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DMS_mod.F90
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DMS_mod.F90
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!|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
module DMS_mod
!BOP
! !MODULE: DMS_mod
!
! !DESCRIPTION:
!
!------------------------------------------------------------------------------
! Multispecies trace gas processing routine based on Chu, Elliott, Maltrud,
! Erickson and company papers > 2000, on references therein,
! and also on assorted supplementary materials as indicated in comments.
! Designed for insertion into POP and CCSM along with DML ecosys_mod
! Trace gases defined roughly as those of concentration order nanomolar or less
! This excludes CO2 and O2 which are handled inside NCAR ecodynamics
!------------------------------------------------------------------------------
!------------------------------------------------------------------------------
! variables/subroutines/functions used from other modules
! The following are called upon extensively in tracegas, and so appear at
! the module level. The use statements for variables that are only needed
! locally are dealt with at the module subprogram level.
!------------------------------------------------------------------------------
! !REVISION HISTORY:
! SVN:$Id: $
!-----------------------------------------------------------------------
!-----------------------------------------------------------------------
! !USES:
! !INPUT PARAMETERS:
!-----------------------------------------------------------------------------
! include tracegas and ecosystem parameters
! all variables from these modules have a parm_ prefix
!-----------------------------------------------------------------------------
use DMS_parms
implicit none
save
private
!-----------------------------------------------------------------------
! public/private declarations
!-----------------------------------------------------------------------
public :: &
DMS_tracer_cnt, &
DMS_init, &
DMS_SurfaceFluxes, &
DMS_SourceSink
!-----------------------------------------------------------------------
! module variables
!-----------------------------------------------------------------------
integer (DMS_i4), parameter :: &
DMS_tracer_cnt = 14
!*****************************************************************************
contains
!*****************************************************************************
!BOP
! !IROUTINE: DMS_init
! !INTERFACE:
subroutine DMS_init(DMS_indices)
! !DESCRIPTION:
! Initialize tracegas tracer module. This involves setting metadata, reading
! the module namelist, setting initial conditions, setting up forcing,
! and defining additional tavg variables.
!
! !REVISION HISTORY:
! same as module
! !INPUT PARAMETERS:
type(DMS_indices_type), intent(inout) :: DMS_indices
! !INPUT/OUTPUT PARAMETERS:
! !OUTPUT PARAMETERS:
!EOP
!BOC
!-----------------------------------------------------------------------
! local variables
!-----------------------------------------------------------------------
!-----------------------------------------------------------------------
!-----------------------------------------------------------------------
!-----------------------------------------------------------------------
DMS_indices%short_name(DMS_indices%dms_ind)='DMS'
DMS_indices%long_name(DMS_indices%dms_ind)='DiMethyl Sulfide'
DMS_indices%short_name(DMS_indices%dmsp_ind)='DMSP'
DMS_indices%long_name(DMS_indices%dmsp_ind)='Dimethylsulfoniopropionate'
DMS_indices%short_name(DMS_indices%no3_ind)='NO3'
DMS_indices%long_name(DMS_indices%no3_ind)='Dissolved Inorganic Nitrate'
DMS_indices%short_name(DMS_indices%doc_ind)='DOC'
DMS_indices%long_name(DMS_indices%doc_ind)='Dissolved Organic Carbon'
DMS_indices%short_name(DMS_indices%zooC_ind)='zooC'
DMS_indices%long_name(DMS_indices%zooC_ind)='Zooplankton Carbon'
DMS_indices%short_name(DMS_indices%spChl_ind) = 'spChl'
DMS_indices%long_name(DMS_indices%spChl_ind) = ' Small Phytoplankton Chlorophyll'
DMS_indices%short_name(DMS_indices%diatChl_ind) = 'diatChl'
DMS_indices%long_name(DMS_indices%diatChl_ind) = ' Diatom Chlorophyll'
DMS_indices%short_name(DMS_indices%diazChl_ind) = 'diazChl'
DMS_indices%long_name(DMS_indices%diazChl_ind) = ' Diazotroph Chlorophyll'
DMS_indices%short_name(DMS_indices%phaeoChl_ind) = 'phaeoChl'
DMS_indices%long_name(DMS_indices%phaeoChl_ind) = 'Phaeocystis Chlorophyll'
DMS_indices%short_name(DMS_indices%spC_ind) = 'spC'
DMS_indices%long_name(DMS_indices%spC_ind) = ' Small Phytoplankton Carbon'
DMS_indices%short_name(DMS_indices%diatC_ind) = 'diatC'
DMS_indices%long_name(DMS_indices%diatC_ind) = ' Diatom Carbon'
DMS_indices%short_name(DMS_indices%diazC_ind) = 'diazC'
DMS_indices%long_name(DMS_indices%diazC_ind) = ' Diazotroph Carbon'
DMS_indices%short_name(DMS_indices%phaeoC_ind) = 'phaeoC'
DMS_indices%long_name(DMS_indices%phaeoC_ind) = 'Phaeocystis Carbon'
DMS_indices%short_name(DMS_indices%spCaCO3_ind) = 'spCaCO3'
DMS_indices%long_name(DMS_indices%spCaCO3_ind) = ' Small Phytoplankton Calcium Carbonate'
DMS_indices%units(:) = 'mmol/m^3'
!-----------------------------------------------------------------------
!EOC
end subroutine DMS_init
!***********************************************************************
!***********************************************************************
!BOP
! !IROUTINE: DMS_SourceSink
! !INTERFACE:
subroutine DMS_SourceSink(DMS_indices, DMS_input, DMS_forcing, DMS_output, DMS_diagnostic_fields, &
numLevelsMax, numColumnsMax, numColumns)
! !DESCRIPTION:
! Compute time derivatives for tracegas state variables
!
