DSD-INT 2017 Ocean wave spectra from phase averaged models and remote sensing - Ardhuin

Ocean wave spectra
from models & remote sensing
Fabrice Ardhuin and Justin Stopa (LOPS, Brest, France)

Infragravity wave & Modeling Conference Ardhuin & Stopa 2
1. Motivations
1.1- Cliff-Top Storm Deposits (CTSD) → paleo-storm analyses
1.2- seismic records : another look at the wave climate
2. Wave modelling (including IGs) with WAVEWATCH III
2.1- Wave height is necessary … but not enough
2.2- Winds sea and swells
2.3- Free IG waves
3. Remote sensing (short waves & IGs)
3.1- Wave-resolved imagery : SARs & optical
3.2- Interferometric SAR for altimetry : SWOT → IGs
3.3- Real aperture radars : SWIM on CFOSAT (available 2018),
and future plans with SKIM

Motivations
1
www.umr-lops.fr
Infragravity Wave and Modelling conference

1.1 Motivations : CTSDs
How did this rock land here ??

How did this rock land here ??
We did not have Panoramix to tell us …
The old scenario (without IG waves) :
(Fichaut and Suanez, Marine Geology 2010)

Example of time series (including large IG waves!)
Sheremet et al. (GRL 2014)
Dodet et al. (2017)

Wave modelling (including IGs)
Using WAVEWATCH III
2
www.umr-lops.fr

2.1. Wave height is necessary …
rr
%
%
difference
Models pretty good at large scales for Hs: WW3 forced by ECMWF
- issues with forcing : winds, currents, ice
Data at ftp://ftp.ifremer.fr/ifremer/ww3/HINDCAST/

2.1. Wave height is necessary
– … but not enough
But spectral shapes can be pretty bad ...

But spectral shapes can be pretty bad ...
Error for Hs10 (T > 10 s)
At EURO, off Rotterdam → navigation …

Directional spread determines run-up levels
Guza & Feddersen (GRL 2012)

it can be well modeled →
but sensitive to many things…
… here shoreline reflection.
(Ardhuin and Roland, JGR, 2012)
Spread
Hs

2.2. Wind seas and swell
General statistics
on wave parameters
Different parameterizations
ST2: Tolman & Chalikov (1996)
ST3: Janssen et al. (1994),
modified by Bidlot et al. (2012)
ST4: Ardhuin et al. (2010),
Modified by Rascle & Ardhuin (2013)
ST6 : Rogers et al. (2012) modified
by Zieger et al. (2015)
(Stopa et al.
Ocean Modelling 2016)

2.3. Free IG waves
Using an empirical relation from Hs & Tm0,-2
to free IG spectrum …. (Ardhuin et al. Ocean Modelling 2014)
Spread & other parameters not yet included …
Parameterization in WW3

2.3. Free IG waves
Validation with independent data … (Ardhuin & al. 2014, Rawat et al. GRL 2015)
46005
46404

Remote sensing
3
www.umr-lops.fr

3. Measuring wave spectra from space
Synthetic Aperture Radars (such as Sentinel 1A &1B) work with all weather …
… but they only measure swells correctly
This is due to the SAR processing : short waves blur the radar « image »

4. Measuring wave spectra from space :
The SWIM revolution
An alternative to SAR is a rotating radar.
- used in airborne systems since the 1980s
- measures wavenumber spectrum along line of sight
→ rotation gives 2D spectrum
The China France Ocean SATellite (CFOSAT),
due for launch in August 2018 will carry SWIM : Ku-band rotating radar
160 km

4. Measuring wave spectra from space :
From SWIM to SKIM
Future evolution : SKIM
- 300 km wide swath (revisit time 3 days at mid-latitudes)
- all waves longer than 20 m
- under evaluation by ESA for possible launch in 2025 : currents & waves
Fraction of resolved wave energy

- Wave models usually good for Hs, maybe not spectra
→ database of spectra at ftp://ftp.ifremer.fr/ifremer/ww3/HINDCAST
→ new data available via Copernicus (CMEMS) :
- models
- buoy data (no spectra yet … but soon)
- satellite data (altimeters & SARs)
- Ongoing work for identifying errors sources : forcing, parameterizations …
- full spectra satellite data coming → spectral bias corrections ?
→ assimilation (OK for swells)
- long-term wave climate time series ? → ESA CCI+ « Sea State »
- Training on wave spectra measurement & modelling : March & June 2018
Ardhuin et al. (2017) : Measuring currents, ice drift, and waves from space: the Sea Surface
KInematics Multiscale monitoring (SKIM) concept. doi : 10.5194/os-2017-65
http://tinyurl.com/SKIMonRG
1.5 km
Summary

1. Wave height is necessary …
Models pretty good at large scales for Hs: WW3 forced by ECMWF
- issues with forcing : winds, currents, ice especially at small scales...

5. Directional wave measurements
from high seas to the top of the dunes
- wave frequency distribution : errors > 50 % for energy at f < 0.1 Hz
Bias at French buoys (courtesy Y. Perignon)
→ CFOSAT will help
… in some regions. Not marginal seas.
Error for Hs10 (T > 10 s)
At EURO, off Rotterdam → navigation …

2. Wind seas and swell
In the open ocean
Spectrum shape in frequency : many sources of errors : - wave growth
(weak @ short fetch with ST4 – TEST471)
- swell dissipation uncertainties :
(Stopa et al. GRL 2016)

2.3. Free IG waves
Example of model results (WAVEWATCH III including free IG, see Rawat et al. GRL 2014)

2. Wind seas and swell
… in coastal / shallow water
Specific issues :
- numerics (limiters, splitting errors …) : see Roland & Ardhuin (Ocean Dynamics 2014)
- bottom friction :
→ roughness
with ripple predictor

3. Measuring wave spectra from space
Visible imagery (e.g. Sentinel 2) :
Kudryavtsev et al. JGR 2017

But it can also be really bad...
(this case has strong currents ….)
Spread
Hs

2.3. Free IG waves
… all the way to seismic hum …
(Ardhuin et al. GRL 2015)

2.3. Free IG waves
… all the way to seismic hum …
(Deen et al., submitted)

DSD-INT 2017 Ocean wave spectra from phase averaged models and remote sensing - Ardhuin

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DSD-INT 2017 Ocean wave spectra from phase averaged models and remote sensing - Ardhuin