Importance of air-sea interaction on the coupled typhoon-wave-ocean modeling

Transcription

1 Importance of air-sea interaction on the coupled typhoon-wave-ocean modeling Collaborators: I. Ginis (GSO/URI) T. Hara (GSO/URI) B. Thomas (GSO/URI) H. Tolman (NCEP/NOAA) IL-JU MOON ( 文一柱 ) Cheju National University Tainan,, Taiwan

2 Air-Sea Fluxes (Bulk Parameterization) Air Sea [ Flux] = U ([ c] [ c] ) T air water Height ν c = flux Air Interface C Water C The vertical fluxes of any variable (c, i.e., wind speed) are assumed to be driven by the difference in variable across the air-sea interface with transport velocity,, U T

3 Air-Sea Momentum Flux (Wind Stress) Air side controlled flux [ Flux] = U [ U ] [ U ] T ( ) air The transport velocity is usually parameterized as surface = 0 Height Wind Profile U Air U Water U T = C DU 10 where U10is the mean horizontal wind speed at height 10m and C is the bulk transfer coefficient (or drag coefficient) D = ] = ρ C [ ] 2 D U [ Flux [ Flux ] a D 10 air

4 Drag Coefficient (C d ) & Roughness Length (z 0 ) Using the logarithmic wind profile in neutral condition, u ( ) * z U z = ln z where z 0 is the surface roughness length and u * is the friction velocity, u* = CDU 10 we obtain 2 1 z C = ln D κ z0 gz0 z ch = = u κ z= 10m A non-dimensional roughness length, called the Charnock Coefficient, is widely used in atmospheric models * Charnock 0 coefficient Height log(z) z 0 Wind speed, U While the C D is widely used in the ocean modeling, the z o & z ch is mostly used in atmospheric models

5 Why do we care about air-sea momentum fluxes (or Wind Stress, Drag Coefficient Cd, Roughness Length)? -.. A crucial subject in atmospheric modeling and weather forecasting -. I. It provides the boundary conditions for atmospheric and oceanic models, including typhoon, wind waves, storm surge prediction models. How do we estimate the air-sea momentum fluxes? Wind Speed

6 1. Simplest Way (Bulk formula) Drag coefficient is a function of wind speed Charnock coefficient (i.e. non-dimensional roughness length) is constant Drag Coefficient, C d Drennan et al. (2003) Wind Speed gz0 = const. ~ 2 u * Most widely used in atmospheric and oceanic models C d = ( U ) 10 Large & Pond (1981) 3 Both formulas show a monotonic increase of drag with wind speed. Observations support that this is a good approximation, especially at low wind conditions.

7 For high wind speed? No field observations Extrapolated from field measurements in low wind conditions Drag Coefficient, C d Drennan et al. (2003) High wind speed of above 20m/s Wind Speed

8 2. Using relationships between Charnock coefficient and wave age Charnock Coefficient = c p gz u * 0 Wave age = is the phase speed of dominant waves (at the spectral peak) u * is the friction velocity and z 0 is roughness length The state of growth of wind waves relative to local wind forcing small (young( sea or growing sea), large (old( sea or mature sea) c p / u * What is the relationship between Charnock coefficient and wave age?

9 Charnock Coefficient vs Wave age There are many relationships that are proposed based on the different obs. data old Wave age young Data : two sources Charnock coefficient Swell Wind waves Field discontinuous NOAA operational wave prediction model, WAVEWATCH III Laboratory GFDL operational Hurricane Model Adapted by Jones & Toba (2001) The relationship Inverse is far wave from conclusive age so far

10 C D behavior of GFDL & WW3 at high winds (>20m/s) Internal Calculations of WAVEWATCH III under hurricane wind forcing Drag Coefficient Most ocean models (Lange & Pond, 1981) = ( U ) 10 C d 3 GFDL operational hurricane model : Constant Zch, Cd increases as wind speed increases at high winds WAVEWATCH III shows even much higher drag No!!!! Is this trend realistic? Can we use these formulas for high wind speeds?

11 Recent studies Alamaro et al. (2002) and Donelan et al. (2004) : Laboratory experiments Powell et al. (2003) : Indirect estimates from GPS sonde observations Emanuel (2003) and Makin (2005) : Theoretical studies Moon et al. (2004a, 2004b, and 2004c) : Model experiments There is general consensus that the Cd ceases to increase with wind speed at high wind speeds, although their physical explanations vary and are not conclusive.

