When modeling chemical and biogeochemical tracers, it is recommended that
OMIP groups use the same formulations for gas exchange and carbonate
chemistry as outlined below. Little effort would be needed to modify code
that is already consistent with previous phases of OCMIP. For gas exchange,
model groups only need to change the value of the gas transfer coefficient,
the formulations and coefficients for Schmidt numbers, and the atmospheric
gas histories. For carbonate chemistry, groups should strive to use the
constants recommended for best practices on the total pH
scale and to avoid common modeling assumptions that lead to significant
biases, notably an oversimplified alkalinity equation .
Fortran 95 code to make these calculations is
made available to OMIP-BGC
participants.
Passive tracers
Inert chemistry
The inert chemistry component of OMIP includes online simulation of CFC-11,
CFC-12, and SF6. While CFC-12 is required (priority 1), CFC-11 and
SF6 are encouraged (priority 2). About the same amount of
observational data in the global ocean exists for both CFC-11 and CFC-12,
starting with early field programs in the 1980s. But CFC-12 has a longer
atmospheric history, with its production starting a decade earlier
(∼ 1936) and a slower decline starting a decade later due to its longer
atmospheric lifetime (112 vs. 52 years) relative to CFC-11
. In contrast, SF6 has continued to increase
rapidly in recent decades. That increase will continue for many years despite
ongoing efforts to restrict production and release of this potent greenhouse
gas, because SF6's atmospheric lifetime is perhaps 3000 years
. Using pairs of these tracers offers a powerful means to
constrain ventilation ages; if model groups are only able to model two of
these tracers, the ideal combination is CFC-12 and SF6.
Simulation protocols are based on the OCMIP2 design document
and its ensuing CFC protocol and model
comparison . These inert passive tracers are computed
online along with the active tracers (i.e., temperature and salinity in the
physical simulation); they are independent of the biogeochemical model. OMIP
models will be forced to follow historical atmospheric concentrations of
CFC-11, CFC-12, and SF6, accounting for gas exchange and their
different solubilities and Schmidt numbers. The same passive tracers should
be included in the forced OMIP simulations and in the coupled CMIP6
historical simulations. Both types of simulations will be analyzed within the
framework of OMIP. These inert chemistry tracers are complementary to the
ideal age tracer that is included in the OMIP-Physics protocols
.
Biogeochemistry
For the other passive tracers, referred to as biogeochemistry, the
OMIP-BGC protocols build on those developed for OCMIP. These include
the OCMIP2 abiotic and biotic protocols and the OCMIP3 protocols for interannually
forced simulations , all available online with
links to code and data (see references) or as one combined PDF (see
Supplement). Each model group will implement the OMIP protocol in their own prognostic
ocean biogeochemical model as in OCMIP3, unlike the common-model approach of
OCMIP2. Each OMIP biogeochemical model will be coupled online to an ocean
general circulation model forced by the CORE-II atmospheric state.
Geochemical boundary conditions for the atmosphere include an imposed
constant atmospheric concentration of O2 (mole fraction
xO2 of 0.20946) but a variable atmospheric CO2 that
follows observations .
In addition, OMIP-BGC simulations should include a natural carbon tracer that
sees a constant atmospheric mole fraction of CO2 in dry air
(xCO2) fixed at the 1 January 1850 value (284.32 ppm), the CMIP6
preindustrial reference. This can be done either in an independent simulation
with identical initial conditions and forcing, except for atmospheric
xCO2, or in the same simulation by adding one or more new tracers
to the biogeochemical model, referred to here as a
dual-CT simulation. For this dual simulation,
OMIP modelers would need to add a second dissolved inorganic carbon tracer
(CTnat), e.g., as in . In OMIP, this
added tracer will isolate natural CO2 and keep track of model drift.
Such doubling may also be necessary for other biogeochemical model
tracers if they are directly affected by the CO2 increase. For
instance, expansion of the PISCES model to a
dual-CT implementation resulted in doubling not only of
CT, but also of its transported CaCO3 tracer, which in
turn affects total alkalinity AT . These
natural tracers are referred to as CTnat,
CaCO3nat, and ATnat. Calculated
variables affected by CO2 should also be doubled, including pH,
pCO2, the air–sea CO2 flux, and carbonate ion
concentration. If biology depends on CO2, additional tracers such as
nutrients and O2 would also need to be doubled, making the doubling
strategy less appealing. That strategy may also be more complex in some ESMs,
e.g., if AT changes abiotically due to warming-related changes in
weathering and river runoff.
Abiotic carbon and radiocarbon
In the omip1-spunup simulation (as well as in its previously run
spin-up) OMIP-BGC groups will also include two abiotic tracers to simulate
total dissolved inorganic carbon CTabio and
corresponding radiocarbon 14CTabio. These abiotic
tracers do not depend on any biotic tracers. They should be included in
addition to the biotic carbon tracers mentioned above (CT and
CTnat). The ratio of the two abiotic tracers will be
used to evaluate and compare models in terms of deep-ocean ventilation ages
(natural radiocarbon) and near-surface anthropogenic invasion of bomb
radiocarbon. In addition, CTabio will be compared to
CT to distinguish physical from biogeochemical effects on total
carbon. For simplicity, simulations will be made abiotically following OCMIP2
protocols . We recommend that participating groups add these
two independent tracers to their biogeochemical model to simulate them
simultaneously, thus promoting internal consistency while reducing costs.
In OMIP, we will use this two-tracer approach rather than the simpler
approach of modeling only the 14C/C ratio directly
. That simpler approach would be a better choice
if our focus were only on comparing simulated and field-based estimates of
the ocean's bomb-14C inventory, both of which are biased low
. The simpler modeling approach
underestimates the inventory, because it assumes a constant air–sea
CO2 disequilibrium during the industrial era; likewise, field
reconstructions of the ocean's bomb-14C inventory
are biased low because they assume
that ocean CT is unaffected by the anthropogenic perturbation.
Yet in terms of oceanic Δ14C, the simple and two-tracer approaches
yield similar results , because the effect of increasing
CT on oceanic Δ14C is negligible .
We also choose the two-tracer approach to take advantage of its
CTabio tracer to help distinguish physical from
biological contributions to CT.
To model 14C, OMIP neglects effects due to fractionation (i.e.,
from biology and gas exchange). Hence model results will be directly
comparable to measurements reported as Δ14C, a transformation of
the 14C / C ratio designed to correct for
fractionation . Thus biases associated with our abiotic
approach may generally be neglected. For natural 14C,
found essentially identical results for simulations
that accounted for biological fractionation vs. those that did not, as long
as the atmospheric CO2 boundary conditions were identical. For bomb
14C, which also includes the Suess effect, neglecting biological
fractionation results in small biases .
Hence for the omip1-spunup simulation, OMIP-BGC groups will simulate
four flavors of dissolved inorganic carbon: biotic natural
(CTnat), biotic total (CT), abiotic total
(CTabio), and abiotic radiocarbon
(14CTabio). Conversely for the omip1
simulation, groups will simulate only the first two flavors,
CTnat and CT. These tracers may be simulated
simultaneously or in separate simulations, although we recommend the former.
Carbon-13
Groups that have experience modeling 13C in their
biogeochemical model are requested to include it as a tracer in the OMIP-BGC
simulations. Groups without experience should avoid adding it. It is not
required to simulate 13C in order to participate in OMIP.
Modeling groups that will simulate ocean 13C are requested to report net
air–sea fluxes of 13CO2 and concentrations of total dissolved
inorganic carbon-13 (13CT) for the omip1-spunup
simulation. In Sect. we recommend how isotopic
fractionation during gas exchange should be modeled. Carbon-13 is typically
included in ocean models as a biotic variable influenced by fractionation
effects during photosynthesis that depend on growth rate and phytoplankton
type; some models also include fractionation during calcium carbonate
formation e.g.,. Modeling groups should incorporate
ecosystem fractionation specific to their ecosystem model formulation. We do
not request that modeling groups report variables related to 13C in
phytoplankton or other organic carbon pools, only 13CT and
net air–sea 13CO2 fluxes.
Duration and initialization
As described by , the physical components of the models
are to be forced over 310 years, i.e., over five repeated forcing cycles of
the 62-year CORE-II forcing (1948–2009). The biogeochemistry should be
included, along with the physical system, during the full 310 years
(1700–2009) and the inert chemistry only during the last 74 years
(1936–2009). The biogeochemical simulations will be initialized on calendar
date 1 January 1700, at the start of the first CORE-II forcing cycle. The
inert anthropogenic chemical tracers (CFC-11, CFC-12, SF6) will be
initialized to zero on 1 January 1936, during the fourth CORE-II forcing
cycle at model date 1 January 0237.
For the omip1 simulation, biogeochemical tracers will be initialized
generally with observational climatologies. Fields from the 2013 World Ocean
Atlas (WOA2013) will be used to initialize model fields of oxygen
as well as nitrate, total dissolved inorganic
phosphorus, and total dissolved inorganic silicon . The
latter two nutrients are often referred to simply as phosphate and silicate,
but other inorganic P and Si species also contribute substantially to
each total concentration (Fig. ). Indeed it is the
total dissolved concentrations (PT and SiT) that are
both modeled and measured. OMIP will provide all these initial biogeochemical
fields by merging WOA2013's means for January, available down to 500 m (for
nitrate, phosphate, and silicate), and down to 1500 m for oxygen, with its
annual-mean fields below.