! !REVISION HISTORY:
! same as module
! !INPUT PARAMETERS:
type(DMS_indices_type), intent(in ) :: DMS_indices
type(DMS_input_type), intent(in ) :: DMS_input
type(DMS_forcing_type), intent(in ) :: DMS_forcing
integer (DMS_i4) :: numLevelsMax, numColumnsMax, numColumns
! !OUTPUT PARAMETERS:
type(DMS_output_type), intent(inout) :: DMS_output
type(DMS_diagnostics_type), intent(inout) :: DMS_diagnostic_fields
!EOP
!BOC
!-----------------------------------------------------------------------
! local variables
!-----------------------------------------------------------------------
real(DMS_r8) :: &
totalChl, & ! total chlorophyll from all phytoplankton
PAR_out, & ! photosynthetically available radiation (W/m^2)
PAR_in, & ! photosynthetically available radiation (W/m^2)
KPARdz, & ! PAR adsorption coefficient (non-dim)
PAR_avg, & ! average PAR over mixed layer depth (W/m^2)
UV_out, & ! generic UV radiation (W/m^2)
UV_in, & ! generic UV radiation (W/m^2)
KUVdz, & ! UV adsorption coefficient (non-dim)
UV_avg ! average UV (W/m^2)
!--------------------------------------------------------------------------------
! DMS and DMSP are the dissolved forms carried as tracers.
! The community would refer to them as DMS/Pd.
! The analytically particulate form DMSPp is for the moment
! defined as computationally local in order to minimize expense.
! Averaging and output will be added as necessary.
!--------------------------------------------------------------------------------
real(DMS_r8), allocatable, dimension(:,:) :: & !mmol molecule/m^3
DMS_loc, & ! local copy of model DMS
DMSP_loc, & ! local copy of model DMSP
NO3_loc, & ! local copy of model NO3
DOC_loc, & ! local copy of model DOC
zooC_loc, & ! local copy of model zooC
spC_loc, & ! local copy of model spC
spCaCO3_loc, & ! local copy of model spCaCO3
diatC_loc, & ! local copy of model diatC
diazC_loc, & ! local copy of model diazC
phaeoC_loc, & ! local copy of model phaeoC
spChl_loc, & ! local copy of model spChl
diatChl_loc, & ! local copy of model diatChl
diazChl_loc, & ! local copy of model diazChl
phaeoChl_loc ! local copy of model phaeoChl
real(DMS_r8) :: &
Fcocco ! Fraction of small carbon associated with calcite
!--------------------------------------------------------------------------------
! Conversion to nitrogen currency as the base for initial sulfur simulations.
! Links will most often be made to models such as Vallina et al. 2008,
! which tend to track organisms as N.
! Thus the CCSM standard carbon quantities are transposed.
! The trace gas system really begins here.
! Note that the DML phyto-classes are often subdivided,
! e.g. into specialists such as phaeocystis or nonS producers cyanobacteria.
! Ordering of the organisms in the code is intended to reflect
! prioritization of this decomposition process.
! E.g. coccolithophorids are partitioned prior to the cyano
! but after phaeocystis due to its traditional local dominance.
! Diatom, diazotroph and zooplanktonic bins are already sulfur appropriate
! and so are not directly altered here.
! Heterotrophic, recycling bacteria will be decoupled from phaeocystis
! which is colonial and generates antibiotics.
!--------------------------------------------------------------------------------
real(DMS_r8) :: & !all mmol N/m^3
diatN_loc, & ! analog to diatC_loc
phaeoN_loc, & ! nitrogen associated with phaeocystis
coccoN_loc, & ! nitrogen associated with coccolithophores
cyanoN_loc, & ! nitrogen associated with cyanobacteria
eukarN_loc, & ! analog to spC_loc but remove specialists
diazN_loc, & ! analog to diazC_loc
phytoN_loc, & ! total phytoplanktonic nitrogen excluding phaeo
zooN_loc ! analog to zooC_loc
!--------------------------------------------------------------------------------
! Further conversion to sulfur quantities.
! These may be thought of as particulate DMSP by class
! and so may be zero as for example in the case of prokaryotes.
! A simple renaming is included at the end of the list
! to align with DMS community convention.
! Phaeocystis is pulled out of the total again,
! but this time because it is not subject to grazing.
! An even, steady state leakage from colonies is assumed.
!--------------------------------------------------------------------------------
real(DMS_r8) :: & !all mmol S/m^3
diatS_loc, & ! DMSP in diatoms
phaeoS_loc, & ! DMSP in phaeocystis
coccoS_loc, & ! DMSP in coccolithophores
cyanoS_loc, & ! DMSP in cyanobacteria
eukarS_loc, & ! DMSP in smalls remaining
diazS_loc, & ! DMSP in diazotrophs
phytoS_loc, & ! total phytoplanktonic sulfur excluding phaeo
zooS_loc ! total zooplanktonic sulfur
!--------------------------------------------------------------------------------
! The mechanism traces to reviews such as Kiene et al. 2000 and Simo 2004
! supplemented by detail taken from low dimensionality models,
! examples being Lefevre et al. 2002, Vallina et al. 2008, Toole et al. 2008.
