White cap measurements and parameterizations based on the

White cap measurements and parameterizations based on thedissipation source term

Ø Breivik, B Scanlon, J-R Bidlot, P A E M Janssen, AH Callaghanand B Ward

Øyvind Breivik (MET Norway) Modelling whitecap coverage 7 September 2016 1 / 16

Outline of presentation

Whitecaps and their relation to the dissipation of ocean wavesParameterizing wave breaking with a spectral wave modelMeasuring whitecapsParameterizing whitecap coverageConclusions and further work


Motivation

Estimates of the energy dissipated from the oceanic wave field due to wavebreaking is needed for among other things

upper-ocean turbulence models

gas transfer estimatescalibrating remotely sensed estimates of sea surface temperature

Parameterizing white cap coverage and comparing it to observationsis an indirect estimate of our ability to model the dissipation frombreaking waves


Motivation


upper-ocean turbulence modelsgas transfer estimates

calibrating remotely sensed estimates of sea surface temperature



Motivation


upper-ocean turbulence modelsgas transfer estimatescalibrating remotely sensed estimates of sea surface temperature



Motivation


upper-ocean turbulence modelsgas transfer estimatescalibrating remotely sensed estimates of sea surface temperature



Observing whitecaps

Cruise track R/VKnorr June-July2011. Day-of-yearis marked alongthe cruise trackand stations aremarked as redsquares.

80oW 72

oW 64

oW 56

oW 48

oW 40

oW

36oN

45oN

54oN

63oN

72oN

176 177 178

180181

182

183

184185

189190191

192

194

Newfoundland

Greenland


Observing whitecaps

Time series of neutral wind speed (U10N), modeled significant wave height(Hs), mean period of the modeled wind-wave spectra (T̄ ) during theNorth Atlantic campaign of 2011. The grey columns mark the periodsduring which whitecap coverage fraction was measured.

Day of year180 185 190 195

0

5

10

15

20

U10N

(

m s−1)

HS (m)T̄m1 (s)


Observing whitecaps

Whitecaps observed with 5 mega pixel 16 mm camera mounted onR/V Knorr.> 114,000 images were processed first with Automated WhitecapExtraction (AWE) algorithm (Callaghan et al, 2009)Secondly, manual inspection using the Spatial Separation of WhitecapPixels (SSWP) method (Scanlon and Ward, 2013) distinguishesactive breaking (stage A, blue) from decaying (stage B, green)


Wave model integration

The ECWAM wave model wasrerun for the cruise period with11-km spatial resolution. Wavefields are output with 1-hourlytemporal resolution.The wind was taken fromoperational analyses whichcompare well with the observedwind speed

U10N (m s−1)0 5 10 15 20

Umod

10N

(ms−

1)

0

5

10

15

20M=0.95, C=0.24, R

2=0.90


Parameterizing whitecaps from a spectral wave model

Craig and Banner (1994) assumed that the energy flux from breakingwaves

Φoc = ρwg∫ 2π

0

∫ ∞0

Sds dωdθ [Wm−2] (1)

is proportional to the cube of the friction velocity, ie,

Φoc ≈ ρwαCBw3∗ = ρamu3

∗ , (2)

where w∗ is the water friction velocity and typically 50< αCB < 150. Craigand Banner (1994) assumed αCB = 100 (or, equivalently, an air-sidecoefficient m ≈ 3.5)


Parameterizing whitecaps from a spectral wave modelThe ECWAM model integration for the cruise period shows that thisproportionality is a good first order approximation

u⋆ (m s−1)0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

(

Φoc

ρa

)

1/3(m

s−1)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

WFA=

0

WFA>

0

WFT = 0

WFT > 0

Φoc = 4.64ρa (u⋆)3, R2 = 0.99

Φoc = 0.013 W m−2 (HS08)u⋆T = 0.065 m s−1 (SW15)


Parameterizing whitecaps from a spectral wave modelBut the proportionality factor αCB is not constant, neither geographicallynor in time as it depends on the maturity of the sea state. A one-monthaverage shows that there are large geographical differences



Kraan et al (1996) parameterized the whitecap fraction (area covered bywhitecaps) from the flux Φoc as

W modF = Φoc

γρwg ω̄E , (3)

where ω̄ = 2π/T̄ is the circular mean frequency, γ a tuning factor andE = (Hs/4)2.



The relationship between observedand modelled whitecap coverage isquite impressive, but there is stillsome room for tuning. The factor γis here used to separately tune WFAand WF.

A: γ = 0.01 for both active andtotal whitecap coverageB: γ set separately for the activeand the total whitecap coverageimproves the fit somewhat. Thecorrelation remains unchangedat R = 0.88 for the totalwhitecap.

(

Wmod

F

)

1/3

0

0.1

0.2

0.3

0.4(a)

WFA

(γ=0.01)

WF

(γ=0.01)

M=1.5, C=0.033, R2=0.74

M=0.9, C=0.041, R2=0.78

WF1/3

0 0.1 0.2 0.3 0.4

(

Wmod

F

)

1/3

0

0.1

0.2

0.3

0.4(b)

WFA

(γ=0.034)

WF

(γ=0.007)

M=1, C=0.021, R2=0.74

M=1, C=0.045, R2=0.78


Conclusions

1 The manual Spatial Separation of Whitecap Pixels (SSWP) method isfound to accurately distinguish between stage A and stage Bwhitecaps

2 The Kraan et al (1996) parameterization is found to yield a goodparameterization of the total whitecap coverage

3 Rerunning the wave model improved the results compared with usingERA-Interim estimates with six-hourly resolution

4 The parameterization is straightforward to implement as it relies onintegrated parameters only


Further workMeasuring wave breaking continuously from a fixed platform in the CentralNorth Sea is planned (Norwegian WAVEMIX proposal)


Further workThe footbridge is located 22 m above still water level, facing N-NW, with alaser array already in place and a WaveRider buoy nearby.

References:Breivik, Ø, K Mogensen, J-R Bidlot, MA Balmaseda, and PAEM Janssen (2015). Surface Wave Effects in the NEMO OceanModel: Forced and Coupled Experiments, J Geophys Res Oceans, 120, doi:10.1002/2014JC010565, arXiv:1503.07677Callaghan, A. H., and M. White (2009). Automated processing of sea surface images for the determination of whitecapcoverage. J. Atmos. Ocean. Tech., 26(2), 383–394, doi:10.1175/2008JTECHO634.1Kraan, G., W. A. Oost, and P. A. E. M. Janssen (1996). Wave energy dissipation by whitecaps. J. Atmos. Ocean. Tech.,13(1), 262–267, doi:10/dnp59mScanlon, B., and B. Ward (2013). Oceanic wave breaking coverage separation techniques for active and maturing whitecaps.Methods in Oc., 8, 1–12, doi:10.1016/j.mio.2014.03.001Scanlon, B, Ø Breivik, J-R Bidlot, P Janssen, A H Callaghan, B Ward (2015). Modelling whitecap fraction with a wave model,J Phys Oceanogr, doi:10.1175/JPO-D-15-0158.1


20 years is a long timeKraan et al (1996)


Documents

White cap measurements and parameterizations based on the