Relative molar abundance of inorganic species of phosphorus (left)
and silicon (right) as a function of pH (total scale) in seawater at a
temperature of 18 ∘C and salinity of 35.
Model fields for AT and preindustrial CT will be
initialized with gridded data from version 2 of the Global Ocean Data
Analysis Project (GLODAPv2) from , based on discrete
measurements during WOCE and CLIVAR . For greater
consistency with GLODAPv1, OMIP-BGC model groups will use the CT
and AT fields from GLODAPv2's first period (1986–1999, the WOCE
era).
To initialize modeled dissolved organic carbon (DOC), OMIP provides fields
from the adjoint model from Schlitzer . For dissolved
iron (Fe), OMIP simulations will not be initialized from observations because
a full-depth, global 3-D data climatology is unavailable due to lack of data
coverage, particularly in the deep ocean. Hence for initial Fe fields, OMIP
provides the median model result from the Iron Model Intercomparison Project
FeMIP,. Yet that initialization field may not be
well suited for all Fe models, which differ greatly. Although OMIP provides
initialization fields for Fe and DOC, their actual initialization is left to
the discretion of each modeling group. In a previous comparison
, groups did not initialize modeled Fe with a common
field or approach because the complexity of the Fe cycle differed greatly
between models. Likewise, there was no common approach to initialize DOC
because biogeochemical models vary greatly in the way they represent its
lability. Initialization of other tracers is less critical (e.g.,
phytoplankton biomass is restricted to the top 200 m and equilibrates
rapidly, as do other biological tracers).
The omip1 simulation is relatively short and is thus manageable by
all groups, but many of its tracers will have large drifts because model
initial states will be far from their equilibrium states. These drifts
complicate assessment of model performance based on model–data agreement
. Hence a complementary simulation,
omip1-spunup, is proposed, where biogeochemical tracers are
initialized instead with a near-equilibrium state. Model groups may generate
this spun-up initial state by any means at their disposal. The classic
approach would be to spin up the model. That could be done either online,
repeating many times the same physical atmospheric forcing (CORE-II), or
offline, repeatedly cycling the physical transport fields from a circulation
model forced by a single loop of the CORE-II forcing.
If the spin-up simulation is made online, groups should reset their model's
physical fields at the end of every fifth cycle of CORE-II forcing to their
state at the beginning of the previous third cycle. Thus groups will avoid
long-term drift in the model's physical fields, and the latter will not
diverge greatly from those of the ocmip1 simulation but be allowed
to evolve freely over a period roughly equivalent to that of the transient
CO2 increase (last three forcing cycles). Conversely, biogeochemical
fields should not be reset. The end of the spin-up simulation will be reached
only after many repetitions of the five consecutive forcing cycles with the
online model. That final state (i.e., the physical and biogeochemical fields
from the end of the final fifth cycle) will be used to initialize the
ocmip1-spunup simulation. Offline spin-up simulations should be performed in
a consistent fashion. That is, groups should first integrate their
circulation model over two cycles of forcing and then use the physical
circulation fields generated during the third forcing cycle to subsequently
drive their offline biogeochemical model, typically until they reach the
criteria described below.
If possible, the spin-up should be run until it reaches the biogeochemical
equilibrium criteria adopted for OCMIP2. These criteria state that the
globally integrated, biotic and abiotic air–sea CO2 fluxes
(FCO2 and FCO2abio) should each drift by less
than 0.01 Pg C year-1 and that abiotic
14CT should be stabilized to the point that 98 % of the
ocean volume has a drift of less than 0.001 ‰ year-1
. The latter is equivalent to a drift of about 10 years
in the 14C age per 1000 years of simulation. For most models, these
drift criteria can be reached only after integrations of a few thousand model
years. To reach the spun-up state with the classic approach, i.e., with the
online or offline methods outlined above, we request that groups spin up
their model for at least 2000 years, if at all possible. Other approaches to
obtain the spun-up state, such as using tracer-acceleration techniques or
fast solvers , are also
permissible. If used, they should also be applied until models meet the same
equilibrium criteria described above.
The spin-up simulation itself should be initialized as for the omip1
simulation, except for the abiotic tracers and the 13CT
tracer. The abiotic initial fields of ATabio and
CTabio will be provided, being derived from initial
fields of T and S. Although CTabio is a passive
tracer carried in the model, ATabio is not. The latter
will be calculated from the initial 3-D salinity field as detailed below;
then that calculated field will be used to compute
CTabio throughout the water column assuming equilibrium
with the preindustrial level of atmospheric CO2 at the initial T and
S conditions (using OMIP's carbonate chemistry routines). For
14CTabio, initial fields will be based on those
from GLODAPv1 for natural Δ14C . OMIP will provide
these initial fields with missing grid cells filled based on values from adjacent
ocean grid points. Groups that include 13CT in
omip1-spunup should initialize that in the precursor spin-up
simulation to 0 ‰ following the approach of .
Beware though that equilibration timescales for 13C are longer than for
CT, implying the need for a much longer spin-up.
Air–sea gas exchange
Non-zero surface boundary conditions must also be included for all tracers
that are affected by air–sea gas exchange: CFC-11, CFC-12, SF6,
dissolved O2, and dissolved inorganic carbon in its various modeled
forms (CT, CTnat,
CTabio, 14CTabio, and
13CT). In OCMIP2, surface boundary conditions also included
a virtual-flux term for some biogeochemical tracers, namely in models that
had a virtual salt flux because they did not allow water transfer across the
air–sea interface. Water transfer calls for different implementations
depending on the way the free surface is treated, as discussed extensively by
. Groups that have implemented virtual fluxes for active
tracers (T and S) should follow the same practices to deal with virtual
fluxes of passive tracers such as CT and AT, as
detailed in the OCMIP2 design document and in the OCMIP2
Abiotic HOWTO . In OMIP, all models should report air–sea
CO2 fluxes due to gas exchange (FCO2,
FCO2nat, FCO2abio,
F14CO2abio, and F13CO2)
without
virtual fluxes included. Virtual fluxes are not requested as they do not
directly represent CO2 exchange between the atmosphere and ocean.
Surface boundary fluxes may be coded simply as adding source–sink terms to
the surface layer, e.g.,
JA=FAΔz1,
where for gas A, JA is its surface-layer source–sink term due
to gas exchange (mol m-3 s-1) and FA is its
air-to-sea flux (mol m-2 s-1), while Δz1 is the
surface-layer thickness (m).
In OMIP, we parameterize air–sea gas transfer of CFC-11, CFC-12,
SF6, O2, CO2, 14CO2, and
13CO2 using the gas transfer formulation also adopted for OCMIP2
(excluding effects of bubbles):
FA=kw[A]sat-[A],
where for gas A, kw is its gas transfer velocity, [A] is its simulated
surface-ocean dissolved concentration, and [A]sat is its
corresponding saturation concentration in equilibrium with the
water-vapor-saturated atmosphere at a total atmospheric pressure
Pa. Concentrations throughout are indicated by square brackets and
are in units of mol m-3.
For all gases that remain purely in dissolved form in seawater, gas exchange
is modeled directly with Eq. (). However, for CT,
only a small part remains as dissolved gas as mentioned in
Sect. . Thus the dissolved gas concentration
CO2* must first be computed, each time step, from
modeled CT and AT, and then the gas exchange is
computed with Eq. (). For example, for the two abiotic tracers
(in omip1-spunup),
FCO2abio=kwCO2*sat-CO2*
and
F14CO2abio=kw14CO2*sat-14CO2*.
For 13C, isotopic fractionation associated with gas exchange must be
included in the flux calculation. We recommend using the formulation of
:
F13CO2=kwαkαaq-g13RatmCO2*sat-13CO2*αCT-g,
where αk is the kinetic fractionation factor,
αaq-g is the fractionation factor for gas dissolution,
αCT-g is the equilibrium fractionation factor
between dissolved inorganic carbon and gaseous CO2, and
13Ratm is the 13C/12C ratio in
atmospheric CO2. Following ,
αCT-g depends on T and the fraction of carbonate
in CT, namely fCO3:
αCT-g=0.0144TcfCO3-0.107Tc+10.531000+1,
where Tc is temperature in units of ∘C, while division by
1000 and addition of 1 converts the fractionation factor from ϵ in
units of ‰ into α. The αaq-g term depends on
temperature following
αaq-g=0.0049Tc-1.311000+1.
Conversely no temperature dependence was found for αk. Hence
we recommend that OMIP modelers use a constant value for αk of
0.99912 (ϵk of -0.88 ‰), the average from
the measurements at 5 and 21 ∘C.
Seawater coefficients for fit of Sc to temperaturea,b
from .
