Satellite Data Assimilation into a Suspended ParticulateMatter Transport Model

2

Model area & seabed fine sediment distribution:

%

fine sediment grain size 20-60μm

3

SPM dynamics modelling concept:

model output

initial databoundary conditions

model

Wave ModelWAM

Circulation SPM transport model

(based on HAMSOM)

Water temperatureSalinity

Topography

significant waves height waves directionwaves period

SPM concentrationSeabed sedimentation field

ATMOSPHERE: CloudinessRelative humiditySolar radiationEvaporationPrecipitationAir temperatureAir pressureWind

OCEAN:Sea surface heightWater temperatureSalinity

RIVERS:Fresh water dischargeSPM Concentration

SPM3D-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

CurrentsTransport

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

MERISMERIS C2R flagsMERIS C2R flags+max SPM

7

New analyzedsurface 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/m3

Z, m

before OI

after OI

First guess field (model)

Data processorand

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 40 450

10

20

30

40

50

Stations

Sur

face

SP

M c

once

ntra

tion,

mg

l -1

observations

modelled without assimilationmodelled with assimilation

Observations, mg/lModel with

assimilation, mg/lModel 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 2003calm

15 October – 15 April 2003storm

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

thank you for your attentionthank you for your attention