Library

Documenting the user interface.

OceanBioME.jl

OceanBioME.OceanBioMEModule

A fast and flexible modelling environment for modelling the coupled interactions between ocean biogeochemistry, carbonate chemistry, and physics.

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OceanBioME.CBMDayLengthType
(day_length::CBMDayLength)(t, φ)

Returns the length of day in seconds at the latitude φ, t seconds after the start of the year.

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OceanBioME.ScaleNegativeTracersMethod
ScaleNegativeTracers(; tracers, scalefactors = ones(length(tracers)), warn = false, invalid_fill_value = NaN)

Constructs a modifier to scale tracers so that none are negative. Use like:

modifier = ScaleNegativeTracers((:P, :Z, :N))
biogeochemistry = Biogeochemistry(...; modifier)

This method is better, though still imperfect, method to prevent numerical errors that lead to negative tracer values compared to ZeroNegativeTracers. Please see discussion in github.

Future plans include implement a positivity-preserving timestepping scheme as the ideal alternative.

~~If warn is true then scaling will raise a warning.~~

invalid_fill_value specifies the value to set the total cell content to if the total is less than 0 (meaning that total tracer conservation can not be enforced). If the value is set to anything other than NaN this scheme no longer conserves mass. While this may be useful to prevent spurious numerics leading to crashing care should be taken that the mass doesn't deviate too much.

This scheme is similar to that used by NEMO-PISCES, although they scale the tendency rather than the value, while other Earth system models simply set negative tracers to zero, for example NCAR's MARBL and NEMO-TOPAZ2, which does not conserve mass. More complicated schemes exist, for example ROMS-BECS uses an implicite-itterative approach where each component is updated in sequence to garantee mass conservation, possibly at the expense of numerical precision.

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OceanBioME.ScaleNegativeTracersMethod
ScaleNegativeTracers(bgc::AbstractBiogeochemistry; warn = false)

Construct a modifier to scale the conserved tracers in bgc biogeochemistry.

If warn is true then scaling will raise a warning.

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OceanBioME.ZeroNegativeTracersType
ZeroNegativeTracers(; exclude = ())

Construct a modifier that zeroes any negative tracers excluding those listed in exclude.

Tracer conservation

This method is not recommended as a way to preserve positivity of tracers since it does not conserve the total tracer.

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OceanBioME.BiogeochemistryMethod
Biogeochemistry(underlying_biogeochemistry;
                light_attenuation = nothing,
                sediment = nothing,
                particles = nothing,
                modifiers = nothing)

Construct a biogeochemical model based on underlying_biogeochemistry which may have a light_attenuation model, sediment, particles, and modifiers.

Keyword Arguments

  • light_attenuation_model: light attenuation model which integrated the attenuation of available light
  • sediment_model: slot for AbstractSediment
  • particles: slot for BiogeochemicalParticles
  • modifiers: slot for components which modify the biogeochemistry when the tendencies have been calculated or when the state is updated
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OceanBioME.conserved_tracersMethod
conserved_tracers(model::UnderlyingBiogeochemicalModel, args...; kwargs...)

Returns the names of tracers which together are conserved in model

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OceanBioME.redfieldMethod
redfield(i, j, k, val_tracer_name, bgc, tracers)

Returns the redfield ratio of tracer_name from bgc at i, j, k.

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OceanBioME.redfieldMethod
redfield(val_tracer_name, bgc)
redfield(val_tracer_name, bgc, tracers)

Returns the redfield ratio of tracer_name from bgc when it is constant across the domain.

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Biogeochemical Models

Nutrient Phytoplankton Zooplankton Detritus (NPZD)

OceanBioME.Models.NPZDModelModule

Nutrient-Phytoplankton-Zooplankton-Detritus model of Kuhn et al. (2015).

Tracers

  • Nutrients: N (mmol N/m³)
  • Phytoplankton: P (mmol N/m³)
  • Zooplankton: Z (mmol N/m³)
  • Detritus: D (mmol N/m³)

Required submodels

  • Photosynthetically available radiation: PAR (W/m²)
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OceanBioME.Models.NPZDModel.NutrientPhytoplanktonZooplanktonDetritusMethod
NutrientPhytoplanktonZooplanktonDetritus(; grid::AbstractGrid{FT},
                                           initial_photosynthetic_slope::FT = 0.1953 / day, # 1/(W/m²)/s
                                           base_maximum_growth::FT = 0.6989 / day, # 1/s
                                           nutrient_half_saturation::FT = 2.3868, # mmol N/m³
                                           base_respiration_rate::FT = 0.066 / day, # 1/s/(mmol N / m³)
                                           phyto_base_mortality_rate::FT = 0.0101 / day, # 1/s/(mmol N / m³)
                                           maximum_grazing_rate::FT = 2.1522 / day, # 1/s
                                           grazing_half_saturation::FT = 0.5573, # mmol N/m³
                                           assimulation_efficiency::FT = 0.9116, 
                                           base_excretion_rate::FT = 0.0102 / day, # 1/s/(mmol N / m³)
                                           zoo_base_mortality_rate::FT = 0.3395 / day, # 1/s/(mmol N / m³)²
                                           remineralization_rate::FT = 0.1213 / day, # 1/s

                                           surface_photosynthetically_active_radiation = default_surface_PAR,
                                           light_attenuation_model::LA =
                                               TwoBandPhotosyntheticallyActiveRadiation(; grid,
                                                                                          surface_PAR = surface_photosynthetically_active_radiation),
                                           sediment_model::S = nothing,
            
                                           sinking_speeds = (P = 0.2551/day, D = 2.7489/day),
                                           open_bottom::Bool = true,

                                           scale_negatives = false,
                                                                                  
                                           particles::P = nothing,
                                           modifiers::M = nothing)

Construct a Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) biogeochemical model.