Gas
A
B
C
D
E
Sc (20 ∘C)
CFC-11
3579.2
-222.63
7.5749
-0.14595
0.0011874
1179
CFC-12
3828.1
-249.86
8.7603
-0.1716
0.001408
1188
SF6
3177.5
-200.57
6.8865
-0.13335
0.0010877
1028
CO2
2116.8
-136.25
4.7353
-0.092307
0.0007555
668
O2
1920.4
-135.6
5.2122
-0.10939
0.00093777
568
N2O
2356.2
-166.38
6.3952
-0.13422
0.0011506
697
DMS
2855.7
-177.63
6.0438
-0.11645
0.00094743
941
a Coefficients for fit to Sc=A+BTc+CTc2+DTc3+ETc4, where Tc is
surface temperature in ∘C. b Conservative temperature
should be converted to in situ temperature before using these coefficients.
Coefficients for fita,b,c of solubility function
ϕA0 (mol L-1 atm-1).
Gas
a1
a2
a3
a4
b1
b2
b3
CFC-11
-229.9261
319.6552
119.4471
-1.39165
-0.142382
0.091459
-0.0157274
CFC-12
-218.0971
298.9702
113.8049
-1.39165
-0.143566
0.091015
-0.0153924
SF6
-80.0343
117.232
29.5817
0.0
0.0335183
-0.0373942
0.00774862
CO2
-160.7333
215.4152
89.8920
-1.47759
0.029941
-0.027455
0.0053407
N2O
-165.8806
222.8743
92.0792
-1.48425
-0.056235
0.031619
-0.0048472
a Fit to Eq. (), where T is in situ,
absolute temperature (K) and S is salinity (practical salinity scale).
b For units of mol m-3 atm-1, coefficients should
be multiplied by 1000. c The units refer to atm of each gas, not
atm of air. d When using these coefficients, conservative
temperature should be converted to in situ temperature (K) and absolute
salinity should be converted to practical salinity.
Gas transfer velocity
OMIP modelers should use the instantaneous gas transfer velocity kw
parameterization from , a quadratic function of
the 10 m wind speed u
kw=aSc660-1/2u2(1-fi),
to which we have added limitation from sea-ice cover following OCMIP2. Here
a is a constant, Sc is the Schmidt number, and fi is the sea-ice
fractional coverage of each grid cell (varying from 0 to 1). Normally, the
constant a is adjusted so that wind speeds used to force the model are
consistent with the observed global inventory of bomb 14C, e.g., as
done in previous phases of OCMIP . Here though,
we choose to use one value of a for all simulations, independent of whether
models are used in forced (OMIP) or coupled mode, namely the CMIP6
DECK (Diagnostic, Evaluation and Characterization of Klima) and
historical simulations. For a in OMIP, we rely on the reassessment
from , who used improved estimates of the
global-ocean bomb-14C inventory along with CCMP (Cross
Calibrated Multi-Platform) wind fields in an inverse approach with the
Modular Ocean Model to derive a best value of
a=0.251cmh-1(ms-1)2,
which will give kw in cm h-1 if winds speeds are in
m s-1. For model simulations where tracers are carried in
mol m-3, kw should be in units of m s-1; thus, a
should be set equal to 6.97×10-7 m s-1. The same
value of a should be adopted for the forced OMIP simulations and for
ESM simulations made under CMIP6.
Schmidt number
Besides a, the Schmidt number Sc is also needed to compute the gas
transfer velocity (Eq. ). The Schmidt number is the ratio of the
kinematic viscosity of water ν to the diffusion coefficient of the gas
D (Sc=ν/D). The coefficients for the fourth-order polynomial fit of
Sc to in situ temperature over the temperature range of -2 to
40 ∘C are provided in Table for
each gas to be modeled in OMIP and CMIP6. Fortran 95 routines using the same
formula and coefficients for all gases modeled in OMIP are available for
download via the gasx module of the mocsy package
(Sect. ).
Atmospheric saturation concentration
The surface gas concentration in equilibrium with the atmosphere (saturation concentration) is
[A]sat=K0fA=K0CfpA=K0CfPa-pH2OxA,
where for gas A, K0 is its solubility, fA is its
atmospheric fugacity, Cf is its fugacity coefficient,
pA is its atmospheric partial pressure, and xA is its
mole fraction in dry air, while Pa is again the total atmospheric
pressure (atm) and pH2O is the vapor pressure of water (also in
atm) at sea surface temperature and salinity .
The combined term K0CfPa-pH2O is available at Pa=1 atm
(i.e., Pa0) for all modeled gases except oxygen. We denote this
combined term as ϕA0 (at Pa0); elsewhere it is
known as the solubility function F
e.g.,, but we do not use the
latter notation here to avoid confusion with the air–sea flux
(Eq. ). For four of the gases to be modeled in OMIP, the
combined solubility function ϕA0 has been computed using the
empirical fit
lnϕA0=a1+a2100T+a3lnT100+a4T1002+Sb1+b2T100+b3T1002,
where T is the model's in situ, absolute temperature (ITS90) and S is its
salinity on the practical salinity scale (PSS-78). Thus separate sets of
coefficients are available for CO2 Table VI,
CFC-11 and CFC-12 Table 5, and SF6
Table 3, the values of which are summarized here in
Table . For O2, it is not ϕA0 that is
available, but rather O2sat0
, as detailed below.
Both the solubility function ϕA0 and the saturation
concentration [A]sat0 can be used at any atmospheric pressure
Pa, with errors of less than 0.1 %, by approximating
Eq. () as
[A]sat=PaPa0ϕA0xA=PaPa0[A]sat0,
where Pa0 is the reference atmospheric pressure (1 atm).
Variations in surface atmospheric pressure must not be neglected in OMIP
because they alter the regional distribution of [A]sat. For
example, the average surface atmospheric pressure between 60 and
30∘ S is 3 % lower than the global mean, thus reducing
surface-ocean pCO2 by 10 µatm and
O2sat by 10 µmol kg-1. The
atmospheric pressure fields used to compute gas saturations should also be
consistent with the other physical forcing. Thus for the OMIP forced
simulations, modelers will use surface atmospheric pressure from CORE II,
converted to atm.
Coefficients for fit of K′ and K0 (both in
mol L-1 atm-1).
Gas
a1
a2
a3
b1
b2
b3
K′
CFC-11
-134.1536
203.2156
56.2320
-0.144449
0.092952
-0.0159977
CFC-12
-122.3246
182.5306
50.5898
-0.145633
0.092509
-0.0156627
SF6
-96.5975
139.883
37.8193
0.0310693
-0.0356385
0.00743254
K0
CO2
-58.0931
90.5069
22.2940
0.027766
-0.025888
0.0050578
N2O
-62.7062
97.3066
24.1406
-0.058420
0.033193
-0.0051313
a Fit to Eq. (), where T is in situ,
absolute temperature (K) and S is practical salinity.
b The final three footnotes of Table also apply
here.
For the two abiotic carbon tracers, abbreviating K′=K0Cf, we can write their surface saturation concentrations
(Eq. ) as
CO2*satabio=K′Pa-pH2OxCO2
and
14CO2*satabio=CO2*satabio14ratm′.
Here 14ratm′ represents the normalized atmospheric ratio of
14C/C, i.e.,
14ratm′=14ratm14rstd=1+Δ14Catm1000,
where 14ratm is the atmospheric ratio of
14C/C, 14rstd is the analogous
ratio for the standard (1.170×10-12; see Appendix A), and
Δ14Catm is the atmospheric
Δ14C, the fractionation-corrected ratio of 14C/C relative to a standard reference given in permil (see
below). We define 14ratm′ and use it in
Eq. () to be able to compare
14CTabio and CTabio
directly, potentially simplifying code verification and testing. With
the above model formulation for the OMIP equilibrium run (where
xCO2atm=284.32 ppm and
Δ14Catm=0 ‰), both
CTabio and 14CTabio
have identical units. Short tests with the same initialization for
both tracers can thus verify consistency. Differences in the spin-up
simulation will stem only from different initializations and
radioactive decay. Differences will grow further during the
anthropogenic perturbation (in omip1-spunup, i.e., after
spin-up) because of the sharp contrast between the shape of the
atmospheric histories of xCO2 and
Δ14Catm.
For 13C, the δ13Catm in atmospheric CO2 is
incorporated into Eq. (9) through the term 13Ratm,
which is given by
13Ratm=δ13Catm1000+113Rstd,
where 13Rstd is the standard ratio 0.0112372
. In this formulation, unlike for
14CTabio, 13CT is not normalized
by the standard ratio. However, modeling groups may wish to simulate
normalized 13CT, e.g., by including a factor of 1/13Rstd analogous to the approach used for
14CTabio. Modeling groups that simulate 13C
in OMIP must report non-normalized values of the concentration
13CT and the air–sea flux F13CO2. No other
13C results are requested.
For all gases simulated in OMIP, the atmospheric saturation concentration
[A]sat is computed using Eq. (). For all gases except
oxygen, the combined solubility function ϕA0 is available,
being computed each time step using modeled T and S with
Eq. (), the corresponding gas-specific coefficients
(Table ), and the atmospheric mole fraction of each gas
xA. The exception is O2 because rather than xA
and ϕA0, it is the reference saturation concentration
O2sat0 that is available Eq. 8,
Table 1.
