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Yalin Fan and Isaac Ginis Yalin Fan and Isaac Ginis GSO, University of Rhode Island GSO, University of Rhode Island Effects of surface waves Effects of surface waves on air-sea momentum and on air-sea momentum and energy fluxes and ocean energy fluxes and ocean response to hurricanes response to hurricanes

Yalin Fan and Isaac Ginis GSO, University of Rhode Island

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Effects of surface waves on air-sea momentum and energy fluxes and ocean response to hurricanes. Yalin Fan and Isaac Ginis GSO, University of Rhode Island. Outline. Modeling of air-sea fluxes in hurricanes Energy and momentum flux budget across air-sea interface Uniform wind Hurricanes - PowerPoint PPT Presentation

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Page 1: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Yalin Fan and Isaac GinisYalin Fan and Isaac Ginis

GSO, University of Rhode IslandGSO, University of Rhode Island

Effects of surface waves on air-Effects of surface waves on air-sea momentum and energy fluxes sea momentum and energy fluxes and ocean response to hurricanes and ocean response to hurricanes

Page 2: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

1.1. Modeling of air-sea fluxes in hurricanes Modeling of air-sea fluxes in hurricanes

2.2. Energy and momentum flux budget Energy and momentum flux budget across air-sea interfaceacross air-sea interface

– Uniform wind Uniform wind

– Hurricanes Hurricanes

3.3. Wind-wave-current interaction in Wind-wave-current interaction in hurricanes hurricanes

4.4. Case study: Hurricane Ivan (2004) Case study: Hurricane Ivan (2004)

OutlineOutline

Page 3: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Effect of surface gravity waves on air-sea fluxes

1. Modeling of air-sea fluxes in hurricanes

c

c

c c

Ocean Currents

EFair = EFc + (EFgrowth + EFdivergence)

divergencegrowthcair

Horizontal wave propagation

(EFdivergence , )divergenceWave growth

( EFgrowth, )growth

Page 4: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

c=air - w EFc = EFair - EFw

Momentum & energy flux

air=f((θ,k),(θ,k))

EFair=f((θ,k),(θ,k))

Air-sea flux calculations in numerical models & in this study

1. Modeling of air-sea fluxes in hurricanes1. Modeling of air-sea fluxes in hurricanes

Wave information (θ,k), Hs, L, T, …

Downward Energy and Momentum

Flux Budget Model

Princeton Ocean Model (POM)

Ocean ResponseU, T, …

c

U

Atmospheric observations(wind speed, Uw )

Traditional parameterization Momentum flux ( )

Energy flux (EFair = 0)wwdairair UUC

Ocean Model

air , EFair

Coupled Wind WaveBoundary Layer Model

(Moon et al. 2004)

Wind Field

Page 5: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

2. Energy and momentum flux budget across air-sea interface2. Energy and momentum flux budget across air-sea interface

WAVEWATCH III

Analytical spectrum model

(Hara & Belcher 2002)

Downward Energyand Momentum

Flux Budget Model

EFt

EEFEF

MFt

M

airc

airc

Wave Boundary Layer Model

Hara & Belcher (2004)

Momentum & energy flux calculations in this study

Wave Information:Wave spectra (), Hs, L,peak freq, Direction, …

growth spatial variation

M – total momentumE – total energyMF – total momentum fluxEF – total energy flux

Momentum &energy flux

air=f((θ,k),(θ,k))

EFair=f((θ,k),(θ,k))

Page 6: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Uniform wind experiments: Model domains

Fetch limited (space variation) experiment

Duration limited (time variation) experiment

2. Energy and momentum flux budget across air-sea interface2. Energy and momentum flux budget across air-sea interface

Steady and homogenous wind: 10, 20, 30, 40, 50 m/s

Steady and homogenous wind: 10, 20, 30, 40, 50 m/s

30o

Page 7: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

TimeDependent

FetchDependent

Uniform Wind experiments: Momentum and energy fluxes

2. Energy and momentum flux budget across air-sea interface2. Energy and momentum flux budget across air-sea interface

|c| / |air| x 100%

|c| / |air| x 100%

EFc / EFair x 100%

EFc / EFair x 100%

= cp/u* = cp/u*

= cp/u* = cp/u*

Page 8: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Wind Field (m/s)

Longitude

Win

d s

pee

d (

m/s

)

0m/sTSP = 5m/s 10m/s

Lat

itu

de

Hurricane experiments

2. Energy and momentum flux budget across air-sea interface2. Energy and momentum flux budget across air-sea interface

TSP: Hurricane translation speed

10

20

3

0

40

0 9 18

Input parameters:Input parameters:Maximum wind speed (MWS)Radius of MWS (RMW)Central & environmental sea-level pressure

Holland Hurricane Wind Model

Page 9: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

0m/sTSP = 5m/s 10m/s

TSP0m/s

TSP5m/s

Hurricane experiments

2. Energy and momentum flux budget across air-sea interface2. Energy and momentum flux budget across air-sea interface

Hs

(m)

Hs

(m)

Hs

(m)TSP

10m/s

Cg (

m/s

)C

g (m

/s)

Group Velocity

Wave Field

Page 10: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Hurricane experiments: Stationary Case (TSP = 0 m/s)

2. Energy and momentum flux budget across air-sea interface2. Energy and momentum flux budget across air-sea interface

|c| / |air| x 100% EFc / EFair x 100%RMW RMW

RMW RMW

Wind Speed Profile Angle between wind & wave ()