Keyword Arguments

  • grid: (required) the geometry to build the model on, required to calculate sinking
  • initial_photosynthetic_slope, ..., remineralization_rate: NPZD parameter values
  • surface_photosynthetically_active_radiation: function (or array in the future) for the photosynthetically available radiation at the surface, should be shape f(x, y, t)
  • light_attenuation_model: light attenuation model which integrated the attenuation of available light
  • sediment_model: slot for AbstractSediment
  • sinking_speed: named tuple of constant sinking, of fields (i.e. ZFaceField(...)) for any tracers which sink (convention is that a sinking speed is positive, but a field will need to follow the usual down being negative)
  • open_bottom: should the sinking velocity be smoothly brought to zero at the bottom to prevent the tracers leaving the domain
  • scale_negatives: scale negative tracers?
  • particles: slot for BiogeochemicalParticles
  • modifiers: slot for components which modify the biogeochemistry when the tendencies have been calculated or when the state is updated

Example

julia> using OceanBioME

julia> using Oceananigans

julia> grid = RectilinearGrid(size=(20, 30), extent=(200, 200), topology=(Bounded, Flat, Bounded));

julia> model = NutrientPhytoplanktonZooplanktonDetritus(; grid)
NutrientPhytoplanktonZooplanktonDetritus{Float64} model, with (:P, :D) sinking 
 Light attenuation: Two-band light attenuation model (Float64)
 Sediment: Nothing
 Particles: Nothing
 Modifiers: Nothing
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The Lodyc-DAMTP Ocean Biogeochemical Simulation Tools for Ecosystem and Resources (LOBSTER)

OceanBioME.Models.LOBSTERModelModule

The Lodyc-DAMTP Ocean Biogeochemical Simulation Tools for Ecosystem and Resources (LOBSTER) model.

Tracers

  • Nitrates: NO₃ (mmol N/m³)
  • Ammonia: NH₄ (mmol N/m³)
  • Phytoplankton: P (mmol N/m³)
  • Zooplankton: Z (mmol N/m³)
  • Small (slow sinking) particulate organic matter: sPOM (mmol N/m³)
  • Large (fast sinking) particulate organic matter: bPOM (mmol N/m³)
  • Dissolved organic matter: DOM (mmol N/m³)

Optional tracers

Carbonate chemistry

  • Dissolved inorganic carbon: DIC (mmol C/m³)
  • Alkalinity: Alk (meq/m³)

Oxygen chemistry

  • Oxygen: O₂ (mmol O₂/m³)

Variable redfield

  • Small (slow sinking) particulate organic matter carbon content: sPOC (mmol C/m³)
  • Large (fast sinking) particulate organic matter carbon content: bPOC (mmol C/m³)
  • Dissolved organic matter carbon content: DOC (mmol C/m³)
  • When this option is enabled then the usual sPOM and bPOM change to sPON and bPON as they explicitly represent the nitrogen contained in the particulate matter

Required submodels

  • Photosynthetically available radiation: PAR (W/m²)

For optional tracers:

  • Temperature: T (ᵒC)
  • Salinity: S (‰)
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OceanBioME.Models.LOBSTERModel.LOBSTERMethod
LOBSTER(; grid::AbstractGrid{FT},
          phytoplankton_preference::FT = 0.5,
          maximum_grazing_rate::FT = 9.26e-6, # 1/s
          grazing_half_saturation::FT = 1.0, # mmol N/m³
          light_half_saturation::FT = 33.0, # W/m² (?)
          nitrate_ammonia_inhibition::FT = 3.0,
          nitrate_half_saturation::FT = 0.7, # mmol N/m³
          ammonia_half_saturation::FT = 0.001, # mmol N/m³
          maximum_phytoplankton_growthrate::FT = 1.21e-5, # 1/s
          zooplankton_assimilation_fraction::FT = 0.7,
          zooplankton_mortality::FT = 2.31e-6, # 1/s/mmol N/m³
          zooplankton_excretion_rate::FT = 5.8e-7, # 1/s
          phytoplankton_mortality::FT = 5.8e-7, # 1/s
          small_detritus_remineralisation_rate::FT = 5.88e-7, # 1/s
          large_detritus_remineralisation_rate::FT = 5.88e-7, # 1/s
          phytoplankton_exudation_fraction::FT = 0.05,
          nitrification_rate::FT = 5.8e-7, # 1/s
          ammonia_fraction_of_exudate::FT = 0.75, 
          ammonia_fraction_of_excriment::FT = 0.5,
          ammonia_fraction_of_detritus::FT = 0.0,
          phytoplankton_redfield::FT = 6.56, # mol C/mol N
          organic_redfield::FT = 6.56, # mol C/mol N
          phytoplankton_chlorophyll_ratio::FT = 1.31, # g Chl/mol N
          organic_carbon_calcate_ratio::FT = 0.1, # mol CaCO₃/mol C
          respiration_oxygen_nitrogen_ratio::FT = 10.75, # mol O/molN
          nitrification_oxygen_nitrogen_ratio::FT = 2.0, # mol O/molN
          slow_sinking_mortality_fraction::FT = 0.5, 
          fast_sinking_mortality_fraction::FT = 0.5,
          dissolved_organic_breakdown_rate::FT = 3.86e-7, # 1/s
          zooplankton_calcite_dissolution::FT = 0.3,

          surface_photosynthetically_active_radiation = default_surface_PAR,

          light_attenuation_model::LA =
              TwoBandPhotosyntheticallyActiveRadiation(; grid, 
                                                         surface_PAR = surface_photosynthetically_active_radiation),
          sediment_model::S = nothing,

          carbonates::Bool = false,
          oxygen::Bool = false,
          variable_redfield::Bool = false,

          sinking_speeds = (sPOM = 3.47e-5, bPOM = 200/day),
          open_bottom::Bool = true,

          scale_negatives = false,

          particles::P = nothing,
          modifiers::M = nothing)

Construct an instance of the LOBSTER biogeochemical model.

Keyword Arguments

  • grid: (required) the geometry to build the model on, required to calculate sinking
  • phytoplankton_preference, ..., dissolved_organic_breakdown_rate: LOBSTER parameter values
  • surface_photosynthetically_active_radiation: funciton (or array in the future) for the photosynthetically available radiation at the surface, should be shape f(x, y, t)
  • light_attenuation_model: light attenuation model which integrated the attenuation of available light
  • sediment_model: slot for AbstractSediment
  • carbonates, oxygen, and variable_redfield: include models for carbonate chemistry and/or oxygen chemistry and/or variable redfield ratio dissolved and particulate organic matter
  • sinking_speed: named tuple of constant sinking, of fields (i.e. ZFaceField(...)) for any tracers which sink (convention is that a sinking speed is positive, but a field will need to follow the usual down being negative)
  • open_bottom: should the sinking velocity be smoothly brought to zero at the bottom to prevent the tracers leaving the domain
  • scale_negatives: scale negative tracers?
  • particles: slot for BiogeochemicalParticles
  • modifiers: slot for components which modify the biogeochemistry when the tendencies have been calculated or when the state is updated

Example

julia> using OceanBioME

julia> using Oceananigans

julia> grid = RectilinearGrid(size=(3, 3, 30), extent=(10, 10, 200));

julia> model = LOBSTER(; grid)
LOBSTER{Float64} with carbonates ❌, oxygen ❌, variable Redfield ratio ❌ and (:sPOM, :bPOM) sinking 
 Light attenuation: Two-band light attenuation model (Float64)
 Sediment: Nothing
 Particles: Nothing
 Modifiers: Nothing
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Pelagic Interactions Scheme for Carbon and Ecosystem Studies (PISCES)

OceanBioME.Models.PISCESModelModule

Pelagic Interactions Scheme for Carbon and Ecosystem Studies (PISCES) model.

