1

Advanced coupled atmosphere-wave-ocean modeling for improving tropical cyclone

prediction models

PI: Isaac GinisUniversity of Rhode Island

Co-PIs: T. Hara (URI), E. Andreas (NWR), R. Lukas (UH), A. Soloviev (NSU)

Collaborators: J.-W. Bao, C. Fairall (NOAA/ESRL)H. Tolman (NOAA/NCEP)

Advanced coupled atmosphere-wave-ocean modeling for improving tropical cyclone

prediction models

PI: Isaac GinisUniversity of Rhode Island

Co-PIs: T. Hara (URI), E. Andreas (NWR), R. Lukas (UH), A. Soloviev (NSU)

Collaborators: J.-W. Bao, C. Fairall (NOAA/ESRL)H. Tolman (NOAA/NCEP) NOPP Review Meeting, 2012, Miami, FL

1) To understand the physical processes that control the air-sea interaction and their impacts on intensity changes in tropical cyclones.

1) To develop a physically based and computationally efficient unified air-sea interface module for use in the next generation of research and operational coupled atmosphere-wave-ocean-land models.

Long-Term GoalsLong-Term Goals

• Evaluation of WAVEWATCH v 3.14 wave model in hurricane conditions.

• Investigation of the sea state dependence of drag coefficient in hurricanes with new URI and UM air-sea momentum.

• Investigation of the Stokes drift velocity and Coriolis-Stokes forcing due to ocean surface waves under hurricane conditions

• Implementation of new methods for coupling the sea-spray parameterization with the surface wave properties.

Year 2: Work CompletedYear 2: Work Completed

• Implementation and testing of the air-sea interface module with URI/ESRL air-sea coupling parameterizations into a research versions of the GFDL and HWRF coupled hurricane-wave-ocean model.

• Investigation of the upper and lower limits of the drag coefficient in high wind conditions

Year 2: Work Completed (contYear 2: Work Completed (cont’’d)d)

Physics of Wind-Wave-Current InteractionPhysics of Wind-Wave-Current Interaction

Image courtesy of Fabrice Veron

Wave model component - WAVEWATCH III

WAVEWATCH III can accurately reproduce observed hurricane surface wave fields if:

- Wind forcing is reduced at very high wind speeds. - Ocean current is explicitly included in the simulation.

WW3 significant wave height field (color) at Sept. 15 2:00 UTC. The thick gray line is the flight track.

Significant wave height comparison between SRA measurements (during this flight) and WW3 results from experiments A, B (with modified wind stress) and C (with modified wind stress and including ocean currents).

Comparison between modeled and measured significant wave heights from all flights.

WW3 v3.14: Extending to Finite/Shallow Water.

* Previous version of WAVEWATCH III (v2.2.2) did not work well for water depth less than 30m (grey area below)

•New version of WAVEWATCH III (v3.1.4) includes improved physics in shallower water.

* We are validating the WAVEWATCH III (v3.1.4) results in shallower water against observations (Scanning Radar Altimeter) in collaboration with Ed Walsh.

Hurricane Ivan (2004) significant wave height predictions

WW3 2.22 WW3 3.14

Difference

WW3 v3.14: Extending to Finite/Shallow Water

Sea state dependent drag coefficientIsaac Ginis, Tetsu Hara, Brandon Reichl (URI), Mark Donelan (UM)

• In the fully coupled hurricane-wave-ocean modeling framework, the sea state dependent air-sea momentum flux (drag coefficient) is calculated using the wave model (WAVEWATCH III or others) output.

• In the air-sea interface module developed during the NOPP project, different flux models (wave boundary layer models) will be available for the flux calculations.

• We have examined two flux models (new URI and UM) as potential candidates for the air-sea interface module.

pdf

Stokes Drift

Isaac Ginis, Tetsu Hara, Colin Hughes, Brandon Reichl, John Bruce (URI)

•In the fully coupled hurricane-wave-ocean modeling framework, the Stokes drift of surface waves introduces: - Langmuir turbulence and enhanced/reduced upper ocean mixing- Coriolis-Stokes effect that effectively modifies the momentum flux into subsurface current

• In addition, the Stokes drift introduces significant near surface mass transport that may affect transport of materials (e.g., oil).

