Satellite Data Assimilation into a

Satellite Data Assimilation into a
Suspended Particulate

Matter Transport Model

2


Model area & seabed fine sediment distribution:

%

fine sediment grain size 20
-
60
μm

3


SPM dynamics
modelling

concept:

model

output

initial data

boundary conditions

model

Wave Model

WAM

Circulation SPM
transport model

(based on HAMSOM)

Water
temperature

Salinity

Topography

significant waves height

waves direction

waves period

SPM concentration

Seabed
sedimentation
field

ATMOSPHERE:


Cloudiness

Relative humidity

Solar radiation

Evaporation

Precipitation

Air temperature

Air pressure

Wind

OCEAN:

Sea surface height

Water temperature

Salinity

RIVERS:

Fresh water
discharge

SPM Concentration

SPM

3D
-
Concentration field

Satellite

data assimilation

+

4


Processes included in the model:

Sedimentation

Resuspension

Sedimentation

Water column


Seabed

Resuspension

Water column

Transport with ocean
currents


Mixing due to waves
and currents


Sinking

Currents

Transport

Mixing

Sinking

Bioturbation

Erosion

Bioturbation

Seabed

21 Water layers

5
-
10 m

21 Seabed layers

0.5
-
1.0 mm

Erosion

5


MERIS data processing:

MERIS RGB view

Modeled max of SPM

6


Spatial coverage of the southern North Sea by MERIS:

Spatial coverage of the southern North Sea by MERIS data in
the year 2003 calculated in % of the modelling domain area.


0
10
20
30
40
50
60
70
80
90
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec


MERIS
MERIS C2R flags
MERIS C2R flags+max SPM
7


New analyzed

surface

SPM

concentration

MERIS data assimilation (Optimum Interpolation, OI)

OI into the

upper model layer


Profile and

mass correction





















0
5
10
15
5
10
15
20
25
30
35
C, g/m
3
Z, m


before OI
after OI
First guess field

(model)

Data processor

and

quality control


Seabed

Mass balance

8


Effect of data assimilation 1:

Surface SPM concentration, mg/l

MERIS

Model with assimilation

Model before assimilation

Model without assimilation

9


Effect of data assimilation 2:

5
10
15
20
25
30
35
40
45
0
10
20
30
40
50
Stations
Surface SPM concentration, mg l
-1


observations
modelled without assimilation
modelled with assimilation
Observations, mg/l

Model with
assimilation, mg/l

Model without
assimilation, mg/l

range

mean

range

mean

range

mean

0.41
–

9.56

3.00

1.67
–

24.99

5.10

0.07
–

47.23

5.40

10


Modeled seasonal mean surface SPM concentration:

Without assimilation

MERIS data assimilation (Optimum Interpolation)

15 April
-
15 October 2003

calm

15 October
–

15 April 2003

storm

mg/l

11


Summary:



Quality control, based on the model results and flags
information calculated by the MERIS Case
-
2 Regional processor
filters out unrealistic values in the MERIS SPM surface
concentration.



About 300 MERIS scenes were assimilated into the SPM
model throughout the year 2003.



The data assimilation signal remains in the model for a couple
of days after the assimilation event.



The seasonal distribution patterns of SPM changed
considerably due to assimilation.



The data assimilation improves the horizontal SPM
distribution, especially its fine structures, i.e. in the location of
SPM front in the German Bight and near English cliffs.

12


Satellite Data Assimilation into a Suspended
Particulate

Matter Transport Model

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