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contribution to Ekman pumping, as discussed previously. 7. Attenuation of eddies as a result of Ekman pumping The different contributions to the total current-induced Ekman pumping [ (10) ] influence the structure and kinematics of eddies in various ways. SST-induced Ekman pumping disrupts the approximate axisymmetric structure of eddies, thus tending to attenuate the eddies ( Jin et al. 2009 ). The surface current vorticity gradient contribution W ζ generates asymmetric dipoles of Ekman upwelling and
contribution to Ekman pumping, as discussed previously. 7. Attenuation of eddies as a result of Ekman pumping The different contributions to the total current-induced Ekman pumping [ (10) ] influence the structure and kinematics of eddies in various ways. SST-induced Ekman pumping disrupts the approximate axisymmetric structure of eddies, thus tending to attenuate the eddies ( Jin et al. 2009 ). The surface current vorticity gradient contribution W ζ generates asymmetric dipoles of Ekman upwelling and
. An important aspect in Fig. 8 is that the stress divergence term causes upwelling where ice concentration is small. The upwelling amplifies the internal waves that propagate along with the ice band. Then, the velocity field associated with the internal wave in turn aggregates ice and enhances the ice-band formation as in Fig. 8 . This is similar to a kinematic explanation of hydrodynamic instability such as the Kelvin–Helmholtz instability (e.g., Baines and Mitsudera 1994 ). Note that the
. An important aspect in Fig. 8 is that the stress divergence term causes upwelling where ice concentration is small. The upwelling amplifies the internal waves that propagate along with the ice band. Then, the velocity field associated with the internal wave in turn aggregates ice and enhances the ice-band formation as in Fig. 8 . This is similar to a kinematic explanation of hydrodynamic instability such as the Kelvin–Helmholtz instability (e.g., Baines and Mitsudera 1994 ). Note that the
−2 ) in CNTL (black contours) and their difference with SMTH (color shading) over the third day of the case study. The gray contours represent CNTL SST (every 2 K). To relate the change of moist entropy to the turbulent heat fluxes, we compute 2D (i.e., horizontal motion in the boundary layer) backward trajectories of parcels from the cold sector. Trajectories are found by solving the kinematic equation. We use a first-order finite difference to discretize the time derivative. The trajectory of
−2 ) in CNTL (black contours) and their difference with SMTH (color shading) over the third day of the case study. The gray contours represent CNTL SST (every 2 K). To relate the change of moist entropy to the turbulent heat fluxes, we compute 2D (i.e., horizontal motion in the boundary layer) backward trajectories of parcels from the cold sector. Trajectories are found by solving the kinematic equation. We use a first-order finite difference to discretize the time derivative. The trajectory of
gradients in observations ( Chelton and Xie 2010 ) and in high-resolution numerical models ( Seo et al. 2007 ; Song et al. 2009 ; Bryan et al. 2010 ). Kinematically, this results from gradients of the frontally induced surface stress direction that diminish the wind stress curl but enhance the wind stress divergence ( O’Neill et al. 2010a ). Here, we seek to dynamically explain these observations using a linearized model for the atmospheric boundary layer that includes advection by background Ekman
gradients in observations ( Chelton and Xie 2010 ) and in high-resolution numerical models ( Seo et al. 2007 ; Song et al. 2009 ; Bryan et al. 2010 ). Kinematically, this results from gradients of the frontally induced surface stress direction that diminish the wind stress curl but enhance the wind stress divergence ( O’Neill et al. 2010a ). Here, we seek to dynamically explain these observations using a linearized model for the atmospheric boundary layer that includes advection by background Ekman