This is not currently an official version supported by the PISCES community and is not yet verified to be capable of producing results mathcing that of the operational PISCES configuration. This is a work in progress, please open an issue or discusison if you'd like to know more.

Notes to developers

Part of the vision for this implementation of PISCES is to harness the features of Julia that would allow it to be fully modular. An obvious step to improve the ease of this would be to do some minor refactoring to group the phytoplankton classes, and zooplankton classes together, and for the other groups to generically call the whole lot. This may cause some issues with argument passing, and although it may not be the best way todo it my first thought is to pass them round as named tuples built from something like,

phytoplankton_tracers = phytoplankton_arguments(bgc.phytoplankton, args...)
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OceanBioME.Models.PISCESModel.DepthDependantSinkingSpeedType
DepthDependantSinkingSpeed(; minimum_speed = 30/day,
                             maximum_speed = 200/day,
                             maximum_depth = 500)

Returns sinking speed for particles which sink at minimum_speed in the surface ocean (the deepest of the mixed and euphotic layers), and accelerate to maximum_speed below that depth and maximum_depth.

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OceanBioME.Models.PISCESModel.PISCESMethod
PISCES(; grid::AbstractGrid{FT},
         phytoplankton = MixedMondoNanoAndDiatoms(),
         zooplankton = MicroAndMesoZooplankton(),
         dissolved_organic_matter = DissolvedOrganicCarbon(),
         particulate_organic_matter = TwoCompartementCarbonIronParticles(),
         
         nitrogen = NitrateAmmonia(),
         iron = SimpleIron(),
         silicate = Silicate(),
         oxygen = Oxygen(),
         phosphate = Phosphate(),
         
         inorganic_carbon = InorganicCarbon(),

         # from Aumount 2005 rather than 2015 since it doesn't work the other way around
         first_anoxia_thresehold = 6.0,
         second_anoxia_thresehold = 1.0,

         nitrogen_redfield_ratio = 16/122,
         phosphate_redfield_ratio = 1/122,
         
         mixed_layer_shear = 1.0,
         background_shear = 0.01, 
         
         latitude = PrescribedLatitude(45),
         day_length = day_length_function,
         
         mixed_layer_depth = Field{Center, Center, Nothing}(grid),
         euphotic_depth = Field{Center, Center, Nothing}(grid),

         silicate_climatology = ConstantField(7.5),

         mean_mixed_layer_vertical_diffusivity = Field{Center, Center, Nothing}(grid),
         mean_mixed_layer_light = Field{Center, Center, Nothing}(grid),

         carbon_chemistry = CarbonChemistry(),
         calcite_saturation = CenterField(grid),

         surface_photosynthetically_active_radiation = default_surface_PAR,

         light_attenuation =
           MultiBandPhotosyntheticallyActiveRadiation(; grid, 
                                                        surface_PAR = surface_photosynthetically_active_radiation),

         sinking_speeds = (POC = 2/day, 
                           # might be more efficient to just precompute this
                           GOC = Field(KernelFunctionOperation{Center, Center, Face}(DepthDependantSinkingSpeed(), 
                                                                                     grid, 
                                                                                     mixed_layer_depth, 
                                                                                     euphotic_depth))),
         open_bottom = true,

         scale_negatives = false,
         invalid_fill_value = NaN,
         
         sediment = nothing,
         particles = nothing,
         modifiers = nothing)

Constructs an instance of the PISCES biogeochemical model.

Keyword Arguments

  • grid: (required) the geometry to build the model on
  • phytoplankton: phytoplankton evolution parameterisation, defaults to nanophyto and diatom size classes with MixedMondo growth
  • zooplankton: zooplankton evolution parameterisation, defaults to two class Z and M
  • dissolved_organic_matter: parameterisaion for the evolution of dissolved organic matter (DOC)
  • particulate_organic_matter: parameterisation for the evolution of particulate organic matter (POC, GOC, SFe, BFe, PSi, CaCO₃)
  • nitrogen: parameterisation for the nitrogen compartements (NH₄ and NO₃)
  • iron: parameterisation for iron (Fe), currently the "complex chemistry" of Aumount 2015 is not implemented
  • silicate: parameterisaion for silicate (Si)
  • oxygen: parameterisaion for oxygen (O₂)
  • phosphate: parameterisaion for phosphate (PO₄)
  • inorganic_carbon: parameterisation for the evolution of the inorganic carbon system (DIC and Alkalinity)
  • first_anoxia_thresehold and second_anoxia_thresehold: thresholds in anoxia parameterisation
  • nitrogen_redfield_ratio and phosphate_redfield_ratio: the assumed element ratios N/C and P/C
  • mixed_layer_shear and background_shear: the mixed layer and background shear rates, TODO: move this to a computed field
  • latitude: model latitude, should be PrescribedLatitude for RectilinearGrids and ModelLatitude for grids providing their own latitude
  • day_length: parameterisation for day length based on time of year and latitude, you may wish to change this to (φ, t) -> 1day if you want to ignore the effect of day length, or something else if you're modelling a differen planet
  • mixed_layer_depth: an AbstractField containing the mixed layer depth (to be computed during update state)
  • euphotic: an AbstractField containing the euphotic depth, the depth where light reduces to 1/1000 of the surface value (computed during update state)
  • silicate_climatology: an AbstractField containing the silicate climatology which effects the diatoms silicate half saturation constant
  • mean_mixed_layer_vertical_diffusivity: an AbstractField containing the mean mixed layer vertical diffusivity (to be computed during update state)
  • mean_mixed_layer_light: an AbstractField containing the mean mixed layer light (computed during update state)
  • carbon_chemistry: the CarbonChemistry model used to compute the calicte saturation
  • calcite_saturation: an AbstractField containing the calcite saturation (computed during update state)
  • surface_photosynthetically_active_radiation: funciton for the photosynthetically available radiation at the surface
  • light_attenuation_model: light attenuation model which integrated the attenuation of available light
  • sinking_speed: named tuple of constant sinking speeds, or fields (i.e. ZFaceField(...)) for any tracers which sink (convention is that a sinking speed is positive, but a field will need to follow the usual down being negative)
  • open_bottom: should the sinking velocity be smoothly brought to zero at the bottom to prevent the tracers leaving the domain
  • scale_negatives: scale negative tracers?
  • particles: slot for BiogeochemicalParticles
  • modifiers: slot for components which modify the biogeochemistry when the tendencies have been calculated or when the state is updated

All parameterisations default to the operaitonal version of PISCES as close as possible.