Lagrangian floats deployed ahead of Hurricane Gustav (2008) measured vertical kinetic energy in

the mixed layer

Courtesy of Eric D’Asaro

Langmuir turbulence

• D’Asaro et al. suggest that near surface turbulence and upper ocean mixing may be significantly reduced when surface waves are opposing the wind and suppress the Langmuir turbulence.

• We have examined the Stokes drift (vertical profile) under fetch dependent cases (uniform wind) and under idealized hurricanes (stationary and translating).

• We are investigating the Langmuir turbulence under hurricanes using LES in collaboration with Tobias Kukulka (U. Del).

Angle difference between wind direction and Stokes drift direction at z=k peak

-1 under Idealized hurricane

UT

Angle exceeds 90 degrees under a translating hurricane.

Left panels: 500x500 km domain

Right panels:100x100 km domain

Surface Mass Transport

• Empirical oil spill models assume drift speed of about 3% of the wind speed.

• Our calculations under fetch-dependent and hurricane winds show that more than half (around 1.5-2% of the wind speed) is due to the Stokes drift. In a moving hurricane, this ratio varies, with the largest on the rear-right side of the track.

Coriolis–Stokes Effect

The momentum flux into the ocean may be different from the wind stress.

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Ocean momentum equation with surface wave effects (Mellor 2008)

In meso-scale, deep water, hurricane ocean model:

Momentum equation is unchanged, but - turbulence closure is modified by (unresolved) Langmuir turbulence.

- surface boundary condition is modified (momentum flux ≠ wind stress).

Air-sea momentum budget Coriolis-Stokes(Fan et al. 2008) already correction toincluded in ASIM wind stress

Coriolis –Stokes effect

• The momentum flux into the ocean may be different from the wind stress. The difference can be as large as 15% of the wind stress near the radius of maximum wind to the right of the hurricane center, and it exceeds 30% further away.

• The direction of the Coriolis-Stokes effect (vector) tends to be to the right of the wind stress direction.

Drag coefficient parameterization by Ed Andreas

Implications of the Straight Line

Best fit is

* N10u 0.0583U 0.243

where both u* and UN10 are in m/s.

Hence, 2 2

*DN10

N10 N10

2

3

N10

u 0.243C 0.0583

U U

4.173.40 10 1

U

The parameterization predicts leveling off of the drag coefficient

We can combine linear relations in the smooth regime and in the rough regime

Air-Sea Interface in Hurricane Conditions

Alex SolovievAlex Soloviev1, 21, 2, Roger Lukas, Roger Lukas33 Silvia MattSilvia Matt11, Atsushi Fujimura, Atsushi Fujimura22

1 1 Nova Southeastern UniversityNova Southeastern University22 University of Miami University of Miami

33 University of Hawaii University of Hawaii

In collaboration with In collaboration with Isaac Ginis and Tetsu HaraIsaac Ginis and Tetsu Hara

March 1, 2012 ONR/NOPP Review at UM RSMAS

Introduction

• In this work, we further develop the hypothesis that the

change of the air-sea interaction regime in hurricane

conditions is associated with the mechanism of direct

disruption of the air-sea interface by pressure fluctuations

working against surface tension.

• This disruption can be achieved through the Kelvin-

Helmholtz (KH) or Tollmien-Schlichting (TS) instability

and leads to formation of two-phase transition layer.

• The transition layer has been related to the lower bound

on the air-sea drag coefficient in hurricane conditions in

an earlier work (Soloviev and Lukas 2010).

Direct Disruption of the Air-Sea Interface

1/ 42/ /a s w aK u g

A non-dimensional number,

which we call here the Koga number, is the criteria for the K-H

instability at an interface (Soloviev and Lukas 2010).

The instability occurs at K > Kcr, where Kcr ~ 0.26

(corresponding to U10 ~ 30 m s-1).

In this formula, u*a is the friction velocity from the air side, g the

acceleration due to gravity, s the surface tension,w and a are

the water and air density, respectively.

Numerical Simulations

• In order to demonstrate the possibility of the direct disruption of the air-

sea interface under hurricane conditions, we have used an idealized 3D

model set-up.

