ROMS-PISCES-APECOSM coupling compared to NEMO ... - meece

ROMS-PISCES-APECOSM coupling
compared to NEMO-PISCES-APECOSM
Eric Machu (CEES/IRD)
Olivier Aumont (IRD/LPO)
Olivier Maury (IRD/EME)
1. Coupling and formalism
2. Few words about APECOSM
3. Processes involved in the coupling LTLs
to HTLs
4. Main differences between RPA and NPA
Meeting, Héraklion, 1 st -4 th February 2010

Formalism coherence
Hydrodynamics: Primitive equations for describing the motion
Navier-Stokes
Forcing
Advection-diffusion equations
For T & S
Dissipation
Equation of state
Boussinesq approximation
Incompressible fluid

Biogeochemistry: Primitive equation for describing the evolution of
concentrations
Forme, taille et
fonctionnement
fortement
variable ...
Advection
Vertical
Diffusion
Horizontal
Diffusion
Source-minus-Sink
terms

Open Ocean Pelagic Communities: Primitive equation for
describing the energy content in each community (epipelagic,
migrants & mesopelagic)
∂
t
ξ
i
=
div
− ∂
−
(
i i i i
) (
i i i i
)
x,y
d ∇
x,yξ
− v ξ + ∂
z
d
z∂
zξ
− vzξ
(
i ii
)
w
γ ξ
Growth
( λ
i + m + s
i ) ξ
i
Sink terms: predatory, non-predatory & starvation
] w , w ] ( 0, t )
in Ω× ×
egg
max
Diffusion /
Advection terms
max
γ
Reproduction
Boundary condition in size
( x,
y,
z,
t) ∈ Ω [ 0 ]
c
t, x,
y,
z,
w
ξt,
x,
y,
z,
w
= rt
, x,
y,
z
∀
,
, t
×
egg egg
max

Energy
NEMO- PISCES-APECOSM
PAR
Predation
Nanophytoplankton 1-10 mm
Diatoms 10-100 mm
Micro-zooplankton
Mesozooplankton
Predation
Fishes
NH4 +
NO -
3
Mortality
Weight
Excretion
t, x, y, z
P.O.M.
Egestion
This formalism insures rigorous
mass-conservation
&
have predictive skills

Few words about APECOSM
Units
• Biogeochemistry: Concentrations µmol.l-1
Redfield ratio: C/N/P=106/16/1
Fe, Si and Chl are prognostically predicted based on external
concentrations of the limiting nutrients like in the quota approach
(McCarthy, 1980; Droop, 1983)
• Open Ocean Pelagic Communities: Energy J.m -3 .kg -1
Conversion [N] or [C] --> E (J.N/C-mol -1 )
Redfield + biomass free energy=474.6 kJ.C-mol-1
N_E_convert: 3144225 – C_E_convert: 474600.

Mean Individual
Bioenergetics
Parameters
ORGANISM
ingestion
assimilation
PREYS
Simplified from Kooijman, 2000
Structure
growth
K
κ
1-κ
somatic
growth
maintenance
gonadic
maintenance
reproduction
1-K
reproduction
Eggs
Predator/Prey interactions
Selectivity
Prey length (m)
Predator
length (m)

~ 20 Parameters (Maury et al., PiO, 2007)

Outputs from the model
Different carrying
capacities
Carrying capacity
oscillation (one year)
and propagation
Maury, Prog. Oceanogr., 2007

Key references for each model
• ROMS: Shchepetkin & McWilliams (OM, 2005)
• PISCES: Aumont & Bopp (GBC, 2006)
• APECOSM: Maury et al. (PiO, 2007)