Notes

Currently only MixedMondoPhytoplankton are implemented, and some work should be done to generalise the classes to a single phytoplankton if more classes are required (see OceanBioME.Models.PISCESModel docstring). Similarly, if a more generic particulate_organic_matter was desired a way to specify arbitary tracers for arguments would be required.

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OceanBioME.Models.PISCESModel.ParticulateOrganicMatter.TwoCompartementCarbonIronParticlesType
TwoCompartementCarbonIronParticles

A quota parameterisation for particulate organic matter with two size classes, each with carbon and iron compartements, and a silicate compartement for the large size class.

Confusingly we decided to name these compartmenets POC and GOC for the small and large carbon classes, SFe and BFe for the small and ̶l̶a̶r̶g̶e̶ big iron compartements, and PSi for the ̶l̶a̶r̶g̶e̶ particulate silicon (not the phytoplankton silicon).

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OceanBioME.Models.PISCESModel.Iron.SimpleIronType
SimpleIron(; excess_scavenging_enhancement = 1000)

Parameterisation for iron evolution, not the "complex chemistry" model of Aumount et al, 2015. Iron is scavenged (i.e. perminemtly removed from the model) when the free iron concentration exeeds the ligand concentration at a rate modified by excess_scavenging_enhancement.

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OceanBioME.Models.PISCESModel.Zooplankton.QualityDependantZooplanktonType
QualityDependantZooplankton

The PISCES zooplankton growth model where each class has preferences for grazing on nanophytoplankton (P), diatoms (D), microzooplankton (Z), and particulate organic matter (POC), and can flux feed on sinking particulates (POC and GOC).

This model assumes a fixed ratio for all other elements (i.e. N, P, Fe).

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OceanBioME.Models.PISCESModel.Phytoplankton.GrowthRespirationLimitedProductionType
NutrientLimitedProduction

BaseProduction with light limitation moderated by nutrient availability. This is the "new production" PISCES phytoplankton growth rate model. Growth rate is of the form:

\[μ = μ₁f₁(τ)f₂(zₘₓₗ)(1-exp(-α θᶜʰˡ PAR / τ (bᵣ + μᵣ))) L.\]

Keyword Arguments

  • base_growth_rate: the base growth rate, μ₀, in (1/s)
  • temperatrue_sensetivity: temperature sensetivity parameter, b, giving μ₁ = μ₀ bᵀ where T is temperature
  • dark_tollerance: the time that the phytoplankton survives in darkness below the euphotic layer, τᵈ (s)
  • initial_slope_of_PI_curve: the relationship between photosynthesis and irradiance, α₀ (1/W/m²)
  • low_light_adaptation: factor increasing the sensetivity of photosynthesis to irradiance, β, giving α = α₀(1 + exp(-PAR)), typically set to zero
  • basal_respiration_rate: reference respiration rate, bᵣ (1/s)
  • reference_growth_rate: reference growth rate, μᵣ (1/s)
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OceanBioME.Models.PISCESModel.Phytoplankton.MixedMondoType
MixedMondo

Holds the parameters for the PISCES mixed mondo phytoplankton parameterisation where nutrient limitation is modelled using the mondo approach for nitrate (NO₃), ammonia (NH₄), phosphate (PO₄), and silicate (Si), but the quota approach is used for iron (Fe) and light (PAR).

Therefore each class has a carbon compartement (generically I), chlorophyll (IChl), and iron (IFe), and may also have silicate (ISi) if the nutrient_limitation specifies that the growth is silicate limited, despite the fact that the silicate still limits the growth in a mondo fashion.

The growth_rate may be different parameterisations, currently either NutrientLimitedProduction or GrowthRespirationLimitedProduction, which represent the typical and newprod versions of PISCES.

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OceanBioME.Models.PISCESModel.Phytoplankton.NutrientLimitedProductionType
NutrientLimitedProduction

BaseProduction with light limitation moderated by nutrient availability. This is the "origional" PISCES phytoplankton growth rate model. Growth rate is of the form:

\[μ = μ₁f₁(τᵈ)f₂(zₘₓₗ)(1-exp(-α θᶜʰˡ PAR / τ μ₀ L)) L.\]

Keyword Arguments

  • base_growth_rate: the base growth rate, μ₀, in (1/s)
  • temperatrue_sensetivity: temperature sensetivity parameter, b, giving μ₁ = μ₀ bᵀ where T is temperature
  • dark_tollerance: the time that the phytoplankton survives in darkness below the euphotic layer, τᵈ (s)
  • initial_slope_of_PI_curve: the relationship between photosynthesis and irradiance, α₀ (1/W/m²)
  • low_light_adaptation: factor increasing the sensetivity of photosynthesis to irradiance, β, giving α = α₀(1 + exp(-PAR)), typically set to zero
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OceanBioME.Models.PISCESModel.Nitrogen.NitrateAmmoniaType
NitrateAmmonia

A parameterisation for the evolution of nitrate (NO₃) and ammonia (NH₄) where ammonia can be nitrified into nitrate, nitrate and ammonia are supplied by the bacterial degredation of dissolved organic matter, and consumed by phytoplankton. Additionally waste produces ammonia through various means.

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Sugar kelp (Saccharina latissima)

OceanBioME.Models.SugarKelpModel.SugarKelpParticlesMethod
SugarKelpParticles(n; grid, kelp_parameters = NamedTuple(), kwargs...)

Sets up n sugar kelp BiogeochemicalParticles with default parameters except those specified in kelp_parameters. kwagrs are passed onto BiogeochemicalParticles.

