The parametrisation of ice crystals is described in Baran et al. (2016). Full treatment of scattering is used in both the SW and LW.
Citations:
Description:The parametrisation of ice crystals is described in Baran et al. (2016). Full treatment of scattering is used in both the SW and LW.
Citations:
Baran, A. J., Hill, P., Walters, D., Hardman, S. C., Furtado, K., Field, P. R., and J. Manners The impact of two coupled cirrus microphysics-radiation parameterizations on the temperature and specific humidity biases in the tropical tropopause layer in a climate model J. Climate, 29, 5299-5316 https://doi.org/10.1175/JCLI-D-15-0821.1, 201
Scientific topic: Longwave cloud liquid Overview: Longwave radiative properties of liquid droplets in clouds
Description:The parametrisation of cloud droplets is described in Edwards and Slingo (1996) using the method of “thick averaging”. Padé fits are used for the variation with effective radius, which is computed from the number of cloud droplets. The parameterisation of Liu et al (2008) is used to represent the effect of droplet size spectral dispersion.
Citations:
Description:The parametrisation of cloud droplets is described in Edwards and Slingo (1996) using the method of “thick averaging”. Padé fits are used for the variation with effective radius, which is computed from the number of cloud droplets. The parameterisation of Liu et al (2008) is used to represent the effect of droplet size spectral dispersion.
Citations:
Yangang Liu, Daum, P. H., Huan Guo and Yiran Peng Dispersion bias, dispersion effect, and the aerosol-cloud conundrum Environmental Research Letters, Volume 3, 045021, 8pp doi:10.1088/1748-9326/3/4/045021
Edwards, 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 http://dx.doi.org/10.1002/qj.49712253107
Scientific topic: Longwave cloud inhomogeneity Overview: Cloud inhomogeneity in the longwave radiation scheme
Description:The sub-grid cloud structure is represented using the Monte Carlo Independent Column Approximation (McICA) as described in Hill et al. (2011), with the parametrisation of subgrid-scale water content variability described in Hill et al. (2015).
Citations:
Description:The sub-grid cloud structure is represented using the Monte Carlo Independent Column Approximation (McICA) as described in Hill et al. (2011), with the parametrisation of subgrid-scale water content variability described in Hill et al. (2015).
Citations:
Hill, P. G., Manners, J., and J. C. Petch Reducing noise associated with the Monte Carlo Independent Column Approximation for weather forecasting models Q. J. R. Meteorol. Soc., 137, 219-228 https://doi.org/10.1002/qj.732, 2011.
Hill, P. G., Morcrette, C. J., and I. A. Boutle A regime-dependent parametrization of subgrid-scale cloud water content variability Q. J. R. Meteorol. Soc., 141, 1975-1986 https://doi.org/10.1002/qj.2506
Scientific topic: Longwave aerosols Overview: Longwave radiative properties of aerosols
Description:The aerosol scattering and absorption coefficients and asymmetry parameters are precomputed for a wide range of plausible Mie parameters and stored in look-up tables for use during run-time when the atmospheric chemical composition, including mean aerosol particle radius and water content are known. As the aerosol species are internally mixed within the modal aerosol scheme the refractive indices of each mode are calculated online as a volume weighted mean of the component species contributing to that mode. The component refractive indices are documented in Bellouin et al. (2013).
Citations:
Description:The aerosol scattering and absorption coefficients and asymmetry parameters are precomputed for a wide range of plausible Mie parameters and stored in look-up tables for use during run-time when the atmospheric chemical composition, including mean aerosol particle radius and water content are known. As the aerosol species are internally mixed within the modal aerosol scheme the refractive indices of each mode are calculated online as a volume weighted mean of the component species contributing to that mode. The component refractive indices are documented in Bellouin et al. (2013).
Citations:
Bellouin, N., Mann, G. W., Woodhouse, M. T., Johnson, C., Carslaw, K. S. and M. Dalvi Impact of the modal aerosol scheme GLOMAP-mode on aerosol forcing in the Hadley Centre Global Environmental Model Atmos. Chem. Phys., 13, 3027-3044 doi:10.5194/acp-13-3027-2013
Scientific topic: Longwave gases Overview: Longwave radiative properties of gases
Description:Based on the HITRAN 2012 spectroscopic database. The water vapour continuum is represented using laboratory results from the CAVIAR project (Continuum Absorption at Visible and Infrared wavelengths and its Atmospheric Relevance) between 1 and 5 microns and version 2.5 of the Mlawer–Tobin_Clough–Kneizys–Davies (MT_CKD-2.5) model at other wavelengths.
Description:Based on the HITRAN 2012 spectroscopic database. The water vapour continuum is represented using laboratory results from the CAVIAR project (Continuum Absorption at Visible and Infrared wavelengths and its Atmospheric Relevance) between 1 and 5 microns and version 2.5 of the Mlawer–Tobin_Clough–Kneizys–Davies (MT_CKD-2.5) model at other wavelengths.
Scientific topic: Turbulence convection Overview: Atmosphere Convective Turbulence and Clouds
Description: Deep and shallow convection are based on the Gregory Rowntree (1990) scheme with modifications. The turbulence convection scheme is that of Lock et al. (2000) with the modifications described in Lock (2001) and Brown et al. (2008). It is a first-order turbulence closure mixing adiabatically conserved heat and moisture variables, momentum and tracers.
Citations:
Description: Deep and shallow convection are based on the Gregory Rowntree (1990) scheme with modifications. The turbulence convection scheme is that of Lock et al. (2000) with the modifications described in Lock (2001) and Brown et al. (2008). It is a first-order turbulence closure mixing adiabatically conserved heat and moisture variables, momentum and tracers.
Citations:
Lock 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. n/a
Lock, A. P. The Numerical Representation of Entrainment in Parameterizations of Boundary Layer Turbulent Mixing Monthly Weather Review, 129, 1148-1163 https://doi.org/10.1175/1520-0493(2001)129<11
Brown, A., Beare, B., Edwards, J.M., Lock, A., Keogh S.J., Milton, S.F. and D. N. Walters Upgrades to the boundary-layer scheme in the Met Office numerical weather prediction model Boundary-Layer Meteorol, 128, 117-132 https://doi.org/10.1007/s10546-008-9275-0
Gregory 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. n/a
Subtopics:
Scientific topic: Boundary layer turbulence Overview: Properties of the boundary layer turbulence scheme
Description:The scheme is that of Lock et al. (2000) with the modifications described in Lock (2001) and Brown et al. (2008). It is a first-order turbulence closure mixing adiabatically conserved heat and moisture variables, momentum and tracers. For unstable boundary layers, diffusion coefficients (K profiles) are specified functions of height within the boundary layer, related to the strength of the turbulence forcing. Two separate 15 K profiles are used, one for surface sources of turbulence (surface heating and wind shear) and one for cloud-top sources (radiative and evaporative cooling).
Citations:
Description:The scheme is that of Lock et al. (2000) with the modifications described in Lock (2001) and Brown et al. (2008). It is a first-order turbulence closure mixing adiabatically conserved heat and moisture variables, momentum and tracers. For unstable boundary layers, diffusion coefficients (K profiles) are specified functions of height within the boundary layer, related to the strength of the turbulence forcing. Two separate 15 K profiles are used, one for surface sources of turbulence (surface heating and wind shear) and one for cloud-top sources (radiative and evaporative cooling).
Citations:
Lock 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. n/a
Lock, A. P. The Numerical Representation of Entrainment in Parameterizations of Boundary Layer Turbulent Mixing Monthly Weather Review, 129, 1148-1163 https://doi.org/10.1175/1520-0493(2001)129<11
Brown, A., Beare, B., Edwards, J.M., Lock, A., Keogh S.J., Milton, S.F. and D. N. Walters Upgrades to the boundary-layer scheme in the Met Office numerical weather prediction model Boundary-Layer Meteorol, 128, 117-132 https://doi.org/10.1007/s10546-008-9275-0
Walters, D., Baran, A., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and M. Zerroukat The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations Geosci. Model Dev. Discuss., in review, 2017. https://doi.org/10.5194/gmd-2017-291
Scientific topic: Deep convection Overview: Properties of the deep convection scheme
Description:Deep convection is based on the Gregory Rowntree (1990) scheme with modifications.
Citations:
Description:Deep convection is based on the Gregory Rowntree (1990) scheme with modifications.
Citations:
Derbyshire, S. H., Maidens, A. V., Milton, S. F., Stratton, R. A. and M. R. Willett Adaptive detrainment in a convective parametrization Q. J. R. Meteorol. Soc. 137: 1856-1871 https://doi.org/10.1002/qj.875
Gregory 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. n/a
Scientific topic: Shallow convection Overview: Properties of the shallow convection scheme
Description:Shallow convection is based on the Gregory Rowntree (1990) scheme with modifications.
Citations:
Description:Shallow convection is based on the Gregory Rowntree (1990) scheme with modifications.
Citations:
Derbyshire, S. H., Maidens, A. V., Milton, S. F., Stratton, R. A. and M. R. Willett Adaptive detrainment in a convective parametrization Q. J. R. Meteorol. Soc. 137: 1856-1871 https://doi.org/10.1002/qj.875
Gregory 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. n/a
Scientific topic: Microphysics precipitation Overview: Large Scale Cloud Microphysics and Precipitation
Description: Based on Wilson and Ballard (1999) with significant additions. Calculates transfers between liquid, ice and vapour allowing for mixed-phase and with assumed particle-size distributions for the liquid and ice, and size-dependent fall speeds. Cloud inhomogeneity is taken into account when calculating autoconversion and accretion. Size distribution for rain is based on Abel and Boutle (2012) and for snow on Field et al., 2007.
Citations:
Description: Based on Wilson and Ballard (1999) with significant additions. Calculates transfers between liquid, ice and vapour allowing for mixed-phase and with assumed particle-size distributions for the liquid and ice, and size-dependent fall speeds. Cloud inhomogeneity is taken into account when calculating autoconversion and accretion. Size distribution for rain is based on Abel and Boutle (2012) and for snow on Field et al., 2007.
Citations:
Wilson 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. n/a
Field, P. R., Heymsfield, A. J., and A. Bansemer Snow Size Distribution Parameterization for Midlatitude and Tropical Ice Clouds J. Atmos. Sci., 64, 4346-4365 https://doi.org/10.1175/2007JAS2344.1, 2007.
Abel S.J. and Boutle I. A. An improved representation of the raindrop size distribution for single-moment microphysics schemes. Q. J. R. Meteorol. Soc., 138, 2151-2162 10.1002/qj.1949
Subtopics:
Scientific topic: Large scale precipitation Overview: Properties of the large scale precipitation scheme
Description:Based on Wilson and Ballard (1999) with significant additions. Calculates transfers between liquid, ice and vapour allowing for mixed-phase and with assumed particle-size distributions for the liquid and ice, and size-dependent fall speeds. Cloud inhomogeneity is taken into account when calculating autoconversion and accretion. Size distribution for rain is based on Abel and Boutle (2012) and for snow on Field et al., 2007.
Description:Based on Wilson and Ballard (1999) with significant additions. Calculates transfers between liquid, ice and vapour allowing for mixed-phase and with assumed particle-size distributions for the liquid and ice, and size-dependent fall speeds. Cloud inhomogeneity is taken into account when calculating autoconversion and accretion. Size distribution for rain is based on Abel and Boutle (2012) and for snow on Field et al., 2007.
Scientific topic: Large scale cloud microphysics Overview: Properties of the large scale cloud microphysics scheme
Description:Based on Wilson and Ballard (1999) with significant additions. Calculates transfers between liquid, ice and vapour allowing for mixed-phase and with assumed particle-size distributions for the liquid and ice, and size-dependent fall speeds. Cloud inhomogeneity is taken into account when calculating autoconversion and accretion. Size distribution for rain is based on Abel and Boutle (2012) and for snow on Field et al., 2007.
Description:Based on Wilson and Ballard (1999) with significant additions. Calculates transfers between liquid, ice and vapour allowing for mixed-phase and with assumed particle-size distributions for the liquid and ice, and size-dependent fall speeds. Cloud inhomogeneity is taken into account when calculating autoconversion and accretion. Size distribution for rain is based on Abel and Boutle (2012) and for snow on Field et al., 2007.
Scientific topic: Cloud scheme Overview: Characteristics of the cloud scheme
Description: The parametrisation used is the prognostic cloud fraction and prognostic condensate (PC2) scheme (Wilson et al., 2008a, b) along with the cloud erosion parametrisation described by Morcrette (2012) and critical relative humidity parametrisation described in Van Weverberg et al. (2016). PC2 uses three prognostic variables for water mixing ratio – vapour, liquid and ice – and a further three prognostic variables for cloud fraction: liquid, ice and mixed-phase. Cloud inhomogeneity is represented in the radiation and in warm rain microphysics using regime-dependent inhomogeneity.
Citations:
Description: The parametrisation used is the prognostic cloud fraction and prognostic condensate (PC2) scheme (Wilson et al., 2008a, b) along with the cloud erosion parametrisation described by Morcrette (2012) and critical relative humidity parametrisation described in Van Weverberg et al. (2016). PC2 uses three prognostic variables for water mixing ratio – vapour, liquid and ice – and a further three prognostic variables for cloud fraction: liquid, ice and mixed-phase. Cloud inhomogeneity is represented in the radiation and in warm rain microphysics using regime-dependent inhomogeneity.
Citations:
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D. and C. J. Morcrette (2008) A prognostic cloud fraction and condensation scheme. I: Scheme description Q.J.R. Meteorol. Soc., 134: 2093–2107 n/a
Wilson, D. R., Bushell, Andrew. C., Kerr-Munslow, A. M., Price, J. D., Morcrette, C. J. and A. Bodas-Salcedo (2008) PC2: A prognostic cloud fraction and condensation scheme. II: Climate model simulations Q.J.R. Meteorol. Soc., 134: 2109–2125 n/a
Morcrette, C. J. Improvements to a prognostic cloud scheme through changes to its cloud erosion parametrization Atmos. Sci. Let., 13, 95-102 10.1002/asl.374, 2012
Van Weverberg, K., Boutle, I. A., Morcrette, C. J., and R. K. Newsom Towards retrieving critical relative humidity from ground-based remote-sensing observations Q. J. R. Meteorol. Soc., 142, 2867-2881 https://doi.org/10.1002/qj.2874, 2016.
Subtopics:
Scientific topic: Optical cloud properties Overview: Optical cloud properties
Description:The parametrisation of cloud droplets is described in Edwards and Slingo (1996) using the method of “thick averaging”. Pade fits are used for the variation with effective radius, which is computed from the number of cloud droplets. The parametrisation of ice crystals is described in Baran et al. (2016). Full treatment of scattering is used in both the SW and LW. The sub-grid cloud structure is represented using the Monte Carlo Independent Column Approximation (McICA) as described in Hill et al. (2011), with the parametrisation of sub-gridscale water content variability described in Hill et al. (2015).