Coupling Higher Trophic Levels to
physical/biogeochemical models
Processes
• Effect of temperature on metabolic rates: rate ( T) = rate ( )
T ref
e
⎛
⎜
T
⎝
T
A
ref
T
−
T
A
⎞
⎟
⎠
• Effect of light on ecosystem dynamics through the habitat of epipelagic,
migratory and mesopelagic communities
• Hydrodynamic advection and diffusion added to active swimming
d
⎧
⎪u
⎪
⎨
⎪
⎪v
⎪⎩
i
2
3
( 1 ⎛
2 ∇f
⎞
i
i
, , , ,
, , , , 1 2 , , , ,
) ⎜
t x y z w ⎛
1
⎟ w
⎟ ⎞
⎜
t x y z w
= d + d − ft
x y z w
−
⎜
i
k + ∇f
⎟
, , , , ⎝ w
food t x y z w max ⎠
i
t , x,
y,
z,
w
i
t , x,
y,
z,
w
=
=
MSS
MSS
max
max
i
( 1−
f )
t , x,
y,
z,
w
i
( 1−
f )
t , x,
y,
z,
w
⎛
⎜
⎜
⎝
k
⎛
⎜
⎜
⎝
k
⎝
food
food
∂
∂
x
+
y
+
f
f
i
t , x,
y,
z,
w
∇f
i
t , x,
y,
z,
w
∇f
i
t , x,
y,
z,
w
i
t , x,
y,
z,
w
⎞
⎟⎛
⎜
⎟
⎠⎝
⎞
⎟⎛
⎜
⎟
⎠⎝
w
w
max
w
w
max
⎞
⎟
⎠
⎞
⎟
⎠
1
3
1
3
⎠
+ cz
+ cm
t,
x,
y,
z
t , x,
y,
z
f = Holling type 2
functional response
Dependence on
size

Energy
NEMO- PISCES-APECOSM
PAR
Predation
Nanophytoplankton 1-10 mm
Diatoms 10-100 mm
Micro-zooplankton
Mesozooplankton
Predation
Fishes
NH4 +
NO -
3
Mortality
Weight
Excretion
t, x, y, z
P.O.M.
Egestion
• Feedback of predation of pelagic communities on autotrophs &
microzooplankton?
• Role of mortality, excretion and egestion on particulate organic
matter?

Size
Fishing
Focus
species 2 Focus
Focus
species 1
species 3
Focus
species 4
x, y, z
Primary
production
Biomass
• Address bottom-up vs top-down control of pelagic exosystems
• Final goal: understand end-to-end dynamics of marine
ecosystems

Coupling Higher Trophic Levels to
physical/biogeochemical models
Technical informations
• The development of ROMS-PISCES-APECOSM takes
advantage of NEMO-PISCES-APECOSM developments
• APECOSM coded in C/C++ but for computing cost
reasons, the model has been changed to fortran
(although the C/C++ coupling option is not given up)

• Source-minus-sink terms for Open Ocean Pelagic
Communities (OOPC) are solved in 3D
• Physical advection and diffusion are solved in 2D
(implicitely 3D since currents are weighted by energynormalized
profile)
• Time steps of the hydrodynamic model are split into a
day and a night fraction (dependent on latitude and
season) mainly because predator/prey interactions
depend on day and night

step.F
step3d_t (advection followed by biogeochemical SMS terms)
step2d_oopc (Apecosm SMS terms followed by advection
t3dmix (tracer mixing)
oopc2d_mix (oopc mixing)
step2d_oopc :
bridge_oopc
calc_habitat (3D projection of 2D OOPC variables)
do dn=0,1
ff_updt (flux feeding)
calc_pred (predation mortality, source & sink terms related to
growth: excretion, egestion, maintenance, reproduction)
if dn=1 : growth (growth advection term, starvation, nonpredatory
mortality)
calc_adv (Compute u_active, v_active and biological diffusion)
calc_meso (meso computed from oopc size spectra)
updt_bgc (update bgc variables)
enddo
do dn=0,1
calc_vmoy (Vertical average to advect and diffuse 2D OOPC variables)
enddo
Compute horizontal advection (U+U_active)
Compute horizontal diffusion (Diff+biological Diff)
oopc2dbc (treatment of the boundary conditions)

Main differences between RPA and NPA
(appart from the hydrodynamic model itself)
• Order of operations
• Advection/Diffusion numerical schemes
• RPA needs oceanic boundary conditions (advection of
conservative quantities) which will be provided by NPA

Future
• Set-up regional configurations (Benguela & Bay of
Biscay) (rely on existing configurations)
• Carry on sensitivity analyses
• Validate the annual cycle of model outputs
(mesozooplankton, ecosystem energy slopes, …)
• Derive process studies from scenarios definition (no
interannual run planned)
• Represent targeted species like anchovy and
sardine (probably post-meece …)