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Carbon Chemistry

OceanBioME.Models.CarbonChemistryModel.CarbonChemistryMethod
(p::CarbonChemistry)(; DIC, T, S, Alk = 0, pH = nothing,
                       return_pH = false,
                       boron = 0.000232 / 10.811 * S / 1.80655,
                       sulfate = 0.14 / 96.06 * S / 1.80655,
                       fluoride = 0.000067 / 18.9984 * S / 1.80655,
                       silicate = 0,
                       phosphate = 0,
                       upper_pH_bound = 14,
                       lower_pH_bound = 0)

Calculates fCO₂ in sea water with DIC, Alkalinity, Temperature, and Salinity unless pH is specified, in which case intermediate computation of pH is skipped and pCO₂ is calculated from the DIC, T, S and pH.

Alternativly, pH is returned if return_pH is true.

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OceanBioME.Models.CarbonChemistryModel.K0Type
K0(; constant = -60.2409,
     inverse_T =  93.4517 * 100,
     log_T =  23.3585,
     T² =  0.0,
     S =  0.023517,
     ST = -0.023656 / 100,
     ST² =  0.0047036 / 100^2)

Parameterisation for carbon dioxide solubility equilibrium constant.

CO₂(g) ⇌ CO₂*(aq)

K₀ = [CO₂*(aq)]/f(CO₂)

Default values from Weiss, R.F. (1974, Mar. Chem., 2, 203–215).

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OceanBioME.Models.CarbonChemistryModel.K1Type
K1(FT = Float64;
   constant =  61.2172,
   inverse_T = -3633.86,
   log_T = -9.67770,
   S =  0.011555,
   S² = -0.0001152,
   pressure_correction = PressureCorrection(FT; a₀=-25.50, a₁=0.1271, a₂=0.0, b₀=-0.00308, b₁=0.0000877))

Parameterisation for aquious carbon dioxide - bicarbonate dissociation equilibrium constant.

CO₂*(aq) + H₂O ⇌ H₂CO₃ ⇌ HCO₃⁻ + H⁺

K₁ = [H⁺][HCO₃⁻]/[CO₂*]

Default values from Lueker et al. (2000, Mar. Chem., 70: 105–119).

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OceanBioME.Models.CarbonChemistryModel.K2Type
K2(FT = Float64;
   constant = -25.9290,
   inverse_T = -471.78,
   log_T = 3.16967,
   S = 0.01781,
   S² = -0.0001122,
   pressure_correction = PressureCorrection(FT; a₀=-15.82, a₁=-0.0219, a₂=0.0, b₀=0.00113, b₁=-0.0001475))

Parameterisation for bicarbonate dissociation equilibrium constant.

HCO₃⁻ ⇌ CO₃²⁻ + H⁺

K₂ = [H⁺][CO₃²⁻]/[HCO₃⁻]

Default values from Lueker et al. (2000, Mar. Chem., 70: 105–119).

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OceanBioME.Models.CarbonChemistryModel.KBType
KB(FT = Float64;
   constant =  148.0248,
   inverse_T = -8966.90,
   inverse_T_sqrt_S = -2890.53,
   inverse_T_S = -77.942,
   inverse_T_sqrt_S³ =  1.728,
   inverse_T_S² = -0.0996,
   sqrt_S = 137.1942,
   S = 1.62142,
   log_T = -24.4344,
   log_T_sqrt_S = -25.085,
   S_log_T = -0.2474,
   T_sqrt_S =  0.053105,
   pressure_correction = PressureCorrection(FT; a₀=-29.48, a₁=0.1622, a₂=-0.0026080, b₀=-0.00284, b₁=0.0))

Parameterisation for boric acid equilibrium with water.

B(OH)₃ + H₂O ⇌ B(OH)₄⁻ + H⁺

Kᵇ = [H⁺][B(OH)₄⁻]/[B(OH)₃]

Default values from Dickson (1990, Deep-Sea Res., 37, 755–766).

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OceanBioME.Models.CarbonChemistryModel.KFType
KF(; ionic_strength = IonicStrength(),
      sulfate_constant = KS(; ionic_strength),
      constant = -9.68,
      inverse_T = 874.0,
      sqrt_S =  0.111,
      log_S = 0.0,
      log_S_KS = 0.0,
      pressure_correction = 
         PressureCorrection(; a₀=-9.78, a₁=-0.0090, a₂=-0.000942, b₀=-0.00391, b₁=0.000054))

Parameterisation for hydrogen fluoride dissociation equilibrium constant.

HF ⇌ F⁻ + H⁺

Kᶠ = [H⁺][F⁻]/[HF]

Default values from Perez and Fraga (1987, Mar. Chem., 21, 161–168).

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OceanBioME.Models.CarbonChemistryModel.KPType
KP(constant,
   inverse_T,
   log_T,
   sqrt_S,
   inverse_T_sqrt_S,
   S,
   inverse_T_S,
   pressure_correction)

Generic equilibrium constant parameterisation of the form used by Millero (1995, Geochim. Cosmochim. Acta, 59, 661–677) for phosphoric acid dissociation.

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OceanBioME.Models.CarbonChemistryModel.KSType
KS(; constant =  148.9652,
     inverse_T = -13847.26,
     log_T = -23.6521,
     sqrt_S = -5.977,
     inverse_T_sqrt_S =  118.67,
     log_T_sqrt_S =  1.0495,
     S = -0.01615,
     pressure_correction = 
        PressureCorrection(; a₀=-18.03, a₁=0.0466, a₂=0.000316, b₀=-0.00453, b₁=0.00009))

Parameterisation for bisulfate dissociation equilibrium constant.

HSO₄⁻ ⇌ SO₄²⁻ + H⁺

Kˢ = [H⁺][SO₄²⁻]/[HSO₄⁻]

Default values from Dickson (1990, Chem. Thermodyn., 22, 113–127).

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OceanBioME.Models.CarbonChemistryModel.KSPType
KSP(therm_constant,
    therm_T,
    therm_inverse_T,
    therm_log_T,
    sea_sqrt_S,
    sea_T_sqrt_S,
    sea_inverse_T_sqrt_S,
    sea_S,
    sea_S_sqrt_S³,
    pressure_correction)

Generic CaCO₃ solubility parameterisation of the form given by Form from Millero, F. J. (2007, Chemical Reviews, 107(2), 308–341).

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OceanBioME.Models.CarbonChemistryModel.KSiType
KSi(; ionic_strength = IonicStrength(),
      constant =  117.385,
      inverse_T = -8904.2,
      log_T = -19.334,
      sqrt_Is = 3.5913,
      inverse_T_sqrt_Is = -458.79,
      Is = -1.5998,
      inverse_T_Is = 188.74,
      Is² = 0.07871,
      inverse_T_Is² = -12.1652,
      log_S = -0.001005)

Parameterisation for silicic acid dissociation equilibrium constant.