! Best descriptions to date appear in our reports on piston velocity testing.
! Channels are similar but not identical to those incorporated into
! the first (SciDAC) coupled ocean-atmosphere chemistry runs in CCSM.
! Key points include:
! Phytoplanktonic intracellular contents consistent with Stefels 2000.
! Zooplanktonic dependence built into the release constant k
! which relaxes coupling to chlorophyll and works toward a summer phase lag.
! Sunda et al. (2002) cell internal oxidant stress under high irradiance
! treated ad hoc by enhancing picoeukaryotic cell content
! in proportion to an arbitrary chlorophyll decrement.
! This situation arose because ultraviolet calculations were running late
! relative to the recent CODiM intercomparison.
! Real UV penetration will soon be computed per Chu et al. CO simulations.
! Direct summer exudation remains a speculative explanation for summer peaks.
! It may be thought of as closely related to the decrement approach
! but is not actually simulated here in a direct sense.
! DMS yield from bacterial processing of DMSP is given a T dependence.
! The concept is that microbial sulfur demand will be higher
! in cold, nutrient rich waters. See Kiene et al. 2000 for concepts involved.
! True sulfur utilization must clearly be incorporated very soon.
! This can begin with application of a cycling time to diagnosed densities,
! but may eventually entail addition of a dynamic bacterial module.
! Microbial consumption is rendered 2nd order per the above reviews,
! but in particular based on the equatorial data of Kiene and Bates 1990.
! Densities depend on free (non-colonial) phytoplankton distributions.
! Injection scale is a dial for dealing simultaneously with uncertainties in
! disruption rate and intracellular DMSP content.
! Optimization issues are thus focused upon average release.
! This collapses their dimensionality considerably.
!--------------------------------------------------------------------------------
!--------------------------------------------------------------------------------
! These kinetically important quantities have geographic dependence.
!--------------------------------------------------------------------------------
real(DMS_r8) :: &
k_S_p, & ! 1st order constant for DMSP release from phyto (1/sec)
yield, & ! fraction of DMSP converion to DMS
B_diagnosed, & ! local bacterial density (mmol N/m^3)
j_dms ! overall dms photolysis rate (1/sec)
real(DMS_r8) :: &
T_ind ! upward temperature index
real(DMS_r8) :: &
Cocco_frac, & ! local fraction of smalls as coccos
Cyano_frac, & ! local fraction of smalls as cyanos
Eukar_frac ! local fraction of remaining smalls
real(DMS_r8) :: &
Sp_dec ! small phytoplanktonic decrement
real(DMS_r8) :: &
Stress_fac ! local up regulation
!--------------------------------------------------------------------------------
! Surface temperature fixed moving down the column
! for several purposes within the fuzzy and binary logic
!--------------------------------------------------------------------------------
real(DMS_r8) :: &
SST_loc ! local surface temperature (C)
!--------------------------------------------------------------------------------
! Average cell contents have geographic dependence for zooplantkon
! because they are weighted averages over food items.
!--------------------------------------------------------------------------------
real(DMS_r8) :: &
Rs2n_zoo ! S/N assuming weighted average of consumable content
!--------------------------------------------------------------------------------
! Begin declaration of source sink terms.
!--------------------------------------------------------------------------------
!--------------------------------------------------------------------------------
! By and large the structure of the mechanism is reflected.
! For example in the present configuration,
! most sulfur release from phytoplankton takes the form DMSP.
! In anticipation of increased mechanistic complexity
! certain likely future permutations are included, e.g. exudation.
! The concepts here are clarity and motivation.
! The ports are simply readied for later connections.
! A few omissions will be obvious.
! There are to date no indications that DMSP photolyzes in the column.
! Note that sea-air transfer is time split into other routines.