12 Comparison of widely-used Cd formulas with recent results WAVEWATCH III (wave models) Most atmospheric models (GFDL) z ch = Most ocean models, Large & Pond Moon et al (2004,a,b,c) from Coupled Wave-Wind model experiments Donelan et al (2004) from wave tank experiments Powell et al (2003) from GPS sonde measurements Cd is leveling off at high wind speeds These trends are very different from those used in the most atmospheric and oceanic models

13 Coupled Wave-Wind Wind (CWW) Model Two dimensional wave spectrum Near the peak : WAVEWATCH III (WW3) model. High frequency part : Equilibrium Spectrum model of Hara and Belcher (2002) Near peak High frequency part Full wave spectrum k min k 3 k 2 k 1 k 0 k max k 2 k 1 k max k v Wave Boundary Layer (WBL) model of Hara and Belcher (2004) To explicitly calculate wave-induced stress Moon et al., (2004a & 2004b, JAS) Moon et al. (2004, GRL) f Wind profile and drag coefficient f = f = f = 1. 1 over any given seas

14 Estimation of momentum flux for 10 real r hurricanes using CWW model Isabel (2003) Tracks of 10 hurricanes occurred in the western Atlantic Ocean during : 1. Bonnie (1998), 2. George (1999), 3. Bret (1999), 4. Dennis (1999), 5. Floyd (1999), 6. Gordon (2000), 7. Keith (2000), 8. Lili (2002), 9. Isidore (2002), 10. Isabel (2003).

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16 Scatterplot of Charnock Coefficient vs Wave Age All data grid points of ten hurricanes every 6-h interval The best fits of each wind speed group Toba et al. (1990) Different color symbols according to wind speed in 5-m/s intervals Donelan (1990) Open ocean Donelan (1990) Laboratory There is a strong correlation between z ch and w age for each wind speed group young old The Because relationship of large between scatter, Charnock it is difficult coefficient to find and a unique wave age relation is not ship unique, but strongly depends between on wind z ch and speed w age! For example, At low winds, younger wave produce higher Cd. But, at high winds lower Cd Moon et al. (2006, MWR)

17 Reduced drag coefficient at high wind speed Scatterplot of C d as a function of wind peed for ten hurricanes. CWW results for 10 hurricanes Drag coefficient levels off at high wind speeds Under strong hurricane wind regimes, waves are extremely young and the young waves produce small drag. GPS sonde observations (non-d z o ) This explains why our drag coefficient levels off at high wind speed. The CWW model results affect not only the magnitude of Cd but also spatial distribution

18 Symmetric Wind Field Asymmetric Wave & Drag coefficient (Moon et al., 2003, JPO; Moon et al., 2004, JAS) Any drag formula expressed as a function of wind speed cannot generate this asymmetric drag distribution! Wave coupling is necessary!!!

19 A Coupled Hurricane-Wave-Ocean Model Hurricane Wave Ocean

20 The NCEP operational GFDL-POM Coupled Model The Coupled Hurricane- Wave-Ocean Model Atmosphere GFDL Hurricane Model Atmosphere GFDL (WRF) Hurricane Model Flux SST Wind & Air Temp. Flux Wind & Air Temp. Wave Boundary Layer Model SST SST & Current Flux Flux Wave Spectra POM Ocean POM (HYCOM) Ocean Currents, Elevations, & SST NCEP WAVEWATCH III Waves Future replacement plan : GFDL->WRF, POM->HYCOM CWW model

21 Model Domains for the Coupled Hurricane- Wave-Ocean Model in the Atlantic Basin Model domains for the coupled hurricane wave ocean model 60 C OW OE Latitude ( N) WL M F WS WL GFDL model: C, M, F POM: OW, OE WAVEWATCH-III: WL, WS Longitude ( W)

22 Model Domains for the Coupled Hurricane- Wave-Ocean Model in the Northwestern Pacific C WW OM M F - GFDL: C, M, F - WAVEWTCH III: WW - POM: OM (WRF) (SWAN) (ROMS)

23 Coupled model simulations for hurricane Katrina (2005) Sea Surface Temperature Significant Wave Height

24 The Ocean Response to Typhoon Ewiniar (2006) Central Pressure SST cooling SST Wind Stress Vertical temp. profile along the storm center Mixed Layer Depth (MLD) First, MLD became deep and then shallow, periodically varying During the strong SST cooling, upwelling is dominant, intensity became weak.

25 Effects of the wave coupling on 1. Hurricane Intensity and Structure Predictions 2. Hurricane Wave Simulation 3. Storm Surge Simulation

26 Comparison between operational model and the coupled model for hurricane Ivan (Initial( time: 00Z 12 Sep) Operational: Uncoupled : NCEP operational GFDL-POM coupled model Coupled: Coupled hurricane-wave-ocean model Operational Operational Difference Levels off at high speeds Operational model uses a constant Charnock coeff. (0.0185) Cd in the coupled model levels off at high wind speeds and the difference between two models become bigger as wind speeds increase.