Citations:
Description:The parametrisation of cloud droplets is described in Edwards and Slingo (1996) using the method of “thick averaging”. Pade fits are used for the variation with effective radius, which is computed from the number of cloud droplets. The parametrisation of ice crystals is described in Baran et al. (2016). Full treatment of scattering is used in both the SW and LW. The sub-grid cloud structure is represented using the Monte Carlo Independent Column Approximation (McICA) as described in Hill et al. (2011), with the parametrisation of sub-gridscale water content variability described in Hill et al. (2015).
Citations:
Baran, A. J., Hill, P., Walters, D., Hardman, S. C., Furtado, K., Field, P. R., and J. Manners The impact of two coupled cirrus microphysics-radiation parameterizations on the temperature and specific humidity biases in the tropical tropopause layer in a climate model J. Climate, 29, 5299-5316 https://doi.org/10.1175/JCLI-D-15-0821.1, 201
Hill, P. G., Manners, J., and J. C. Petch Reducing noise associated with the Monte Carlo Independent Column Approximation for weather forecasting models Q. J. R. Meteorol. Soc., 137, 219-228 https://doi.org/10.1002/qj.732, 2011.
Edwards, 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 http://dx.doi.org/10.1002/qj.49712253107
Scientific topic: Sub grid scale water distribution Overview: Sub-grid scale water distribution
Description:Cloud water is derived from saturation adjustment. Droplet number concentration is a function of aerosol number, calculated by UKCA-activate (West et al., 2014). Droplet number affects radiation, utilising the shape function of Liu et al. (2008), and autoconversion (Khairoutdinov and Kogan, 2000).
Citations:
Description:Cloud water is derived from saturation adjustment. Droplet number concentration is a function of aerosol number, calculated by UKCA-activate (West et al., 2014). Droplet number affects radiation, utilising the shape function of Liu et al. (2008), and autoconversion (Khairoutdinov and Kogan, 2000).
Citations:
West R.E.L, Stier P., Jones, A., Johnson, C. E., Mann, G. W., Bellouin, N., Partridge, D. G., and Z. Kipling The importance of vertical velocity variability for estimates of the indirect aerosol effects Atmospheric Chemistry and Physics, 14, 6369-6393 doi:10.5194/acp-14-6369-2014, https://www.atm
Yangang Liu, Daum, P. H., Huan Guo and Yiran Peng Dispersion bias, dispersion effect, and the aerosol-cloud conundrum Environmental Research Letters, Volume 3, 045021, 8pp doi:10.1088/1748-9326/3/4/045021
Khairoutdinov, M. and Kogan, Y. A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus Mon. Weather Rev., 128, 229-243 https://doi.org/10.1175/1520-0493(2000)128 2.
Scientific topic: Sub grid scale ice distribution Overview: Sub-grid scale ice distribution
Description:Cloud ice snow is represented by a single frozen water species. Field et al. (2007) and mass-diameter relations of Cotton et al. (2013). Microphysical process rates obtained using moment-prediction equations which depend on temperature and ice water content. A consistent particle size distribution uses a sum of exponential and gamma function. Fall speed calculated according to Furtado (2016).
Citations:
Description:Cloud ice snow is represented by a single frozen water species. Field et al. (2007) and mass-diameter relations of Cotton et al. (2013). Microphysical process rates obtained using moment-prediction equations which depend on temperature and ice water content. A consistent particle size distribution uses a sum of exponential and gamma function. Fall speed calculated according to Furtado (2016).
Citations:
Field, P. R., Heymsfield, A. J., and A. Bansemer Snow Size Distribution Parameterization for Midlatitude and Tropical Ice Clouds J. Atmos. Sci., 64, 4346-4365 https://doi.org/10.1175/2007JAS2344.1, 2007.
Cotton, R. J., Field, P. R., Ulanowski, Z., Kaye, P. H., Hirst, E., Greenaway, R. S., Crawford, I., Crosier, J., and J. Dorsey The effective density of small ice particles obtained from in situ aircraft observations of mid-latitude cirrus Q. J. R. Meteorol. Soc., 139, 1923-1934 https://doi.org/10.1002/qj.2058
Furtado, K., Field, P. R., Boutle, I. A., Morcrette, C. J., and J. M. Wilkinson A physically based subgrid parameterization for the production and maintenance of mixed-phase clouds in a general circulation model, J. Atmos. Sci., 73, 279-291 https://doi.org/10.1175/JAS-D-15- 0021.1
Scientific topic: Observation simulation Overview: Characteristics of observation simulation
Description: The Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) simulates observational datasets from model variables. Several simulators are included in COSP. The ones relevant for CMIP6 are: ISCCP cloud products, CALIPSO lidar forward model and CALIPSO/GOCCP cloud products, CloudSat radar forward model, MISR cloud products, and MODIS cloud products. COSP is a stand-alone software, documented in Bodas-Salcedo et al. (2011) and Swales et al. (2018).
Citations:
Description: The Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) simulates observational datasets from model variables. Several simulators are included in COSP. The ones relevant for CMIP6 are: ISCCP cloud products, CALIPSO lidar forward model and CALIPSO/GOCCP cloud products, CloudSat radar forward model, MISR cloud products, and MODIS cloud products. COSP is a stand-alone software, documented in Bodas-Salcedo et al. (2011) and Swales et al. (2018).
Citations:
Bodas-Salcedo, A. et al. (2011) COSP: satellite simulation software for model assessment. Bull. Am. Meteorol. Soc. submitted, https://doi.org/10.1175/2011BAMS2856.1
Swales, D. J., Pincus, R. and A. Bodas-Salcedo Cloud Feedback Model Intercomparison Project Observational Simulator Package: version 2 Geosci. Model Devel., 11, 77-81 10.5194/gmd-11-77-2018.
Subtopics:
Scientific topic: Isscp attributes Overview: ISSCP Characteristics
Description:ISCCP simulator 4.2, as distributed in the COSP package.
Citations:
Description:ISCCP simulator 4.2, as distributed in the COSP package.
Citations:
Klein, S.A., and C. Jakob (1999) Validation and sensitivities of frontal clouds simulated by the ECMWF model. Mon. Weather Rev., 127 (10), 2514-2531 n/a
Webb, 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, 905-922 https://doi.org/10.1007/s003820100157
Scientific topic: Cosp attributes Overview: CFMIP Observational Simulator Package attributes
Description:The Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) simulates observational datasets from model variables. Several simulators are included in COSP. The ones relevant for CMIP6 are: ISCCP cloud products, CALIPSO lidar forward model and CALIPSO/GOCCP cloud products, CloudSat radar forward model, MISR cloud products, and MODIS cloud products. COSP is a stand-alone software, documented in Bodas-Salcedo et al. (2011) and Swales et al. (2018).
Description:The Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) simulates observational datasets from model variables. Several simulators are included in COSP. The ones relevant for CMIP6 are: ISCCP cloud products, CALIPSO lidar forward model and CALIPSO/GOCCP cloud products, CloudSat radar forward model, MISR cloud products, and MODIS cloud products. COSP is a stand-alone software, documented in Bodas-Salcedo et al. (2011) and Swales et al. (2018).
Scientific topic: Radar inputs Overview: Characteristics of the cloud radar simulator
Description:CloudSat radar simulator that is distributed as part of the COSP package. Documented in Haynes et al. (2007).
Citations:
Description:CloudSat radar simulator that is distributed as part of the COSP package. Documented in Haynes et al. (2007).
Citations:
Haynes, J.M (2007) A multipurpose radar simulation package: Quickbeam Bull. Am. Meteorol. Soc., 88 (11), 1723-1727 doi:10.1175/BAMS-88-11-1723.
Scientific topic: Lidar inputs Overview: Characteristics of the cloud lidar simulator
Description:CALIPSO lidar simulator that is distributed as part of the COSP package. Documented in Chepfer et al. (2008) and Cesana and Chepfer (2013).
Citations:
Description:CALIPSO lidar simulator that is distributed as part of the COSP package. Documented in Chepfer et al. (2008) and Cesana and Chepfer (2013).
Citations:
Chepfer, H. et al. (2008) Use of CALIPSO lidar observations to evaluate the cloudiness simulated by a climate model Geophys. Res. Lett., 35, L15 704 https://doi.org/10.1029/2008GL034207
Cesana, G. and H. Chepfer Evaluation of the cloud thermodynamic phase in a climate model using CALIPSO-GOCCP J. Geophys. Res., 118, 7922-7937 10.1002/jgrd.50376
Scientific topic: Gravity waves Overview: Characteristics of the parameterised gravity waves in the atmosphere, whether from orography or other sources
Description: Separate schemes are used for orographic and non-orographic gravity waves, namely Warner and McIntyre (2001) for non-orographic and Palmer, Shutts and Swinbank (1986) for orographic.
Subtopics:
Description: Separate schemes are used for orographic and non-orographic gravity waves, namely Warner and McIntyre (2001) for non-orographic and Palmer, Shutts and Swinbank (1986) for orographic.
Subtopics:
Scientific topic: Orographic gravity waves Overview: Gravity waves generated due to the presence of orography
Description:When Froude number is less than a critical value, a fraction of the flow is assumed to pass around the sides of the orography, and a drag is applied to the flow within this blocked layer. Mountain waves are generated by the remaining proportion of the layer, which the orography pierces through. The acceleration of the flow due to wave stress divergence is exerted at levels where wave breaking is diagnosed.
Citations:
Description:When Froude number is less than a critical value, a fraction of the flow is assumed to pass around the sides of the orography, and a drag is applied to the flow within this blocked layer. Mountain waves are generated by the remaining proportion of the layer, which the orography pierces through. The acceleration of the flow due to wave stress divergence is exerted at levels where wave breaking is diagnosed.
Citations:
Palmer, T. N., Shutts, G. J. and R. Swinbank Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parametrization Quart. J. R. Met. SOC., 112. 474, 1001-1039 https://doi.org/10.1002/qj.49711247406
Scientific topic: Non orographic gravity waves Overview: Gravity waves generated by non-orographic processes.
Description:Waves on scales too small for the model to sustain explicitly are represented by a spectral sub-grid parametrisation scheme (Scaife et al., 2002), which by contributing to the deposited momentum leads to a more realistic tropical quasi-biennial oscillation. The scheme, described in more detail in Walters et al. (2011), represents processes of wave generation, conservative propagation and dissipation by critical-level filtering and wave saturation acting on a vertical wavenumber spectrum of gravity wave fluxes following Warner and McIntyre (2001). Momentum conservation is enforced at launch in the lower troposphere, where isotropic fluxes guarantee zero net momentum, and by imposing a condition of zero vertical wave flux at the model’s upper boundary. In between, momentum deposition occurs in each layer where reduced integrated flux results from erosion of the launch spectrum, after transformation by conservative propagation, to match the locally evaluated saturation spectrum. See Walters et al. (2011) for more detail.
Citations:
Description:Waves on scales too small for the model to sustain explicitly are represented by a spectral sub-grid parametrisation scheme (Scaife et al., 2002), which by contributing to the deposited momentum leads to a more realistic tropical quasi-biennial oscillation. The scheme, described in more detail in Walters et al. (2011), represents processes of wave generation, conservative propagation and dissipation by critical-level filtering and wave saturation acting on a vertical wavenumber spectrum of gravity wave fluxes following Warner and McIntyre (2001). Momentum conservation is enforced at launch in the lower troposphere, where isotropic fluxes guarantee zero net momentum, and by imposing a condition of zero vertical wave flux at the model’s upper boundary. In between, momentum deposition occurs in each layer where reduced integrated flux results from erosion of the launch spectrum, after transformation by conservative propagation, to match the locally evaluated saturation spectrum. See Walters et al. (2011) for more detail.
Citations:
Walters, D. N., Best, M. J., Bushell, A. C., Copsey, D., Edwards, J. M., Falloon, P. D., Harris, C. M., Lock, A. P., Manners, J. C., Morcrette, C. J., Roberts, M. J., Stratton, R. A., S. Webster, J. M. W., Willett, M. R., Boutle, I. A., Earnshaw, P. D., Hill, P. G., MacLachlan, C., Martin, G. M., Moufouma-Okia, W., Palmer, M. D., Petch, J. C., Rooney, G. G., Scaife, A. A., and K. D. Williams The Met Office Unified Model Global Atmosphere 3.0/3.1 and JULES Global Land 3.0/3.1 configurations Geosci. Model Dev., 4, 919-941 https://doi.org/10.5194/gmd- 4-919-2011
Warner, C. D. and McIntyre, M. E. An ultra-simple spectral parameterization for non-orographic gravity waves J. Atmos. Sci., 58, 1837-1857 https://doi.org/10.1175/1520-0469(2001)058<18
Scaife, A. A., N. Butchart, C. D. Warner and R. Swinbank (2002) Impact of a spectral gravity wave parameterization on the stratosphere in the Met Office Unified Model. J. Atmos. Sci., 59, 1473–1489. n/a
Scientific topic: Natural forcing Overview: Natural forcing: solar and volcanic.
Description: Covers orbital parameters, solar constant, solar pathways (SW radiation only) and the treatment of volcanoes. Variations in solar insolation have no impact on model ozone.
Subtopics:
Description: Covers orbital parameters, solar constant, solar pathways (SW radiation only) and the treatment of volcanoes. Variations in solar insolation have no impact on model ozone.
Subtopics:
Scientific topic: Solar pathways Overview: Pathways for solar forcing of the atmosphere
Description:The model takes account of SW radiation only.
Description:The model takes account of SW radiation only.
Scientific topic: Solar constant Overview: Solar constant and top of atmosphere insolation characteristics
Description:Transient solar forcing is applied using the data of Matthes et al. (2017), including temporal variability of the solar constant and spectral distribution.
Citations:
Description:Transient solar forcing is applied using the data of Matthes et al. (2017), including temporal variability of the solar constant and spectral distribution.
Citations:
Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretzschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A. C., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and S. Versick Solar forcing for CMIP6 (v3.2) Geosci. Model Dev., 10, 2247-2302 https://doi.org/10.5194/gmd-10-2247-2017
Scientific topic: Orbital parameters Overview: Orbital parameters and top of atmosphere insolation characteristics
Description:For CMIP6-DECK and all CMIP6 MIPs except PMIP, orbital parameters are fixed at epoch J2000, using parameters recommended by NASA-JPL (http://ssd.jpl.nasa.gov/elem_planets.html). Year length and time of perihelion are adjusted for the model’s 360-day calendar. For PMIP experiments, the equations of Berger (1978) are used to calculate the orbital parameters.
Citations:
Description:For CMIP6-DECK and all CMIP6 MIPs except PMIP, orbital parameters are fixed at epoch J2000, using parameters recommended by NASA-JPL (http://ssd.jpl.nasa.gov/elem_planets.html). Year length and time of perihelion are adjusted for the model’s 360-day calendar. For PMIP experiments, the equations of Berger (1978) are used to calculate the orbital parameters.
Citations:
Berger, A. Long-term variations of daily insolation and Quaternary climatic changes J. Atmos. Sci., 35, 2362-2367 n/a
Scientific topic: Insolation ozone Overview: Impact of solar insolation on stratospheric ozone
Description:Variations in solar insolation have no impact on model ozone.
Description:Variations in solar insolation have no impact on model ozone.