!--------------------------------------------------------------------------------
real(DMS_r8) :: &
dms_s_exu, & ! DMS source from exudation (mmol S/m^3/sec)
dms_s_dmsp, & ! DMS source by conversion of DMSP (mmol S/m^3/sec)
dms_s ! DMS source total (mmol S/m^3/sec)
real(DMS_r8) :: &
dms_r_B, & ! DMS removal by bacteria (mmol S/m^3/sec)
dms_r_phot, & ! DMS removal by photolysis (mmol S/m^3/sec)
dms_r_bkgnd, & ! DMS removal low level in thermocline
dms_r ! DMS removal total (mmol S/m^3/sec)
real(DMS_r8) :: &
dmsp_s_phaeo, & ! DMSP source from phaeo (mmol S/m^3/sec)
dmsp_s_nonphaeo, & ! DMSP source from other phytoplankton (mmol S/m^3/sec)
dmsp_s_zoo, & ! DMSP source from zooplankton (mmol S/m^3/sec)
dmsp_s ! DMSP source total (mmol S/m^3/sec)
real(DMS_r8) :: &
dmsp_r_B, & ! DMSP removal by bacteria (mmol S/m^3/sec)
dmsp_r_bkgnd, & ! DMSP removal low level in thermocline
dmsp_r ! DMSP removal total (mmol S/m^3/sec)
real(DMS_r8) :: &
work
integer(DMS_i4) :: &
column, kmax, k
integer (DMS_i4) :: &
dms_ind, & ! DMS index
dmsp_ind, & ! DMSP index
no3_ind, & ! DMSP index
doc_ind, & ! DMSP index
zooC_ind, & ! DMSP index
spC_ind, & ! DMSP index
spCaCO3_ind, & ! DMSP index
diatC_ind, & ! DMSP index
diazC_ind, & ! DMSP index
phaeoC_ind, & ! DMSP index
spChl_ind, & ! DMSP index
diatChl_ind, & ! DMSP index
diazChl_ind, & ! DMSP index
phaeoChl_ind ! DMSP index
!---------------------------------------------------------------------------
!---------------------------------------------------------------------------
!-----------------------------------------------------------------------
! initialize all tendencies to zero
!-----------------------------------------------------------------------
DMS_output%DMS_tendencies = 0.0_DMS_r8
!-----------------------------------------------------------------------
! allocate local copies of tracers
!-----------------------------------------------------------------------
allocate(DMS_loc(numLevelsMax,numColumns))
allocate(DMSP_loc(numLevelsMax,numColumns))
allocate(NO3_loc(numLevelsMax,numColumns))
allocate(DOC_loc(numLevelsMax,numColumns))
allocate(spC_loc(numLevelsMax,numColumns))
allocate(spCaCO3_loc(numLevelsMax,numColumns))
allocate(diatC_loc(numLevelsMax,numColumns))
allocate(diazC_loc(numLevelsMax,numColumns))
allocate(phaeoC_loc(numLevelsMax,numColumns))
allocate(spChl_loc(numLevelsMax,numColumns))
allocate(diatChl_loc(numLevelsMax,numColumns))
allocate(diazChl_loc(numLevelsMax,numColumns))
allocate(phaeoChl_loc(numLevelsMax,numColumns))
allocate(zooC_loc(numLevelsMax,numColumns))
!-----------------------------------------------------------------------
! assign indices. this is not necessary but results in fewer
! differences between original and new code.
!-----------------------------------------------------------------------
no3_ind = DMS_indices%no3_ind
doc_ind = DMS_indices%doc_ind
zooC_ind = DMS_indices%zooC_ind
spC_ind = DMS_indices%spC_ind
diatC_ind = DMS_indices%diatC_ind
diazC_ind = DMS_indices%diazC_ind
phaeoC_ind = DMS_indices%phaeoC_ind
spChl_ind = DMS_indices%spChl_ind
diatChl_ind = DMS_indices%diatChl_ind
diazChl_ind = DMS_indices%diazChl_ind
phaeoChl_ind = DMS_indices%phaeoChl_ind
spCaCO3_ind = DMS_indices%spCaCO3_ind
dms_ind = DMS_indices%dms_ind
dmsp_ind = DMS_indices%dmsp_ind
!-----------------------------------------------------------------------
! loop over columns
!-----------------------------------------------------------------------
setup_loop: do column = 1, numColumns
kmax = DMS_input%number_of_active_levels(column)
if (kmax < 1) cycle setup_loop
do k = 1, kmax
!---------------------------------------------------------------------------
! create local copies of requisite ecotracers
! treat negative values as zero and apply mask to locals
!---------------------------------------------------------------------------
NO3_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,no3_ind))
DOC_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,doc_ind))
zooC_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,zooC_ind))
spC_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,spC_ind))
diatC_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,diatC_ind))
diazC_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,diazC_ind))
phaeoC_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,phaeoC_ind))
spChl_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,spChl_ind))
diatChl_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,diatChl_ind))
diazChl_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,diazChl_ind))
phaeoChl_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,phaeoChl_ind))
spCaCO3_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,spCaCO3_ind))
DMS_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,dms_ind))
DMSP_loc(k,column) = max(0.0_DMS_r8, DMS_input%DMS_tracers(k,column,dmsp_ind))
end do ! end of setup k loop
enddo setup_loop ! end of setup column loop
!-----------------------------------------------------------------------
! loop over columns
!-----------------------------------------------------------------------
column_loop: do column = 1, numColumns
kmax = DMS_input%number_of_active_levels(column)
if (kmax < 1) cycle column_loop
!-----------------------------------------------------------------------
! various k==1 initializations
!-----------------------------------------------------------------------
SST_loc = DMS_forcing%SST(column)
PAR_out = max (0.0_DMS_r8, DMS_forcing%ShortWaveFlux_surface(column))
PAR_out = PAR_out*f_qsw_par_DMS
! UV is 1% of PAR
UV_out = PAR_out*0.01_DMS_r8
!-----------------------------------------------------------------------
! loop over levels
!-----------------------------------------------------------------------
do k = 1, kmax
!---------------------------------------------------------------------------
! Baseline phytoplanktonic sulfur release rate constant is here adjusted
! by local zooplanktonic densities normalized to an average.
! This has the effect of partially decoupling sulfur from chlorophyll.
! Carbon is used in this case since conversions would simply cancel.
! Mortality modulates the decoupling but may be zeroed.
! Note that phaeocystis release is treated as an independent leak
! adjusted in fact to control grazing.
