Physical and Biogeochemical Coupled Modelling

Regional Advanced School on Physical and Mathematical Tools for the study of Marine Processes of Coastal Areas

Physical and Biogeochemical Coupled Modelling

Presented by Christel PINAZOMediterranean University

Oceanographic Center of MarseillePhysical & Biogeochemical Oceanographic Laboratory

• IntroductionWhy use Coupled Models ?Historical considerations

• Different types of Coupled Models Box models Fine grid Models (1D, 2D and 3D)

• Different ways of Coupling Models « Off-line » Coupling « On-line » Coupling

• Examples

LECTURE SCHEDULE

COUPLING TYPES


INTRODUCTION COUPLING TYPES >FINE COUPLING WAYS EXAMPLES

THE STUDY SITE COULD BE SPATIALLY DESCRIBED BY FINE MESH GRID IN

1D, 2D OR 3D

COUPLING TYPES



TO CALCULATE THE VARIATION OF BIOGEOCHEMICAL CONCENTRATIONS :

- EQUATION OF TEMPERATURE VARIATION OF THE HYDRODYNAMIC MODEL

?t

C

Time

evolution

COUPLING TYPES



1D FINE GRID MODEL (VERTICAL)

SEDIMENT

z=-h

z=0

z

Trendz

CK

zz

Cww

t

Czsettling

Vertical eddy

diffusivity Vertical

advectionSettlingVelocity

ConcentrationTrend term=

Sources – Sinks

COUPLING TYPES



ADVANTAGES:

•FINE DISCRETISATION ONLY ALONG VERTICAL AXIS

•SIMULATION OF VERTICAL EDDY DIFFUSIVITY (MIXED LAYER)

AND UP OR DOWNWELLING PHENOMENA

•RELATIVE SHORT COMPUTATIONAL TIME

•LONG SIMULATION OF SEASONS OR YEARS

DISADVANTAGES:

•NOT SIMULATE HORIZONTAL ADVECTION

•NOT SIMULATE CORIOLIS EFFECT

1D FINE GRID MODEL (VERTICAL)

COUPLING TYPES



2D FINE GRID MODEL (HORIZONTAL)depth-integrating Navier-Stokes equations

O x

y

x y

DC DC DC DC DCU V K K Trend

t x y x x y y

Time evolution

Horizontal advection

Horizontal eddy

diffusivity


Sources – Sinks

COUPLING TYPES



ADVANTAGES:

•DISCRETISATION ONLY ALONG HORIZONTAL AXES

•SIMULATION OF HORIZONTAL ADVECTION AND DIFFUSIVITY

•SIMULATION OF CORIOLIS EFFECT

•MEAN COMPUTATIONAL TIME

•SIMULATION OF MONTHS OR SEASONS

DISADVANTAGES:

•NOT SIMULATE VERTICAL EDDY DIFFUSIVITY (MIXED LAYER)

•NOT SIMULATE UP OR DOWNWELLING PHENOMENA

•NOT SIMULATE SEVERAL-LAYERS

2D FINE GRID MODEL (HORIZONTAL)

COUPLING TYPES



3D FINE GRID MODELNavier-Stokes equations

Trendz

CK

zy

CK

yx

CK

xz

Cw

y

Cv

x

Cu

t

Czyx

Time

evolution 3D

advection3D eddy

diffusivity


Sources – Sinks

O x

y

z

COUPLING TYPES



ADVANTAGES:

•FINE DISCRETISATION ALONG THE 3D AXES

•SIMULATION OF ALL THE MAIN PHENOMENA

DISADVANTAGES:

•RELATIVE LONG COMPUTATIONAL TIME

•SHORT SIMULATION OF FORTNIGTH TO MONTHS

3D FINE GRID MODEL




• Examples

LECTURE SCHEDULE

COUPLING WAYS


INTRODUCTION COUPLING TYPES COUPLING WAYS EXAMPLES

2DIFFERENT COUPLING WAYS :