Scientific topic: Volcanoes treatment Overview: Characteristics and treatment of volcanic forcing in the atmosphere
Description:For stratospheric volcanic aerosol, the radiation scheme is given the temporally, vertically and meridionally varying optical properties provided in the CMIP6 forcing: extinction, single scattering albedo and asymmetry parameter. In the troposphere, aerosols are simulated interactively based on emissions of primary aerosol and precursor gases. Included in these emissions is a constant background 3D emission of SO2 from continuously outgassing volcanoes (Dentener et al., 2006).
Citations:
Description:For stratospheric volcanic aerosol, the radiation scheme is given the temporally, vertically and meridionally varying optical properties provided in the CMIP6 forcing: extinction, single scattering albedo and asymmetry parameter. In the troposphere, aerosols are simulated interactively based on emissions of primary aerosol and precursor gases. Included in these emissions is a constant background 3D emission of SO2 from continuously outgassing volcanoes (Dentener et al., 2006).
Citations:
Dentener, F., Kinne, S., Bond, T., Boucher, O., Cofala, J., Generoso, S., Ginoux, P., Gong, S., Hoelzemann, J. J., Ito, A., Marelli, L., Penner, J. E., Putaud, J. P., Textor, C., Schulz, M., Van Der Werf, G. R. and J. Wilson Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom Atmos. Chem. Phys., 6, 4321-4344 10.5194/acp-6-4321-2006
Canonical name: seaice
Short name:
Description: Sea ice realm
Overview: Sea ice realm
Grid
Scientific topic: Grid Overview: Sea Ice grid
Description: The sea ice model CICE uses eORCA1, a tripolar grid with poles located in Canada, Russia and Antarctica. It has resolution of roughly 1 degree over most of the world, but latitudinal resolution is higher in the tropics. Ice velocities, forces and stresses are calculated at the corners of grid cells. The model has four vertical layers of ice, equally-spaced, and one vertical layer of snow which is used in thermodynamic calculations only if the snow is greater than 10 cm thick.
Subtopics:
Description: The sea ice model CICE uses eORCA1, a tripolar grid with poles located in Canada, Russia and Antarctica. It has resolution of roughly 1 degree over most of the world, but latitudinal resolution is higher in the tropics. Ice velocities, forces and stresses are calculated at the corners of grid cells. The model has four vertical layers of ice, equally-spaced, and one vertical layer of snow which is used in thermodynamic calculations only if the snow is greater than 10 cm thick.
Subtopics:
Scientific topic: Discretisation Overview: Sea ice discretisation
Description:The sea ice is discretised on the eORCA1 grid in the horizontal (with surface calculations carried out on the N96 atmosphere grid), with four equally-spaced layers and an optional snow layer in the vertical, with equal dynamic and thermodynamic timesteps of 2700 seconds, and with five thickness categories.
Properties:
Description:The sea ice is discretised on the eORCA1 grid in the horizontal (with surface calculations carried out on the N96 atmosphere grid), with four equally-spaced layers and an optional snow layer in the vertical, with equal dynamic and thermodynamic timesteps of 2700 seconds, and with five thickness categories.
Properties:
Description: Sea ice discretisation in the horizontalGrid: Ocean grid
Grid type: Structured grid
Scheme: Incremental remapping
Thermodynamics time step: 2700
Dynamics time step: 2700
Additional details: nil:inapplicable
Description: Sea ice vertical propertiesLayering: Multi-layers
Number of layers: 4
Additional details: The layers are equally-spaced.
Scientific topic: Seaice categories Overview: What method is used to represent sea ice categories ?
Description:CICE uses a discretised sub gridscale thickness distribution, as described by Thorndike et al. (1975), which is evolved according to ice advection, ice growth and melt, and mechanical ridging.
Citations:
Description:CICE uses a discretised sub gridscale thickness distribution, as described by Thorndike et al. (1975), which is evolved according to ice advection, ice growth and melt, and mechanical ridging.
Citations:
Thorndike, A. S., D. A. Rothrock, G. A. Maykut and R. Colony (1975) The thickness distribution of sea ice Journal of Geophysical Research, 80, 4501-4513. n/a
Scientific topic: Snow on seaice Overview: Snow on sea ice details
Description:Snow on sea ice is modelled per category. For thermodynamic purposes its area fraction is equal to the sea ice area fraction in its category, and it becomes thermodynamically active at a thickness of 10 cm. For radiative purposes, its area fraction is parameterised from its thickness.
Description:Snow on sea ice is modelled per category. For thermodynamic purposes its area fraction is equal to the sea ice area fraction in its category, and it becomes thermodynamically active at a thickness of 10 cm. For radiative purposes, its area fraction is parameterised from its thickness.
Realm’s Key Properties
Scientific topic: Key properties Overview: Sea Ice key properties
Description: Information on key assumptions made in the sea ice model, including conserved quantities, resolution and tuning.
Subtopics:
Description: Information on key assumptions made in the sea ice model, including conserved quantities, resolution and tuning.
Subtopics:
Scientific topic: Variables Overview: List of prognostic variable in the sea ice model.
Description:Identifies the prognostic variables in the sea ice model.
Description:Identifies the prognostic variables in the sea ice model.
Scientific topic: Seawater properties Overview: Properties of seawater relevant to sea ice
Description:Most properties of seawater used to calculate the formation or melt of sea ice are located in the ocean model, NEMO.
Description:Most properties of seawater used to calculate the formation or melt of sea ice are located in the ocean model, NEMO.
Scientific topic: Resolution Overview: Resolution of the sea ice grid
Description:The eORCA1 grid, on which the ice state and subsurface variables are provided, has a resolution of approximately 1 degree in most places, although latitudinal resolution rises to 1.33 degrees in the tropics. In the Arctic the grid becomes irregular with respect to latitude and longitude, and has a resolution of approximately 50 km. The N96 grid, on which the ice surface variables are provided, has a longitudinal resolution of 1.875 degrees and latitudinal resolution of 1.25 degrees.
Description:The eORCA1 grid, on which the ice state and subsurface variables are provided, has a resolution of approximately 1 degree in most places, although latitudinal resolution rises to 1.33 degrees in the tropics. In the Arctic the grid becomes irregular with respect to latitude and longitude, and has a resolution of approximately 50 km. The N96 grid, on which the ice surface variables are provided, has a longitudinal resolution of 1.875 degrees and latitudinal resolution of 1.25 degrees.
Scientific topic: Tuning applied Overview: Tuning applied to sea ice model component
Description:The objective of the tuning was to simulate seasonal cycles of ice extent and ice volume in the present-day control simulation (using forcing from the year 2000) which were entirely within 20% of HadISST.2 1990-2009 (Titchner and Rayner, 2014; Arctic and Antarctic) and PIOMAS 1990-2009 (Schweiger et al, 2011; Arctic only). The tuning was implemented by varying three parameters within observational constraints: bare ice albedo, snow albedo and basal drag. Due to differences in oceanic heat transport in the different model configurations, snow albedo was tuned to different values in each, to enable realistic extent and volume simulations. For HadGEM3-GC31-LL visible snow albedo = 0.96 and near-IR = 0.68.
Citations:
Description:The objective of the tuning was to simulate seasonal cycles of ice extent and ice volume in the present-day control simulation (using forcing from the year 2000) which were entirely within 20% of HadISST.2 1990-2009 (Titchner and Rayner, 2014; Arctic and Antarctic) and PIOMAS 1990-2009 (Schweiger et al, 2011; Arctic only). The tuning was implemented by varying three parameters within observational constraints: bare ice albedo, snow albedo and basal drag. Due to differences in oceanic heat transport in the different model configurations, snow albedo was tuned to different values in each, to enable realistic extent and volume simulations. For HadGEM3-GC31-LL visible snow albedo = 0.96 and near-IR = 0.68.
Citations:
Schweiger, A., R. Lindsay, J. Zhang, M. Steele, H. Stern Uncertainty in modeled arctic sea ice volume J. Geophys. Res., 116, C00D06 doi:10.1029/2011JC007084
Titchner, H. A., and N. A. Rayner The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations J. Geophys. Res. Atmos., 119, 2864-2889 doi: 10.1002/2013JD020316
Laxon, S. W., Giles, K. A., Ridout, A. L., Wingham, D. J. Willatt, R., Cullen, R., Kwok, R., Schweiger, A., Zhang, J., Haas, C.,Hendricks, S., Krishfield, R., Kurtz, N., Farrell, S. and M. Davidson CryoSat-2 estimates of Arctic sea ice thickness and volume Geophysical Research Letters, 40, 732-737 doi:10.1002/grl.50193
Scientific topic: Assumptions Overview: Assumptions made in the sea ice model
Description:Sea ice is modelled as a continuum; salinity is uniform in the horizontal; for the purposes of thermodynamics, snow covers either all or none of the ice present in a category; snow has a constant density and conductivity; a constant floe diameter of 200 m is used in lateral melt calculations.
Description:Sea ice is modelled as a continuum; salinity is uniform in the horizontal; for the purposes of thermodynamics, snow covers either all or none of the ice present in a category; snow has a constant density and conductivity; a constant floe diameter of 200 m is used in lateral melt calculations.
Scientific topic: Conservation Overview: Conservation in the sea ice component
Description:Energy and mass of sea ice are conserved by the model. Salt is not conserved. The incremental remapping scheme conserves energy and mass quantities under advection. Energy is conserved in the thermodynamic scheme to a maximum error of 1e-5 Wm-2 per grid cell by iterating the scheme until the error falls below this value.
Description:Energy and mass of sea ice are conserved by the model. Salt is not conserved. The incremental remapping scheme conserves energy and mass quantities under advection. Energy is conserved in the thermodynamic scheme to a maximum error of 1e-5 Wm-2 per grid cell by iterating the scheme until the error falls below this value.
Scientific topic: Key parameter values Overview: Values of key parameters
Description:The key parameters values specified include ice strength, snow conductivity and minimum ice thickness.
Description:The key parameters values specified include ice strength, snow conductivity and minimum ice thickness.
Realm’s Processes
Scientific topic: Dynamics Overview: Sea Ice Dynamics
Description: The ice dynamics are solved by integrating a two-dimensional simplification of the momentum equation to obtain ice velocities. The five forces which affect the sea ice in this equation are: atmosphere-ice stress, ocean-ice stress, Coriolis force, internal ice stress and sea surface tilt. The internal ice stress is calculated using the elastic-viscous-plastic formulation of Hunke (1997).
Citations:
Description: The ice dynamics are solved by integrating a two-dimensional simplification of the momentum equation to obtain ice velocities. The five forces which affect the sea ice in this equation are: atmosphere-ice stress, ocean-ice stress, Coriolis force, internal ice stress and sea surface tilt. The internal ice stress is calculated using the elastic-viscous-plastic formulation of Hunke (1997).
Citations:
Hunke E., and J. Dukowicz (1997) An elastic-viscous-plastic model for sea-ice dynamics.. Journal of Physical Oceanography, 27, 1849-1867. n/a
Scientific topic: Thermodynamics Overview: Sea Ice Thermodynamics
Description: The sea ice thermodynamics scheme is based on the energy-conserving method of Bitz and Lipscomb (1999), with four sea ice layers and optionally one snow layer. Conductivity and specific heat capacity are allowed to vary depending on temperature and salinity (the latter being a constant, horizontally-uniform prescribed profile). Unlike in Bitz and Lipscomb (1999), the surface variables (e.g. surface temperature, surface fluxes) are calculated separately in the surface exchange scheme. Ice temperature and effective conductivity form the lower boundary condition for the surface exchange, while top conductive flux, sublimation flux and top melting flux are calculated by the surface exchange and act as forcing for the sea ice thermodynamics. More details can be found in West et al (2016). In situations of very thin ice, or of very cold ice occurring in small concentrations, conductive flux is transferred directly to the ice base to preserve the thermodynamic solver, as described in Ridley et al. (2018).
Citations:
Description: The sea ice thermodynamics scheme is based on the energy-conserving method of Bitz and Lipscomb (1999), with four sea ice layers and optionally one snow layer. Conductivity and specific heat capacity are allowed to vary depending on temperature and salinity (the latter being a constant, horizontally-uniform prescribed profile). Unlike in Bitz and Lipscomb (1999), the surface variables (e.g. surface temperature, surface fluxes) are calculated separately in the surface exchange scheme. Ice temperature and effective conductivity form the lower boundary condition for the surface exchange, while top conductive flux, sublimation flux and top melting flux are calculated by the surface exchange and act as forcing for the sea ice thermodynamics. More details can be found in West et al (2016). In situations of very thin ice, or of very cold ice occurring in small concentrations, conductive flux is transferred directly to the ice base to preserve the thermodynamic solver, as described in Ridley et al. (2018).
Citations:
Bitz, C. M. and Lipscomb, W. H. An energy-conserving thermodynamic sea ice model for climate study J. Geophys. Res.-Oceans, 104:15669-15677 n/a
Ridley, J. K., Blockley, E. W., Keen, A. B., Rae., J. G. L., West, A. E. and Schroeder, D. The sea ice model component of HadGEM3-GC3.1, Geosci. Model Dev., 11, 713-723 https://doi.org/10.5194/gmd-11-713-2018
West, A. E, McLaren, A. J., Hewitt, H. T. and Best, M. J. The location of the thermodynamic atmosphere-ice interface in fully coupled models – a case study using JULES and CICE Geosci. Mod. Dev., 9, 1125-1141 https://doi.org/10.5194/gmd-9-1125-2016
Subtopics:
Scientific topic: Energy Overview: Processes related to energy in sea ice thermodynamics
Description:Energy is accounted in CICE using sea ice enthalpy, the energy required to bring a unit volume of sea ice (or snow) to the melting point. Enthalpy is treated as a tracer variable and is remapped during sea ice advection with all other such variables; during thermodynamic growth and melt enthalpy is remapped between layers as the boundaries shift, and between categories as required. During sensible ice heating or cooling energy is conserved by an iterative solver to within 10^-5 Wm-2.
Citations:
Description:Energy is accounted in CICE using sea ice enthalpy, the energy required to bring a unit volume of sea ice (or snow) to the melting point. Enthalpy is treated as a tracer variable and is remapped during sea ice advection with all other such variables; during thermodynamic growth and melt enthalpy is remapped between layers as the boundaries shift, and between categories as required. During sensible ice heating or cooling energy is conserved by an iterative solver to within 10^-5 Wm-2.
Citations:
Bitz, C. M. and Lipscomb, W. H. An energy-conserving thermodynamic sea ice model for climate study J. Geophys. Res.-Oceans, 104:15669-15677 n/a
Scientific topic: Mass Overview: Processes related to mass in sea ice thermodynamics
Description:Ice and snow are assumed to be of constant density, hence ice and snow mass are directly related to volume. Volume is conserved during advection using incremental remapping. It is also conserved during ridging. Processes which can change ice and snow mass are: top ice melting, basal ice melting, lateral ice melting, top snow melting, congelation ice growth, new ice growth (also known as frazil ice growth), snowfall, and net sublimation. In addition, snow mass can be converted to ice mass by snow-ice formation.