! This is normally given the base rate but could be as slow as senescence.
!---------------------------------------------------------------------------
k_S_p = k_S_p_base * (mort + (zooC_loc(k,column)/0.3_DMS_r8))
UV_in = UV_out
KUVdz = (0.01e-2_DMS_r8 * DOC_loc(k,column) + 0.04e-4_DMS_r8) * DMS_input%cell_thickness(k,column)
UV_out = UV_in * exp(-KUVdz)
UV_avg = UV_in * (1.0_DMS_r8 - exp(-KUVdz)) / KUVdz
PAR_in = PAR_out
totalChl = spChl_loc(k,Column) + diatChl_loc(k,Column) + diazChl_loc(k,Column) &
+ phaeoChl_loc(k,Column)
work = max(totalChl, 0.02_DMS_r8)
if (work < 0.13224_DMS_r8) then
KPARdz = 0.000919_DMS_r8*(work**0.3536_DMS_r8)
else
KPARdz = 0.001131_DMS_r8*(work**0.4562_DMS_r8)
end if
KPARdz = KPARdz * DMS_input%cell_thickness(k,column)
PAR_out = PAR_in * exp(-KPARdz)
PAR_avg = PAR_in * (1.0_DMS_r8 - exp(-KPARdz)) / KPARdz
!---------------------------------------------------------------------------
! Momentarily we follow Gabric et al. 1993 who speculate implicitly that
! DMS photolytic wavelengths attenuate as PAR.
! This is confirmed in part by the review Mopper and Kieber 2002,
! But modernization will be required per Toole et al. 2004 and related.
! Photolysis per unit intensity is based by Gabric on
! Brimblecombe and Shooter 1986 results for wavelengths unknown.
!---------------------------------------------------------------------------
j_dms = j_dms_perI * PAR_avg
!---------------------------------------------------------------------------
! Fcocco is the fraction of sp organic matter in coccolithophores
! as imported from the driver DML ecology.
! In the S model this takes precedence over all but phaeocystis.
!---------------------------------------------------------------------------
Fcocco = spCaCO3_loc(k,column) / (spC_loc(k,column) + epsC)
if (Fcocco > 0.4_DMS_r8) Fcocco = 0.4_DMS_r8
Cocco_frac = Fcocco
!--------------------------------------------------------------------------
! Fuzzy logical segregation into relevant subclasses
!--------------------------------------------------------------------------
!--------------------------------------------------------------------------
! Further distribution of the DML small phytoplanktonic biomass
! is now undertaken per requirements of the sulfur cycle.
! Phaeocystis is considered dominant and ultimately trumps other autotrophs.
!--------------------------------------------------------------------------
T_ind = (SST_loc - T_lo)/(T_hi - T_lo)
if (T_ind <= 0.0_DMS_r8) T_ind = 0.0_DMS_r8
if (T_ind >= 1.0_DMS_r8) T_ind = 1.0_DMS_r8
Cyano_frac = (T_ind * (Max_cyano_frac - Min_cyano_frac)) + Min_cyano_frac
Cyano_frac = (1.0_DMS_r8 - Cocco_frac) * Cyano_frac
Eukar_frac = 1.0_DMS_r8 - Cocco_frac - Cyano_frac
!--------------------------------------------------------------------------
! Convert to nitrogen currency plus distribute into new classes
!--------------------------------------------------------------------------
diatN_loc = R * diatC_loc(k,column)
phaeoN_loc = R * phaeoC_loc(k,column)
coccoN_loc = Cocco_frac * R * spC_loc(k,column)
cyanoN_loc = Cyano_frac * R * spC_loc(k,column)
eukarN_loc = Eukar_frac * R * spC_loc(k,column)
diazN_loc = R*diazC_loc(k,column)
zooN_loc = R*zooC_loc(k,column)
!--------------------------------------------------------------------------
! Collect noncolonial nitrogen
! (swang) since phaeocystis is grazed in BEC, include it in grazing-dmsp production too
!--------------------------------------------------------------------------
phytoN_loc = diatN_loc + coccoN_loc + cyanoN_loc + eukarN_loc + diazN_loc &
+ phaeoN_loc
!--------------------------------------------------------------------------
! Gyre oxidant stress now exerts upregulation per chlorophyll decrement.
! Functional form maintains round figure parameters and powers,
! but was essentially determined by offline, postprocessing trial and error.
! Real physiology must be incorporated in short order.
!--------------------------------------------------------------------------
Sp_dec = (Sp_ref - spChl_loc(k,column))/Sp_ref
if (Sp_dec <= 0.0_DMS_r8) Sp_dec = 0.0_DMS_r8
if (Sp_dec >= 1.0_DMS_r8) Sp_dec = 1.0_DMS_r8
Stress_fac = 1.0_DMS_r8 + Stress_mult* Sp_dec * Sp_dec
if (Stress_fac >= 10.0_DMS_r8) Stress_fac = 10.0_DMS_r8
!--------------------------------------------------------------------------
! Yields for bacterial conversion of DMSP also determined by fuzzy logic.
! Since Phaeocystis is colonial and produces antimicrobials,
! its habitat constitutes an exception at very low S demand.
