Coastal Observation and a Coastal Observation and a Forecasting - - PowerPoint PPT Presentation

Coastal Observation and a Coastal Observation and a Forecasting System for the Forecasting System for the German Bight German Bight

Emil V. Stanev and Franciscus Colijn

emil.stanev@gkss.de

Taipei, 23-25 April 2008

North Sea German Bight Wadden Sea

How the coastal

• cean will be

affected by changes in the tidal currents and the sediment supply due to climatic change

Monitoring and forecasting these changes can Monitoring and forecasting these changes can

• nly be addressed by a
• nly be addressed by a combination of state

combination of state-

• f
• f-
• the

the-

• art observations and modelling

art observations and modelling activities. activities. Objective measures of Objective measures of uncertainties in the uncertainties in the state estimates and forecasts state estimates and forecasts are needed. are needed. I mproving the performance of observing and I mproving the performance of observing and forecasting systems requires a clear forecasting systems requires a clear identification of relevant parameters identification of relevant parameters and and representation of representation of multiple physical and multiple physical and biogeochemical processes biogeochemical processes in numerical in numerical models. models.

Outline Outline

• Observations

Observations

• Numerical Modelling

Numerical Modelling

• Model Validations

Model Validations

• States Estimates

States Estimates

• Conclusions

Conclusions Address regional Address regional

• bservations and predictions
• bservations and predictions

with a focus on the German with a focus on the German Bight and Wadden Sea Bight and Wadden Sea I dentify further perspectives I dentify further perspectives

• f (pre)operational
• f (pre)operational
• ceanography
• ceanography

Aims of this Talk Aims of this Talk

I ntegrated Coastal I ntegrated Coastal Observation Observation Network (I CON) Network (I CON)

Elbe Germ an Bight FI NO NSboje I I I NSboje I I

Buoy Data

WERA Data

validations

Observations DWD product

Real–time data

Other Data Other Data

Uni-Oldenburg m eteo- and hydro physical data Senkenberg ADCP data

RG RG-

• W ATT Data Station: Data

W ATT Data Station: Data are Already Extensively Used to are Already Extensively Used to Calibrate the W ATT Calibrate the W ATT-

• Model

Model

ADCP Transects ADCP Transects

Use New Data: Use New Data: MERI S TSM MERI S TSM -

• 3 0 0 m Data and

3 0 0 m Data and num erical m odel sim ulations num erical m odel sim ulations 1 9 Feb 2 0 0 5 1 9 Feb 2 0 0 5 9 Sep 2 0 0 4 9 Sep 2 0 0 4

Gemein et al. (2006)

Data Data -

• Data, but also Data

Data, but also Data -

• Model

Model Calibration is Needed Calibration is Needed

Ships of Opportunity Ships of Opportunity (FerryBoxes) (FerryBoxes)

Numerical Modelling Can Help a Lot in the Numerical Modelling Can Help a Lot in the Regional Studies. Regional Studies.

East Frisian W adden Sea

200 m 3 nm 6 nm 1 km

GETM: flooding and drying

One One-

• w ay Nested

w ay Nested Modelling Modelling System System

... Coupled ... Coupled with with Sediment Transport Sediment Transport Model Model

• 3 D equations

3 D equations

• Tw o classes

Tw o classes of

• f sedim ent

sedim ent ( ( m ud m ud and and sand sand) )

• Com plex physical param eterizations

Com plex physical param eterizations

• Calibrated

Calibrated to to present present day observations day observations

• Hydrodynam ic m odel

Hydrodynam ic m odel forced by w aves forced by w aves and tides and tides

Areas of Application: Areas of Application:

• North Sea (in cooperation with BSH)

North Sea (in cooperation with BSH)

• German Bight (HAMSOM

German Bight (HAMSOM-

• based)

based)

• East Frisian Wadden Sea

East Frisian Wadden Sea

• H

Hö örnum Bay (North Frisian Wadden Sea) rnum Bay (North Frisian Wadden Sea)

Are Models Enough Mature and Are Models Enough Mature and Validated in Order to be Used in Validated in Order to be Used in Pre Pre-

• operational Activities?
• perational Activities?

Germ an Bight ( BSH data) W adden Sea ( U_ Ol data)

GKSS-ADCP data versus sim ulated data Stanev et al. (2003a, OD)

Validation of Validation of the W adden Sea m odel the W adden Sea m odel

Circulation Circulation

Can tidal asymmerties Can tidal asymmerties cause cause net net transport transport

• f
• f sediment? GROEN

sediment? GROEN ( ( Neth

• Neth. J. S. Res, 1967): YES!

. J. S. Res, 1967): YES!

I nward transport I nward transport

Tidal asymmetry due Tidal asymmetry due to to topograpgy control topograpgy control

' sin(2 t / T) sin( t) ζ = π = ω

( )

2

dV' 1 cos t sin( t) d 2 t 2 = εω + ω ω ε ω

Tidal asymmetry due Tidal asymmetry due to to superposition superposition of M2 and

• f M2 and

M4 M4 tide tide

Outward transport Outward transport

t t flood

flood= 2t

= 2t ebb

ebb

Conceptual Models and Process Studies

Asymmetric transport Asymmetric transport in in the vertical the vertical plane plane (Stanev et al., 2007, CSR) could (Stanev et al., 2007, CSR) could be be another candidate another candidate to to explain explain the the landward transport landward transport of

• f sediment

sediment. .