Citations:
Description:Ice and snow are assumed to be of constant density, hence ice and snow mass are directly related to volume. Volume is conserved during advection using incremental remapping. It is also conserved during ridging. Processes which can change ice and snow mass are: top ice melting, basal ice melting, lateral ice melting, top snow melting, congelation ice growth, new ice growth (also known as frazil ice growth), snowfall, and net sublimation. In addition, snow mass can be converted to ice mass by snow-ice formation.
Citations:
Steele, M. Sea Ice Melting and Floe Geometry in a Simple Ice-Ocean Model Journal of Geophysical Research, 97, C11, 17,729-17,738 n/a
Scientific topic: Salt Overview: Processes related to salt in sea ice thermodynamics.
Description:Ice salinity is used in the calculation of ice conductivity and heat capacity, as specified by Bitz and Lipscomb (1999). The ice salinity used in the thermodynamic calculations is constant and horizontally uniform, but varies in the vertical. A different constant salinity, 8, is used to calculate salt flux to and from the ocean during ice growth and melt.
Citations:
Description:Ice salinity is used in the calculation of ice conductivity and heat capacity, as specified by Bitz and Lipscomb (1999). The ice salinity used in the thermodynamic calculations is constant and horizontally uniform, but varies in the vertical. A different constant salinity, 8, is used to calculate salt flux to and from the ocean during ice growth and melt.
Citations:
Bitz, C. M. and Lipscomb, W. H. An energy-conserving thermodynamic sea ice model for climate study J. Geophys. Res.-Oceans, 104:15669-15677 n/a
Properties:
Description: Mass transport of saltSalinity type: Constant
Constant salinity value: 8
Additional details: nil:inapplicable
Description: Salt thermodynamicsSalinity type: Prescribed salinity profile
Constant salinity value: nil:inapplicable
Additional details: salinity = saltmax/2 * (1 – cos(pi * layer number – 0.5 * (ns/(ms + depth)))) where saltmax, ns, ms = 9.6, 0.407, 0.573 respectively, where layer varies from 1 to 4.
Scientific topic: Ice thickness distribution Overview: Ice thickness distribution details.
Description:The sea ice thickness distribution is represented explicitly using five thickness categories.
Description:The sea ice thickness distribution is represented explicitly using five thickness categories.
Scientific topic: Melt ponds Overview: Characteristics of melt ponds.
Description:Only the impact of melt ponds on surface albedo is included; the impacts on freshwater flux and on thermodynamics are neglected. The melt pond area fraction and depth for ice in each thickness category are calculated with the CICE topographic melt pond formulation (Flocco et al., 2010, 2012; Hunke et al., 2015). Where the pond depth on ice of a particular thickness category is shallower than 4 mm, the ponds are assumed to have no impact on albedo, and the albedo of such ponded ice is simply equal to that of bare ice. Where the pond depth is greater than 20 cm, the underlying bare ice is assumed to have no impact, and the ponded ice albedo is assumed to be equal to that of the melt pond. For ponds deeper than 4 mm but shallower than 20 cm, the underlying bare ice is assumed to have an impact on the total pond albedo, and the bare ice and melt pond albedos are combined linearly as described by Ridley et al. (2018).
Citations:
Description:Only the impact of melt ponds on surface albedo is included; the impacts on freshwater flux and on thermodynamics are neglected. The melt pond area fraction and depth for ice in each thickness category are calculated with the CICE topographic melt pond formulation (Flocco et al., 2010, 2012; Hunke et al., 2015). Where the pond depth on ice of a particular thickness category is shallower than 4 mm, the ponds are assumed to have no impact on albedo, and the albedo of such ponded ice is simply equal to that of bare ice. Where the pond depth is greater than 20 cm, the underlying bare ice is assumed to have no impact, and the ponded ice albedo is assumed to be equal to that of the melt pond. For ponds deeper than 4 mm but shallower than 20 cm, the underlying bare ice is assumed to have an impact on the total pond albedo, and the bare ice and melt pond albedos are combined linearly as described by Ridley et al. (2018).
Citations:
Ridley, J. K., Blockley, E. W., Keen, A. B., Rae., J. G. L., West, A. E. and Schroeder, D. The sea ice model component of HadGEM3-GC3.1, Geosci. Model Dev., 11, 713-723 https://doi.org/10.5194/gmd-11-713-2018
Flocco, D., D.L. Feltham, and A.K. Turner Incorporation of a physically based melt pond scheme into the sea ice component of a climate model J. Geophys. Res., 115, C08012 doi:10.1029/2009JC005568
Flocco, D., Schroeder, D., Feltham, D. L. and Hunke, E. C. Impact of melt ponds on Arctic sea ice simulations from 1990 to 2007 J. Geophys. Res., 117, C09032 doi:10.1029/2012JC008195.
Hunke, E.C. W.H. Lipscomb, A.K. Turner, N. Jeffery, and Elliott, S. CICE: the Los Alamos Sea Ice Model Documentation and Software User’s Manual Version 5.1, LA-CC-06-012, Los Alamos National Laboratory, N.M. n/a
Scientific topic: Snow processes Overview: Thermodynamic processes in snow on sea ice
Description:Snow becomes thermodynamically active when it reaches a thickness of 10 cm; below this thickness, it is ignored by the thermodynamics scheme. For the purposes of thermodynamics, snow is assumed to cover each thickness category to a uniform thickness. Density and conductivity of snow are assumed to be constant, and heat capacity is that of fresh ice. Only a single layer of snow is permitted by the thermodynamics scheme.
Description:Snow becomes thermodynamically active when it reaches a thickness of 10 cm; below this thickness, it is ignored by the thermodynamics scheme. For the purposes of thermodynamics, snow is assumed to cover each thickness category to a uniform thickness. Density and conductivity of snow are assumed to be constant, and heat capacity is that of fresh ice. Only a single layer of snow is permitted by the thermodynamics scheme.
Scientific topic: Ice floe size distribution Overview: Ice floe-size distribution details.
Description:The floe size is specified as a single parameter, 300 m.
Description:The floe size is specified as a single parameter, 300 m.
Scientific topic: Radiative processes Overview: Sea Ice Radiative Processes
Description: Radiative processes at the surface are handled in the surface exchange scheme using a multi-band albedo scheme based on that used in the CCSM3 model. This has separate albedos for visible (< 700 nm) and near-infrared (> 700 nm) wavelengths for both bare ice and snow, and is described in the CICE User’s Manual (Hunke et al., 2015). Penetration of radiation into the ice is not included. A correction is therefore applied to the surface albedo to account for scattering within the ice pack (Semtner, 1976). The impact of surface melt ponds on albedo is included as an addition to the CCSM3 albedo scheme, as described in the Melt Ponds subtopic under Thermodynamics below. Because the impact of melt ponds on albedo has been included explicitly, the reduction in bare ice albedo with increasing temperature, which was intended to account for melt pond formation, is not included. However, the reduction in snow albedo with increasing surface skin temperature, intended to take account of the lower albedo of melting snow, has been retained. The total gridbox albedo of ice in each thickness category is calculated for each of the two wavebands by combining the melt pond, bare ice and snow albedos, weighted by the melt pond and snow fractions. Further details of the scheme and its implementation are given by Ridley et al. (2018).
Citations:
Description: Radiative processes at the surface are handled in the surface exchange scheme using a multi-band albedo scheme based on that used in the CCSM3 model. This has separate albedos for visible (< 700 nm) and near-infrared (> 700 nm) wavelengths for both bare ice and snow, and is described in the CICE User’s Manual (Hunke et al., 2015). Penetration of radiation into the ice is not included. A correction is therefore applied to the surface albedo to account for scattering within the ice pack (Semtner, 1976). The impact of surface melt ponds on albedo is included as an addition to the CCSM3 albedo scheme, as described in the Melt Ponds subtopic under Thermodynamics below. Because the impact of melt ponds on albedo has been included explicitly, the reduction in bare ice albedo with increasing temperature, which was intended to account for melt pond formation, is not included. However, the reduction in snow albedo with increasing surface skin temperature, intended to take account of the lower albedo of melting snow, has been retained. The total gridbox albedo of ice in each thickness category is calculated for each of the two wavebands by combining the melt pond, bare ice and snow albedos, weighted by the melt pond and snow fractions. Further details of the scheme and its implementation are given by Ridley et al. (2018).
Citations:
Hunke, E.C. W.H. Lipscomb, A.K. Turner, N. Jeffery, and Elliott, S. CICE: the Los Alamos Sea Ice Model Documentation and Software User’s Manual Version 5.1, LA-CC-06-012, Los Alamos National Laboratory, N.M. n/a
Ridley, J. K., Blockley, E. W., Keen, A. B., Rae., J. G. L., West, A. E. and Schroeder, D. The sea ice model component of HadGEM3-GC3.1, Geosci. Model Dev., 11, 713-723 https://doi.org/10.5194/gmd-11-713-2018
Semtner A., (1976) A model for the thermodynamic growth of sea ice in numerical investigations of climate.. Journal of Physical Oceanography, 6, 379-389 n/a
Canonical name: ocean
Short name:
Description: Ocean Realm
Overview: Ocean Realm
Grid
Scientific topic: Grid Overview: Ocean grid
Description: The horizontal grid is based on the ORCA tripolar Arakawa C-grid (Madec, 2008). The vertical grid varies in thickness over time (the z* coordinate of Adcroft and Campin, 2004). Cells spanning partial model levels are allowed next to the bathymetry (Barnier et al., 2006).
Citations:
Description: The horizontal grid is based on the ORCA tripolar Arakawa C-grid (Madec, 2008). The vertical grid varies in thickness over time (the z* coordinate of Adcroft and Campin, 2004). Cells spanning partial model levels are allowed next to the bathymetry (Barnier et al., 2006).
Citations:
Madec G. (2008) NEMO ocean engine Note du Pole de modélisation, Institut Pierre-Simon Laplace (IPSL), France, No 27 ISSN No 1288-1619 n/a
Barnier, B., Madec, G., Penduff, T., Molines, J.-M., Treguier, A.-M., Le Sommer, J., Beckmann, A., Biastoch, A., Böning, C., Dengg, J., Derval, C., Durand, E., Gulev, S., Remy, E., Talandier, C., Theetten, S., Maltrud, M., McClean, J., and De Cuevas, B. Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy-permitting resolution. Ocean Dynamics, 56, 543-567. http://dx.doi.org/10.1007/s10236-006-0082-1
Adcroft, A. and Campin, J.-M. Rescaled height coordinates for accurate representation of free-surface flows in ocean circulation models Ocean Modelling, 7, 269 – 284 10.1016/j.ocemod.2003.09.003
Subtopics:
Scientific topic: Discretisation Overview: Type of discretisation scheme in ocean
Description:The horizontal grid is based on the ORCA tripolar Arakawa C-grid (Madec, 2008). The vertical grid varies in thickness over time (the z* coordinate of Adcroft and Campin, 2004). Cells spanning partial model levels are allowed next to the bathymetry (Barnier et al., 2006).
Properties:
Description:The horizontal grid is based on the ORCA tripolar Arakawa C-grid (Madec, 2008). The vertical grid varies in thickness over time (the z* coordinate of Adcroft and Campin, 2004). Cells spanning partial model levels are allowed next to the bathymetry (Barnier et al., 2006).
Properties:
Description: Type of horizontal discretisation scheme in oceanType: Two north poles (ORCA-style)
Scheme: Finite difference / Arakawa C-grid
Staggering: Arakawa C-grid
Description: Properties of vertical discretisation in oceanCoordinates: Z*-coordinate
Partial steps: true
Realm’s Key Properties
Scientific topic: Key properties Overview: Ocean key properties
Description: Key properties provides an overview of the model and summary properties for bathymetry, non-oceanic water, seawater and the software. Sub-topics address conservation, resolution and tuning.
Citations:
Description: Key properties provides an overview of the model and summary properties for bathymetry, non-oceanic water, seawater and the software. Sub-topics address conservation, resolution and tuning.
Citations:
Kuhlbrodt, T., Jones, C. G., Sellar, A., Storkey, D., Blockley, E., Stringer, M., Hill, R., Graham, T., Ridley, J., Blaker, A., Calvert, D., Copsey, D., Ellis, R., Hewitt, H., Hyder, P., Ineson, S., Mulcahy, J., Siahaan, A. and J. Walton. The low-resolution version of HadGEM3 GC3.1: Development and evaluation for global climate Journal of Advances in Modeling Earth Systems (in review) n/a
Storkey, D., Blaker, A. T., Mathiot, P., Megann, A., Aksenov, Y., Blockley, E. W., Calvert, D., Graham, T., Hewitt, H. T., Hyder, P., Kuhlbrodt, T., Rae, J. G. L. and B. Sinha. UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions. Geoscientific Model Development (in review) 10.5194/gmd-2017-263
NOAA ETOPO2v2 NOAA online information n/a
Arndt, J. E., Schenke, H. W., Jakobsson, M., Nitsche, F. O., Buys, G., Goleby, B., Rebesco, M., Bohoyo, F., Hong, J., Black, J., Greku, R., Udintsev, G., Barrios, F., Reynoso-Peralta, W., Taisei, M. and R. Wigley. The International Bathymetric Chart of the Southern Ocean (IBCSO) Version 1.0—A new bathymetric compilation covering circum-Antarctic waters Geophysical Research Letters, 40, 3111-3117 10.1002/grl.50413
Madec G. (2008) NEMO ocean engine Note du Pole de modélisation, Institut Pierre-Simon Laplace (IPSL), France, No 27 ISSN No 1288-1619 n/a
Mathiot, P., Jenkins, A., Harris, C., and G. Madec. Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6 Geoscientific Model Development, 10, 2849-2874 https://doi.org/10.5194/gmd-10-2849-2017
Properties:
Description: Properties of bathymetry in oceanReference dates: Present day
Type: true
Ocean smoothing: The model bathymetry is based on the ETOPO2 dataset (NOAA, 2006) with bathymetry on the Antarctic shelf based on IBSCO (Arndt et al., 2013). The Antarctic coastline is smoothed to remove single grid point inlets and avoid the spurious accumulation of sea ice related to the different grid of the coupled sea ice model.
Source: ETOPO2, IBSCO
Description: Non oceanic waters treatement in oceanIsolated seas: Caspian Sea as ocean points
River mouth: nil:inapplicable
Description: Physical properties of seawater in oceanEos type: Polynomial EOS-80
Eos functional temp: Potential temperature
Eos functional salt: Practical salinity Sp
Eos functional depth: Depth (meters)
Ocean freezing point: UNESCO 1983
Ocean specific heat: 3991.8679571196
Ocean reference density: 1026
Description: Software properties of ocean codeRepository: http://forge.ipsl.jussieu.fr/nemo/browser/branches/UKMO/dev_r5518_GO6_package
Code version: 3.6 stable
Code languages: Fortran
Subtopics:
Scientific topic: Resolution Overview: Resolution in the ocean grid
Description:The horizontal grid is eORCA1, which is a tripolar Arakawa C-grid (Madec, 2008), with the southern boundary extended from 77S to 85S to permit the modelling of circulation under ice shelves in Antarctica (Mathiot et al., 2017). This has nominal 1 degree resolution (360 x 330 grid points) at the equator decreasing poleward and uses an isotropic Mercator grid between 22N and 67S, with meridional refinement to 1/3 degree in the tropics. Three quasi-isotropic bipolar grids are joined to the Mercator grid; one north of 22N with poles in Siberia and Canada, and two south of 67S in the Weddell Sea and Bellingshausen, Amundsen and Ross Sea sectors. The model has 75 vertical levels which are a double tanh function of depth such that the thickness increases from 1 m near the surface to 200 m at 6000 m. This provides high resolution near the surface for short- to mid-range forecasting purposes, while retaining reasonable resolution at mid-depths for long-term climate studies.