! (swang) assume an optimal temperautre for cryoprotention
!--------------------------------------------------------------------------
yield = (T_ind * (Max_yld - Min_yld)) + Min_yld
if (SST_loc < T_cryo_hi .and. SST_loc > T_cryo_lo) yield = 0.5_DMS_r8
if (SST_loc < -1.0_DMS_r8) yield = 0.25_DMS_r8
!--------------------------------------------------------------------------
! Phytoplanktonic sulfur content determined.
! This is where oxidant stress is in fact applied.
!--------------------------------------------------------------------------
diatS_loc = Rs2n_diat * diatN_loc
phaeoS_loc = Rs2n_phaeo * phaeoN_loc
coccoS_loc = Rs2n_cocco * coccoN_loc
cyanoS_loc = Rs2n_cyano * cyanoN_loc
eukarS_loc = Rs2n_eukar * eukarN_loc * Stress_fac
diazS_loc = Rs2n_diaz * diazN_loc
!--------------------------------------------------------------------------
! Collect noncolonials
! (swang) assume only a fraction (40%) of phaeo S contribute to dsmp release when grazed
!--------------------------------------------------------------------------
phytoS_loc = diatS_loc + coccoS_loc + cyanoS_loc + eukarS_loc + diazS_loc &
+ G_phaeo_S * phaeoS_loc
!--------------------------------------------------------------------------
! Weight the zooplanktonic reduced sulfur content per the various
! phytoplankton types available unprotected in the column as food.
! Observe that plant nitrogen may total zero under some circumstances
! and in this case it is assumed that all concentrations are equally small.
! Note that phaeocystis has been segregated entirely.
! In colonial form it exhibits multiple grazing inhibition strategies.
!--------------------------------------------------------------------------
if (phytoN_loc > 0.0_DMS_r8) then
Rs2n_zoo = (Rs2n_diat * diatN_loc + &
G_phaeo_S * Rs2n_phaeo * phaeoN_loc + &
Rs2n_cocco * coccoN_loc + &
Rs2n_cyano * cyanoN_loc + &
Rs2n_eukar * eukarN_loc * Stress_fac + &
Rs2n_diaz * diazN_loc)/phytoN_loc
else
! (swang) include 1group phaeo
Rs2n_zoo = (Rs2n_diat + Rs2n_cocco + Rs2n_cyano + Rs2n_eukar + Rs2n_diaz &
+ Rs2n_phaeo)/6.0
end if
zooS_loc = Rs2n_zoo * zooN_loc
!---------------------------------------------------------------------------
! Given a nitrogen distribution diagnose B which is bacterial N.
! Phaeocystis excluded because it is colonial and exudes antibiotics.
! Given a turnover time B could serve as the basis for S demand calcs.
! However our tendency is to move directly to bacterial populations.
! Second order DMS removal is based on reports of biotic uptake presented
! by Kiene and Bates 1991 for the eastern equatorial Pacific.
!---------------------------------------------------------------------------
B_diagnosed = B_preexp*(phytoN_loc**B_exp)
!-------------------------------------------------------------------------
! Construction of kinetic terms for the sulfur cycle
!-------------------------------------------------------------------------
dms_s_dmsp = yield * k_conv * DMSP_loc(k,column)
dms_s = dms_s_dmsp
dms_r_B = k_S_B * B_diagnosed * DMS_loc(k,column)
dms_r_phot = j_dms * DMS_loc(k,column)
dms_r_bkgnd = k_bkgnd * DMS_loc(k,column)
dms_r = dms_r_B + dms_r_phot + dms_r_bkgnd
dmsp_s_phaeo = inject_scale * k_S_p_base * phaeoS_loc
dmsp_s_nonphaeo = inject_scale * k_S_p * phytoS_loc
dmsp_s_zoo = inject_scale * k_S_z * zooS_loc
dmsp_s = dmsp_s_phaeo + dmsp_s_nonphaeo + dmsp_s_zoo
dmsp_r_B = k_conv * DMSP_loc(k,column)
dmsp_r_bkgnd = k_bkgnd * DMSP_loc(k,column)
dmsp_r = dmsp_r_B + dmsp_r_bkgnd
DMS_output%DMS_tendencies(k,column,dms_ind) = dms_s - dms_r
DMS_output%DMS_tendencies(k,column,dmsp_ind) = dmsp_s - dmsp_r
! all other tendencies were initialized to 0
! DMS source terms
DMS_diagnostic_fields%diag_DMS_S_DMSP(k,column) = dms_s_dmsp
DMS_diagnostic_fields%diag_DMS_S_TOTAL(k,column) = dms_s
! DMS removal terms
DMS_diagnostic_fields%diag_DMS_R_B(k,column) = dms_r_B
DMS_diagnostic_fields%diag_DMS_R_PHOT(k,column) = dms_r_phot
DMS_diagnostic_fields%diag_DMS_R_BKGND(k,column) = dms_r_bkgnd
DMS_diagnostic_fields%diag_DMS_R_TOTAL(k,column) = dms_r
! DMSP source terms
DMS_diagnostic_fields%diag_DMSP_S_PHAEO(k,column) = dmsp_s_phaeo
