Current in the Soya Strait Wei Zhang 1 , Naoto Ebuchi 1 , Yasushi - PowerPoint PPT Presentation

Estimation of Wind Drift Current in the Soya Strait Wei Zhang 1 , Naoto Ebuchi 1 , Yasushi Fukamachi 1 , and Yutaka Yoshikawa 2 1 Institute of Low Temperature Science, Hokkaido University 2 Graduate School of Science, Kyoto University 1

The Soya Strait Russia Sea of Okhotsk China Japan  Connection of Sea of Japan Sea and Sea of Okhotsk  Soya warm current  Fishery 2

Wind Drift Current   Wind u u u s g wd Surface current u wd : Wind Drift Current Geostrophic Current 3 Cushuman-Roisin (1994)

Drift Parameter   u u u wd s g   = ( , ) A W     c o s s i n       A ( , )      s i n c o s α: speed factor θ: deflection angle W : wind vector u s : surface current u g : geostrophic current 4 Cushuman-Roisin (1994)

How to calculate wind drift parameter   A   min[( u u ) ( , ) W ] LSM s g   ( , )       W W *Complex     1 st     ( , )   CEOF      u u PCA/EOF u     s g wd st 1  Surface current (HF radar data)  Geostrophic current (ADCP data / Tide gauges data)  Wind (JMA GPV/MSM) 5 * Kundu and Allen (1976)

CEOF Brief Introduction   W ( , ) U V U Vi   CEOF ( W ) EOF ( U Vi )   ( ) U V i 1 st 1 st 6 Kundu and Allen (1976)

Observation Long Term: • HF Radars • Tide Gauges • Wind (JMA GPV/MSM) Short Term: (22 months) • ADCP (Bottom mounted) 7

Example of HF Radar Snapshot 17h20m (JST) 3 Aug 2003 http://wwwoc.lowtem.hokudai.ac.jp/hf-radar/index.html

Example of ADCP vertical profiles Monthly-mean of alongshore velocity observed by ADCP. Fukamachi et al .(2010)

Geostrophic Current Estimation (Method 1) LSM 1 Along-shore Component Cross-shore Component 25 25 Complex PCA/EOF 20 20 Extrapolation Bin Number Bin number 15 15 10 10 5 5 0 0 0 0.2 0.4 -0.2 0 0.2 Velocity (m/s) Velocity (m/s) Dec. 23 2007 ~ Dec. 27 2007 5-day geostrophic current estimation from ADCP 10

Sea Level Difference vs. Along-shore Current Correlation Coefficient between Sea Level Difference (SLD) and alongshore velocities of ADCP bins. Surface Bin24 25 Bin22 20 ADCP bins Number Bin15 15 ~51m Bin10 10 Bin5 5 Bottom Bin1 0 0.77 0.77 0.78 0.78 0.79 0.79 0.8 0.8 0.81 0.81 0.82 0.82 0.83 0.83 0.84 0.84 Correlation Coeffiicent 11 Alongshore velocities correspond well with sea level difference.

Geostrophic Current Estimation (Method 2) LSM 2     u a b     u a b Complex g Bin 24 Bin 24 iB in iBin iBi n PCA/EOF Coefficient a iBin Coefficient b iBin     u a b 25 25 Bi n 22 B in 2 2 B in 2 2 20 20 15 15     u a b Bins Bins Bi n 18 B in 1 8 B in 1 8 10 10 5 5     u a b 0 0 Bi n 15 B in 1 5 B in 1 5 0 5 0 0.5 1 Coefficient Coefficient Aug. 2007 Geostrophic current estimated from Sea Level Difference Coefficient 12

Monthly-Mean Drift Parameters LSM 1 LSM 1 0.03 100 LSM 2 LSM 2 CEOF CEOF Turning Angle (deg.) 0.025 Speed Factor 50 0.02 0.015 0 0.01 0.005 -50 0 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 700 600 500 number of data The drift parameters are 400 roughly similar. 300 200 100 13 0 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 time (month)

Annual-Mean Drift Parameter α ( × 10 -2 ) θ (deg.) LSM1 0.87 18 LSM2 1.39 34 Value CEOF 1.10 21 LSM1 1.64 78 LSM2 2.60 77 RMSE CEOF 1.93 98 Root-Mean-Square error with daily drift parameters 14

Wind Drift Current Estimation (a) By monthly-mean wind drift parameters (b) By annual-mean wind drift parameters LSM 1 LSM 1 0.1 0.1 LSM 2 LSM 2 CEOF CEOF Velocity (m/s) Velocity (m/s) 0.05 0.05 0 0 -0.05 -0.05 -0.1 -0.1 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 The wind drift current is strong in winter, but weak in summer. 15

