I Hcantabria Datasets

Wind, Sea level & Wave Datasets

November 2011

REQUIREMENTS:

• High quality data (mean / extremes)

• Long time series

• High temporal resolution

• Good spatial distribution (global / regional / local)

• Local characterization (from offshore to nearshore)

Engineering applicationsDesign, maintenance, problems

Climate analysisVariability, forecast, projections

Risk assessmentcoastal impact

Management

• Dataset required for estimation of ocean climate

• Calibration / validation techniques and methods

• Downscaling (from global to regional to local)

• Climate variability (at different temporal/spatial scales)

• Risk analysis (impact due to climate change)

1. Wind data SeaWind (SW)

2. Offshore wave data Global Ocean Waves (GOW)

3. Nearshore wave data Downscaling of Ocean Waves (DOW)

4. Surge data (sea level) Global Ocean Surge (GOS)

DATABASESDATABASES

Research Interests of the Climate IH‐team:

Downscaled offshore WindsSeawind (SW)

SWSeaWind reanalysis

[Menendez et al. 2011]

DynamicDownscalling

Global

Local

DOWNSCALINGDOWNSCALING

Regional


Spatial domain: Regional



With the best physics configuration, we test the performance of wind simulations on a small domain at higher resolution (<2 km).


Dataset Validation

[Espejo et al. 2011]


Offshore wave dataGlobal Ocean Waves (GOW)

Global Winds Global Ice

Generation of Waves

Preliminary Validation

Calibration

Validation of results

Buoy data Satellite data

Apps

GOWGlobal Ocean Waves reanalysis


Spatial domain:Global

[Reguero et al. 2011 a,b]

Validation of numerical modeling with dataset from satellite and buoy measurements

Dataset Validation


[Reguero et al. 2011 a]

0.25º

0.5º

0.5º



Dataset Validation

Dataset Validation


GOW‐SW‐EraIntGOW‐SW‐NCEP

Rii

i

bC R Rs i i s iH a H

Calibration (correction with altimeter data) [Minguez et al. 2011b]


Identification of outliers(hurricanes and tropical cyclones) [Minguez et al. 2011a]

Temporal series of different wave climate parameters


Spatial domain: Local


GOW outputs:

Nearshore wave dataDownscaled Ocean Waves (DOW)

Historicaldata bases

Selection

Reconstruction

Propagation

Wave climate

Validation

SWAN

K-means

RBF

•Inputs: energy spectra (offshore)•Downscaling with hybrid method •Reconstruction & validation nearshore

DOWDownscaled Ocean Waves

GOW – Spain.

[Camus et al., 2011]


Selection

Reconstruction

Propagation

Wave climate

Validation

SWAN

K-means

N-Dim. Interp.

•Inputs: energy spectra (offshore)•Downscaling with hybrid method •Reconstruction & validation nearshore


SWAN

Nearshore processes:•Refraction•Shoaling•Wave breaking•Diffraction

Spatial scale of interest=100 m



Selection

Reconstruction

Propagation

Wave climate

Validation

X i H i ,Ti , i ,Wi ,i ;i 1,..., N



Selection

Reconstruction

Propagation

Wave climate

Validation

Local wave propagations: SWAN



Selection

Reconstruction

Propagation

Wave climate

ValidationRBF X i p X i a j X i D j j 1

M

p X i b0 b1H i b2Ti b3i b4Wi b5i

X i D j exp X i D j

2

2c 2

Radial Basis Functions


Spatial domain:local



from ~275m to ~45mCanarias IslandsSW-NCEPDOW-SWNCEP

from ~500m to ~90mAtlantic cost of SpainSW-NCEPDOW-SWNCEP

from ~280m to ~55mMediterranean coast of SpainSW-NCEPDOW-SWNCEP

from ~280m to ~55mMediterranean coast of SpainSW-EraIntDOW-SWEraInt

~1KmBrasil CoastNCEP-NCARDOW-NCEP

from ~275m to ~45mCanarias IslandsNCEP-NCARDOW-NCEP

from ~500m to ~100mAtlantic coast of SpainNCEP-NCARDOW-NCEP

Spatial ResolutionMeshesForcingName

Storm Surge dataGlobal Ocean Surge (GOS)

GOSGlobal Ocean Surges

Spatial domain: regional

1/8º48742146.034 N25 N37 E-20 W

∆x (º)

Gridpoints

number(Y)

Gridpoints

number(X)

FinalLat.

InitialLat.

FinalLon.

InitialLon

GOS domain


Málaga

Santander

Dataset Validation

Storm Surge


Surge elevationSurge currents (v2D)



Surge elevation

OUTPUT

SEAWIND-NCEPCC: GOS 1.1

100 m1 h

1948-2009Fangar (Ebro delta)DOS 1.2(Downscaled Ocean Surge)

NCEP-NCARBC: Inverse Barometer

1/4º1 h

1948-2008South America & Caribe

GOS 1.0

Seawind-EraInterimBC: Inverse Barometer

1/8º1 h

1989-2009SE Atlantic ocean &Mediterranean Sea

GOS 2.1

SEAWIND-NCEPBC: Inverse Barometer

1/8º1 h

1948-2009SE Atlantic ocean &Mediterranean Sea

GOS 1.1

RESOLUTIONNAME TIME PERIOD

FORCINGREGION


Model: Armonic forecast TOPEX (10 componentes)

(H): 5km1 h

1948-2010South America & Caribe

GOT1D:Tide(eta)

(H): 1’(V): 30 levels1 h

(H): 1/16º1 h

SPATIAL/TEMPORAL RESOLUTION

GOT3D: Tide(eta, u2D, v2D, u3D, v3D)

GOT2D:Tide(eta, u2D, v2D)

VARIABLE

Model: ROMSCC: TOPEX (10 components)

Model: ROMSCC: TOPEX (10 components)

2001

2001

PERIOD COMMENTS

SE Atlantic ocean &Mediterranean Sea

Biscay GulfCanarias IslandsSpanish Mediterranean Sea

LOCALIZATION

REANALYSIS

GOTGlobal Ocean Tide

Model: MEDiNA (DIECAST-rigid lid) Forzing: Climatologies:- T y S: MEDAR-MEDATLAS (1/5º, 25

levels, monthly means)- Wind: Hellerman (2º; medias mensuales;

Goddard Space Flight Center)

(H): Atlántico España:

1/4Golfo de Vizcaya:

1/16Mediterráneo: 1/8Estrecho: 1/24(V): 30 levels6 h (surface), 5 days averaged

(3D)

Año medioSE Atlantic oceanMediterranean SeaGibraltar Straight

Barocliniccurrents(u3D, v3D)

(H): 1/16(V): 71 levels1d: Daily mean

SPATIAL/TEMPORAL RESOLUTION

BarocliniccurrentsSSH, u3D, v3D, T, S, wind stress, heat flux, water flux and short wave radiation

VARIABLE

Model: OGCM (based on OPA model) Forzing: - T y S: MEDATLAS climatology (monthly

means)- Atmosphere: ECMWF (1985-1992:

reanalysis ERA-15 y 1993-2007: operational). E y P de NCEP-NCAR.

BC: Atlantic, 18ºWOwner: [email protected]

1985-2007

PERÍOD COMMENTS

Mediterranean Sea

LOCALIZATION

REANALISIS Currents

I Hcantabria Datasets

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