In all cases, the same Pa/Pa0 term is used to
account for effects of atmospheric pressure (Eq. ). For
Pa, modelers must use the fields of surface atmospheric pressure
(sap) from CORE II, i.e., for OMIP's forced ocean simulations
(omip1 and omip1-spunup), whereas for any CMIP6 coupled
simulation, modelers should use sap from the coupled atmospheric
model.
To compute [A]sat then, we only need one additional type of
information, namely the xA's for each of CO2, CFC-11,
CFC-12, and SF6, as well as corresponding atmospheric histories for
carbon isotopes.
xCFC-11, xCFC-12, and xSF6.
Atmospheric records for observed CFC-11 and CFC-12 (in parts per
trillion – ppt) are based on station data at 41∘ S and
45∘ N from with subsequent extensions
as compiled by . For OMIP, each station will
be treated as representative of its own hemisphere, except between
10∘ S and 10∘ N, where those station values will
be interpolated linearly as a function of latitude. Thus there are
three zones: 90–10∘ S, where CFCs are held to the same
value as at the station at 41∘ S;
10∘ S–10∘ N, a buffer zone where values are
interpolated linearly; and 10–90∘ N, where values are held
to the same value as at the measuring station at 45∘ N. For
SF6, OMIP also relies on the
synthesis over the same latitudinal bands. Values for all three
inert chemical tracers are given at mid-year. It is recommended that
modelers linearly interpolate these mid-year values to each time
step, because annual growth rates can be large and variable. These
atmospheric records are available at
http://cdiac.ornl.gov/ftp/oceans/CFC_ATM_Hist/CFC_ATM_Hist_2015;
eventually they will be made available at input4mips
(https://esgf-node.llnl.gov/search/input4mips).
xCO2. In the spin-up simulation, needed to
initialize omip1-spunup simulation, atmospheric CO2
is held constant at xCO2=284.32 ppm, the same
preindustrial value as used for the CMIP6 piControl
simulation. Over the industrial era, defined as between years
1850.0 and 2010.0 for both of OMIP's transient simulations
(omip1 and omip1-spunup), atmospheric
xCO2 will follow the same observed historical increase as
provided for CMIP6 . Modelers should use the
record of global annual-mean atmospheric xCO2,
interpolated to each time step. That increasing xCO2
affects the total tracer CT in both transient
simulations as well as the two abiotic tracers and
13CT in the omip1-spunup
simulation. However, it does not affect the natural tracer
CTnat, for which the atmosphere is always held
at xCO2=284.32 ppm. These xCO2 data are
available in the supplement to .
Δ14Catm. For the OMIP spin-up
simulation, Δ14Catm is held constant at
0 ‰. For the omip1-spunup simulation, the
equilibrium reference is thus year 1850.0. Then the model must be
integrated until 2010.0 following the observed record of
Δ14Catm, separated into three latitudinal
bands (90–20∘ S, 20∘ S–20∘ N, and
20–90∘ N). The Δ14Catm record is
the same as adopted for C4MIP, a compilation of tree-ring and
atmospheric measurements from and other sources
(I. Levin, personal communication, 2016). It is available at
input4mips (https://esgf-node.llnl.gov/search/input4mips).
δ13Catm. The atmospheric record of
δ13C is the same as adopted for C4MIP, a compilation of
ice-core data and atmospheric measurements at
Mauna Loa . It is available at input4mips
(https://esgf-node.llnl.gov/search/input4mips).
Surface-ocean concentration
The equation above for the atmospheric equilibrium (saturation)
concentration of a gas (Eq. ) should not be confused with
the analogous equation for the simulated ocean concentration. The
surface-ocean equation allows conversion between the simulated
surface-ocean dissolved gas concentration [A], the corresponding
fugacity fO, and the partial pressure pO of
the surface ocean as follows:
[A]=K0fO=K0CfpO=K′pO.
This surface-ocean equation is analogous to that for the atmospheric
equilibrium saturation concentration [A]sat (Eq. ),
except that the ocean equation omits the final portion of the atmospheric
equation which computes the mole fraction, a conventional parameter only for
the atmosphere. Thus the combined term that includes the atmospheric pressure
and humidity corrections (last term in parentheses) in Eq. () is
not pertinent for the surface-ocean equation. It should not be used when
converting between simulated oceanic [A] and the corresponding
pO. Confusion on this point was apparent in the publicly
available OMIP2 code, i.e., for the conversion from
CO2* to pCO2, although that did not affect
simulated FCO2.
To avoid potential confusion and redundancy, OMIP modelers may prefer to
separately compute the parts of ϕA rather than computing
ϕA0 and using it directly. Since
ϕA=K0Cf(Pa-pH2O)=K′(Pa-pH2O),
modelers need only compute K′, and use that in both the ocean equation
(Eq. ) and the atmospheric saturation equation (Eq. ),
while for the latter also correct for atmospheric pressure and humidity,
i.e., the (Pa-pH2O) term. That combined correction
is to be computed with Pa from the CORE II forcing and with
pH2O calculated from model surface T and S
Eq. 10:
pH2O=24.4543-67.4509100T-4.8489lnT100-0.000544S,
where pH2O is in atm, T is the in situ,
absolute temperature, and S is practical salinity. In this way, OMIP
modelers may avoid using the sometimes confusing combined term
ϕA0 altogether as well as its approximative pressure
correction when calculating the saturation concentration
(Eq. ). Pressure corrections for K′ may be neglected
in the surface ocean where total pressure remains close to 1 atm
.
The ocean equation (Eq. ) converts a simulated dissolved gas
concentration to a partial pressure using its combined product K′, which
can be computed directly for some gases or via a two-step process for others.
For OMIP's inert chemical tracers, tabulated coefficients can be used to
compute K′ directly, i.e., for CFC-11 and CFC-12
Table 2 and for SF6
Table 2 using modeled T and S in an equation just
like Eq. () but without the first T2 term (a4=0):
ln(K′)=a1+a2100T+a3lnT100+Sb1+b2T100+b3T1002,
where T is the in situ absolute temperature and S is practical salinity.
For O2, K′ is not needed for the saturation calculations, but it
is necessary when using the simulated dissolved O2
to compute the corresponding surface-ocean pO2, an output
variable for OMIP and CMIP6. That solubility conversion factor K′ can be
derived by substituting its definition into Eq. () and
rearranging, so that
KO2′=O2sat0xO2(Pa0-pH2O),
where the numerator is from Eq. (8) of using coefficients
from their Table 1, and the denominator is the product of the corresponding
constant atmospheric mole fraction of
O2 (xO2=0.20946)
and the wet-to-dry correction at 1 atm as described above. The
computed KO2′ is then exploited to compute the partial pressure of
oxygen (pO2=O2/KO2′).
For CO2, tabulated coefficients are not available to compute K′,
but they are available to compute K0 Table 1.
Hence given that K′=K0Cf, modelers must also compute
the fugacity coefficient Cf from Eq. (9) of :
Cf=expB+2x22δ12PaoRT,
where B is the virial coefficient of CO2 Eq. 6,
x2 is the sum of the mole fractions of all remaining gases (1-xCO2, when xCO2≪1), and δ12=57.7-0.118T. Here Pao is the total pressure
(atmospheric + hydrostatic) in atm, R is the gas constant
(82.05736 cm3 atm mol-1 K-1), and T is the in situ
absolute temperature (K).
Although the surface-ocean concentration of dissolved carbon dioxide gas
CO2* is needed to compute air–sea CO2
exchange, it is not that inorganic carbon species that is carried as a tracer
in ocean carbon models (Sect. ). Instead the
CO2* concentration (mol m-3) must be computed
each time step from a model's simulated surface CT,
AT, T, and S as well as nutrient concentrations (total
dissolved inorganic phosphorus PT and silicon SiT) as
detailed in the following section. All OMIP biogeochemical models will carry
CT and AT as passive tracers. Most if not all models
will also carry at least one inorganic nutrient, nitrogen or phosphorus. Some will
carry silicon. For models that carry only nitrogen, it is preferred that they
compute and report
PT by dividing the total dissolved inorganic nitrogen
concentration by 16, the constant N : P ratio from .
For models without SiT, it is preferred that they use
climatological SiT data interpolated to their model grid (i.e.,
annual average data from WOA2013). These options offer a better alternative
than assuming
that nutrient concentrations are zero, which leads to systematic
shifts on
the order of 10 µatm in calculated surface-water pCO2.
The abiotic portion of the biogeochemical simulation carries only two
tracers, CTabio and
14CTabio, which are not connected to other
biogeochemical tracers. Hence to compute corresponding abiotic
CO2* and 14CO2*
concentrations, we also need abiotic alkalinity. Following OCMIP2, the
abiotic alkalinity in OMIP will be calculated simply as a normalized linear
function of salinity:
ATabio=AT‾SS‾,
where A‾T is the global mean of surface observations
2297 µmol kg-1 and S‾ is the
model's global- and annual-mean surface salinity. In practice, it is
recommended that S‾ is first computed as the global mean of the
initial salinity field and then, after 1 year of simulation, from the
annual-mean salinity of the previous year. Also needed are two other input
arguments, PT and SiT. Although accounting for both
of their acid systems makes a difference, these abiotic tracers are not
included along with abiotic CT. Hence we take their
concentrations as being constant, equal to the global mean of surface
observations for PT of 0.5 µmol kg-1 and for
SiT of 7.5 µmol kg-1. The assumption of constant
nutrient distributions applies only to the carbonate chemistry calculations
for abiotic CT (i.e., CTabio).