• A series of numerical experiments has been conducted using the

computational fluid dynamics software ANSYS Fluent.

• Wind stress was applied at the upper boundary of the air layer, ranging

from no wind stress to hurricane force wind stress.

periodic periodic

Disruption of the air-water interface due to the K-H type instability

Wind stress 4 N m-2

The numerical experiment with an initially flat interface illustrates the possibility of the direct disruption of the air-water interface due to the K-H type instability and formation of the two-phase environment under hurricane force winds.

Elapsed time = 2 s

10 cm

Soloviev, Fujimura and Matt, submitted to JGR-Oceans

The numerical experiment with imposed short waves

Wind stress 4 N m-2

The numerical experiment with imposed short waves demonstrates the tearing of wave crests, formationof water sheets and spume ejected into the air

Elapsed time = 0.5 s

Soloviev, Fujimura and Matt, submitted to JGR-Oceans

Averaged vertical density and velocity profiles at the air-sea interface from CFD simulation

22 / /Ri N u z

2 loggN g

z z

For air-water density difference, Boussinesq approximation is no longer valid:

2log / / ,a z c gu

1/ uu z c gu

Linear profiles for log and u follow from dimensional analysis:

0.43crRi

“Theoretical” value for non Boussinesq: Ricr = 1/2 Cushman-Rosin (1994)

The density profile in the atmospheric boundary layer is assumed to obey the log layer law as well but cannot be seen in this diagram scale.

Schematic representation of density and velocity profiles in the atmospheric and oceanic boundary

layers under hurricane conditions

The CFD model has provided a better estimate for the lower

bound on the air-sea drag coefficient in hurricane conditions

The two-phase layer resistance and wave resistance parameterizations in comparison with available laboratory and field data. Transition to hurricane force wind is associated with the drop of the drag coefficient, which then may slowly increase with wind speed.

potential local minimum in Cd?

Thickness of the two-phase transition layer as a function of wind speed

The two-phase environment suppresses short waves. This effect can be included in the wave model via the condition:

cutoffk H C»

kcutoff is cut-off wavenumber

H is thickness of the transition layer

C is dimensionless constant of the order of 1.

Conclusions

• Change of the air-sea interaction regime in hurricane

conditions can be linked to the effect of direct disruption of

the air-sea interface and formation of a relatively thin two-

phase transition layer

• Analysis including computational fluid dynamics

experiments has provided an estimate for the lower bound

on the air-sea drag coefficient Cd in hurricane conditions

assuming regime of marginal stability in the transition layer

• An ad hoc “sweet spot” type parameterization for Cd can be

implemented

• Two-phase environment can be included into wave model

SummarySummary

• Hurricane model: air-sea fluxes depend on sea state, sea spray and include surface current.

• Wave model: forced by sea state dependent wind forcing and includes surface current

• Ocean model: forced by sea state dependent wind stress modified by growing or decaying wave fields and Coriolis-Stokes. Turbulent mixing is modified by the Stokes drift (Langmiur turbulence).

Coupled Atmosphere-Wave-Ocean FrameworkCoupled Atmosphere-Wave-Ocean Framework

Red - atmospheric parameters, Green – wave parameters, Blue - ocean parameters

• Implement the new URI and UM sea state momentum flux parameterizations into the air-sea interface module (ASIM)

• Implement the effect of Coriolis-Stokes forcing into ASIM

• Refine the wave-driven sea spray parameterization and implement it into ASIM (in collaboration with ESRL)

• Insure that all components of ASIM are modular, so the same codes can be moved between the coupler and component models as needed and different coupled atmosphere-wave-ocean models

Year 3 Plans for the URI Co-PIsYear 3 Plans for the URI Co-PIs

• Implement and test ASIM into the HWRF-WAVEWATCH III-POM/HYCOM system (in collaboration with EMC)

• Transition components of ASIM into the COAMPS TC-WAVEWATCH III-NCOM system (in collaboration with NRL)

• Run test simulations with HWRF-WW3-POM/HYCOM as part of HFIP Stream 2 and evaluate the model results against available observations

• Assist in transitioning the HWRF-WW3-POM/HYCOM to the research community via DTC

Year 3 Plans for the URI Co-PIsYear 3 Plans for the URI Co-PIs