Courtesy B. Flemming

Transport of vertically non Transport of vertically non-

• uniform sediment

uniform sediment concentrations is another level of complication. concentrations is another level of complication. Stanev et al. (2007, JGR): Without shear Stanev et al. (2007, JGR): Without shear diffusion, the sediment dynamics are largely diffusion, the sediment dynamics are largely governed by the governed by the ‘‘ ‘‘displacement mechanism displacement mechanism’’ ’’

Along Channel Change Along Channel Change

• f Correlation Patterns:
• f Correlation Patterns:

Asymmetries along the channels would contribute to accumulating sediments enabling feedback between circulation, basin hypsometry and sediment transport

Are Tidal Basins Only Ebb Are Tidal Basins Only Ebb-

• Dominated?

Dominated?

The Response to Extreme The Response to Extreme Events (Storm Surge Brita) Events (Storm Surge Brita) is Different From the One is Different From the One to Tides. to Tides.

The The I mpact of Wind I mpact of Wind Waves Waves on

• n the

the Sediment Transport Sediment Transport

EOF Analysis of Forcing: EOF Analysis of Forcing: Bed Shear Stress due to Surface Waves Bed Shear Stress due to Surface Waves and Tides (Currents) and Tides (Currents)

Tides Tides W aves W aves

Stanev et al. ( 2 0 0 6 , OD)

Bed Shear Stress Due to Tides and Wind Bed Shear Stress Due to Tides and Wind Display Different Patterns Also in the Display Different Patterns Also in the Wadden Sea Wadden Sea

Deposition Deposition Minus Minus Erosion Erosion

Stanev et al. ( 2 0 0 6 , OD)

The Response to Climate Change The Response to Climate Change Affects in a Non Affects in a Non-

• Trivial

Trivial Way Spatial and Way Spatial and Temporal Temporal Variability Variability Patterns. Patterns.

MERI S/ ENVI SAT, 0 3 / 2 9 / 0 4 , 9 :5 0 , 3 0 0 m , Gem ein et al. ( 2 0 0 6 )

The im portance of exchange betw een tidal flats and open ocean

Suspended Suspended Sedim ent Sedim ent ( GETM, 2 0 0 m ( GETM, 2 0 0 m Resolution Resolution) )

Num erical sim ulations MERI S I m age

Gemein et al. (2006)

Validation Validation Against Against MERI S MERI S Data Data

Sediment Sorting Sediment Sorting (Different (Different Transport Transport of

• f Water

Water, , Suspended Suspended Matter Matter and and Sand) Sand)

1 2 3 Sediment is advected

• n average more

slowly than fluid mass.

model output initial data boundary conditions model

Wave Model WAM

Circulation SPM transport model

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

RI VERS:

Fresh water discharge SPM Concentration

SPM 3D-Concentration field

Satellite data assimilation

+

Towards Data Assimilation: Optimal I ntrrpolation of MERI S Data

Mikhail Dobrynin and Heinz Guenther

WAM WAM

MERI S Data MERI S Data

Simulated seasonal mean surface SPM concentration, 2003, mg/l

15 April-15 October calm 16 October – 14 April storm No assimilation MERIS data assimilation (Optimum Interpolation)

Optimal I nterpolation is not the Optimal I nterpolation is not the Best Solution for Near Best Solution for Near-

• Coastal

Coastal Regions. Regions. Compressing Data and Compressing Data and Statistical Forecasts Statistical Forecasts (Tidal Oscillations) (Tidal Oscillations)

Goals: consolidate existing system s, develop new ones, detect environm ental and clim ate changes in coastal areas, produce forecasts, provide products and know ledge.

Further perspectives Further perspectives

COSYNA ( Coastal Observation System for Northern and Arctic Seas ) Enable a future long term observational netw ork for the North Sea and Arctic coastal w aters Link to preoperational m odels for scientific and m anagem ent purposes

New enhancem ents: ( AUVs, gliders)

• ffshore w ind turbines ( W EAs)

platform s

How ever, How ever,

• The existing system s are not harm onised.
• Quality assessm ent is still a problem .
• Real-tim e data transfer and exchange, as

w ell as availability to m odellers is not w ell solved.

• Assim ilation of various sources of near

coastal data is still a com plex scientific problem .

• No enough coherence betw een physical,

chem ical, geological and biological data.

To Summarize: Our Plans To Summarize: Our Plans

• I ncrease synergy between observation and

I ncrease synergy between observation and modelling, modelling,

• I mprove observing/ forecasting systems

I mprove observing/ forecasting systems

• Model supported monitoring

Model supported monitoring

• I n Longer

I n Longer-

• term Perspective: Consider Data

term Perspective: Consider Data-

• Adaptive Sampling

Adaptive Sampling

Thanks for your attention Thanks for your attention