For the abiotic simulation's radiocarbon tracer, we must likewise
compute its surface-ocean dissolved gas concentration
14CO2*. The latter is related to the calculated
dissolved gas concentration of the stable abiotic carbon tracer as
follows:
14CO2*abio=CO2*abio14rocn′,
where
14rocn′=14rocn14rstd=14CTabioCTabio
and 14rocn is the 14C/C of seawater.
This normalization essentially means that 14CTabio
represents the actual fractionation-corrected 14C concentration
divided by 14rstd. This output must be saved in normalized
form. But for subsequent 14C budget calculations, it will be
necessary to back-correct the normalized and fractionation-corrected modeled
concentration (14CTabio) and 14C flux
(F14CO2abio), i.e., the only two 14C
variables saved in OMIP, to molar units of actual 14C (see
Appendix A). For eventual comparison to ocean measurements, one can compute
oceanic Δ14C as
Δ14Cocnabio=100014rocn′-1.
For 13C, the surface-ocean dissolved gas concentration
[13CO2*] is given by
13CO2*=CO2*13rocn,
where 13rocn=13CT/CT. Here
13CT is not normalized by the standard ratio, but modeling
groups may wish to simulate normalized 13CT by including a
factor of 1/13rstd, analogous to what is done for the
14CTabio normalization above.
Carbonate chemistry
Unlike other modeled gases in OMIP,
CO2 does not occur in seawater as a simple dissolved passive tracer.
Instead, it reacts with seawater, forming carbonic acid (H2CO3),
most of which dissociates into two other inorganic species, bicarbonate
(HCO3-) and carbonate (CO32-) ions. Since dissolved
CO2 cannot be distinguished analytically from the much less abundant
H2CO3, common practice is to refer to the sum of the two,
CO2+H2CO3, as CO2*. The sum of the three
species CO2*+HCO3-+CO32- is referred to
as total dissolved inorganic carbon CT, while their partitioning
depends on seawater pH, temperature, salinity, and pressure. The pH may be
calculated from CT and seawater's ionic charge balance,
formalized as total alkalinity AT. Both CT and
AT are conservative with respect to mixing and changes in
seawater temperature, salinity, and pressure. Hence both are carried as
passive tracers in all ocean models, and both are used, along with
temperature, salinity, and nutrient concentrations, to compute the dissolved
concentration of CO2 and the related pCO2, as needed to compute
air–sea CO2 fluxes.
Output for inert chemistry.
Symbol
Variable name
Units
Shape
Priority
Long name
Annual means
SF6
sf6
mol m-3
XYZ
2
Mole concentration of SF6 in seawater
CFC-11
cfc11
mol m-3
XYZ
2
Mole concentration of CFC-11 in seawater
CFC-12
cfc12
mol m-3
XYZ
1
Mole concentration of CFC-12 in seawater
Monthly means
SF6
sf6
mol m-3
XYZ
2
Mole concentration of SF6 in seawater
CFC-11
cfc11
mol m-3
XYZ
2
Mole concentration of CFC-11 in seawater
CFC-12
cfc12
mol m-3
XYZ
1
Mole concentration of CFC-12 in seawater
FSF6
fgsf6
mol m-2 s-1
XY
2
Surface downward SF6 flux
FCFC-11
fgcfc11
mol m-2 s-1
XY
2
Surface downward CFC-11 flux
FCFC-12
fgcfc12
mol m-2 s-1
XY
1
Surface downward CFC-12 flux
Daily mean biogeochemical output.
Variable name
Units
Shape
Priority
Long name
chlos
kg m-3
XY
3
Surface mass conc. of total phytoplankton expressed as chlorophyll seawater
phycos
mol m-3
XY
3
Surface phytoplankton carbon concentration
To simulate carbonate chemistry, OMIP groups should use the total pH
scale and the equilibrium constants recommended for best practices
. Additionally, the model's total
alkalinity equation should include alkalinity from phosphoric and
silicic acid systems as well as from carbonic acid, boric acid, and
water, namely
AT=AC+AB+AW+AP+ASi+AO,
where
AC=HCO3-+2CO32-,AB=B(OH)4-,AW=[OH-]-[H+]F-HSO4--[HF],AP=HPO42-+2PO43--[H3PO4],ASi=SiO(OH)3-,AO=[NH3]+[HS-]+…
The right side of Eq. () thus separates the contributions
from components of carbonic acid, boric acid, water, phosphoric acid, silicic
acid, and other species, respectively. Neglect of AP and
ASi has been common among model groups but leads to systematic
errors in computed pCO2, e.g., in the Southern Ocean
. Models with the nitrogen cycle should also
account for effects of changes in the different inorganic forms of nitrogen
on total alkalinity, including changes due to denitrification and nitrogen
fixation plus nitrification.
Models with PT as the sole macronutrient tracer should
consider accounting for the effect of nitrate assimilation and
remineralization on alkalinity, effects that are 16 times larger than
for those for PT .
Although phosphorus and silicon alkalinity is included in the carbonate
chemistry routines provided for OCMIP2 and OCMIP3
, those routines focused only on computing
surface pCO2 and are now outdated. They have been replaced by
mocsy, a Fortran 95 package for ocean modelers
. Relative to the former OCMIP code, mocsy computes
derived variables (e.g., pCO2, pH, CO32-, and CaCO3 saturation
states) throughout the water column, corrects for common errors in pressure
corrections, and replaces the solver of the pH-alkalinity equation with the
faster and safer SolveSaphe algorithm from . The latter
converges under all conditions, even for very low salinity (low
CT and AT), unlike other approaches. Although by
default mocsy uses older scales for temperature and salinity (ITS90
and PSS78, respectively) for input, it now includes a new option so that
modelers can choose to use the TEOS-10 standards (Conservative Temperature
and Absolute Salinity) instead. The mocsy routines may be downloaded
from
https://github.com/jamesorr/mocsy.git
Annual-mean biogeochemical output: priority 1.
Symbol
Variable name
Units
Shape
Priority
Long name
CT
dissic
mol m-3
XYZ
1
Dissolved inorganic carbon concentration
CTnat
dissicnat
mol m-3
XYZ
1
Natural dissolved inorganic carbon concentration
CTabio
dissicabio
mol m-3
XYZ
1
Abiotic dissolved inorganic carbon concentration
14CTabio
dissi14cabio
mol m-3
XYZ
1
Abiotic dissolved inorganic 14carbon concentration
13CT
dissi13c
mol m-3
XYZ
1
Dissolved inorganic 13carbon concentration
AT
talk
mol m-3
XYZ
1
Total alkalinity
ATnat
talknat
mol m-3
XYZ
1
Natural total alkalinity
pH
ph
1
XYZ
1
pH
pHnat
phnat
1
XYZ
1
Natural pH
pHabio
phabio
1
XYZ
1
Abiotic pH
O2
o2
mol m-3
XYZ
1
Dissolved oxygen concentration
NO3-
no3
mol m-3
XYZ
1
Dissolved nitrate concentration
PT
po4a,b
mol m-3
XYZ
1
Total dissolved inorganic phosphorus concentration
SiT
sic
mol m-3
XYZ
1
Total dissolved inorganic silicon concentration
Fe
dfed
mol m-3
XYZ
1
Mole concentration of dissolved iron in seawater
Chl
chle
kg m-3
XYZ
1
Mass concentration of total chlorophyll in seawater
FCO2tot
fgco2
kg m-2 s-1
XY
1
Surface downward flux of total CO2
FCO2nat
fgco2nat
kg m-2 s-1
XY
1
Surface downward flux of natural CO2
FCO2abio
fgco2abio
kg m-2 s-1
XY
1
Surface downward flux of abiotic CO2
F14CO2abio
fg14co2abio
kg m-2 s-1
XY
1
Surface downward flux of abiotic 14CO2
F13CO2
fg13co2
kg m-2 s-1
XY
1
Surface downward flux of 13CO2
a For models that do not carry PT as a tracer,
it should be computed from NO3- assuming N : P = 16 : 1;
b PT=H3PO4+H2PO4-+HPO42-+PO43-. In seawater most PT is
in the form of HPO42-, while PO43- makes up only
∼ 10 % at pH 8. c SiT=Si(OH)4+SiO(OH)3-,
dominated by the former (silicic acid). d Modeled dissolved iron
includes all simulated dissolved species, both free and organically
complexed. e Sum of chlorophyll from all phytoplankton group
concentrations. In most models this is equal to chldiat + chlmisc.
Annual-mean biogeochemical output: priority 2
(concentrations).