Page 11: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

TSP = 5 m/s TSP = 10 m/s(N/m2) (N/m2)

(%) (%)

Hurricane experiments: Moving cases (TCP = 5 m/s and 10 m/s)

Longitude Longitude

Longitude Longitude

Lat

itu

de

Lat

itu

de

Lat

itu

de

Lat

itu

de

2. Energy and momentum flux budget across air-sea interface2. Energy and momentum flux budget across air-sea interface

|c| / |air| x 100% |c| / |air| x 100%

|air - c| |air - c|

Page 12: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

EFair – EFc

EFc/EFairx100%

Hurricane experiments: Moving cases (TCP = 5 m/s and 10 m/s)

2. Energy and momentum flux budget across air-sea interface2. Energy and momentum flux budget across air-sea interface

Longitude Longitude

Longitude Longitude

Lat

itu

de

Lat

itu

de

Lat

itu

de

Lat

itu

de

TSP = 5 m/s TSP = 10 m/s

EFc/EFairx100%

EFair – EFc

Page 13: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

air

c

3. Wind-wave-current interaction in hurricanes3. Wind-wave-current interaction in hurricanes

Control (one-way interaction,

fluxes from air)

Exp. A (one-way interaction,fluxes into currents)

Exp. B (two-way interaction,

partial)

Exp. D (fully coupled)

Exp. C (two-way interaction,

partial)

Momentum & energy flux

air=f((θ,k),(θ,k))

EFair=f((θ,k),(θ,k))

c

Page 14: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Ocean response in Control Experiment

3. Wind-wave-current interaction in hurricanes

air CurrentsW at 90 m

Page 15: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Ocean response in Control Experiment

3. Wind-wave-current interaction in hurricanes3. Wind-wave-current interaction in hurricanes

a b

Initial Tprofile

Sea Surface Temperature anomalyTemperature, TKE profile

RMW 2RMW

TKET TKE

T

Page 16: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

3. Wind-wave-current interaction in hurricanes3. Wind-wave-current interaction in hurricanes Momentum Flux ratio

c in A / air in Control air in B / air in Control

air in C / air in Control c in D / air in Control (%

)

(%)

(%)

(%)

Page 17: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Differences in the Sea Surface Temperature cooling

3. Wind-wave-current interaction in hurricanes3. Wind-wave-current interaction in hurricanes

Longitude

Longitude Longitude

Longitude

A – Control B – Control

C – Control D – Control

Page 18: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Impact of wind-wave-current interaction on the wave fields

3. Wind-wave-current interaction in hurricanes3. Wind-wave-current interaction in hurricanes

Control & A Exp. B

Exp. C Exp. D

RMW

Page 19: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

4. Case study: Hurricane Ivan (2004)4. Case study: Hurricane Ivan (2004) Ivan track and reconnaissance flight tracks

Flight tracks/Scanning Radar Altimeter measurementsNASA/Goddard spacing flight center & NOAA/HRD

Exp. A: WAVEWATCH III wave model (operational model)Exp. B: Coupled wind-wave model Exp. C: Coupled wind-wave-current model

Page 20: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

3000 m

50 m

2400 m

4. Case study: Hurricane Ivan (2004)4. Case study: Hurricane Ivan (2004)Scanning Radar Altimeter (SRA) measurements

Page 21: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

4. Case study: Hurricane Ivan (2004)4. Case study: Hurricane Ivan (2004) Hurricane research division (HRD) wind

Page 22: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

4. Case study: Hurricane Ivan (2004)4. Case study: Hurricane Ivan (2004) Wind swath and sea surface temperature

Page 23: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Significant Wave Height SwathsExperiment A

Experiment B

Experiment C

Longitude

4. Case study: Hurricane Ivan (2004)4. Case study: Hurricane Ivan (2004)

Page 24: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

4. Case study: Hurricane Ivan (2004)4. Case study: Hurricane Ivan (2004) Surface wave field & flight track

September 9 18:00 UTC

Page 25: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Dominant Wave Length Significant Wave Height

Wave Direction

4. Case study: Hurricane Ivan (2004)4. Case study: Hurricane Ivan (2004)

Wave parameter comparisons between model and SRA data

Left-rear Right-rear

SRA

SRA data number

SRA data number SRA data number

Vertical velocity

Page 26: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Main ConclusionsMain Conclusions

Uniform Wind Study:

• For momentum flux calculations at the air-sea interface, the effect of time variation of the wave field is small but the effect of spatial variation is important. Both effects, however, are important for energy flux calculations.

• The energy flux into currents depends on both wave age and friction velocity, and is roughly proportional to the 3.5th power of the friction velocity, rather than the 3rd power previously suggested by the literature.

Page 27: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Main ConclusionsMain Conclusions

Hurricane Study:

• The surface wave effects on the air-sea fluxes are most significant in the rear-right quadrant of the hurricane and consequently reduce the magnitude of subsurface currents and sea surface temperature cooling to the right of the storm track.

• Wave-current interaction reduces the momentum flux into currents mainly due to the reduction of wind speed input into the wave model relative to the ocean currents.

• The improved momentum flux parameterization, together with wave-current interaction is shown to improve forecast of significant wave height and wave energy in Hurricane Ivan.

Page 28: Yalin Fan and Isaac Ginis GSO, University of Rhode Island

Thank You