Citations:
Description:The horizontal grid is eORCA1, which is a tripolar Arakawa C-grid (Madec, 2008), with the southern boundary extended from 77S to 85S to permit the modelling of circulation under ice shelves in Antarctica (Mathiot et al., 2017). This has nominal 1 degree resolution (360 x 330 grid points) at the equator decreasing poleward and uses an isotropic Mercator grid between 22N and 67S, with meridional refinement to 1/3 degree in the tropics. Three quasi-isotropic bipolar grids are joined to the Mercator grid; one north of 22N with poles in Siberia and Canada, and two south of 67S in the Weddell Sea and Bellingshausen, Amundsen and Ross Sea sectors. The model has 75 vertical levels which are a double tanh function of depth such that the thickness increases from 1 m near the surface to 200 m at 6000 m. This provides high resolution near the surface for short- to mid-range forecasting purposes, while retaining reasonable resolution at mid-depths for long-term climate studies.
Citations:
Mathiot, P., Jenkins, A., Harris, C., and G. Madec. Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6 Geoscientific Model Development, 10, 2849-2874 https://doi.org/10.5194/gmd-10-2849-2017
Madec G. (2008) NEMO ocean engine Note du Pole de modélisation, Institut Pierre-Simon Laplace (IPSL), France, No 27 ISSN No 1288-1619 n/a
Scientific topic: Tuning applied Overview: Tuning methodology for ocean component
Description:Tuning details covered in coupled model information.
Description:Tuning details covered in coupled model information.
Scientific topic: Conservation Overview: Conservation in the ocean component
Description:The tracer equations are written in flux form and are conservative. The use of a nonlinear free surface (z* vertical coordinate) ensures the conservation of heat and salt. A vector-invariant form of the momentum equations is used with an energy and enstrophy conserving scheme for advection.
Description:The tracer equations are written in flux form and are conservative. The use of a nonlinear free surface (z* vertical coordinate) ensures the conservation of heat and salt. A vector-invariant form of the momentum equations is used with an energy and enstrophy conserving scheme for advection.
Realm’s Processes
Scientific topic: Timestepping framework Overview: Ocean Timestepping Framework
Description: Timestepping of tracers and dynamics uses a leap-frog scheme and Asselin filter with an integration time step of 45 minutes. Vertical diffusion of tracers uses an implicit backward time stepping scheme.
Properties:
Description: Timestepping of tracers and dynamics uses a leap-frog scheme and Asselin filter with an integration time step of 45 minutes. Vertical diffusion of tracers uses an implicit backward time stepping scheme.
Properties:
Description: Baroclinic dynamics in oceanType: Preconditioned conjugate gradient
Scheme: Leap-frog + Asselin filter
Time step: 2700
Description: Barotropic time stepping in oceanSplitting: None
Time step: 2700
Description: Properties of tracers time stepping in oceanScheme: Leap-frog + Asselin filter
Time step: 2700
Description: Vertical physics time stepping in oceanMethod: implicit / backward stepping
Scientific topic: Advection Overview: Ocean advection
Description: Advection of momentum uses a vector-invariant (rotational and irrotational) formulation. The irrotational component is formulated according to Hollingsworth et al. (1983) in order to avoid vertical numerical instabilities. The vorticity term is calculated using the energy and enstrophy conserving scheme of Arakawa and Lamb (1981). Advection of tracers uses the Total Variance Dissipation (TVD) scheme of Zalesak (1979).
Citations:
Description: Advection of momentum uses a vector-invariant (rotational and irrotational) formulation. The irrotational component is formulated according to Hollingsworth et al. (1983) in order to avoid vertical numerical instabilities. The vorticity term is calculated using the energy and enstrophy conserving scheme of Arakawa and Lamb (1981). Advection of tracers uses the Total Variance Dissipation (TVD) scheme of Zalesak (1979).
Citations:
Hollingsworth, A., Kallberg, P., Renner, V., and Burridge, D. M. An internal symmetric computational instability, Quarterly Journal of the Royal Meteorological Society, 109, 417-428 http://dx.doi.org/10.1002/qj.49710946012
Zalesak, S. T. Fully multidimensional flux corrected transport algorithms for fluids J. Comput. Phys., 31, 335-362 http://dx.doi.org/10.1016/0021-9991(79)90051-
Arakawa, A. and Lamb, V. R. A Potential Enstrophy and Energy Conserving Scheme for the Shallow Water Equations Monthly Weather Review, 109, 18-36 http://dx.doi.org/10.1175/1520-0493(1981)109
Subtopics:
Scientific topic: Momentum Overview: Properties of lateral momemtum advection scheme in ocean
Description:Advection of momentum uses a vector-invariant (rotational and irrotational) formulation. The irrotational component is formulated according to Hollingsworth et al. (1983) in order to avoid vertical numerical instabilities. The vorticity term is calculated using the energy and enstrophy conserving scheme of Arakawa and Lamb (1981). Advection of tracers uses the Total Variance Dissipation (TVD) scheme of Zalesak (1979).
Citations:
Description:Advection of momentum uses a vector-invariant (rotational and irrotational) formulation. The irrotational component is formulated according to Hollingsworth et al. (1983) in order to avoid vertical numerical instabilities. The vorticity term is calculated using the energy and enstrophy conserving scheme of Arakawa and Lamb (1981). Advection of tracers uses the Total Variance Dissipation (TVD) scheme of Zalesak (1979).
Citations:
Arakawa, A. and Lamb, V. R. A Potential Enstrophy and Energy Conserving Scheme for the Shallow Water Equations Monthly Weather Review, 109, 18-36 http://dx.doi.org/10.1175/1520-0493(1981)109
Hollingsworth, A., Kallberg, P., Renner, V., and Burridge, D. M. An internal symmetric computational instability, Quarterly Journal of the Royal Meteorological Society, 109, 417-428 http://dx.doi.org/10.1002/qj.49710946012
Scientific topic: Lateral tracers Overview: Properties of lateral tracer advection scheme in ocean
Description:Advection of momentum uses a vector-invariant (rotational and irrotational) formulation. The irrotational component is formulated according to Hollingsworth et al. (1983) in order to avoid vertical numerical instabilities. The vorticity term is calculated using the energy and enstrophy conserving scheme of Arakawa and Lamb (1981). Advection of tracers uses the Total Variance Dissipation (TVD) scheme of Zalesak (1979).
Citations:
Description:Advection of momentum uses a vector-invariant (rotational and irrotational) formulation. The irrotational component is formulated according to Hollingsworth et al. (1983) in order to avoid vertical numerical instabilities. The vorticity term is calculated using the energy and enstrophy conserving scheme of Arakawa and Lamb (1981). Advection of tracers uses the Total Variance Dissipation (TVD) scheme of Zalesak (1979).
Citations:
Zalesak, S. T. Fully multidimensional flux corrected transport algorithms for fluids J. Comput. Phys., 31, 335-362 http://dx.doi.org/10.1016/0021-9991(79)90051-
Scientific topic: Vertical tracers Overview: Properties of vertical tracer advection scheme in ocean
Description:Advection of momentum uses a vector-invariant (rotational and irrotational) formulation. The irrotational component is formulated according to Hollingsworth et al. (1983) in order to avoid vertical numerical instabilities. The vorticity term is calculated using the energy and enstrophy conserving scheme of Arakawa and Lamb (1981). Advection of tracers uses the Total Variance Dissipation (TVD) scheme of Zalesak (1979).
Citations:
Description:Advection of momentum uses a vector-invariant (rotational and irrotational) formulation. The irrotational component is formulated according to Hollingsworth et al. (1983) in order to avoid vertical numerical instabilities. The vorticity term is calculated using the energy and enstrophy conserving scheme of Arakawa and Lamb (1981). Advection of tracers uses the Total Variance Dissipation (TVD) scheme of Zalesak (1979).
Citations:
Zalesak, S. T. Fully multidimensional flux corrected transport algorithms for fluids J. Comput. Phys., 31, 335-362 http://dx.doi.org/10.1016/0021-9991(79)90051-
Scientific topic: Lateral physics Overview: Ocean lateral physics
Description: Lateral diffusion of momentum is on geopotential surfaces and uses a laplacian operator with a coefficient of 2×10^4 m2s-1, reducing linearly with the grid spacing in order to avoid numerical diffusion instabilities and reducing with a hyperbolic profile over depth. Lateral diffusion of tracers is along isoneutral surfaces and uses a laplacian operator with a coefficient of 1000 m2s-1, reducing linearly with the grid spacing. Adiabatic mixing by transient mesoscale eddies is parameterised according to Held and Larichev (1996).
Citations:
Description: Lateral diffusion of momentum is on geopotential surfaces and uses a laplacian operator with a coefficient of 2×10^4 m2s-1, reducing linearly with the grid spacing in order to avoid numerical diffusion instabilities and reducing with a hyperbolic profile over depth. Lateral diffusion of tracers is along isoneutral surfaces and uses a laplacian operator with a coefficient of 1000 m2s-1, reducing linearly with the grid spacing. Adiabatic mixing by transient mesoscale eddies is parameterised according to Held and Larichev (1996).
Citations:
Held, I.M. and Larichev, V. D. A scaling theory for horizontally homogeneous, baroclinically unstable flow on a beta plane Journal of the Atmospheric Sciences, 53, 946-952 doi:10.1175/1520-0469(1996)053<0946:ASTFHH>2.
Subtopics:
Scientific topic: Momentum Overview: Properties of lateral physics for momentum in ocean
Description:Lateral diffusion of momentum is on geopotential surfaces and uses a laplacian operator with a coefficient of 2×10^4 m2s-1, reducing linearly with the grid spacing in order to avoid numerical diffusion instabilities and reducing with a hyperbolic profile over depth. Lateral diffusion of tracers is along isoneutral surfaces and uses a laplacian operator with a coefficient of 1000 m2s-1, reducing linearly with the grid spacing. Adiabatic mixing by transient mesoscale eddies is parameterised according to Held and Larichev (1996).
Properties:
Description:Lateral diffusion of momentum is on geopotential surfaces and uses a laplacian operator with a coefficient of 2×10^4 m2s-1, reducing linearly with the grid spacing in order to avoid numerical diffusion instabilities and reducing with a hyperbolic profile over depth. Lateral diffusion of tracers is along isoneutral surfaces and uses a laplacian operator with a coefficient of 1000 m2s-1, reducing linearly with the grid spacing. Adiabatic mixing by transient mesoscale eddies is parameterised according to Held and Larichev (1996).
Properties:
Description: Properties of eddy viscosity coeff in lateral physics momemtum scheme in the oceanType: Space varying
Constant coefficient: nil:inapplicable
Variable coefficient: 2×10^4 m2/s-1 at equator reducing linearly with grid spacing and with a hyperbolic profile over depth
Coeff background: 0
Coeff backscatter: false
Description: Properties of lateral physics operator for momentum in oceanDirection: Geopotential
Order: Harmonic
Discretisation: Second order
Scientific topic: Tracers Overview: Properties of lateral physics for tracers in ocean
Description:Lateral diffusion of momentum is on geopotential surfaces and uses a laplacian operator with a coefficient of 2×10^4 m2s-1, reducing linearly with the grid spacing in order to avoid numerical diffusion instabilities and reducing with a hyperbolic profile over depth. Lateral diffusion of tracers is along isoneutral surfaces and uses a laplacian operator with a coefficient of 1000 m2s-1, reducing linearly with the grid spacing. Adiabatic mixing by transient mesoscale eddies is parameterised according to Held and Larichev (1996).
Citations:
Description:Lateral diffusion of momentum is on geopotential surfaces and uses a laplacian operator with a coefficient of 2×10^4 m2s-1, reducing linearly with the grid spacing in order to avoid numerical diffusion instabilities and reducing with a hyperbolic profile over depth. Lateral diffusion of tracers is along isoneutral surfaces and uses a laplacian operator with a coefficient of 1000 m2s-1, reducing linearly with the grid spacing. Adiabatic mixing by transient mesoscale eddies is parameterised according to Held and Larichev (1996).
Citations:
Held, I.M. and Larichev, V. D. A scaling theory for horizontally homogeneous, baroclinically unstable flow on a beta plane Journal of the Atmospheric Sciences, 53, 946-952 doi:10.1175/1520-0469(1996)053<0946:ASTFHH>2.
Properties:
Description: Properties of eddy diffusity coeff in lateral physics tracers scheme in the oceanType: Space varying
Constant coefficient: nil:inapplicable
Variable coefficient: 1000 m2/s at equator reducing linearly with the grid spacing
Coeff background: 0
Coeff backscatter: false
Description: Properties of eddy induced velocity (EIV) in lateral physics tracers scheme in the oceanType: HL
Constant val: nil:inapplicable
Flux type: advective
Added diffusivity: none
Description: Properties of lateral physics operator for tracers in oceanDirection: Isoneutral
Order: Harmonic
Discretisation: Second order
Scientific topic: Vertical physics Overview: Ocean Vertical Physics
Description: The vertical mixing of tracers and momentum is parameterised using a modified version of the Gaspar et al. (1990) Turbulent Kinetic Energy (TKE) scheme. Unresolved mixing due to internal wave breaking is represented by a background vertical diffusivity of 1.2×10^-5 m2/s which decreases linearly from 15 degrees latitude to 1.2×10^-6 m2/s at 5 degrees latitude (Gregg et al., 2003), and a globally constant background viscosity of 1.2×10^-4 m2/s. The wave breaking parameterisation of Craig and Banner (1994) is used as the TKE surface boundary condition. Vertical mixing in the boundary layer includes an ad-hoc parameterisation of near-inertial wave breaking (Madec, 2008; Rodgers et al., 2014) with an e-decay vertical length scale increasing sinusoidally from 0.5 m at the equator to 10 m and 30 m at ~13 N and ~40 S respectively (Storkey et al., 2018). Langmuir turbulence is parameterised following Axell (2002). Vertical mixing in the ocean interior includes parameterisations of tidal mixing with a special formulation for the Indonesian Throughflow (Simmons et al., 2004; Koch-Larrouy et al., 2008) and double diffusive mixing (Merryfield et al., 1999). Convection is parameterised as an enhanced vertical diffusivity of 10 m2/s where the density profile is statically unstable.