Symbol
Variable name
Units
Shape
Priority
Long name
DOC
dissoc
mol m-3
XYZ
2
Dissolved organic carbon concentration
phyc
mol m-3
XYZ
2
Phytoplankton carbon concentration
zooc
mol m-3
XYZ
2
Zooplankton carbon concentration
detoc
mol m-3
XYZ
2
Detrital organic carbon concentration
[CaCO3]calc
calc
mol m-3
XYZ
2
Calcite concentration
[CaCO3]arag
arag
mol m-3
XYZ
2
Aragonite concentration
[O2]sat
o2sat
mol m-3
XYZ
2
Dissolved oxygen concentration at saturation
[NH4+]
nh4
mol m-3
XYZ
2
Dissolved ammonium concentration
chldiata
kg m-3
XYZ
2
Mass concentration of diatoms expressed as chlorophyll in seawater
chldiazb
kg m-3
XYZ
2
Mass concentration of diazotrophs expressed as chlorophyll in seawater
chlcalcc
kg m-3
XYZ
2
Mass concentration of calcareous phytoplankton expressed as chlorophyll in seawater
chlpicod
kg m-3
XYZ
2
Mass concentration of picophytoplankton expressed as chlorophyll in seawater
chlmisce
kg m-3
XYZ
2
Mass concentration of other phytoplankton expressed as chlorophyll in seawater
pon
mol m-3
XYZ
2
Mole concentration of particulate organic matter expressed as nitrogen in seawater
pop
mol m-3
XYZ
2
Mole concentration of particulate organic matter expressed as phosphorus in seawater
bfef
mol m-3
XYZ
2
Mole concentration of particulate organic matter expressed as ironin seawater
bsig
mol m-3
XYZ
2
Mole concentration of particulate organic matter expressed as silicon in seawater
phyn
mol m-3
XYZ
2
Mole concentration of total phytoplankton expressed as nitrogenin seawater
phyp
mol m-3
XYZ
2
Mole concentration of total phytoplankton expressed as phosphorus in seawater
phyfe
mol m-3
XYZ
2
Mole concentration of total phytoplankton expressed as iron inseawater
physi
mol m-3
XYZ
2
Mole concentration of total phytoplankton expressed as silicon inseawater
DMS
dms
mol m-3
XYZ
2
Mole concentration of dimethyl sulfide in seawater
[CO32-]
co3
mol m-3
XYZ
2
Carbonate ion concentration
[CO32-]nat
co3nat
mol m-3
XYZ
2
Natural carbonate ion concentration
[CO32-]abio
co3abio
mol m-3
XYZ
2
Abiotic carbonate ion concentration
[CO32-]satcalc
co3satcalc
mol m-3
XYZ
2
Carbonate ion concentration for seawater in equilibrium with pure calcite
[CO32-]satarag
co3satarag
mol m-3
XYZ
2
Carbonate ion concentration for seawater in equilibrium with pure aragonite
a Chlorophyll from the diatom phytoplankton component
concentration alone; b chlorophyll concentration from the
diazotrophic phytoplankton component alone; c chlorophyll
concentration from the calcite-producing phytoplankton component alone;
d chlorophyll concentration from the picophytoplankton
(< 2 µm) component alone; e chlorophyll from
additional phytoplankton component concentrations alone; f sum of
particulate organic iron component concentrations; g sum of
particulate silica component concentrations.
Annual-mean biogeochemical output: priority 2
(rates).
Variable name
Units
Shape
Priority
Long name
pp
mol m-3 s-1
XYZ
2
Primary carbon production by total phytoplankton
pnitrate
mol m-3 s-1
XYZ
2
Primary carbon production by phytoplankton due to nitrate uptake alone
pbfe
mol m-3 s-1
XYZ
2
Biogenic iron production
pbsi
mol m-3 s-1
XYZ
2
Biogenic silica production
pcalc
mol m-3 s-1
XYZ
2
Calcite production
parag
mol m-3 s-1
XYZ
2
Aragonite production
expc
mol m-2 s-1
XYZ
2
Sinking particulate organic carbon flux
expn
mol m-2 s-1
XYZ
2
Sinking particulate organic nitrogen flux
expp
mol m-2 s-1
XYZ
2
Sinking particulate organic phosphorus flux
expfe
mol m-2 s-1
XYZ
2
Sinking particulate iron flux
expsi
mol m-2 s-1
XYZ
2
Sinking particulate silica flux
expcalc
mol m-2 s-1
XYZ
2
Sinking calcite flux
exparag
mol m-2 s-1
XYZ
2
Sinking aragonite flux
remoc
mol m-3 s-1
XYZ
2
Remineralization of organic carbon
dcalc
mol m-3 s-1
XYZ
2
Calcite dissolution
darag
mol m-3 s-1
XYZ
2
Aragonite dissolution
ppdiat
mol m-3 s-1
XYZ
2
Diatom primary carbon production
Annual-mean biogeochemical output: priority 3.
Variable name
Units
Shape
Priority
Long name
bacc
mol m-3
XYZ
3
Bacterial carbon concentration
phydiat
mol m-3
XYZ
3
Mole concentration of diatoms expressed as carbon in seawater
phydiaz
mol m-3
XYZ
3
Mole conc. of diazotrophs expressed as carbon in seawater
phycalc
mol m-3
XYZ
3
Mole conc. of calcareous phytoplankton expressed as carbon in seawater
phypicoa
mol m-3
XYZ
3
Mole conc. of picophytoplankton expressed as carbon in seawater
phymiscb
mol m-3
XYZ
3
Mole conc. of miscellaneous phytoplankton expressed as carbon in seawater
zmicroc
mol m-3
XYZ
3
Mole conc. of microzooplankton expressed as carbon in seawater
zmesod
mol m-3
XYZ
3
Mole conc. of mesozooplankton expressed as carbon in seawater
zmisce
mol m-3
XYZ
3
Mole conc. of other zooplankton expressed as carbon in seawater
dpocdtdiaz
mol m-3 s-1
XYZ
3
Tendency of mole conc. of organic carbon in seawater due to NPP by diazotrophs
dpocdtcalc
mol m-3 s-1
XYZ
3
Tendency of mole conc. of organic carbon in seawater due to NPP by calcareous phytoplankton
dpocdtpico
mol m-3 s-1
XYZ
3
Tendency of mole conc. of organic carbon in seawater due to NPP by picophytoplankton
ppdiat
mol m-3 s-1
XYZ
3
Net primary organic carbon production by diatoms
ppdiaz
mol m-3 s-1
XYZ
3
Net primary mole productivity of carbon by diazotrophs
ppcalc
mol m-3 s-1
XYZ
3
Net primary mole productivity of carbon by calcareous phytoplankton
pppico
mol m-3 s-1
XYZ
3
Net primary mole productivity of carbon by picophytoplankton
ppmisc
mol m-3 s-1
XYZ
3
Net primary organic carbon production by other phytoplankton
bddtdic
mol m-3 s-1
XYZ
3
Rate of change in dissolved inorganic carbon due to biological activity
bddtdin
mol m-3 s-1
XYZ
3
Rate of change in nitrogen nutrients due to biological activity
bddtdip
mol m-3 s-1
XYZ
3
Rate of change in dissolved phosphorus due to biological activity
bddtdife
mol m-3 s-1
XYZ
3
Rate of change in dissolved inorganic iron due to biological activity
bddtdisi
mol m-3 s-1
XYZ
3
Rate of change in total dissolved inorganic silicon due to biological activity
bddtalk
mol m-3 s-1
XYZ
3
Rate of change in alkalinity due to biological activity
fescav
mol m-3 s-1
XYZ
3
Nonbiogenic iron scavenging
fediss
mol m-3 s-1
XYZ
3
Particle source of dissolved iron
graz
mol m-3 s-1
XYZ
3
Total grazing of phytoplankton by zooplankton
a Carbon concentration from the picophytoplankton
(< 2 µm) component alone; b carbon concentration
from the additional phytoplankton component alone; c carbon
concentration from the microzooplankton (< 20 µm) component
alone; d carbon concentration from the mesozooplankton
(20–200 µm) component alone; e carbon from additional
zooplankton component concentrations alone (e.g., micro, meso). Provides
check for model intercomparison since some phytoplankton groups are
supersets.
Monthly mean biogeochemical output: priority
1.
