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p4zbc

Overview

The p4zbc module handles the reading, interpolation, and application of time-varying external nutrient fluxes from atmospheric deposition, river inputs, sediment mobilization, hydrothermal vents, and sea ice supplies.

Version: NEMO 5.0
Model: PISCES (version NEMO 5.0)
Subroutines: p4z_bc, p4z_bc_init


p4z_bc

Main routine that applies external nutrient sources at each time step.

1. Atmospheric Dust Deposition

External nutrient input from dust deposition which dissolve in the water column (calculated from the 2\(^{nd}\) ocean level)

Activation: ll_dust = .TRUE.

Affected Tracers:

  • Iron (Fe): jpfer
  • Phosphate (PO4): jppo4 (p4z and p5z only)
  • Silicate (Si): jpsil (p4z and p5z only)

Key Features:

  • Reads dust deposition from external NetCDF files
  • Applies vertical dissolution profile for Fe, PO4, Si: exponential decay with 250m e-folding depth
  • Iron solubilization: 3.5% of dust iron is soluble
  • Dissolution rate: 1/(250 days)
  • Sinking speed: configurable via wdust parameter

Mineral Fractions:

  • Iron: mfrac / mMass_Fe
  • Phosphate: 1.e-3 / mMass_P
  • Silicate: 0.269 / mMass_Si

2. River Input

External input of nutrients from river.

Activation: ll_river = .TRUE.

Affected Tracers:

  • Nitrate (NO3): jpno3
  • Total Alkalinity (TALK): jptal (indirect effect)

Key Features:

  • Reads river nutrient concentrations from boundary condition files
  • Distributes input over river runoff depth or surface layer
  • Adjusts alkalinity due to nitrogen input

Implementation:

  • With runoff (ln_rnf = .TRUE.): Distributes over nk_rnf levels
  • Without runoff: Applies to surface layer only

3. Nitrogen Deposition

Activation: ll_ndepo = .TRUE.

Affected Tracers:

  • Nitrate (NO\(_3\)): jpno3
  • Ammonium (NH\(_4\)): jpnh4 (p4z and p5Z only)
  • Total Alkalinity (TALK): jptal

Key Features:

  • Atmospheric deposition of oxidized and reduced nitrogen
  • Applied to surface layer only
  • Accounts for alkalinity effects:
    • NO\(_3\) decreases TALK
    • NH\(_4\) increases TALK

4. Sea-Ice Iron Source

Activation: ln_ironice = .TRUE.

Affected Tracers:

  • Iron (Fe): jpfer

Key Features:

  • Simple parameterization based on Lancelot et al, 20091
  • Constant Fe concentration in sea ice: icefeinput
  • Fe flux computed from ice formation/melting rate
  • Limited to prevent complete Fe depletion: maximum 99% removal

5. Sediment Iron Mobilization

Activation: ln_ironsed = .TRUE.

Affected Tracers:

  • Iron (Fe): jpfer

Key Features:

  • Coastal and shelf iron supply
  • Spatially variable based on:
    • Distance from coast
    • Bathymetry
    • Continental slope geometry
  • Active only in upper 50m when available
  • Uses pre-computed mask from external file (pre-computed sediment Fe field)
  • Denitride function applied for intensity modulation

6. Hydrothermal Vent Iron

Activation: ln_hydrofe = .TRUE.

Affected Tracers:

  • Iron (Fe): jpfer
  • Weak ligands (LGW): jplgw (if ln_ligand = .TRUE.)

Key Features:

  • Reads 3D helium-3 flux from external files
  • Converts to iron using Fe:3He ratio (hratio)
  • Optional ligand co-release at ratio lgw_rath
  • 3D implementation

Input parameters

Parameter Type Intent Description
kt INTEGER IN Ocean time step index
Kbb INTEGER IN Time level index (before)
Kmm INTEGER IN Time level index (now/middle)
Krhs INTEGER IN Right-hand side index

Unit Conversions

  • Dust: kg/m²/s → mol Fe/m³/s via mfrac/mMass_Fe
  • Hydrothermal: nmol/cm²/s → mol/m³/s with volume and time adjustments
  • Time scaling: rfact converts per-second to per-timestep rates

7. Output Diagnostics

The module provides the following diagnostic fields via iom_put:

Field Name Units Description
Irondep mmol/m²/s Atmospheric iron deposition
Po4dep mmol/m²/s Atmospheric phosphate deposition
Sildep mmol/m²/s Atmospheric silicate deposition
No3dep mmol/m²/s Atmospheric nitrate deposition
Nh4dep mmol/m²/s Atmospheric ammonium deposition
pdust kg/m²/s Surface dust concentration
Ironice mmol/m²/s Iron flux from sea ice
Ironsed mmol/m³/s Sediment iron supply
HYDR mmol/m³/s Hydrothermal iron input

p4z_bc_init

Initialization routine for external nutrient sources. The module reads the files and computes the budget called at the first timestep.

Execution Sequence

  1. Read namelist parameters in nampisbc
  2. Determine which sources are enabled
  3. Allocate required arrays
  4. Initialize field reading structures for dust and hydrothermal inputs
  5. Compute sediment iron mask if ln_ironsed = .TRUE.
  6. Write configuration summary to output

Input parameters

Parameter Type Intent Description
Kmm INTEGER IN Time level index (now/middle)

Namelist Parameters

Variable Type Units Description
sedfeinput REAL(wp) - Coastal iron release rate
icefeinput REAL(wp) mol/L Iron concentration in sea ice
wdust REAL(wp) m/d Sinking speed of dust particles
mfrac REAL(wp) - Mineral content of dust
lgw_rath REAL(wp) - Weak ligand ratio from hydrothermal sources
hratio REAL(wp) - Fe:3He ratio for hydrothermal vent iron supply
distcoast REAL(wp) (m) Distance off coast for sediment iron calculation

Data Array Allocation

Variable Dimensions Description
dust (jpi, jpj) Surface dust deposition field
ironsed (jpi, jpj, jpk) Coastal iron supply from sediments
hydrofe (jpi, jpj, jpk) Hydrothermal vent iron supply
zcmask (jpi, jpj, jpk) Coastal/island iron mask

Control Flags

Variable Type Description
ln_ironsed LOGICAL Enable iron input from sediments
ln_hydrofe LOGICAL Enable iron input from hydrothermal vents
ln_ironice LOGICAL Enable iron exchange with sea ice
ll_bc LOGICAL Master switch for boundary conditions
ll_dust LOGICAL Enable atmospheric dust input
ll_river LOGICAL Enable river nutrient input
ll_ndepo LOGICAL Enable atmospheric nitrogen deposition

Document Version: 1.0
Last Updated: October 2025
Source code: NEMO 5.0


  1. C. Lancelot, A. de Montety, H. Goosse, S. Becquevort, V. Schoemann, B. Pasquer, and M. Vancoppenolle. Spatial distribution of the iron supply to phytoplankton in the southern ocean: a model study. Biogeosciences, 6(12):2861–2878, 2009. URL: https://bg.copernicus.org/articles/6/2861/2009/, doi:10.5194/bg-6-2861-2009