27 Wave Coupled Spatial Distribution of Drag Coefficient 21 Drag Coefficient: Ivan, Initial time: 00Z 12 Sep Coupled 18Z 12 Sep Drag Coefficient: Ivan, Initial time: 00Z 12 Sep Uncoupled 18Z 12 Sep 2004 Operational Latitude ( N) ( ) Latitude ( N) ( ) x x Wave Fields Longitude ( W) Wave Field: Ivan, Initial time: 00Z 12 Sep Coupled 18Z 12 Sep 2004 [M] Longitude ( W) Snapshot of C d for Hurricane Ivan (I.T 00Z 12 Sep) Latitude ( N) ( ) Longitude ( W) The coupled model : C d is clearly asymmetry relative to the storm center, which is produced by the asymmetric wave field. The operational model : C d is simply determined by wind fields regardless of wave field. So, the difference is large

28 Surface Wind Fields Wave Coupled 25 Wind Field: Isabel, Initial time: 06Z 12 Sep Coupled 06Z 14 Sep 2003 [m/s] 70 Wind Field: Isabel, Initial time: 06Z 12 Sep Uncoupled 06Z 14 Sep 2003 Operational [m/s] Latitude ( N) Latitude ( N) Observed (HRD) Latitude ( N) Longitude ( W) HRD HRD Wind Field at 7:30Z 14 Sep Longitude ( W) 10 [m/s] Longitude ( W) Wind speed distributions for hurricane Ivan Initial time: 00Z 12 Sep In the coupled model, the wind structure, in shape and location of strong wind regime, is in a better agreement with HRD wind. 10

29 Improvement of hurricane intensity forecast Latitude ( N) Wind speed [m/s] Maximum Wind Speed: Ivan 09/12/ Z Forecast Wave coupled Observation Operational Uncoupled Maximum wind speed Time[hour] Hurricane Track: Ivan 09/12/ Z Forecast Track forecast Coupled Wave coupled Uncoupled Observation Pressure [hpa] Minimum Pressure: Ivan 09/12/ Z Forecast Wave coupled Observation Uncoupled Observation Minimum pressure Time[hour] Forecast comparisons between two models for hurricane Ivan Track forecast of two models are almost identical, but the intensity forecast is much improved by the wave coupling Longitude ( W)

30 2. Impact of the coupling on wind wave modeling under hurricane conditions Moon et al (Mon. Wea. Rev.)

31 Original parameterization of Cd used in WAVEWATCH III Model (WW3) C d = R Wave age R = ln χ 10g α 2 u e 10 α = 0.57 c p u * 3/ 2 Drag coefficient is a function of wave age Young waves produce high drags, which is very different from CWW

32 Comparisons between original and CWW parameterization in WW3 Because of the difference, the Cd at high wind speeds are very different WW3 have used a unrealistically high drag at high winds Although WW3 used very high drag, wave simulations showed good performance so far. We found that this is because WW3 used to use underestimated typhoon wind inputs, due to low grid resolution of atmospheric model under hurricane conditions

33 Speed [m/s] Hs [m] Comparisons of two model results with buoy measurements for hurricane Katrina /28/05 12:00 8/29/05 00:00 8/29/05 12:00 8/30/05 00: (a) (b) Direction (Buoy) Speed (Buoy) Original CWW Buoy Wind Speed & Direction Significant Wave Height Original CWW Direction (Model) Speed (Model) Buoy /28/05 12:00 8/29/05 00:00 8/29/05 12:00 8/30/05 00:00 Date/Time 0 Direction [degree] Wind direction Wind speed When we use accurate wind inputs, the original WW3 overestimates Hs. The CWW model shows better agreement with observations

34 Mean and rms errors between buoy and models (original and CWW parameterizations) for wind speed, wind direction, and significant wave heights. Comparisons are made at five locations along the track of hurricane Katrina Mean error Rms error wind Speed (m/s) Direction ( o ) Significant wave height Original (m) CWW (m) Statistically, the mean and rms errors are reduced by the coupled model

35 3. Effect of coupling on the storm surge modeling Moon et al (Ocean Modeling)

36 Experimental Designs 1. Three types of wind stress parameterizations (i) The linear relationship by Wu (1981) (ii) A fast-increasing Cd used in WAVEWATCH III (WW3) (iii) A leveling-off Cd by Coupled Wave-Wind (CWW) model (Moon et al., 2004), which is consistent with recent measurements at high winds

37 Experimental Designs 2. Three domains to investigate effects of model grid resolution 1/12 o (5 ) (i) Large domain: Coarse resolution (1/12 o ) grid 1/60 o (1 ) (ii) First nested domain: High resolution (1/60 o ) grid (iii) Second nested domain: Very high resolution (1/360 o, 300m) 1/360 o (300m)