Citations:
Description: The vertical mixing of tracers and momentum is parameterised using a modified version of the Gaspar et al. (1990) Turbulent Kinetic Energy (TKE) scheme. Unresolved mixing due to internal wave breaking is represented by a background vertical diffusivity of 1.2×10^-5 m2/s which decreases linearly from 15 degrees latitude to 1.2×10^-6 m2/s at 5 degrees latitude (Gregg et al., 2003), and a globally constant background viscosity of 1.2×10^-4 m2/s. The wave breaking parameterisation of Craig and Banner (1994) is used as the TKE surface boundary condition. Vertical mixing in the boundary layer includes an ad-hoc parameterisation of near-inertial wave breaking (Madec, 2008; Rodgers et al., 2014) with an e-decay vertical length scale increasing sinusoidally from 0.5 m at the equator to 10 m and 30 m at ~13 N and ~40 S respectively (Storkey et al., 2018). Langmuir turbulence is parameterised following Axell (2002). Vertical mixing in the ocean interior includes parameterisations of tidal mixing with a special formulation for the Indonesian Throughflow (Simmons et al., 2004; Koch-Larrouy et al., 2008) and double diffusive mixing (Merryfield et al., 1999). Convection is parameterised as an enhanced vertical diffusivity of 10 m2/s where the density profile is statically unstable.
Citations:
Axell, L. B. Wind-driven Internal Waves and Langmuir Circulations in a Numerical Ocean Model of the Southern Baltic Sea J. Geophys. Res., 107, C11, 3204, 20pp doi:10.1029/2001JC000922, 2002.
Craig, P. D. and Banner, M. L. Layer Modelling Wave-Enhanced Turbulence in the Ocean Surface J. Phys. Oceanogr., 24, 2546-2559 n/a
Gaspar, P., Grégoris, Y., and Lefevre, J.-M. A simple eddy kinetic energy model for simulations of the oceanic vertical mixing: tests at Station Papa and long-term upper ocean study site J. Geophys. Res., 95, 16179-16193 doi:10.1029/JC095iC09p16179
Gregg, M. C., Sanford, T. B. and Winkel, D. P. Reduced mixing from the breaking of internal waves in equatorial waters Nature, 422, 513-515 10.1038/nature01507
Koch-Larrouy, A., Madec, G., Blanke, B. and Molcard, R. Water mass transformation along the Indonesian throughflow in an OGCM Ocean Dynam., 58, 289-309 10.1007/s10236-008-0155-4
Madec G. (2008) NEMO ocean engine Note du Pole de modélisation, Institut Pierre-Simon Laplace (IPSL), France, No 27 ISSN No 1288-1619 n/a
Merryfield, W. J., Holloway, G. and Gargett, A. E. A global ocean model with double-diffusive mixing J. Phys. Ocean., 29, 1124-1142 10.1175/1520-0485(1999)029<1124:AGOMWD>2.0.CO
Rodgers, K. B., Aumont, O., Mikaloff Fletcher, S. E., Plancherel, Y., Bopp, L., de Boyer Montégut, C., Iudicone, D., Keeling, R. F., Madec, G. and Wanninkhof, R. Strong sensitivity of Southern Ocean carbon uptake and nutrient cycling to wind stirring Biogeosciences, 11, 4077-4098 10.5194/bg-11-4077-2014
Simmons, H., Jayne, S., Laurent, L. S. and Weaver, A. Tidally driven mixing in a numerical model of the ocean general circulation Ocean Model., 6, 245-263 10.1016/S1463-5003(03)00011-8i
Storkey, D., Blaker, A. T., Mathiot, P., Megann, A., Aksenov, Y., Blockley, E. W., Calvert, D., Graham, T., Hewitt, H. T., Hyder, P., Kuhlbrodt, T., Rae, J. G. L. and B. Sinha. UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions. Geoscientific Model Development (in review) 10.5194/gmd-2017-263
Subtopics:
Scientific topic: Boundary layer mixing Overview: Properties of boundary layer mixing in the ocean (aka mixed layer)
Description:The vertical mixing of tracers and momentum is parameterised using a modified version of the Gaspar et al. (1990) Turbulent Kinetic Energy (TKE) scheme. Unresolved mixing due to internal wave breaking is represented by a background vertical diffusivity of 1.2×10^-5 m2/s which decreases linearly from 15 degrees latitude to 1.2×10^-6 m2/s at 5 degrees latitude (Gregg et al., 2003), and a globally constant background viscosity of 1.2×10^-4 m2/s. The wave breaking parameterisation of Craig and Banner (1994) is used as the TKE surface boundary condition. Vertical mixing in the boundary layer includes an ad-hoc parameterisation of near-inertial wave breaking (Madec, 2008; Rodgers et al., 2014) with an e-decay vertical length scale increasing sinusoidally from 0.5 m at the equator to 10 m and 30 m at ~13 N and ~40 S respectively (Storkey et al., 2018). Langmuir turbulence is parameterised following Axell (2002). Vertical mixing in the ocean interior includes parameterisations of tidal mixing with a special formulation for the Indonesian Throughflow (Simmons et al., 2004; Koch-Larrouy et al., 2008) and double diffusive mixing (Merryfield et al., 1999). Convection is parameterised as an enhanced vertical diffusivity of 10 m2/s where the density profile is statically unstable.
Properties:
Description:The vertical mixing of tracers and momentum is parameterised using a modified version of the Gaspar et al. (1990) Turbulent Kinetic Energy (TKE) scheme. Unresolved mixing due to internal wave breaking is represented by a background vertical diffusivity of 1.2×10^-5 m2/s which decreases linearly from 15 degrees latitude to 1.2×10^-6 m2/s at 5 degrees latitude (Gregg et al., 2003), and a globally constant background viscosity of 1.2×10^-4 m2/s. The wave breaking parameterisation of Craig and Banner (1994) is used as the TKE surface boundary condition. Vertical mixing in the boundary layer includes an ad-hoc parameterisation of near-inertial wave breaking (Madec, 2008; Rodgers et al., 2014) with an e-decay vertical length scale increasing sinusoidally from 0.5 m at the equator to 10 m and 30 m at ~13 N and ~40 S respectively (Storkey et al., 2018). Langmuir turbulence is parameterised following Axell (2002). Vertical mixing in the ocean interior includes parameterisations of tidal mixing with a special formulation for the Indonesian Throughflow (Simmons et al., 2004; Koch-Larrouy et al., 2008) and double diffusive mixing (Merryfield et al., 1999). Convection is parameterised as an enhanced vertical diffusivity of 10 m2/s where the density profile is statically unstable.
Properties:
Description: Properties of vertical physics in oceanLangmuir cells mixing: true
Description: Properties of boundary layer (BL) mixing on momentum in the oceanType: Turbulent closure – TKE
Closure order: 1.5
Constant: nil:inapplicable
Background: constant, 1.2e-4 m2/s
Description: Properties of boundary layer (BL) mixing on tracers in the oceanType: Turbulent closure – TKE
Closure order: 1.5
Constant: nil:inapplicable
Background: constant but reduced in tropics, 1.2e-5 m2/s
Scientific topic: Interior mixing Overview: Properties of interior vertical mixing in the ocean
Description:The vertical mixing of tracers and momentum is parameterised using a modified version of the Gaspar et al. (1990) Turbulent Kinetic Energy (TKE) scheme. Unresolved mixing due to internal wave breaking is represented by a background vertical diffusivity of 1.2×10^-5 m2/s which decreases linearly from 15 degrees latitude to 1.2×10^-6 m2/s at 5 degrees latitude (Gregg et al., 2003), and a globally constant background viscosity of 1.2×10^-4 m2/s. The wave breaking parameterisation of Craig and Banner (1994) is used as the TKE surface boundary condition. Vertical mixing in the boundary layer includes an ad-hoc parameterisation of near-inertial wave breaking (Madec, 2008; Rodgers et al., 2014) with an e-decay vertical length scale increasing sinusoidally from 0.5 m at the equator to 10 m and 30 m at ~13 N and ~40 S respectively (Storkey et al., 2018). Langmuir turbulence is parameterised following Axell (2002). Vertical mixing in the ocean interior includes parameterisations of tidal mixing with a special formulation for the Indonesian Throughflow (Simmons et al., 2004; Koch-Larrouy et al., 2008) and double diffusive mixing (Merryfield et al., 1999). Convection is parameterised as an enhanced vertical diffusivity of 10 m2/s where the density profile is statically unstable.
Properties:
Description:The vertical mixing of tracers and momentum is parameterised using a modified version of the Gaspar et al. (1990) Turbulent Kinetic Energy (TKE) scheme. Unresolved mixing due to internal wave breaking is represented by a background vertical diffusivity of 1.2×10^-5 m2/s which decreases linearly from 15 degrees latitude to 1.2×10^-6 m2/s at 5 degrees latitude (Gregg et al., 2003), and a globally constant background viscosity of 1.2×10^-4 m2/s. The wave breaking parameterisation of Craig and Banner (1994) is used as the TKE surface boundary condition. Vertical mixing in the boundary layer includes an ad-hoc parameterisation of near-inertial wave breaking (Madec, 2008; Rodgers et al., 2014) with an e-decay vertical length scale increasing sinusoidally from 0.5 m at the equator to 10 m and 30 m at ~13 N and ~40 S respectively (Storkey et al., 2018). Langmuir turbulence is parameterised following Axell (2002). Vertical mixing in the ocean interior includes parameterisations of tidal mixing with a special formulation for the Indonesian Throughflow (Simmons et al., 2004; Koch-Larrouy et al., 2008) and double diffusive mixing (Merryfield et al., 1999). Convection is parameterised as an enhanced vertical diffusivity of 10 m2/s where the density profile is statically unstable.
Properties:
Description: Properties of interior mixing in the oceanConvection type: Enhanced vertical diffusion
Tide induced mixing: baroclinic based on climatologies
Double diffusion: true
Shear mixing: false
Description: Properties of interior mixing on momentum in the oceanType: Turbulent closure / TKE
Constant: nil:inapplicable
Profile: false
Background: constant, 1.2e-4 m2/s
Description: Properties of interior mixing on tracers in the oceanType: Turbulent closure / TKE
Constant: nil:inapplicable
Profile: false
Background: constant but reduced at tropics, 1.2e-5 m2/s
Scientific topic: Uplow boundaries Overview: Ocean upper / lower boundaries
Description: The model uses a non-linear free surface in which the cell thicknesses throughout the water column are allowed to vary with time (the z* coordinate of Adcroft and Campin, 2004). This permits an exact representation of the surface freshwater flux. The equation for the surface pressure gradient is solved using a filtered solution in which the fast gravity waves are damped by an additional force in the equation (Roullet and Madec, 2000). An advective and diffusive bottom boundary layer scheme is used (Beckmann and Doscher, 1997) with a lateral mixing coefficient of 1000 m2/s.
Citations:
Description: The model uses a non-linear free surface in which the cell thicknesses throughout the water column are allowed to vary with time (the z* coordinate of Adcroft and Campin, 2004). This permits an exact representation of the surface freshwater flux. The equation for the surface pressure gradient is solved using a filtered solution in which the fast gravity waves are damped by an additional force in the equation (Roullet and Madec, 2000). An advective and diffusive bottom boundary layer scheme is used (Beckmann and Doscher, 1997) with a lateral mixing coefficient of 1000 m2/s.
Citations:
Adcroft, A. and Campin, J.-M. Rescaled height coordinates for accurate representation of free-surface flows in ocean circulation models Ocean Modelling, 7, 269 – 284 10.1016/j.ocemod.2003.09.003
Beckmann, A. and Doscher, R. A method for improved representation of dense water spreading over topography in geopotential-coordinate models J. Phys. Oceanogr., 27, 581-591 10.1175/1520-0485(1997)027<0581:AMFIRO>2.0.CO
Roullet, G. and Madec, G. Salt conservation, free surface, and varying levels: A new formulation for ocean general circulation models Journal of Geophysical Research, 105, C10, 23927-23942 http://dx.doi.org/10.1029/2000JC900089
Properties:
Description: Properties of bottom boundary layer in oceanOverview: The model uses a non-linear free surface in which the cell thicknesses throughout the water column are allowed to vary with time (the z* coordinate of Adcroft and Campin, 2004). This permits an exact representation of the surface freshwater flux. The equation for the surface pressure gradient is solved using a filtered solution in which the fast gravity waves are damped by an additional force in the equation (Roullet and Madec, 2000). An advective and diffusive bottom boundary layer scheme is used (Beckmann and Doscher, 1997) with a lateral mixing coefficient of 1000 m2/s.
Type of bbl: Advective and Diffusive
Lateral mixing coef: 1000
Sill overflow: nil:inapplicable
Description: Properties of free surface in oceanScheme: Non-linear filtered
Embeded seaice: false
Scientific topic: Boundary forcing Overview: Ocean boundary forcing
Description: Freshwater runoff from land is added to the surface layer of the ocean, assuming the runoff is fresh and at the same temperature as the local SST. An enhanced vertical diffusion of 2×10^-3 m2/s is added over the top 10 m of the water column at runoff points to avoid instabilities associated with very shallow fresh layers at the surface. Meltwater fluxes from land ice are parameterised using a Lagrangian iceberg model (Bigg et al., 1997; Martin and Adcroft, 2010) and a prescribed freshwater flux at the edge of ice shelves to represent basal melting (Mathiot et al., 2017). Penetration of the shortwave heat flux into the ocean is parameterised using a 3-band RGB scheme (Lengaigne et al., 2007) assuming a constant chlorophyll concentration of 0.05 g.Chl/L. Dense overflows are parameterised using an advective and diffusive bottom boundary layer scheme (Beckmann and Doscher, 1997). A quadratic bottom friction is used with enhancements in the Indonesian Throughflow, Denmark Strait and Bab el Mandab regions.
Citations:
Description: Freshwater runoff from land is added to the surface layer of the ocean, assuming the runoff is fresh and at the same temperature as the local SST. An enhanced vertical diffusion of 2×10^-3 m2/s is added over the top 10 m of the water column at runoff points to avoid instabilities associated with very shallow fresh layers at the surface. Meltwater fluxes from land ice are parameterised using a Lagrangian iceberg model (Bigg et al., 1997; Martin and Adcroft, 2010) and a prescribed freshwater flux at the edge of ice shelves to represent basal melting (Mathiot et al., 2017). Penetration of the shortwave heat flux into the ocean is parameterised using a 3-band RGB scheme (Lengaigne et al., 2007) assuming a constant chlorophyll concentration of 0.05 g.Chl/L. Dense overflows are parameterised using an advective and diffusive bottom boundary layer scheme (Beckmann and Doscher, 1997). A quadratic bottom friction is used with enhancements in the Indonesian Throughflow, Denmark Strait and Bab el Mandab regions.