Affection of coastline on drift parameter The horizontal boundary layer width * : 1/2   2 A D      H 2.2 km  H   f E    2 1 A 200 m s , D 50 m H + ADCP The horizontal boundary layer effect on the wind drift current can be neglected. 16 * Yoshikawa and Masuda (2009); Pedlosky (1987)

Affection of bottom on drift parameter Surface The bottom boundary layer depth * : Bottom boundary U    * 0.4 40 m ~51m E f        2 1 4 1 U 10 ms , f 1 10 s 40m * The bottom boundary layer affects on the wind drift current. Bottom 17 * Yoshikawa and Masuda (2009); Cushuman-Roisin (1994)

Wind in Summer Jul. 07 Aug. 07 Sept. 07 Jul. 08 Oct. 06 Oct. 07 18 The wind is weak, and its direction is unstable.

Wind in Winter Dec. 07 Jan. 07 Feb. 07 Feb. 08 Jan. 08 Dec. 06 The wind is strong, and its direction is stable. 19

Along-shore Current Evaluation Surface Current 1 Estimated Geocurrent 0.9 0.8 0.7 Velocity (m/s) ˆ 0.6   A   ˆ ˆ u u ( , ) W 0.5 g s 0.4 0.3 0.2 0.1 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 Along-shore current vs. sea level difference HF LSM 1 LSM 2 CEOF Monthly Mean Monthly Mean Monthly Mean Corre u s lation 0.710 0.757 0.759 0.785 0.774 0.763 0.768 20

Summary  Wind drift parameters calculated from 3 methods are roughly similar.  Annual-mean wind drift parameters are a simple and effective way to estimate wind drift current.  Wind drift current estimation is more obvious in winter, but weak in summer. 21

Main reference • Yoshikawa, Y. and A. Masuda (2009): Seasonal variations in the speed factor and deflection angle of the wind-driven surface flow in the Tsushima Strait. J. Geophys. Res. Oceans, 114, C12022, doi:10.1029/2009JC005632. • Cushuman-Roisin, B. (1994), Introduction to Geophysical Fluid Dynamics, 320 pp., Prentice-Hall, Englewood Cliffs, N. J. • Fukamachi, Y., K. I. Ohshima, N. Ebuchi, T. Bando, K. Ono, and M. Sano (2010): Volume Transport in the Soya Strait during 2006- 2008, Journal of Oceanography, 66 , 685-696. • Kundu, P. K., and J. S. Allen (1976), Some three-dimensional characteristics of low-frequency current fluctuations near the Oregon coast, J. Phys. Oceanogr., 6, 181 – 199. • Pedlosky, J. (1987), Geophysical Fluid Dynamics, 2nd ed., 710 pp., Springer, New York. • Yoshikawa, Y., et al. A surface velocity spiral observed with ADCP and HF radar in the Tsushima Strait. Journal of Geophysical Research: Oceans (1978 – 2012) 112.C6 (2007).

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Monthly Drift Parameters 120 LSM 1 LSM 1 0.03 LSM 2 LSM 2 100 CEOF CEOF 80 0.025 deflection angle (deg.) 60 0.02 speed factor 40 20 0.015 0 0.01 -20 -40 0.005 -60 0 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 time (month) time (month) 700 600 CEOF is a better way 500 number of data to estimate wind drift 400 300 parameter. 200 100 25 0 Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 time (month)

Annual-Mean Drift Parameter α ( × 10 -2 ) θ (deg.) (b) By annual-mean wind drift parameters LSM 1 0.1 LSM 2 LSM1 0.87 18 CEOF Velocity (m/s) 0.05 LSM2 1.39 34 Value CEOF 1.10 21 0 LSM1 1.64 78 -0.05 LSM2 2.60 77 -0.1 RMSE Nov/06 Feb/07 Jun/07 Sep/07 Dec/07 Apr/08 Jul/08 CEOF 1.93 98 Root-Mean-Square error with daily drift parameters 26

LSM 2 LSM1            ( , ) min( u ) min(( u u ) ( cos( err s g     ( , ) ( , )      ( , ) ( u u ) A ( , ) W u v err err s g 27 * Kundu and Allen (1976)

LSM 2    ( , ) min( ) u err   ( , )      ( , ) ( u u ) A ( , ) W u v err err s g 28 * Kundu and Allen (1976)

LSM1 & CEOF    ( , ) min[( , ) ] u v LSM1 err err   ( , )      ( , ) ( ) ( , ) u v u u A W err err s g       W W     1 st     ( , )   *CEOF CEOF      u u u     s g wd st 1   W U V * i 29 * Kundu and Allen (1976)