DMS_diagnostic_fields%diag_DMSP_S_NONPHAEO(k,column) = dmsp_s_nonphaeo
DMS_diagnostic_fields%diag_DMSP_S_ZOO(k,column) = dmsp_s_zoo
DMS_diagnostic_fields%diag_DMSP_S_TOTAL(k,column) = dmsp_s
! DMSP removal terms
DMS_diagnostic_fields%diag_DMSP_R_B(k,column) = dmsp_r_B
DMS_diagnostic_fields%diag_DMSP_R_BKGND(k,column) = dmsp_r_bkgnd
DMS_diagnostic_fields%diag_DMSP_R_TOTAL(k,column) = dmsp_r
! fractional compositions
DMS_diagnostic_fields%diag_Cyano_frac(k,column) = Cyano_frac
DMS_diagnostic_fields%diag_Cocco_frac(k,column) = Cocco_frac
DMS_diagnostic_fields%diag_Eukar_frac(k,column) = Eukar_frac
! sulfur content
DMS_diagnostic_fields%diag_diatS(k,column) = diatS_loc
DMS_diagnostic_fields%diag_diatN(k,column) = diatN_loc
DMS_diagnostic_fields%diag_phytoN(k,column) = phytoN_loc
DMS_diagnostic_fields%diag_coccoS(k,column) = coccoS_loc
DMS_diagnostic_fields%diag_cyanoS(k,column) = cyanoS_loc
DMS_diagnostic_fields%diag_eukarS(k,column) = eukarS_loc
DMS_diagnostic_fields%diag_diazS(k,column) = diazS_loc
DMS_diagnostic_fields%diag_phaeoS(k,column) = phaeoS_loc
DMS_diagnostic_fields%diag_zooS(k,column) = zooS_loc
! other
DMS_diagnostic_fields%diag_zooCC(k,column) = zooC_loc(k,column)
DMS_diagnostic_fields%diag_RSNzoo(k,column) = Rs2n_zoo
enddo ! k loop
enddo column_loop ! i loop
!-----------------------------------------------------------------------
!EOC
end subroutine DMS_SourceSink
!***********************************************************************
!***********************************************************************
!BOP
! !IROUTINE: DMS_SurfaceFluxes
! !INTERFACE:
subroutine DMS_SurfaceFluxes(DMS_indices, DMS_input, DMS_forcing, &
DMS_flux_diagnostic_fields, &
numColumnsMax, numColumns)
! !DESCRIPTION:
! Compute surface fluxes for tracegas tracer module.
!
! !REVISION HISTORY:
! same as module
! !INPUT PARAMETERS:
type(DMS_indices_type), intent(in ) :: DMS_indices
type(DMS_input_type), intent(in ) :: DMS_input
type(DMS_forcing_type), intent(inout) :: DMS_forcing
integer (DMS_i4) :: numColumnsMax, numColumns
! !OUTPUT PARAMETERS:
type(DMS_flux_diagnostics_type), intent(inout) :: DMS_flux_diagnostic_fields
!EOP
!BOC
!-----------------------------------------------------------------------
! local variables
!-----------------------------------------------------------------------
real (DMS_r8) :: &
seaSurfaceTemp, &
seaSurfaceSalt, &
seaSurfaceDMS, &
xkw, &
xkw_ice, &
SCHMIDT_DMS, &
DMSSAT_1atm, &
pistonVel_DMS, &
DMSSAT, &
WIND_SPEED, &
FW92, & ! apportionment to Wanninkhof 1992
FLM86, & ! apportionment to Liss and Merlivat 1986
XKW_W92, & ! the Wanninkhof limit
XKW_LM86 ! the Liss and Merlivat limit
real (DMS_r8) :: scalar_temp
integer (DMS_i4) :: &
column ! index for looping over columns
!-----------------------------------------------------------------------
! local parameters
!-----------------------------------------------------------------------
real(DMS_r8), parameter :: &
a = 0.31_DMS_r8, & ! W92
e1 = 0.17_DMS_r8, & ! LM86 from here
e2 = 2.85_DMS_r8, &
e3 = 0.612_DMS_r8, &
e4 = 5.9_DMS_r8, &
e5 = 26.79_DMS_r8, &
e6 = 0.612_DMS_r8
!-----------------------------------------------------------------------
!-----------------------------------------------------------------------
! compute DMS flux
!-----------------------------------------------------------------------
if (DMS_forcing%lcalc_DMS_gas_flux) then
!-----------------------------------------------------------------------
! loop over columns
!-----------------------------------------------------------------------
column_loop: do column = 1, numColumns
seaSurfaceDMS = max(0.0_DMS_r8, DMS_input%DMS_tracers(1,column,DMS_indices%dms_ind))
seaSurfaceTemp = DMS_forcing%SST(column)
seaSurfaceSalt = DMS_forcing%SSS(column)
if (DMS_forcing%iceFraction(column) < 0.0_DMS_r8) DMS_forcing%iceFraction(column) = 0.0_DMS_r8
if (DMS_forcing%iceFraction(column) > 1.0_DMS_r8) DMS_forcing%iceFraction(column) = 1.0_DMS_r8
SCHMIDT_DMS = SCHMIDT_DMS_singleValue(seaSurfaceTemp)
! SCHMIDT_DMS = min(SCHMIDT_DMS,1.e20)
! SCHMIDT_DMS = max(SCHMIDT_DMS,1.)