Citations:
Beckmann, A. and Doscher, R. A method for improved representation of dense water spreading over topography in geopotential-coordinate models J. Phys. Oceanogr., 27, 581-591 10.1175/1520-0485(1997)027<0581:AMFIRO>2.0.CO
Bigg, G. R., Wadley, M. R., Stevens, D. P., and Johnson, J. A. Modelling dynamics and thermodynamics of icebergs Cold Regions Science and Technology, 26, 113-135 10.1016/S0165-232X(97)00012-8
Goutorbe, B., J. Poort, F. Lucazeau, and S. Raillard Global heat flow trends resolved from multiple geological and geophysical proxies, Geophys. J. Int., 187, 1405-1419. 10.1111/j.1365-246X.2011.05228.x
Lengaigne, M., Menkes, C., Aumont, O., Gorgues, T., Bopp, L., André, J.-M. and Madec, G. Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model Climate Dynamics, 28(5), 503-516. 0.1007/s00382-006-0200-2
Martin, T. and Adcroft, A. Parameterizing the fresh-water flux from land ice to ocean with interactive icebergs in a coupled climate model Ocean Modelling, 34, 111-124 http://www.sciencedirect.com/science/article/
Mathiot, P., Jenkins, A., Harris, C., and G. Madec. Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6 Geoscientific Model Development, 10, 2849-2874 https://doi.org/10.5194/gmd-10-2849-2017
Subtopics:
Scientific topic: Momentum Overview: Key properties of momentum boundary forcing in the ocean
Description:Freshwater runoff from land is added to the surface layer of the ocean, assuming the runoff is fresh and at the same temperature as the local SST. An enhanced vertical diffusion of 2×10^-3 m2/s is added over the top 10 m of the water column at runoff points to avoid instabilities associated with very shallow fresh layers at the surface. Meltwater fluxes from land ice are parameterised using a Lagrangian iceberg model (Bigg et al., 1997; Martin and Adcroft, 2010) and a prescribed freshwater flux at the edge of ice shelves to represent basal melting (Mathiot et al., 2017). Penetration of the shortwave heat flux into the ocean is parameterised using a 3-band RGB scheme (Lengaigne et al., 2007) assuming a constant chlorophyll concentration of 0.05 g.Chl/L. Dense overflows are parameterised using an advective and diffusive bottom boundary layer scheme (Beckmann and Doscher, 1997). A quadratic bottom friction is used with enhancements in the Indonesian Throughflow, Denmark Strait and Bab el Mandab regions.
Properties:
Description:Freshwater runoff from land is added to the surface layer of the ocean, assuming the runoff is fresh and at the same temperature as the local SST. An enhanced vertical diffusion of 2×10^-3 m2/s is added over the top 10 m of the water column at runoff points to avoid instabilities associated with very shallow fresh layers at the surface. Meltwater fluxes from land ice are parameterised using a Lagrangian iceberg model (Bigg et al., 1997; Martin and Adcroft, 2010) and a prescribed freshwater flux at the edge of ice shelves to represent basal melting (Mathiot et al., 2017). Penetration of the shortwave heat flux into the ocean is parameterised using a 3-band RGB scheme (Lengaigne et al., 2007) assuming a constant chlorophyll concentration of 0.05 g.Chl/L. Dense overflows are parameterised using an advective and diffusive bottom boundary layer scheme (Beckmann and Doscher, 1997). A quadratic bottom friction is used with enhancements in the Indonesian Throughflow, Denmark Strait and Bab el Mandab regions.
Properties:
Description: Properties of momentum bottom friction in oceanType: Non-linear
Description: Properties of momentum lateral friction in oceanType: Free-slip
Scientific topic: Tracers Overview: Key properties of tracer boundary forcing in the ocean
Description:Freshwater runoff from land is added to the surface layer of the ocean, assuming the runoff is fresh and at the same temperature as the local SST. An enhanced vertical diffusion of 2×10^-3 m2/s is added over the top 10 m of the water column at runoff points to avoid instabilities associated with very shallow fresh layers at the surface. Meltwater fluxes from land ice are parameterised using a Lagrangian iceberg model (Bigg et al., 1997; Martin and Adcroft, 2010) and a prescribed freshwater flux at the edge of ice shelves to represent basal melting (Mathiot et al., 2017). Penetration of the shortwave heat flux into the ocean is parameterised using a 3-band RGB scheme (Lengaigne et al., 2007) assuming a constant chlorophyll concentration of 0.05 g.Chl/L. Dense overflows are parameterised using an advective and diffusive bottom boundary layer scheme (Beckmann and Doscher, 1997). A quadratic bottom friction is used with enhancements in the Indonesian Throughflow, Denmark Strait and Bab el Mandab regions.
Citations:
Description:Freshwater runoff from land is added to the surface layer of the ocean, assuming the runoff is fresh and at the same temperature as the local SST. An enhanced vertical diffusion of 2×10^-3 m2/s is added over the top 10 m of the water column at runoff points to avoid instabilities associated with very shallow fresh layers at the surface. Meltwater fluxes from land ice are parameterised using a Lagrangian iceberg model (Bigg et al., 1997; Martin and Adcroft, 2010) and a prescribed freshwater flux at the edge of ice shelves to represent basal melting (Mathiot et al., 2017). Penetration of the shortwave heat flux into the ocean is parameterised using a 3-band RGB scheme (Lengaigne et al., 2007) assuming a constant chlorophyll concentration of 0.05 g.Chl/L. Dense overflows are parameterised using an advective and diffusive bottom boundary layer scheme (Beckmann and Doscher, 1997). A quadratic bottom friction is used with enhancements in the Indonesian Throughflow, Denmark Strait and Bab el Mandab regions.
Citations:
Mathiot, P., Jenkins, A., Harris, C., and G. Madec. Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6 Geoscientific Model Development, 10, 2849-2874 https://doi.org/10.5194/gmd-10-2849-2017
Martin, T. and Adcroft, A. Parameterizing the fresh-water flux from land ice to ocean with interactive icebergs in a coupled climate model Ocean Modelling, 34, 111-124 http://www.sciencedirect.com/science/article/
Lengaigne, M., Menkes, C., Aumont, O., Gorgues, T., Bopp, L., André, J.-M. and Madec, G. Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model Climate Dynamics, 28(5), 503-516. 0.1007/s00382-006-0200-2
Bigg, G. R., Wadley, M. R., Stevens, D. P., and Johnson, J. A. Modelling dynamics and thermodynamics of icebergs Cold Regions Science and Technology, 26, 113-135 10.1016/S0165-232X(97)00012-8
Beckmann, A. and Doscher, R. A method for improved representation of dense water spreading over topography in geopotential-coordinate models J. Phys. Oceanogr., 27, 581-591 10.1175/1520-0485(1997)027<0581:AMFIRO>2.0.CO
Properties:
Description: Properties of surface fresh water forcing in oceanFrom atmopshere: Freshwater flux
From sea ice: Freshwater flux
Forced mode restoring: Restoration to monthly climatology using a -33.33 mm/day/psu retroaction coefficient.
Description: Properties of sunlight penetration scheme in oceanScheme: 3 extinction depth
Ocean colour: false
Extinction depth description: The three-band RGB model of Lengaigne et al. (2007) is used, in which visible light is split into red (600-700nm), green (500-600nm) and blue (400-500nm) wavebands. The given extinction depths are valid for a constant 0.05 g.Chl/L chlorophyll concentration.
Extinction depths: 2.619 m (red), 12.713 m (green), 39.984 m (blue)
Coupled components
UKCA-StratTrop
Canonical ID: UKCA-StratTrop
Long name: UKCA-StratTrop
Version: UM11.0
Description: The Atmospheric Chemistry model in UKESM1 is part of the United Kingdom Chemistry and Aerosols (UKCA) modelling framework and consists of a Whole Atmosphere (Stratospheric+Tropospheric or ‘StratTrop’) scheme with aerosol chemistry and online photolysis. This is a marked improvement over the scheme used in the UM-HadGEM2-ES model for CMIP5 simulations that used a Tropospheric-only scheme with tabulated photolysis rates. The StratTrop scheme (Morgenstern et al 2009, O’Connor et al 2014) with aerosol chemistry and Fast-JX (Telford et al 2013) photolysis includes 83 tracers, 212 bi-molecular, 25 tri-molecular, 60 photolytic and 8 heterogeneous reactions. The scheme uses prescribed emissions for NO, CO, HCHO, C2H6, C3H8, Me2CO, MeCHO, NVOC(MeOH), SO2, NH3 and interactive emissions for Lightning NOx (online), terrestrial Monoterpene and Isoprene (from JULES) and DMS (from MEDUSA).
Model type: Process
Citations:
Long name: UKCA-StratTrop
Version: UM11.0
Description: The Atmospheric Chemistry model in UKESM1 is part of the United Kingdom Chemistry and Aerosols (UKCA) modelling framework and consists of a Whole Atmosphere (Stratospheric+Tropospheric or ‘StratTrop’) scheme with aerosol chemistry and online photolysis. This is a marked improvement over the scheme used in the UM-HadGEM2-ES model for CMIP5 simulations that used a Tropospheric-only scheme with tabulated photolysis rates. The StratTrop scheme (Morgenstern et al 2009, O’Connor et al 2014) with aerosol chemistry and Fast-JX (Telford et al 2013) photolysis includes 83 tracers, 212 bi-molecular, 25 tri-molecular, 60 photolytic and 8 heterogeneous reactions. The scheme uses prescribed emissions for NO, CO, HCHO, C2H6, C3H8, Me2CO, MeCHO, NVOC(MeOH), SO2, NH3 and interactive emissions for Lightning NOx (online), terrestrial Monoterpene and Isoprene (from JULES) and DMS (from MEDUSA).
Model type: Process
Citations:
Morgenstern, O., Braesicke, P., O’Connor, F. M, Bushell, A. C., Johnson, C. E., Osprey, S. M., and J. A. Pyle Evaluation of the new UKCA climate-composition model – Part 1: The stratosphere Geoscientific Model Development, 2, 43-57 n/a
O’Connor, F. M., C. E. Johnson, O. Morgenstern, M. G. Sanderson, P. Young, G. Zeng, W. J. Collins and J. A. Pyle Evaluation of the new UKCA climate-composition model. Part II. The troposphere Atmos. Chem. Phys., 14, 11221-11246 n/a
Telford, P. J., Abraham, N. L., Archibald, A. T., Braesicke, P., Dalvi, M., Morgenstern, O>, O’Connor, F. M., Richards, N. A. D. and J. A. Pyle Implementation of the Fast-JX Photolysis scheme (v6.4) into the UKCA component of the MetUM chemistry-climate model (v7.3) Geoscientific Model Development, 6, 161-177 n/a
MEDUSA2
Canonical ID: MEDUSA2
Long name: Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification, version 2
Version: 2.1
Description: The Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification (MEDUSA) is an “intermediate complexity” plankton ecosystem model designed to incorporate sufficient complexity to address key feedbacks between anthropogenically-driven changes (climate, acidification) and oceanic biogeochemistry. MEDUSA-2 resolves a dual size-structured ecosystem of small (nanophytoplankton and microzooplankton) and large (microphytoplankton and mesozooplankton) components that explicitly includes the biogeochemical cycles of nitrogen, silicon and iron nutrients as well as the cycles of carbon, alkalinity and dissolved oxygen. Large phytoplankton are assumed synonymous with diatoms and utilise silicic acid in addition to nitrogen, iron and carbon. Similar to living components, MEDUSA-2’s detrital components are split into two size classes. Small, slow-sinking detritus is represented explicitly as separate nitrogen and carbon tracers (iron is slaved to nitrogen). Large, fast-sinking detritus is represented implicitly, and created and remineralised within a single timestep. Fast-sinking detritus consists of organic nitrogen, carbon and iron, together with silicon and calcium carbonate biominerals that are involved in a ballast parameterisation (Armstrong et al., 2002). At the seafloor, MEDUSA-2 resolves five reservoirs to temporarily store sinking organic material reaching the sediment. The model’s nitrogen, silicon and alkalinity cycles are closed and conservative (e.g. no riverine inputs), while the other three cycles are open. The ocean’s iron cycle includes additions from aeolian and benthic sources, and is depleted by scavenging. The ocean’s carbon cycle exchanges CO2 with the atmosphere. The ocean’s oxygen cycle exchanges with the atmosphere, and dissolved oxygen is additionally created by primary production and depleted by remineralisation. The various elemental cycles include both fixed and variable stoichiometry. Iron is slaved to nitrogen throughout; nitrogen and carbon have fixed (but different) ratios in phytoplankton and zooplankton, and variable ratios in detritus; diatom silicon has a variable ratio with nitrogen; calcium carbonate (cf. alkalinity) is produced at a variable rate relative to organic carbon; oxygen production and consumption reflects the C:N of organic matter produced and consumed. During its development within UKESM1, several changes have occurred to the science and code of MEDUSA-2 compared to that originally described in Yool et al. (2013). These include: [1] The carbonate chemistry submodel in MEDUSA-2 has been upgraded to MOCSY-2.0 (Orr and Epitalon 2015). [2] Several empirical submodels of surface DMS concentration have been added to MEDUSA-2 to permit this Earth system feedback (e.g. Anderson et al., 2001). [3] Code has been added to average the diel light cycle experienced by MEDUSA-2 within UKESM1. [4] The code itself has been reorganised into smaller blocks and subroutines for better future management, and adopts newer Fortran conventions. [5] The code has also been reorganised to reflect changing norms within NEMO (e.g. around restarting). [6] Changes to benthic time-stepping and slow detritus sinking have been made to reflect NEMO v3.6’s adoption of VVL. [7] Diagnostics have been upgraded to utilise XIOS, and new diagnostics had been added, largely for CMIP6 purposes.
Model type: Process
Citations:
Long name: Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification, version 2
Version: 2.1
Description: The Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification (MEDUSA) is an “intermediate complexity” plankton ecosystem model designed to incorporate sufficient complexity to address key feedbacks between anthropogenically-driven changes (climate, acidification) and oceanic biogeochemistry. MEDUSA-2 resolves a dual size-structured ecosystem of small (nanophytoplankton and microzooplankton) and large (microphytoplankton and mesozooplankton) components that explicitly includes the biogeochemical cycles of nitrogen, silicon and iron nutrients as well as the cycles of carbon, alkalinity and dissolved oxygen. Large phytoplankton are assumed synonymous with diatoms and utilise silicic acid in addition to nitrogen, iron and carbon. Similar to living components, MEDUSA-2’s detrital components are split into two size classes. Small, slow-sinking detritus is represented explicitly as separate nitrogen and carbon tracers (iron is slaved to nitrogen). Large, fast-sinking detritus is represented implicitly, and created and remineralised within a single timestep. Fast-sinking detritus consists of organic nitrogen, carbon and iron, together with silicon and calcium carbonate biominerals that are involved in a ballast parameterisation (Armstrong et al., 2002). At the seafloor, MEDUSA-2 resolves five reservoirs to temporarily store sinking organic material reaching the sediment. The model’s nitrogen, silicon and alkalinity cycles are closed and conservative (e.g. no riverine inputs), while the other three cycles are open. The ocean’s iron cycle includes additions from aeolian and benthic sources, and is depleted by scavenging. The ocean’s carbon cycle exchanges CO2 with the atmosphere. The ocean’s oxygen cycle exchanges with the atmosphere, and dissolved oxygen is additionally created by primary production and depleted by remineralisation. The various elemental cycles include both fixed and variable stoichiometry. Iron is slaved to nitrogen throughout; nitrogen and carbon have fixed (but different) ratios in phytoplankton and zooplankton, and variable ratios in detritus; diatom silicon has a variable ratio with nitrogen; calcium carbonate (cf. alkalinity) is produced at a variable rate relative to organic carbon; oxygen production and consumption reflects the C:N of organic matter produced and consumed. During its development within UKESM1, several changes have occurred to the science and code of MEDUSA-2 compared to that originally described in Yool et al. (2013). These include: [1] The carbonate chemistry submodel in MEDUSA-2 has been upgraded to MOCSY-2.0 (Orr and Epitalon 2015). [2] Several empirical submodels of surface DMS concentration have been added to MEDUSA-2 to permit this Earth system feedback (e.g. Anderson et al., 2001). [3] Code has been added to average the diel light cycle experienced by MEDUSA-2 within UKESM1. [4] The code itself has been reorganised into smaller blocks and subroutines for better future management, and adopts newer Fortran conventions. [5] The code has also been reorganised to reflect changing norms within NEMO (e.g. around restarting). [6] Changes to benthic time-stepping and slow detritus sinking have been made to reflect NEMO v3.6’s adoption of VVL. [7] Diagnostics have been upgraded to utilise XIOS, and new diagnostics had been added, largely for CMIP6 purposes.