Si(OH)₄ ⇌ SiO(OH)₃⁻ + H⁺

Kʷ = [H⁺][SiO(OH)₃⁻]/[Si(OH)₄]

Default values from Millero (1995, Geochim. Cosmochim. Acta, 59, 661–677).

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OceanBioME.Models.CarbonChemistryModel.KWType
KW(; constant =  148.9652,
     inverse_T = -13847.26,
     log_T = -23.6521,
     sqrt_S = -5.977,
     inverse_T_sqrt_S =  118.67,
     log_T_sqrt_S =  1.0495,
     S = -0.01615,
     pressure_correction = 
        PressureCorrection(; a₀=-20.02, a₁=0.1119, a₂=-0.001409, b₀=-0.00513, b₁=0.0000794))

Parameterisation for water dissociation equilibrium constant.

H₂O ⇌ OH⁻ + H⁺

Kʷ = [H⁺][OH⁻]

Default values from Millero (1995, Geochim. Cosmochim. Acta, 59, 661–677).

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OceanBioME.Models.CarbonChemistryModel.KP1Method
KP1(; constant = 115.525,
      inverse_T = -4576.752,
      log_T = - 18.453,
      sqrt_S = 0.69171,
      inverse_T_sqrt_S = -106.736,
      S = -0.01844,
      inverse_T_S = -0.65643,
      pressure_correction = 
         PressureCorrection(; a₀=-14.51, a₁=0.1211, a₂=-0.000321, b₀=-0.00267, b₁=0.0000427))

Instance of KP returning the first phosphocic acid equilibrium constant.

H₃PO₄ ⇌ H₂PO₄⁻ + H⁺

Kᵖ¹ = [H⁺][H₂PO₄]/[H₃PO₄]

Default values from Millero (1995, Geochim. Cosmochim. Acta, 59, 661–677).

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OceanBioME.Models.CarbonChemistryModel.KP2Method
KP2(; constant = 172.0883,
      inverse_T = -8814.715,
      log_T = -27.927,
      sqrt_S = 1.3566,
      inverse_T_sqrt_S = -160.340,
      S = -0.05778,
      inverse_T_S = 0.37335,
      pressure_correction = 
        PressureCorrection(; a₀=-23.12, a₁=0.1758, a₂=-0.002647, b₀=-0.00515, b₁=0.00009))

Instance of KP returning the second phosphocic acid equilibrium constant.

H₂PO₄⁻ ⇌ HPO₄²⁻ + H⁺

Kᵖ² = [H⁺][HPO₄²⁻]/[H₂PO₄⁻]

Default values from Millero (1995, Geochim. Cosmochim. Acta, 59, 661–677).

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OceanBioME.Models.CarbonChemistryModel.KP3Method
KP3(; constant = -18.141,
      inverse_T = -3070.75,
      log_T = 0.0,
      sqrt_S = 2.81197,
      inverse_T_sqrt_S = 17.27039,
      S = -0.09984,
      inverse_T_S = -44.99486,
      pressure_correction = 
        PressureCorrection(; a₀=-26.57, a₁=0.2020, a₂=-0.0030420, b₀=-0.00408, b₁=0.0000714))

Instance of KP returning the third phosphocic acid equilibrium constant.

HPO₄²⁻ ⇌ PO₄ + H⁺

Kᵖ³ = [H⁺][PO₄³⁻]/[HPO₄⁻]

Default values from Millero (1995, Geochim. Cosmochim. Acta, 59, 661–677).

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OceanBioME.Models.CarbonChemistryModel.KSP_aragoniteFunction

KSParagonite(; thermconstant = -171.945, thermT = -0.077993, therminverseT = 2903.293, thermlogT = 71.595, seasqrtS = -0.068393, seaTsqrtS = 0.0017276, seainverseTsqrtS = 88.135, seaS = -0.10018, seaSsqrtS³ = 0.0059415, pressure_correction = PressureCorrection(; a₀=-45.96, a₁=0.5304, a₂=-0.0, b₀=-0.01176, b₁=0.0003692))

Instance of KSP returning calcite solubility.

Default values from Millero, F. J. (2007, Chemical Reviews, 107(2), 308–341).

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OceanBioME.Models.CarbonChemistryModel.KSP_calciteFunction
KSP_calcite(; therm_constant = -171.9065,
              therm_T = -0.077993,
              therm_inverse_T = 2839.319,
              therm_log_T = 71.595,
              sea_sqrt_S = -0.77712,
              sea_T_sqrt_S = 0.0028426,
              sea_inverse_T_sqrt_S = 178.34,
              sea_S = -0.07711,
              sea_S_sqrt_S³ = 0.0041249,
              pressure_correction =
                  PressureCorrection(; a₀=-48.76, a₁=0.5304, a₂=-0.0, b₀=-0.01176, b₁=0.0003692))

Instance of KSP returning calcite solubility.

Default values from Millero, F. J. (2007, Chemical Reviews, 107(2), 308–341).

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OceanBioME.Models.CarbonChemistryModel.alkalinity_residualMethod
alkalinity_residual(H, p)

Returns the difference between total alkalinity computed from H(hydrogen ion concentration),DIC,borate,sulfate,phosphate,silicate, andfluorideconcentration and chemical equilibrium constants specified inp, and the specified totalAlk`alinity.

TAlk = [HCO₃⁻] + 2[CO₃²⁻] + [B(OH)₄⁻] + [OH⁻] + [HPO₄²⁻] + 2[PO₄³⁻] + [SiO(OH)₃⁻] 
       + [NH₃] + [HS⁻] - [H⁺] - [HSO₄⁻] - [HF] - [H₃PO₄] + minor acids and bases

Concentrations diagnosed as specified in Dickson et. al best practice descried in CarbonChemistry docstring.

Note ammonia (NH₃) is not currently included.

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Light Attenuation Models

OceanBioME.Light.MultiBandPhotosyntheticallyActiveRadiationType
MultiBandPhotosyntheticallyActiveRadiation{F, FN, K, E, C, SPAR, SPARD}

Light attenuation model with multiple wave length bands where each band (i) is attenuated like:

∂PARᵢ(z)/∂z = PARᵢ(kʷ(i) + χ(i)Chl(z)ᵉ⁽ⁱ⁾)

Where kʷ(i) is the band specific water attenuation coefficient, e(i) the chlorophyll exponent, and χ(i) the chlorophyll attenuation coefficient.

When the fields are called with biogeochemical_auxiliary_fields an additional field named PAR is also returned which is a sum of the bands.