! convert to m/s
WIND_SPEED = sqrt(abs(DMS_forcing%windSpeedSquared10m(column)))*0.01_DMS_r8
XKW_W92 = &
a*((660.0_DMS_r8/SCHMIDT_DMS)**0.500_DMS_r8)*WIND_SPEED*WIND_SPEED
XKW_LM86 = &
e2*((600.0_DMS_r8/SCHMIDT_DMS)**0.500_DMS_r8)*(WIND_SPEED - 3.6_DMS_r8) &
+ e3*((600.0_DMS_r8/SCHMIDT_DMS)**0.667_DMS_r8)
if (WIND_SPEED < 3.6_DMS_r8) xkw = XKW_W92
if ((WIND_SPEED >= 3.6_DMS_r8) .and. (WIND_SPEED < 5.6_DMS_r8)) then
FLM86 = 0.5_DMS_r8*(WIND_SPEED - 3.6_DMS_r8)
FW92 = 1.0_DMS_r8 - FLM86
xkw = FW92*XKW_W92 + FLM86*XKW_LM86
end if
if (WIND_SPEED >= 5.6_DMS_r8) xkw = XKW_LM86
xkw = xkw/3600.0_DMS_r8 ! conversion to cm/s
xkw_ice = (1.0_DMS_r8 - DMS_forcing%iceFraction(column)) * xkw
DMSSAT_1atm = DMSSAT_singleValue(seaSurfaceTemp, seaSurfaceSalt)
pistonVel_DMS = xkw_ice * SQRT(660.0_DMS_r8 / SCHMIDT_DMS)
DMSSAT = DMS_forcing%surfacePressure(column) * DMSSAT_1atm
DMS_forcing%netFlux(column, DMS_indices%dms_ind) = pistonVel_DMS * (DMSSAT - seaSurfaceDMS)
DMS_forcing%netFlux(column, DMS_indices%dmsp_ind) = 0.0_DMS_r8
DMS_flux_diagnostic_fields%diag_DMS_IFRAC(column) = DMS_forcing%iceFraction(column)
DMS_flux_diagnostic_fields%diag_DMS_XKW(column) = xkw_ice
DMS_flux_diagnostic_fields%diag_DMS_ATM_PRESS(column) = DMS_forcing%surfacePressure(column)
DMS_flux_diagnostic_fields%diag_DMS_PV(column) = pistonVel_DMS
DMS_flux_diagnostic_fields%diag_DMS_SCHMIDT(column) = SCHMIDT_DMS
DMS_flux_diagnostic_fields%diag_DMS_SAT(column) = DMSSAT
DMS_flux_diagnostic_fields%diag_DMS_SURF(column) = seaSurfaceDMS
DMS_flux_diagnostic_fields%diag_DMS_WS(column) = WIND_SPEED
enddo column_loop
endif ! lflux_gas_dms
!-----------------------------------------------------------------------
!EOC
end subroutine DMS_SurfaceFluxes
!*****************************************************************************
!BOP
! !IROUTINE: SCHMIDT_DMS
! !INTERFACE:
function SCHMIDT_DMS_singleValue(SST)
! !DESCRIPTION:
!---------------------------------------------------------------------------
! Compute Schmidt number in seawater as function of SST
! where LAND_MASK is true. Give zero where LAND_MASK is false.
!
! ref : Kettle and Andreae 2000
!---------------------------------------------------------------------------
!
! !REVISION HISTORY:
! same as module
! !INPUT PARAMETERS:
real (DMS_r8), intent(in) :: SST
! !OUTPUT PARAMETERS:
real (DMS_r8) :: SCHMIDT_DMS_singleValue
!EOP
!BOC
!-----------------------------------------------------------------------
! local variables
!-----------------------------------------------------------------------
!---------------------------------------------------------------------------
! coefficients in expansion
!---------------------------------------------------------------------------
real(DMS_r8), parameter :: &
a = 2674.0_DMS_r8, &
b = 147.12_DMS_r8, &
c = 3.726_DMS_r8, &
d = 0.038_DMS_r8
!-----------------------------------------------------------------------
SCHMIDT_DMS_singleValue = a + SST * (-b + SST * (c + SST * (-d)))
!-----------------------------------------------------------------------
!EOC
end function SCHMIDT_DMS_singleValue
!*****************************************************************************
!BOP
! !IROUTINE: DMSSAT_singleValue
! !INTERFACE:
function DMSSAT_singleValue(SST, SSS)
! !DESCRIPTION:
!
! Sat functions normally compute for a given molecule
! a sea surface saturation concentration estimate at 1 atm total pressure
! in mmol/m^3 given the temperature (t, in deg C) and the salinity (s,
! in permil) where LAND_MASK is true. Give zero where LAND_MASK is false.
! For DMS the assumption is made per Kettle and Andreae 2000
! that the atmospheric concentration is negligible.
! Henrys Law is thus not accounted here but passes for temperature and
! salinity influences are preserved pending.
!
! !REVISION HISTORY:
! same as module
! !USES:
! !INPUT PARAMETERS:
real (DMS_r8), intent(in) :: &
SST, & ! sea surface temperature (C)
SSS ! sea surface salinity (psu)
! !OUTPUT PARAMETERS:
real (DMS_r8) :: DMSSAT_singleValue
!EOP
!BOC
!-----------------------------------------------------------------------
!-----------------------------------------------------------------------
!---------------------------------------------------------------------------
! Units should lead to mmol/m^3 for saturation level