1 / 28

Yalin Fan and Isaac Ginis GSO, University of Rhode Island

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

doane
Download Presentation

Yalin Fan and Isaac Ginis GSO, University of Rhode Island

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 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

  2. Outline • Modeling of air-sea fluxes in hurricanes • Energy and momentum flux budget across air-sea interface • Uniform wind • Hurricanes • Wind-wave-current interaction in hurricanes • Case study: Hurricane Ivan (2004)

  3. 1. Modeling of air-sea fluxes in hurricanes • Effect of surface gravity waves on air-sea fluxes EFair = EFc + (EFgrowth + EFdivergence) c c Wave growth ( EFgrowth, ) Horizontal wave propagation (EFdivergence , ) Ocean Currents c c

  4. 1. Modeling of air-sea fluxes in hurricanes • Air-sea flux calculations in numerical models & in this study Wind Field Atmospheric observations (wind speed, Uw ) Coupled Wind Wave Boundary Layer Model (Moon et al. 2004) Traditional parameterization Momentum flux ( ) Energy flux (EFair = 0) Wave information (θ,k), Hs, L, T, … Momentum & energy flux air=f((θ,k),(θ,k)) EFair=f((θ,k),(θ,k)) , EFair Downward Energy and Momentum Flux Budget Model Ocean Model Princeton Ocean Model (POM) c=air - w EFc = EFair - EFw Ocean Response U, T, … U

  5. 2. Energy and momentum flux budget across air-sea interface Momentum & energy flux calculations in this study Analytical spectrum model (Hara & Belcher 2002) WAVEWATCH III Wave Boundary Layer Model Hara & Belcher (2004) Wave Information: Wave spectra (), Hs, L, peak freq, Direction, … Momentum &energy flux air=f((θ,k),(θ,k)) EFair=f((θ,k),(θ,k)) Downward Energy and Momentum Flux Budget Model M – total momentum E – total energy MF – total momentum flux EF – total energy flux growth spatial variation

  6. 2. Energy and momentum flux budget across air-sea interface • Uniform wind experiments: Model domains Fetch limited (space variation) experiment Steady and homogenous wind: 10, 20, 30, 40, 50 m/s 30o Duration limited (time variation) experiment Steady and homogenous wind: 10, 20, 30, 40, 50 m/s

  7. 2. Energy and momentum flux budget across air-sea interface • Uniform Wind experiments: Momentum and energy fluxes |c| / |air| x 100% EFc / EFair x 100% Time Dependent = cp/u* = cp/u* |c| / |air| x 100% EFc / EFair x 100% Fetch Dependent = cp/u* = cp/u*

  8. 2. Energy and momentum flux budget across air-sea interface • Hurricane experiments Holland Hurricane Wind Model TSP: Hurricane translation speed Latitude Wind Field (m/s) 10 20 30 40 0m/s TSP = 5m/s 10m/s Input parameters: Maximum wind speed (MWS) Radius of MWS (RMW) Central & environmental sea-level pressure Wind speed (m/s) 0 9 18 Longitude

  9. 2. Energy and momentum flux budget across air-sea interface • Hurricane experiments Hs (m) Wave Field TSP 0m/s 0m/s TSP = 5m/s 10m/s Group Velocity Cg (m/s) Hs (m) TSP 5m/s Cg (m/s) Hs (m) TSP 10m/s

  10. 2. Energy and momentum flux budget across air-sea interface • Hurricane experiments: Stationary Case (TSP = 0 m/s) Angle between wind & wave () Wind Speed Profile RMW RMW |c| / |air| x 100% EFc / EFair x 100% RMW RMW

  11. 2. Energy and momentum flux budget across air-sea interface • Hurricane experiments: Moving cases (TCP = 5 m/s and 10 m/s) TSP = 5 m/s TSP = 10 m/s (N/m2) (N/m2) |air - c| |air - c| Latitude Latitude Longitude Longitude |c| / |air| x 100% |c| / |air| x 100% (%) (%) Latitude Latitude Longitude Longitude

  12. 2. Energy and momentum flux budget across air-sea interface • Hurricane experiments: Moving cases (TCP = 5 m/s and 10 m/s) TSP = 5 m/s TSP = 10 m/s EFair – EFc EFair – EFc Latitude Latitude Longitude Longitude EFc/EFairx100% EFc/EFairx100% Latitude Latitude Longitude Longitude

  13. 3. 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. C (two-way interaction, partial) Exp. D (fully coupled) Momentum & energy flux air=f((θ,k),(θ,k)) EFair=f((θ,k),(θ,k))

  14. 3. Wind-wave-current interaction in hurricanes • Ocean response in Control Experiment air W at 90 m Currents

  15. 3. Wind-wave-current interaction in hurricanes • Ocean response in Control Experiment Temperature, TKE profile Sea Surface Temperature anomaly T T TKE TKE RMW 2RMW Initial T profile a b

  16. 3. Wind-wave-current interaction in hurricanes • Momentum Flux ratio cin A/ airin Control airin B/ airin Control (%) (%) airin C/ airin Control cin D/ airin Control (%) (%)

  17. 3. Wind-wave-current interaction in hurricanes • Differences in the Sea Surface Temperature cooling A – Control B – Control Longitude Longitude C – Control D – Control Longitude Longitude

  18. 3. Wind-wave-current interaction in hurricanes • Impact of wind-wave-current interaction on the wave fields Control & A Exp. B Exp. C Exp. D RMW

  19. 4. Case study: Hurricane Ivan (2004) • Ivan track and reconnaissance flight tracks Flight tracks/Scanning Radar Altimeter measurements NASA/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

  20. 4. Case study: Hurricane Ivan (2004) • Scanning Radar Altimeter (SRA) measurements 3000 m 50 m 2400 m

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

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

  23. 4. Case study: Hurricane Ivan (2004) • Significant Wave Height Swaths Experiment A Experiment B Experiment C Longitude

  24. 4. Case study: Hurricane Ivan (2004) • Surface wave field & flight track September 9 18:00 UTC

  25. 4. Case study: Hurricane Ivan (2004) • Wave parameter comparisons between model and SRA data Vertical velocity Wave Direction SRA SRA data number Dominant Wave Length Significant Wave Height Right-rear Left-rear SRA data number SRA data number

  26. Main 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.

  27. Main 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.

  28. Thank You

More Related