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OceanBioME.Light.MultiBandPhotosyntheticallyActiveRadiationMethod
MultiBandPhotosyntheticallyActiveRadiation(; grid::AbstractGrid{FT}, 
                                             bands = ((400, 500), (500, 600), (600, 700)), #nm
                                             base_bands = MOREL_λ,
                                             base_water_attenuation_coefficient = MOREL_kʷ,
                                             base_chlorophyll_exponent = MOREL_e,
                                             base_chlorophyll_attenuation_coefficient = MOREL_χ,
                                             field_names = [par_symbol(n, length(bands)) for n in 1:length(bands)],
                                             surface_PAR = default_surface_PAR)

Returns a MultiBandPhotosyntheticallyActiveRadiation attenuation model of surface_PAR in divided into bands by surface_PAR_division.

The attenuation morelcoefficients are computed from `basewaterattenuationcoefficient,basechlorophyllexponent, andbasechlorophyllattenuationcoefficientwhich should be arrays of the coefficients atbasebands` wavelengths.

The returned field_names default to PAR₁, PAR₂, etc., but may be specified by the user instead.

Keyword Arguments

  • grid: grid for building the model on
  • water_red_attenuation, ..., phytoplankton_chlorophyll_ratio: parameter values
  • surface_PAR: function (or array in the future) for the photosynthetically available radiation at the surface, which should be f(x, y, t) where x and y are the native coordinates (i.e. meters for rectilinear grids and latitude/longitude as appropriate)
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OceanBioME.Light.PrescribedPhotosyntheticallyActiveRadiationType
PrescribedPhotosyntheticallyActiveRadiation(fields)

PrescribedPhotosyntheticallyActiveRadiation returns "prescribed" PAR fields which are user specified, e.g. they may be FunctionFields or ConstantFields.

fields may either be an AbstractField or a NamedTuple of names and fields which will be returned in biogeochemical_auxiliary_fields, if only one field is present the field will be named PAR.

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OceanBioME.Light.TwoBandPhotosyntheticallyActiveRadiationMethod
TwoBandPhotosyntheticallyActiveRadiation(; grid::AbstractGrid{FT}, 
                                           water_red_attenuation::FT = 0.225, # 1/m
                                           water_blue_attenuation::FT = 0.0232, # 1/m
                                           chlorophyll_red_attenuation::FT = 0.037, # 1/(m * (mgChl/m³) ^ eʳ)
                                           chlorophyll_blue_attenuation::FT = 0.074, # 1/(m * (mgChl/m³) ^ eᵇ)
                                           chlorophyll_red_exponent::FT = 0.629,
                                           chlorophyll_blue_exponent::FT = 0.674,
                                           pigment_ratio::FT = 0.7,
                                           phytoplankton_chlorophyll_ratio::FT = 1.31,
                                           surface_PAR::SPAR = default_surface_PAR)

Keyword Arguments

  • grid: grid for building the model on
  • water_red_attenuation, ..., phytoplankton_chlorophyll_ratio: parameter values
  • surface_PAR: function (or array in the future) for the photosynthetically available radiation at the surface, which should be f(x, y, t) where x and y are the native coordinates (i.e. meters for rectilinear grids and latitude/longitude as appropriate)
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Sediments

OceanBioME.Models.Sediments.InstantRemineralisationMethod
InstantRemineralisation(; grid,
    burial_efficiency_constant1::FT = 0.013,
    burial_efficiency_constant2::FT = 0.53,
    burial_efficiency_half_saturation::FT = 7)

Return a single-layer instant remineralisaiton model for NPZD bgc models.

Example

using OceanBioME, Oceananigans, OceanBioME.Sediments

grid = RectilinearGrid(size=(3, 3, 30), extent=(10, 10, 200))

sediment_model = InstantRemineralisation(; grid)
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OceanBioME.Models.Sediments.SimpleMultiGMethod
SimpleMultiG(; grid
               fast_decay_rate = 2/day,
               slow_decay_rate = 0.2/day,
               fast_redfield = 0.1509,
               slow_redfield = 0.13,
               fast_fraction = 0.74,
               slow_fraction = 0.26,
               refactory_fraction = 0.1,
               nitrate_oxidation_params = on_architecture(architecture(grid), [- 1.9785, 0.2261, -0.0615, -0.0289, - 0.36109, - 0.0232]),
               denitrification_params = on_architecture(architecture(grid), [- 3.0790, 1.7509, 0.0593, - 0.1923, 0.0604, 0.0662]),
               anoxic_params = on_architecture(architecture(grid), [- 3.9476, 2.6269, - 0.2426, -1.3349, 0.1826, - 0.0143]),
               solid_dep_params = on_architecture(architecture(grid), [0.233, 0.336, 982.0, - 1.548]))

Return a single-layer "multi G" sediment model (SimpleMultiG) on grid, where parameters can be optionally specified.

The model is a single layer (i.e. does not include porous diffusion) model with three classes of sediment organic matter which decay at three different rates (fast, slow, refactory). The nitrification/denitrification/anoxic mineralisation fractions default to the parameterisation of Soetaert et al. 2000; doi:10.1016/S0012-8252(00)00004-0.

This model has not yet been validated or compared to observational data. The variety of degridation processes is likely to be strongly dependent on oxygen availability (see https://bg.copernicus.org/articles/6/1273/2009/bg-6-1273-2009.pdf) so it will therefore be important to also thoroughly validate the oxygen model (also currently limited).

Example

julia> using OceanBioME, Oceananigans, OceanBioME.Sediments

julia> grid = RectilinearGrid(size=(3, 3, 30), extent=(10, 10, 200));

julia> sediment_model = SimpleMultiG(; grid)
┌ Warning: Sediment models are an experimental feature and have not yet been validated.
└ @ OceanBioME.Models.Sediments ~/Documents/Projects/OceanBioME.jl/src/Models/Sediments/simple_multi_G.jl:104
[ Info: This sediment model is currently only compatible with models providing NH₄, NO₃, O₂, and DIC.
Single-layer multi-G sediment model (Float64)
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Gas exchange boundary conditions

OceanBioME.Models.GasExchangeModel.CarbonDioxideConcentrationType
CarbonDioxideConcentration(; carbon_chemistry, 
                             first_virial_coefficient = PolynomialVirialCoefficientForCarbonDioxide(),
                             cross_viral_coefficient = CrossVirialCoefficientForCarbonDioxide(),
                             air_pressue = 1 # atm)

Converts fCO₂ to partial pressure as per Dickson, A.G., Sabine, C.L. and Christian, J.R. (2007), Guide to Best Practices for Ocean CO 2 Measurements. PICES Special Publication 3, 191 pp.

