Estimation of Wind Drift Current in the Soya Strait
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1 Estimation of Wind Drift Crrent in the Soya Strait Wei Zhang 1, Naoto Ebchi 1, Yasshi Fkamachi 1, and Ytaka Yoshikawa 2 1 Institte of Low Temperatre Science, Hokkaido University 2 Gradate School of Science, Kyoto University 1
2 The Soya Strait Rssia China Sea of Okhotsk Japan Connection of Sea of Japan Sea and Sea of Okhotsk Soya warm crrent Fishery 2
3 Wind Drift Crrent Wind s g wd Srface crrent wd : Wind Drift Crrent Geostrophic Crrent Cshman-Roisin (1994) 3
4 Drift Parameter wd s g = A(, ) W cos sin A(, ) sin cos α: speed factor θ: deflection angle W: wind vector s : srface crrent g : geostrophic crrent Cshman-Roisin (1994) 4
5 How to calclate wind drift parameter LSM min[( ) A(, ) W] (, ) s g *Complex PCA/EOF (, ) W 1st CEOF wd1st s g W Srface crrent (HF radar data) Geostrophic crrent (ADCP data / Tide gages data) Wind (JMA GPV/MSM) * Knd and Allen (1976) 5
6 CEOF Brief Introdction W( UV, ) U Vi CEOF( W ) EOF( U Vi) ( U V i) 1st 1st Knd and Allen (1976) 6
7 Observation Long Term: HF Radars Tide Gages Wind (JMA GPV/MSM) Short Term: (22 months) ADCP (Bottom monted) 7
8 Example of HF Radar Snapshot 17h20m (JST) 3 Ag
9 Example of ADCP vertical profiles Monthly-mean of alongshore velocity observed by ADCP. Fkamachi et al.(2010)
10 Geostrophic Crrent Estimation (Method 1) Extrapolation Along-shore Component Cross-shore Component LSM 1 Complex PCA/EOF Bin Nmber Bin nmber Velocity (m/s) Velocity (m/s) Dec ~ Dec day geostrophic crrent estimation from ADCP 10
11 Sea Level Difference vs. Along-shore Crrent Correlation Coefficient between Sea Level Difference (SLD) and alongshore velocities of ADCP bins. 25 Bin24 Srface 20 Bin ADCP bins Nmber Bin15 Bin10 Bin5 ~51m Correlation Coeffiicent Bottom Alongshore velocities correspond well with sea level difference. Bin1 11
12 Geostrophic Crrent Estimation (Method 2) g a b Bin24 Bin24 ibin a ibin b ibin LSM 2 Complex PCA/EOF a b Bin22 Bin22 Bin22 25 Coefficient a ibin 25 Coefficient b ibin a b Bin18 Bin18 Bin18 Bins Bins a b Bin15 Bin15 Bin Coefficient Coefficient Ag Geostrophic crrent estimated from Sea Level Difference Coefficient 12
13 Trning Angle (deg.) Monthly-Mean Drift Parameters LSM 1 LSM 2 CEOF Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/08 Speed Factor LSM 1 LSM 2 CEOF Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/ nmber of data The drift parameters are roghly similar Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/08 time (month) 13
14 Annal-Mean Drift Parameter α ( 10-2 ) θ (deg.) LSM Vale LSM CEOF LSM RMSE LSM CEOF Root-Mean-Sqare error with daily drift parameters 14
15 Wind Drift Crrent Estimation (a) By monthly-mean wind drift parameters (b) By annal-mean wind drift parameters 0.1 LSM 1 LSM 2 CEOF 0.1 LSM 1 LSM 2 CEOF Velocity (m/s) Velocity (m/s) Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/ Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/08 The wind drift crrent is strong in winter, bt weak in smmer. 15
16 Affection of coastline on drift parameter The horizontal bondary layer width * : H 2A f H D 1/2 2.2km 2 1 AH 200 m s, D 50m E + ADCP The horizontal bondary layer effect on the wind drift crrent can be neglected. * Yoshikawa and Masda (2009); Pedlosky (1987) 16
17 Affection of bottom on drift parameter The bottom bondary layer depth * : Srface E * U f * m U 10 ms, f 110 s Bottom bondary 40m ~51m The bottom bondary layer affects on the wind drift crrent. * Yoshikawa and Masda (2009); Cshman-Roisin (1994) Bottom 17
18 Wind in Smmer Jl. 07 Ag. 07 Sept. 07 Jl. 08 Oct. 06 Oct. 07 The wind is weak, and its direction is nstable. 18
19 Wind in Winter Dec. 07 Jan. 07 Feb. 07 Dec. 06 Feb. 08 Jan. 08 The wind is strong, and its direction is stable. 19
20 Evalation Along-shore Crrent Srface Crrent Estimated Geocrrent 0.8 ˆ ( ˆ, ˆ) W g s A Velocity (m/s) Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/08 Along-shore crrent vs. sea level difference Corre lation HF LSM 1 LSM 2 CEOF s Monthly Mean Monthly Mean Monthly Mean
21 Smmary Wind drift parameters calclated from 3 methods are roghly similar. Annal-mean wind drift parameters are a simple and effective way to estimate wind drift crrent. Wind drift crrent estimation is more obvios in winter, bt weak in smmer. 21
22 Main reference Yoshikawa, Y. and A. Masda (2009): Seasonal variations in the speed factor and deflection angle of the wind-driven srface flow in the Tsshima Strait. J. Geophys. Res. Oceans, 114, C12022, doi: /2009jc Cshman-Roisin, B. (1994), Introdction to Geophysical Flid Dynamics, 320 pp., Prentice-Hall, Englewood Cliffs, N. J. Fkamachi, Y., K. I. Ohshima, N. Ebchi, T. Bando, K. Ono, and M. Sano (2010): Volme Transport in the Soya Strait dring , Jornal of Oceanography, 66, Knd, P. K., and J. S. Allen (1976), Some three-dimensional characteristics of low-freqency crrent flctations near the Oregon coast, J. Phys. Oceanogr., 6, Pedlosky, J. (1987), Geophysical Flid Dynamics, 2nd ed., 710 pp., Springer, New York. Yoshikawa, Y., et al. A srface velocity spiral observed with ADCP and HF radar in the Tsshima Strait. Jornal of Geophysical Research: Oceans ( ) 112.C6 (2007).
23 Thank yo for yor Attention
24 Back Up
25 Monthly Drift Parameters LSM 1 LSM 2 CEOF LSM 1 LSM 2 CEOF deflection angle (deg.) speed factor Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/08 time (month) 0 Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/08 time (month) 700 nmber of data CEOF is a better way to estimate wind drift parameter Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/08 time (month) 25
26 Annal-Mean Drift Parameter α ( 10-2 ) θ (deg.) (b) By annal-mean wind drift parameters LSM LSM 1 LSM 2 CEOF Vale LSM CEOF LSM Velocity (m/s) RMSE LSM CEOF Nov/06 Feb/07 Jn/07 Sep/07 Dec/07 Apr/08 Jl/08 Root-Mean-Sqare error with daily drift parameters 26
27 LSM 2 LSM1 (, ) min( ) min(( ) ( cos( err (, ) (, ) s g (, v ) ( ) A(, ) W err err s g * Knd and Allen (1976) 27
28 LSM 2 (, ) min( ) (, ) err (, v ) ( ) A(, ) W err err s g * Knd and Allen (1976) 28
29 LSM1 & CEOF LSM1 (, ) min[(, v )] (, ) err err (, v ) ( ) A(, ) W err err s g *CEOF (, ) W 1st CEOF wd1st s g W W U V * i * Knd and Allen (1976) 29
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