38 A Selected Typhoon for Experiments 42 The strongest typhoon that ever Typhoon hit Maemi Korean Track (Sep. coasts 2003) Ieodo marine tower Typhoon Maemi (2003) Produced a lot of storm surge damage Pohai Yangtze River China Taiwan Strait Taiwan Yellow Sea East China Sea 11/18Z 11/12Z 11/06Z 11/00Z 10/18Z Korea 12/06Z 12/00Z 12/12Z Tokara Strait 10/00Z 09/18Z East Sea 12/18Z Korea Strait Japan [day/hour] Longitude [ o E]

39 Storm Surge Model KORDI-S (Lee et al., 2007) : A depth-averaged hydrodynamics model developed by KORDI 2m Spatial distributions of computed surge level for typhoon Maemi Maximum surge about 2m occurs at southern coasts of Korea

40 Experiment 1 Effects of model resolution on the surge prediction In this experiment, all conditions are same except model resolution Used three model grid resolution : 1/12 o, 1/60 o, 1/360 o Higher resolution grids produce higher surge level In the past, many storm surge model could not have sufficient grid resolution!! As a result, storm surge was underestimated in many models. To compensate this, it seems that model requires higher wind stress

41 Experiment 2 Effects of wind stress parameterization If we use very accurate wind input and high resolution grid, the Wu and WW3 with high drag at high wind speed produce overestimated surge The CWW with the reduced Cd at high wind speeds produces the most accurate surge height

42 For the case when the wave-coupled model is not available A New Empirical Formula of Z 0 Zo is expressed by a function of wind speed Ignoring sea state dependence Overcome the big difference Moon et al. (2007, Mon Wea Rev) Zch= CWW Based on the CWW model simulations for 10 hurricanes Difference Regression coeff.= z0 = (0.001W W ), W 12.5 g 3 z = (0.085W 0.58) 10, W 12.5 m / s 0 > m / s

43 Drag Coefficients Zch= C d 2 10 = κ ln z0 2. Drag coefficient relationship as a function of wind speed For W 12.5 m/s, the new Cd represents a monotonic increase with wind speed as in the operational GFDL model. But for W > 12.5 m/s, the new Cd tends to level off between 2 and 3. This is similar to the trend observed by Donelan et al. (2004) and is within the error bars estimated by Powell et al. (2003)

44 Test of the new momentum flux parameterization for the GFDL model hurricane predictions Moon et al (Mon. Wea. Rev.) Five-day Forecasts Experiments : Eleven cases during five hurricanes Isabel (00 UTC 10 September, 18 UTC 18 September, 00 UTC 12 September, 00 UTC 12 September), Ivan (00 UTC 10 September, 06 UTC 10 September, 00 UTC 11 September, 00 UTC 12 September) Frances (06 UTC 1 September), Jeanne (00 UTC 19 September) Charley (18 UTC 11 August)

45 Hurricane Maximum Wind Prediction (b) 00 UTC 12 Sep [72h forecast] 80 CHWOM Observed CHOM CHOM Z0MOD Wind speed [m/s] Observation Wave-Coupled Empirical Zo Operational Time [hour] The skill of empirical parameterization is comparable to that of the full wave-coupled model

46 Limitation of predicting hurricane wind structure Operational Wind Field: Isabel, Initial time: 06Z 12 Sep Uncoupled 06Z 14 Sep 2003 [m/s] Wind Field: Isabel, Initial time: 06Z 12 Sep Coupled 06Z 14 Sep 2003 [m/s] 70 Wave- Coupled Latitude ( N) Latitude ( N) Empirical Zo Longitude ( W) (b) Wind Field: Isabel, Initial time: 06 UTC 12 Sep CHOM Z0MOD 06 UTC 14 Sep 2003 [m/s] Longitude ( W) HRD HRD Wind Field at 7:30Z 14 Sep. HRD [m/s] Latitude ( N) Latitude ( N) Longitude ( W) Because we ignore the wave dependency Longitude ( W)

47 Conclusion & Summary Air-sea momentum flux is strongly wave-dependent. The behaviors of drag coefficient at high wind speeds are very different from those at low winds Simulation results from the coupled wave-wind model show that drag ceases to increase with wind speed at high winds, which is consistent with recent observational and theoretical trends From the experiment of the coupled hurricane-waveocean model, it is demonstrated that hurricane intensity and wind structure as well as wind wave and storm surge predictions can be improved by the wave coupling. A new parameterization can be used for the case when the wave model is not available.

48 International Workshop on Tropical Cyclone-Ocean Interaction in the Northwest Pacific ( TCOI 2009 ) April 27 ~ 29, 2009 Jeju, Korea

49 THE END pdf files of references