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OceanBioME.Models.GasExchangeModel.GasExchangeType
GasExchange

GasExchange returns the air-sea flux of a gas betwen water_concentration and air_concentration with a transfer_velocity computed from the temperature (provided later), and the wind_speed.

transfer_velocity should behave as a function of wind speed and temperature (i.e. k(u, T)), water_concentration a function of c(x, y, t, T, field_dependencies...).

water_concentration, air_concentration and wind_speed can either be numbers, functions of the form (x, y, t), functions of the form (i, j, grid, clock, model_fields) if discrete_form is set to true, or any kind of Field.

water_concentration should usually be a [Tracer]Concentration where is the name of the tracer (you will have to build your own if this is not OxygenConcentration), or a CarbonDioxideConcentration which diagnoses the partial pressure of CO₂ in the water.

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OceanBioME.Models.GasExchangeModel.PartiallySolubleGasType
PartiallySolubleGas(; air_concentration, solubility)

Parameterises the available concentration of a gas dissolving in water in the form $\alpha C_a$ where $lpha$ is the Ostwald solubility coeffieient and $C_a$ is the concentration in the air.

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OceanBioME.Models.GasExchangeModel.CarbonDioxideGasExchangeBoundaryConditionFunction
CarbonDioxideGasExchangeBoundaryCondition(FT = Float64; 
                                          carbon_chemistry = CarbonChemistry(FT),
                                          transfer_velocity = SchmidtScaledTransferVelocity(schmidt_number = CarbonDioxidePolynomialSchmidtNumber(FT)),
                                          air_concentration = 413, # ppmv
                                          wind_speed = 2,
                                          water_concentration = nothing,
                                          silicate_and_phosphate_names = nothing,
                                          kwargs...)

Returns a FluxBoundaryCondition for the gas exchange between carbon dioxide dissolved in the water specified by the carbon_chemisty model, and air_concentration with transfer_velocity (see GasExchangeBoundaryCondition for details).

silicate_and_phosphate_names should either be nothing, a Tupleof symbols specifying the name of the silicate and phosphate tracers, or aNamedTupleof values for thecarbon_chemistry` model.

kwargs are passed on to GasExchangeBoundaryCondition.

Note: The model always requires T, S, DIC, and Alk to be present in the model.

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OceanBioME.Models.GasExchangeModel.GasExchangeBoundaryConditionFunction
GasExchangeBoundaryCondition(; water_concentration,
                               air_concentration,
                               transfer_velocity,
                               wind_speed)

Returns a FluxBoundaryCondition for the gas exchange between water_concentration and air_concentration with transfer_velocity.

water_concentration, air_concentration and wind_speed can either be numbers, functions of the form (x, y, t), functions of the form (i, j, grid, clock, model_fields) if discrete_form is set to true, or any kind of Field.

water_concentration should usually be a [Tracer]Concentration where is the name of the tracer (you will have to build your own if this is not OxygenConcentration), or a CarbonDioxideConcentration which diagnoses the partial pressure of CO₂ in the water.

transfer_velocity should be a function of the form k(u₁₀, T).

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OceanBioME.Models.GasExchangeModel.OxygenGasExchangeBoundaryConditionFunction
OxygenGasExchangeBoundaryCondition(FT = Float64; 
                                   transfer_velocity = SchmidtScaledTransferVelocity(schmidt_number = OxygenPolynomialSchmidtNumber(FT)),
                                   water_concentration = OxygenConcentration(),
                                   air_concentration = 9352.7, # mmolO₂/m³
                                   wind_speed = 2,
                                   kwagrs...)

Returns a FluxBoundaryCondition for the gas exchange between oxygen dissolved in the water specified by the the OxygenConcentration in the base model, and air_concentration with transfer_velocity (see GasExchangeBoundaryCondition for details).

kwargs are passed on to GasExchangeBoundaryCondition.

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OceanBioME.Models.GasExchangeModel.ScaledGasTransferVelocity.SchmidtScaledTransferVelocityType
SchmidtScaledTransferVelocity(; schmidt_number, 
                                base_transfer_velocity = Ho06())

Returns a model for gas transfer velocity which depends on the u₁₀, the 10m-wind, and Temperature. The model is of the typical form:

k(u₁₀, T) = k₆₆₀(u₁₀) √(660/Sc(T))

The base_transfer_velocity (k₆₆₀) is typically an empirically derived gas transfer velocity normalised by the Scmidt number for CO₂ at 20°C (660), and the schmidt_number (Sc) is a parameterisation of the gas specific Schmidt number.

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Box Model

OceanBioME.BoxModels.BoxModelMethod
BoxModel(; biogeochemistry,
           forcing = NamedTuple(),
           timestepper = :RungeKutta3,
           clock = Clock(; time = 0.0),
           prescribed_tracers::PT = NamedTuple())

Constructs a box model of a biogeochemistry model. Once this has been constructed you can set initial condiitons by set!(model, X=1.0...).

Keyword Arguments

  • biogeochemistry: (required) an OceanBioME biogeochemical model, most models must be passed a grid which can be set to a BoxModelGrid for box models
  • forcing: NamedTuple of additional forcing functions for the biogeochemical tracers to be integrated
  • timestepper: Timestepper to integrate model
  • clock: Oceananigans clock to keep track of time
  • prescribed_tracers: named tuple of tracer names and function (f(t)) prescribing tracer values
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Oceananigans.Fields.set!Method
set!(model::BoxModel; kwargs...)

Set the values for a BoxModel

Arguments

  • model - the model to set the arguments for

Keyword Arguments

  • variables and value pairs to set
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Particles

OceanBioME.Particles.BiogeochemicalParticlesMethod
BiogeochemicalParticles(number; 
                        grid,
                        biogeochemistry,
                        advection = LagrangianAdvection(),
                        timestepper = ForwardEuler,
                        field_interpolation = NearestPoint(),
                        scalefactors = ones(number))

Creates number particles with biogeochemistry on grid, advected by advection which defaults to LagrangianAdvection (i.e. they comove with the water). The biogeochemistry is stepped by timestepper and tracer fields are interpolated by field_interpolation, which defaults to directly reading the nearest center point and taking up/depositing in the same.

Particles can also have a scalefactor which scales their tracer interaction (e.g. to mimic the particle representing multiple particles).

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