Symbol
Variable name
Units
Shape
Priority
Long name
dissicos
mol m-3
XY
1
Surface dissolved inorganic carbon concentration
dissicnatos
mol m-3
XY
1
Surface natural dissolved inorganic carbon concentration
dissicabioos
mol m-3
XY
1
Surface abiotic dissolved inorganic carbon concentration
dissi14cabioos
mol m-3
XY
1
Surface abiotic dissolved inorganic 14carbon concentration
dissi13cos
mol m-3
XY
1
Surface dissolved inorganic 13carbon concentration
talkos
mol m-3
XY
1
Surface total alkalinity
talknatos
mol m-3
XY
1
Surface natural total alkalinity
phos
1
XY
1
Surface pH on total scale
sios
mol m-3
XY
1
Surface total dissolved inorganic silicon concentration
o2os
mol m-3
XY
1
Surface dissolved oxygen concentration
o2satos
mol m-3
XY
1
Surface dissolved oxygen concentration at saturation
po4os
mol m-3
XY
1
Surface total dissolved inorganic phosphorus concentration
chlos
kg m-3
XY
1
Surface mass conc. of total phytoplankton expressed as chlorophyll in seawater
CT
dissic
mol m-3
XYZ
1
Dissolved inorganic carbon concentration
AT
talk
mol m-3
XYZ
1
Total alkalinity
pH
ph
1
XYZ
1
pH on total scale
PT
po4a
mol m-3
XYZ
1
Total dissolved inorganic phosphorus concentration
intppb
mol m-2 s-1
XY
1
Primary organic carbon production by all types of phytoplankton
expc100c
mol m-2 s-1
XY
1
Downward flux of particle organic carbon
expcalc100b
mol m-2 s-1
XY
1
Downward flux of calcite
exparag100b
mol m-2 s-1
XY
1
Downward flux of aragonite
pCO2
spco2
Pa
XY
1
Surface aqueous partial pressure of CO2
pCO2nat
spco2nat
Pa
XY
1
Natural surface aqueous partial pressure of CO2
pCO2abio
spco2abio
Pa
XY
1
Abiotic surface aqueous partial pressure of CO2
FCO2tot
fgco2
kg m-2 s-1
XY
1
Surface downward flux of total CO2
FCO2nat
fgco2nat
kg m-2 s-1
XY
1
Surface downward flux of natural CO2
FCO2abio
fgco2abio
kg m-2 s-1
XY
1
Surface downward flux of abiotic CO2
F14CO2abio
fg14co2abio
kg m-2 s-1
XY
1
Surface downward flux of abiotic 14CO2
F13CO2
fg13co2
kg m-2 s-1
XY
1
Surface downward flux of 13CO2
FO2
fgo2
mol m-2 s-1
XY
1
Surface downward flux of O2
a For models that do not carry PT as a
tracer, compute it from NO3- assuming N : P = 16 : 1.
b Vertically integrated total primary (organic carbon) production
by phytoplankton. This should equal the sum of intpdiat + intpphymisc, but
those individual components may be unavailable in some models. c At
100 m depth.
Monthly mean biogeochemical output: priority 2 (2-D fields).
Symbol
Variable name
Units
Shape
Priority
Long name
dissocos
mol m-3
XY
2
Surface dissolved organic carbon concentration
phycos
mol m-3
XY
2
Surface phytoplankton carbon concentration
zoocos
mol m-3
XY
2
Surface zooplankton carbon concentration
detocos
mol m-3
XY
2
Surface detrital organic carbon concentration
calcos
mol m-3
XY
2
Surface calcite concentration
aragos
mol m-3
XY
2
Surface aragonite concentration
phnatos
1
XY
2
Surface natural pH on total scale
phabioos
1
XY
2
Surface abiotic pH on total scale
no3os
mol m-3
XY
2
Surface dissolved nitrate concentration
nh4os
mol m-3
XY
2
Surface dissolved ammonium concentration
dfeos
mol m-3
XY
2
Surface dissolved iron concentration
co3os
mol m-3
XY
2
Surface carbonate ion concentration
co3natos
mol m-3
XY
2
Surface natural carbonate ion concentration
co3abioos
mol m-3
XY
2
Surface abiotic carbonate ion concentration
co3satcalcos
mol m-3
XY
2
Surface carbonate ion conc. for seawater in equilibrium with pure calcite
co3sataragos
mol m-3
XY
2
Surface carbonate ion conc. for seawater in equilibrium with pure aragonite
limndiatf
1
XY
2
Nitrogen limitation of diatoms
limirrdiatf
1
XY
2
Irradiance limitation of diatoms
limfediatf
1
XY
2
Iron limitation of diatoms
intppnitratea
mol m-2 s-1
XY
2
Primary organic carbon production by phytoplankton based on nitrate uptake alone
intppdiatb
mol m-2 s-1
XY
2
Primary organic carbon production by diatoms
∫CTdz
intdicc
kg m-2
XY
2
Dissolved inorganic carbon content
∫DOCdz
intdocd
kg m-2
XY
2
Dissolved organic carbon content
∫OCdz
intpoce
kg m-2
XY
2
Particulate organic carbon content
a Vertically integrated primary (organic carbon)
production by phytoplankton based on nitrate uptake alone;b vertically integrated primary (organic carbon) production by the
diatom phytoplankton component alone;c vertically integrated CT;d vertically integrated DOC (explicit pools only);e vertically integrated POC;f these 2-D limitation terms should be calculated as the carbon biomass weighted average for the upper
100 m.
Monthly mean biogeochemical output: priority 2 (3-D fields).
Symbol
Variable name
Units
Shape
Priority
Long name
CTnat
dissicnat
mol m-3
XYZ
2
Natural dissolved inorganic carbon concentration
CTabio
dissicabio
mol m-3
XYZ
2
Abiotic dissolved inorganic carbon concentration
14CTabio
dissi14cabio
mol m-3
XYZ
2
Abiotic dissolved inorganic 14carbon concentration
13CT
dissi13c
mol m-3
XYZ
2
Dissolved inorganic 13carbon concentration
ATnat
talknat
mol m-3
XYZ
2
Natural total alkalinity
pHnat
phnat
1
XYZ
2
Natural pH
pHabio
phabio
1
XYZ
2
Abiotic pH
[O2]
o2
mol m-3
XYZ
2
Dissolved oxygen concentration
o2sat
mol m-3
XYZ
2
Dissolved oxygen concentration at saturation
[NO3-]
no3
mol m-3
XYZ
2
Dissolved nitrate concentration
[NH4+]
nh4
mol m-3
XYZ
2
Dissolved ammonium concentration
Fec
dfe
mol m-3
XYZ
2
Dissolved iron concentration
SiT
si
mol m-3
XYZ
2
Total dissolved inorganic silicon concentration
Chl
chl
kg m-3
XYZ
2
Mass concentration of total phytoplankton expressed as chlorophyll in seawater
DOC
dissoc
mol m-3
XYZ
2
Dissolved organic carbon concentration
phyc
mol m-3
XYZ
2
Phytoplankton carbon concentration
zooc
mol m-3
XYZ
2
Zooplankton carbon concentration
detoc
mol m-3
XYZ
2
Detrital organic carbon concentration
[CaCO3]calc
calc
mol m-3
XYZ
2
Calcite concentration
[CaCO3]arag
arag
mol m-3
XYZ
2
Aragonite concentration
[CO32-]
co3
mol m-3
XYZ
2
Carbonate ion concentration
[CO32-]nat
co3nat
mol m-3
XYZ
2
Natural carbonate ion concentration
[CO32-]abio
co3abio
mol m-3
XYZ
2
Abiotic carbonate ion concentration
[CO32-]satcalc
co3satcalc
mol m-3
XYZ
2
Carbonate ion concentration for seawater in equilibrium with pure calcite
[CO32-]satarag
co3satarag
mol m-3
XYZ
2
Carbonate ion concentration for seawater in equilibrium with pure aragonite
Monthly mean biogeochemical output: priority 3 (concentrations of
surface fields).
Variable name
Units
Shape
Priority
Long name
baccos
mol m-3
XY
3
Surface bacterial carbon concentration
phydiatos
mol m-3
XY
3
Surface mole concentration of diatoms expressed as carbon in seawater
phydiazos
mol m-3
XY
3
Surface mole concentration of diazotrophs expressed as carbon in seawater
phycalcos
mol m-3
XY
3
Surface mole concentration of calcareous phytoplankton expressed as carbon in seawater
phypicoos
mol m-3
XY
3
Surface mole concentration of picophytoplankton expressed as carbon in seawater
phymiscos
mol m-3
XY
3
Surface mole concentration of miscellaneous phytoplankton expressed ascarbon in seawater
zmicroos
mol m-3
XY
3
Surface mole concentration of microzooplankton expressed as carbon in seawater
zmesoos
mol m-3
XY
3
Surface mole concentration of mesozooplankton expressed as carbon in seawater
zmiscos
mol m-3
XY
3
Surface mole concentration of other zooplankton expressed as carbon in seawater
chldiatos
kg m-3
XY
3
Surface mass concentration of diatoms expressed as chlorophyll in seawater
chldiazos
kg m-3
XY
3
Surface mass concentration of diazotrophs expressed as chlorophyll in seawater
chlcalcos
kg m-3
XY
3
Surface mass concentration of calcareous phytoplankton expressed as chlorophyll in seawater
chlpicoos
kg m-3
XY
3
Surface mass concentration of picophytoplankton expressed as chlorophyll in seawater
chlmiscos
kg m-3
XY
3
Surface mass concentration of other phytoplankton expressed as chlorophyll in seawater
ponos
mol m-3
XY
3
Surface mole concentration of particulate organic matter expressed as nitrogen in seawater
popos
mol m-3
XY
3
Surface mole concentration of particulate organic matter expressed as phosphorus in seawater
bfeos
mol m-3
XY
3
Surface mole concentration of particulate organic matter expressed as iron in seawater
bsios
mol m-3
XY
3
Surface mole concentration of particulate organic matter expressed as silicon in seawater
phynos
mol m-3
XY
3
Surface mole concentration of phytoplankton nitrogen in seawater
phypos
mol m-3
XY
3
Surface mole concentration of total phytoplankton expressed as phosphorus in seawater
phyfeos
mol m-3
XY
3
Surface mass concentration of diazotrophs expressed as chlorophyll in seawater
physios
mol m-3
XY
3
Surface mole concentration of total phytoplankton expressed as silicon in seawater
dmsos
mol m-3
XY
3
Surface mole concentration of dimethyl sulfide in seawater
Monthly mean biogeochemical output: priority 3 (concentrations of
3-D fields).
