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Wind-SST Coupling in the Coastal Upwelling --- An Empirical Numerical Simulation X. Jin, C. Dong, and J. C. McWilliams (IGPP/UCLA) D. B. Chelton (COAS/OSU)

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Presentation on theme: "Wind-SST Coupling in the Coastal Upwelling --- An Empirical Numerical Simulation X. Jin, C. Dong, and J. C. McWilliams (IGPP/UCLA) D. B. Chelton (COAS/OSU)"— Presentation transcript:

1 Wind-SST Coupling in the Coastal Upwelling --- An Empirical Numerical Simulation X. Jin, C. Dong, and J. C. McWilliams (IGPP/UCLA) D. B. Chelton (COAS/OSU) Thanks: Z. Li (JPL)

2 OUTLINE Introduction Methods Results Conclusions and Outlook

3 Introduction Observations  Significant coupling between SST and wind stress: –CCS, (Chelton et al., 2007) –Southern Ocean, (O’Neill et al., 2003) –East Tropical Pacific (Wallace et al., 1989; Chelton et al., 2001) Coupling: SST----  Wind stress--  SST

4 SST and wind stress fields for an example 29-day averages of QuikSCAT wind stress : (left) AMSR-E estimates of SST with wind stress vectors overlaid, (middle) wind stress curl with contours of crosswind SST gradient, and (right) wind stress divergence with contours of downwind SST gradient. the contours are the magnitude of the vector-average wind stress with a contour interval of 0.03 N m−2, and the heavy contour corresponds to 0.12 N m−2. The contour interval for the SST gradient components in the middle and right panels is 0.5°C (100 km)−1 (Chelton et al., 2007)

5 Maps of the correlations (left) between the wind stress curl and the crosswind SST gradient and (right) between the wind stress divergence and the downwind SST gradient computed from summertime 29-day averages (Chelton et al., 2007).

6 Chelton et al, 2007

7 Mechanisms for the coupling SST--  Wind stress: – Cold—decrease, and Warm—increase (Wallace et al. 1989; Chelton et al. 2001) Wind stress ----SST: – SST was reduced (Coupled modeling, Perlin et al., 2007)

8 Objective We take the advantage of empirical relationship between the SST gradient and wind stress in place of a dynamical atmosphere and couple it to a regional oceanic numerical model to examine the coupling effect.

9 Empirical Coupling Model ROMS Model Wind Stress SST

10 Empirical Relationship (Chelton et al.)

11 Basis for Empirical Coupling Model Helmholtz decomposition Poisson equations Within a closed domain, is uniquely determined by solving the Poisson equations (Li et al. (2006)

12 ROMS Model Domain: 120 km west-east, 240 km north-south, and depth 500 m Uniform wind stress: 0.1 N/m2, equatorward constantly Open boundaries: Flather condition Temp: A typical vertical temperature profile, uniform Salinity: constant (35.00 PSU) Grid size: horizontal 1 km, vertical 30 levels with theta_s =5.0 and theta_b=0

13 Experiments Uncoupled simulation: initial condition:rest Coupled simulation: –Initial condition :rest

14 SST in the uncoupled simulation at day 20

15 Cross-shore vertical section averaged along shore: SST; along-shore current (cm/s); u (cm/s). Uncoupled

16 SST time series: from day 50 to day 57 with interval of 30 hours

17

18 Along-shore averaged wind stress in coupled simulations on different days. The background wind stress is - 0.1 N/m2

19 The distributions of wind stress changes simulated in the coupled model on day 20 (unit: N/m2)

20 Simulated SST distributions. Left, uncoupled; middle, coupled; right, the differences. Note: the colorbar for uncoupled and coupled simulations are different.

21 Cross-shore vertical section of T on day 20, averaged alongshore.

22 Along-shore velocity (cm/s) on day 20

23 Cross-shore velocity (cm/s) on day 20

24 Time variations of the kinetic energy averaged over the model surface (u^2+v^2)/2

25 Time variations of the averaged over the model surface.

26 Conclusions and Further work SST gradients induce substantial wind stress changes Large impacts on ocean circulations by increasing SST near the coast and moving SST front westenly. Improving uncoupled model Further analyses Impacts on meso- and submeso- scale dynamics


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