- OFF-LINE : 2 SEPARATED RUNS WITH PHYSICAL FORCING CONDITIONS STORED IN FILES

- ON-LINE : DIRECT AND DYNAMIC COUPLING IN 1 RUN




• Examples

LECTURE SCHEDULE

OFF-LINE COUPLING


INTRODUCTION COUPLING TYPES COUPLING WAYS>OFF-LINE EXAMPLES

dt= 600 s

HydrodynamicModel

MARS 3D

WindTide

Physical Forcing Variables :

CurrentsEddy diffusivity

Surface elevation…

Irradiance River inputs Wastewater inputs

EcologicalModelEco3M

dt= 1 hour

dt= 1200 sEcological

trends

Physical Forcing

dt = 50 s

Spatial and temporal evolution

Of biogeochemical variables

AdvectionDiffusion

Biogeochemicalvariables

DIRECT AND DYNAMIC COUPLING


INTRODUCTION COUPLING TYPES COUPLING WAYS>ON-LINE EXAMPLES


EcologicalModel

dt= 1 hour dt= 1200 s

Ecological trends

dt= 600 s

HydrodynamicModel

WindTide

Physical Variables :Currents


dt= 50 s

dt = 50 s

AdvectionDiffusionvariables

bio

Spatial and temporal evolutionOf biogeochemical variables

EXAMPLES


INTRODUCTION COUPLING TYPES COUPLING WAYS EXAMPLES

3D coupled physical and biogeochemical Modelling

Study of ecosystem functioningOf the SW lagoon of New Caledonia

Study site description

Nord

West wind

Trade winds

Study site

Study Site

0

60

120

180

240

300

360

4/4 5/6 6/8 7/10 8/12 8/2 11/4

Win

d d

irection 3

60 °

0

8

16

4/4 5/6 6/8 7/10 8/12 8/2 11/4

win

d s

peed m

.s-1

Vite

sse,

m s

-1D

irect

ion,

360

°

Data from PhD thesis S. Jacquet (2005)

Wind measurements (îlot Maître)Dumbéa river Inputs

0

20

40

60

80

100

120

140

160

180

03/4 23/5 12/7 31/8 20/10 09/12

Déb

it,

m3

s-1

Dé

bit,

m3 s

-1

High short-term variability of meteorological forcings

Low seasonal variability

Study site

Model description

horizontal mesh grid: 500m

Nb horizontal cells: 340*90

10 vertical sigma levels

Forcings : wind, tides

Mars3D

IFREMER-IRD (P. DOUILLET)

Ecological Model:170*90

Horizontal cells

Physical Modelling

ECO3M

Surface currents:Trade winds 8 m s-1

NOUM

ÉA

Physical Modelling

Current Model

• C and N Cycles

• 12 variables

• Zooplankton = « forcing function »

• Eco3M tool

Ecological Modelling

Phytoplankton biomass measurements

Chl.a

Phytoplankton biomass modelling

Carbon Nitrogen ….?

• Constant ratio Carbon : Chlorophyll a

• Chl.a : diagnostic variable calculated from other state variables

• Chl.a : Dynamic state variable

But: /molCgChl. 96.0Chl.

12.0 aC

a

Faure et a (2006)

Ecological Modelling


EcologicalModelEco3M(LOB)

dt= 1 hour dt= 1200 s

Ecological trends

dt= 600 sHydrodynamic

ModelMARS 3D

(IFREMER-IRD)

WindTide

Physical Variables :Currents


dt= 50 s

dt = 50 s

AdvectionDiffusionvariables

bio

Spatial and temporal evolutionOf biogeochemical variables

Dynamic coupling between the 2 models

Model results

Irradiance

Débit des rivières

Vent

0

50

100

150

200

250

300

350

18/06 23/06 28/06 03/07 08/07 13/07 18/07 23/07 28/07 02/08 07/08 12/08

Riv

er F

low

m3

s-1

Dumbéa RiverCoulée RiverPirogues River

Measured forcings

Field measurements : HIVER 2003

Realistic Simulation

Chla, µg l-1

19 June

3 July

Weak Trade winds Weak West wind

Realistic Simulation : HIVER 2003, 2D Results

Chla, µg l-1

3 July

15 July

West wind Trade Winds


Chla, µg l-1

15 July

26 July

Trade Winds and rainfall


Chla, µg l-1

26 July

7 August

West wind Trade winds


Documents

Physical and Biogeochemical Coupled Modelling