Variable name
Units
Shape
Priority
Long name
bacc
mol m-3
XYZ
3
Bacterial carbon concentration
phydiat
mol m-3
XYZ
3
Mole concentration of diatoms expressed as carbon in seawater
phydiaz
mol m-3
XYZ
3
Mole concentration of diazotrophs expressed as carbon in seawater
phycalc
mol m-3
XYZ
3
Mole concentration of calcareous phytoplankton expressed as carbon in seawater
phypico
mol m-3
XYZ
3
Mole concentration of picophytoplankton expressed as carbon in seawater
phymisc
mol m-3
XYZ
3
Mole concentration of miscellaneous phytoplankton expressed as carbon in seawater
zmicro
mol m-3
XYZ
3
Mole concentration of microzooplankton expressed as carbon in seawater
zmeso
mol m-3
XYZ
3
Mole concentration of mesozooplankton expressed as carbon in seawater
zmisc
mol m-3
XYZ
3
Mole concentration of other zooplankton expressed as carbon in seawater
chldiat
kg m-3
XYZ
3
Mass concentration of diatoms expressed as chlorophyll in seawater
chldiaz
kg m-3
XYZ
3
Mass concentration of diazotrophs expressed as chlorophyll in seawater
chlcalc
kg m-3
XYZ
3
Mass concentration of calcareous phytoplankton expressed as chlorophyll in seawater
chlpico
kg m-3
XYZ
3
Mass concentration of picophytoplankton expressed as chlorophyll in seawater
chlmisc
kg m-3
XYZ
3
Mass concentration of other phytoplankton expressed as chlorophyll in seawater
pon
mol m-3
XYZ
3
Mole concentration of particulate organic matter expressed as nitrogen in seawater
pop
mol m-3
XYZ
3
Mole concentration of particulate organic matter expressed as phosphorus in seawater
bfe
mol m-3
XYZ
3
Mole concentration of particulate organic matter expressed as iron in seawater
bsi
mol m-3
XYZ
3
Mole concentration of particulate organic matter expressed as silicon in seawater
phyn
mol m-3
XYZ
3
Mole concentration of phytoplankton nitrogen in seawater
phyp
mol m-3
XYZ
3
Mole concentration of total phytoplankton expressed as phosphorus in seawater
phyfe
mol m-3
XYZ
3
Mass concentration of diazotrophs expressed as chlorophyll in seawater
physi
mol m-3
XYZ
3
Mole concentration of total phytoplankton expressed as silicon in seawater
dmso
mol m-3
XYZ
3
Mole concentration of dimethyl sulfide in seawater
Monthly mean biogeochemical output: priority 3 (gas exchange, river,
burial, N2 fixation, thresholds).
Symbol
Variable name
Units
Shape
Priority
Long name
ΔpCO2
dpco2a
Pa
XY
3
Delta pCO2
ΔpCO2nat
dpco2nata
Pa
XY
3
Natural delta pCO2
ΔpCO2abio
dpco2abioa
Pa
XY
3
Abiotic delta pCO2
ΔpO2
dpo2b
Pa
XY
3
Delta pO2
FDMS
fgdms
mol m-2 s-1
XY
3
Surface upward flux of DMS
icfriver
mol m-2 s-1
XY
3
Flux of inorganic carbon into ocean surface by runoff
fric
mol m-2 s-1
XY
3
Downward inorganic carbon flux at ocean bottom
ocfriver
mol m-2 s-1
XY
3
Flux of organic carbon into ocean surface by runoff
froc
mol m-2 s-1
XY
3
Downward organic carbon flux at ocean bottom
intpn2
mol m-2 s-1
XY
3
Nitrogen fixation rate in ocean
fsn
mol m-2 s-1
XY
3
Surface downward net flux of nitrogen
frn
mol m-2 s-1
XY
3
Nitrogen loss to sediments and through denitrification
fsfe
mol m-2 s-1
XY
3
Surface downward net flux of iron
frfe
mol m-2 s-1
XY
3
Iron loss to sediments
o2min
mol m-3
XY
3
Oxygen minimum concentration
zo2min
m
XY
3
Depth of oxygen minimum concentration
CSH
zsatcalcc
m
XY
3
Calcite saturation depth
ASH
zsataragd
m
XY
3
Aragonite saturation depth
a Difference between atmospheric and oceanic partial
pressure of CO2 (positive meaning ocean > atmosphere);
b difference between atmospheric and oceanic partial pressure of
O2 (positive meaning ocean > atmosphere); c depth of
calcite saturation horizon (0 if < surface, “missing” if > bottom; if
2, then the shallower); d depth of the aragonite saturation
horizon (0 if < surface, “missing” if > bottom; if 2, then the
shallower).
Monthly mean biogeochemical output: priority 3 (production and rates
of change).
Variable name
Units
Shape
Priority
Long name
expn100a
mol m-2 s-1
XY
3
Downward flux of particulate nitrogen
expp100a
mol m-2 s-1
XY
3
Downward flux of particulate phosphorus
expfe100a
mol m-2 s-1
XY
3
Downward flux of particulate iron
expsi100a
mol m-2 s-1
XY
3
Downward flux of particulate silica
fddtdicb
mol m-2 s-1
XY
3
Rate of change in net dissolved inorganic carbon
fddtdinb,c
mol m-2 s-1
XY
3
Rate of change in net dissolved inorganic nitrogen
fddtdipb
mol m-2 s-1
XY
3
Rate of change in net dissolved inorganic phosphorus
fddtdifeb
mol m-2 s-1
XY
3
Rate of change in net dissolved inorganic iron
fddtdisib
mol m-2 s-1
XY
3
Rate of change in net dissolved inorganic silicon
fddtalkb
mol m-2 s-1
XY
3
Rate of change in total alkalinity
fbddtdicb
mol m-2 s-1
XY
3
Rate of change in dissolved inorganic carbon due to biological activity
fbddtdinb,d
mol m-2 s-1
XY
3
Rate of change in dissolved inorganic nitrogen due to biological activity
fbddtdipb
mol m-2 s-1
XY
3
Rate of change in total dissolved inorganic phosphorus due to biological activity
fbddtdifeb
mol m-2 s-1
XY
3
Rate of change in dissolved inorganic iron due to biological activity
fbddtdisib
mol m-2 s-1
XY
3
Rate of change in total dissolved inorganic silicon due to biological activity
a At 100 m depth; b integral over upper
100 m only; c net time rate of change in nitrogen nutrients
(e.g., NO3-+NH4+); d vertical
integral of net biological terms in time rate of change in nitrogen nutrients
(e.g., NO3-+NH4+).
Monthly mean biogeochemical output: priority 3 (production, grazing,
sinking, limitation).
Variable name
Units
Shape
Priority
Long name
pp
mol m-3 s-1
XYZ
3
Primary carbon production by phytoplankton
graz
mol m-3 s-1
XYZ
3
Total grazing of phytoplankton by zooplankton
expc
mol m-2 s-1
XY
3
Sinking particulate organic carbon flux
limndiaz
1
XY
3
Nitrogen limitation of fiazotrophs
limncalc
1
XY
3
Nitrogen limitation of calcareous phytoplankton
limnpico
1
XY
3
Nitrogen limitation of picophytoplankton
limnmisc
1
XY
3
Nitrogen limitation of other phytoplankton
limirrdiaz
1
XY
3
Irradiance limitation of diazotrophs
limirrcalc
1
XY
3
Irradiance limitation of calcareous phytoplankton
limirrpico
1
XY
3
Irradiance limitation of picophytoplankton
limirrmisc
1
XY
3
Irradiance limitation of other phytoplankton
limfediaz
1
XY
3
Iron limitation of diazotrophs
limfecalc
1
XY
3
Iron limitation of calcareous phytoplankton
limfepico
1
XY
3
Iron limitation of picophytoplankton
limfemisc
1
XY
3
Iron limitation of other phytoplankton
intppdiaz
mol m-2 s-1
XY
3
Net primary mole productivity of carbon by diazotrophs
intppcalc
mol m-2 s-1
XY
3
Net primary mole productivity of carbon by calcareous phytoplankton
intpppico
mol m-2 s-1
XY
3
Net primary mole productivity of carbon by picophytoplankton
intppmisc
mol m-2 s-1
XY
3
Net primary organic carbon production by other phytoplankton
intpbn
mol m-2 s-1
XY
3
Nitrogen production
intpbp
mol m-2 s-1
XY
3
Phosphorus production
intpbfe
mol m-2 s-1
XY
3
Iron production
intpbsi
mol m-2 s-1
XY
3
Silica production
intpcalcite
mol m-2 s-1
XY
3
Calcite production
intparag
mol m-2 s-1
XY
3
Aragonite production