Model type: Process
Citations:
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies Geosci. Model Dev., 6, 1767-1811, https://doi.org/10.5194/gmd-6-1767-2013
Anderson, T. R., Spall, S. A., Yool, A., Cipollini, P., Challenor, P. G., and Fasham, M. J. R. Global fields of sea surface dimethylsulphide predicted from chlorophyll, nutrients and light, J. Mar. Syst., 30, 1-20, n/a
Armstrong, R. A., Lee, C., Hedges, J. I., Honjo, S., and S. G. Wakeham A new, mechanistic model for organic carbon fluxes in the ocean: based on the quantitative association of POC with ballast minerals, Deep-Sea Res. Pt. II, 49, 219-236 n/a
Orr, J. C. and Epitalon, J.-M. Improved routines to model the ocean carbonate system: mocsy 2.0, Geosci. Model Dev., 8, 485-499, https://doi.org/10.5194/gmd-8-485-2015,
JULES-ES-1.0
Canonical ID: JULES-ES-1.0
Long name: n/a
Version: UM10.7 VN4.8
Description: Land-surface component of UKESM1.0. The joint UK Land Environment Simulator (JULES) model is based on the Met Office Surface Exchange Scheme (MOSES). Sub-grid scale surface heterogeneity is represented by a tiling system. A multi-layer snow scheme has been implemented since HadGEM2. Includes both carbon cycle and nitrogen cycle processes
Model type: Process
Citations:
Long name: n/a
Version: UM10.7 VN4.8
Description: Land-surface component of UKESM1.0. The joint UK Land Environment Simulator (JULES) model is based on the Met Office Surface Exchange Scheme (MOSES). Sub-grid scale surface heterogeneity is represented by a tiling system. A multi-layer snow scheme has been implemented since HadGEM2. Includes both carbon cycle and nitrogen cycle processes
Model type: Process
Citations:
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Menard, C. B., Edwards, J. M., Hendry, M. A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and R. J. Harding (2011) The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes Geosci. Model Dev., 4, 677– 699 n/a
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M (2011) The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics Geosci. Model Dev., 4, 701-722 n/a
UKCA-GLOMAP-mode
Canonical ID: UKCA-GLOMAP-mode
Long name: UKCA-GLOMAP-mode
Version: part of UM11.0
Description: UKCA-GLOMAP-mode (Mann et al., 2010, 2012) is a multi-component and multi-modal aerosol model representing microphysical processes in the form of size-resolved primary emissions, new particle formation, condensation, coagulation, cloud processing, dry deposition, sedimentation, nucleation scavenging and impaction scavenging. The model transports aerosol particle number and component mass concentrations of sulfate, sea salt, black carbon and organic carbon in five internally mixed log-normal modes. Mineral dust is simulated separately using the 6-bin emission scheme of Woodward et al. (2001). This represents the direct interaction of dust with radiation, but not interactions with cloud microphysics. Dust does not mix internally with the aerosols represented by the modal scheme.
Model type: Process
Citations:
Long name: UKCA-GLOMAP-mode
Version: part of UM11.0
Description: UKCA-GLOMAP-mode (Mann et al., 2010, 2012) is a multi-component and multi-modal aerosol model representing microphysical processes in the form of size-resolved primary emissions, new particle formation, condensation, coagulation, cloud processing, dry deposition, sedimentation, nucleation scavenging and impaction scavenging. The model transports aerosol particle number and component mass concentrations of sulfate, sea salt, black carbon and organic carbon in five internally mixed log-normal modes. Mineral dust is simulated separately using the 6-bin emission scheme of Woodward et al. (2001). This represents the direct interaction of dust with radiation, but not interactions with cloud microphysics. Dust does not mix internally with the aerosols represented by the modal scheme.
Model type: Process
Citations:
Woodward S., (2001) Modelling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model.. J. Geophys. Res., 106, D16, 18,155-18,166, 2001. n/a
Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J. and C. E. Johnson Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model, Geosci. Model Dev., 3, 519-551 https://doi.org/10.5194/gmd-3-519-2010
Mann, G. W., Carslaw, K. S., Ridley, D. A., Spracklen, D. V., Pringle, K. J., Merikanto, J., Korhonen, H., Schwarz, J. P., Lee, L. A., Manktelow, P. T., Woodhouse, M. T., Schmidt, A., Breider, T. J., Emmerson, K. M., Reddington, C. L., Chipperfield, M. P, and S. J. Pickering Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model Atmos. Chem. Phys., 12, 4449-4476 https://doi.org/10.5194/acp-12-4449-2012
Mulcahy, J. P., Jones, C., Sellar, A., Johnson,B., Boutle, I., Jones, A., Andrews, T., Rumbold, S., Mollard, J., Bellouin, N., Johnson, C., Williams, K., Grosvenor, D. and D. T. McCoy Improved aerosol processes and effective radiative forcing in HadGEM3 and UKESM1 in prep 2018 n/a
MetUM-HadGEM3-GA7.1
Canonical ID: MetUM-HadGEM3-GA7.1
Long name: MetUM-HadGEM3-GA7.1
Version: 7.1
Description: The atmosphere component of HadGEM3-GC3.1 is labelled GA7.1 and is fully described in Walters et al. (2017) and Mulcahy et al. (2018). This atmosphere component is developed for weather forecasting applications as well as seasonal-to-centennial climate simulations. The model includes a number of major developments since HadGEM2-AO, principally: a new dynamical core; increased vertical resolution with a higher model top to fully resolve the stratosphere; prognostic treatment of cloud, condensate and rain amounts; and a 2-moment 5-mode aerosol scheme. Other developments include an improved treatment of gaseous absorption in the radiation scheme, improvements to the treatment of warm rain and ice clouds and an improvement to the numerics in the model’s convection scheme.
Model type: Atm Only
Citations:
Long name: MetUM-HadGEM3-GA7.1
Version: 7.1
Description: The atmosphere component of HadGEM3-GC3.1 is labelled GA7.1 and is fully described in Walters et al. (2017) and Mulcahy et al. (2018). This atmosphere component is developed for weather forecasting applications as well as seasonal-to-centennial climate simulations. The model includes a number of major developments since HadGEM2-AO, principally: a new dynamical core; increased vertical resolution with a higher model top to fully resolve the stratosphere; prognostic treatment of cloud, condensate and rain amounts; and a 2-moment 5-mode aerosol scheme. Other developments include an improved treatment of gaseous absorption in the radiation scheme, improvements to the treatment of warm rain and ice clouds and an improvement to the numerics in the model’s convection scheme.
Model type: Atm Only
Citations:
Walters, D., Baran, A., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and M. Zerroukat The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations Geosci. Model Dev. Discuss., in review, 2017. https://doi.org/10.5194/gmd-2017-291
Mulcahy, J. P., Jones, C., Sellar, A., Johnson,B., Boutle, I., Jones, A., Andrews, T., Rumbold, S., Mollard, J., Bellouin, N., Johnson, C., Williams, K., Grosvenor, D. and D. T. McCoy Improved aerosol processes and effective radiative forcing in HadGEM3 and UKESM1 in prep 2018 n/a
CICE-HadGEM3-GSI8
Canonical ID: CICE-HadGEM3-GSI8
Long name: CICE-HadGEM3-GSI8
Version: 5.1.2
Description: The sea ice configuration in HadGEM3 GC3.1, GSI8.1, is described by Ridley et al. (2018). It is largely based on the the Los Alamos sea ice model CICE, version 5.1.2. It is modified as described in West et al. (2016) with surface variables calculated in the surface exchange scheme JULES, on the atmosphere grid. It is configured to use a 5-category thickness distribution, multilayer thermodynamics and explicit meltponds for albedo calculation.
Model type: Process
Citations:
Long name: CICE-HadGEM3-GSI8
Version: 5.1.2
Description: The sea ice configuration in HadGEM3 GC3.1, GSI8.1, is described by Ridley et al. (2018). It is largely based on the the Los Alamos sea ice model CICE, version 5.1.2. It is modified as described in West et al. (2016) with surface variables calculated in the surface exchange scheme JULES, on the atmosphere grid. It is configured to use a 5-category thickness distribution, multilayer thermodynamics and explicit meltponds for albedo calculation.
Model type: Process
Citations:
Ridley, J. K., Blockley, E. W., Keen, A. B., Rae., J. G. L., West, A. E. and Schroeder, D. The sea ice model component of HadGEM3-GC3.1, Geosci. Model Dev., 11, 713-723 https://doi.org/10.5194/gmd-11-713-2018
West, A. E, McLaren, A. J., Hewitt, H. T. and Best, M. J. The location of the thermodynamic atmosphere-ice interface in fully coupled models – a case study using JULES and CICE Geosci. Mod. Dev., 9, 1125-1141 https://doi.org/10.5194/gmd-9-1125-2016
NEMO-HadGEM3-GO6.0
Canonical ID: NEMO-HadGEM3-GO6.0
Long name: Nucleus for European Modelling of the Ocean
Version: 3.6 stable
Description: The ocean component of the low-resolution version of HadGEM3 GC3.1 is the 1 degree GO6 configuration (Kuhlbrodt et al., 2018; Storkey et al., 2018) of version 3.6_stable of the NEMO primitive equation model (Madec, 2008). Since 2010 the UK Met Office, the National Oceanography Centre and the British Antarctic Survey have collaborated on the development of standard global ocean model configurations based on the NEMO code. These are intended to be used for a variety of applications across a range of timescales from ocean forecasting a few days ahead to century-scale climate modelling. The use of a single ocean model configuration for multiple applications is in the spirit of the seamless forecasting approach. The GO6 ocean model is the ocean component of the GC3.1 version of the Met Office Hadley Centre coupled climate model (Williams et al., 2017) and the ocean component of the UKESM1 UK Earth System model (Kuhlbrodt et al., 2018), both of which will be used in CMIP6 simulations and associated OMIP simulations. GO6 is expected to be incorporated into future versions of the FOAM ocean forecasting system, the GloSea seasonal forecasting system and the DePreSys decadal forecasting system. The previous configuration GO5 was only released at a single resolution of a nominal 1/4 degree horizontal grid spacing. GO6 is a traceable hierarchy of three horizontal resolutions: 1 degree, 1/4 degree and 1/12 degree, all with the same vertical grid – traceable means that the only differences between the three configurations are those that can be justified as necessitated by the change in resolution, an example being tuning of the horizontal viscosity.
Model type: Ocean Only
Citations:
Long name: Nucleus for European Modelling of the Ocean
Version: 3.6 stable
Description: The ocean component of the low-resolution version of HadGEM3 GC3.1 is the 1 degree GO6 configuration (Kuhlbrodt et al., 2018; Storkey et al., 2018) of version 3.6_stable of the NEMO primitive equation model (Madec, 2008). Since 2010 the UK Met Office, the National Oceanography Centre and the British Antarctic Survey have collaborated on the development of standard global ocean model configurations based on the NEMO code. These are intended to be used for a variety of applications across a range of timescales from ocean forecasting a few days ahead to century-scale climate modelling. The use of a single ocean model configuration for multiple applications is in the spirit of the seamless forecasting approach. The GO6 ocean model is the ocean component of the GC3.1 version of the Met Office Hadley Centre coupled climate model (Williams et al., 2017) and the ocean component of the UKESM1 UK Earth System model (Kuhlbrodt et al., 2018), both of which will be used in CMIP6 simulations and associated OMIP simulations. GO6 is expected to be incorporated into future versions of the FOAM ocean forecasting system, the GloSea seasonal forecasting system and the DePreSys decadal forecasting system. The previous configuration GO5 was only released at a single resolution of a nominal 1/4 degree horizontal grid spacing. GO6 is a traceable hierarchy of three horizontal resolutions: 1 degree, 1/4 degree and 1/12 degree, all with the same vertical grid – traceable means that the only differences between the three configurations are those that can be justified as necessitated by the change in resolution, an example being tuning of the horizontal viscosity.
Model type: Ocean Only
Citations:
Madec G. (2008) NEMO ocean engine Note du Pole de modélisation, Institut Pierre-Simon Laplace (IPSL), France, No 27 ISSN No 1288-1619 n/a
Williams, K., Copsey, D., Blockley, E., Bodas-Salcedo, A., Calvert, D., Comer, R., Davis, P., Graham, T., Hewitt, H., Hill, R., Hyder, P., Ineson, S., Johns, T., Keen, A., Lee, R., Megann, A., Milton, S., Rae, J., Roberts, M., Scaife, A., Schiemann, R., Storkey, D., Thorpe, L., Watterson, I., Walters, D., West, A., Wood, R., Woollings, T., and Xavier, P. The Met Office Global Coupled model 3.0 and 3.1 (GC3.0 and GC3.1) configurations Journal of Advances in Modeling Earth Systems, 10, 357-380 https://doi.org/10.1002/2017MS001115
Storkey, D., Blaker, A. T., Mathiot, P., Megann, A., Aksenov, Y., Blockley, E. W., Calvert, D., Graham, T., Hewitt, H. T., Hyder, P., Kuhlbrodt, T., Rae, J. G. L. and B. Sinha. UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions. Geoscientific Model Development (in review) 10.5194/gmd-2017-263
Kuhlbrodt, T., Jones, C. G., Sellar, A., Storkey, D., Blockley, E., Stringer, M., Hill, R., Graham, T., Ridley, J., Blaker, A., Calvert, D., Copsey, D., Ellis, R., Hewitt, H., Hyder, P., Ineson, S., Mulcahy, J., Siahaan, A. and J. Walton. The low-resolution version of HadGEM3 GC3.1: Development and evaluation for global climate Journal of Advances in Modeling Earth Systems (in review) n/a
Mathiot, P., Jenkins, A., Harris, C., and G. Madec. Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6 Geoscientific Model Development, 10, 2849-2874 https://doi.org/10.5194/gmd-10-2849-2017