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This discretisation requires extra prognostic vorticity variables on the boundary in addition to the prognostic velocity and layer depth variables.
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The distinct features of the presented semi-Lagrangian model are the use of vorticity and divergence as prognostic variables in conjunction with the fourth-order compact finite differences on the unstaggered regular latitude longitude grid.
The global estimation of flow velocity vector fields across the whole image provides useful information on vorticity which defines the vortices within regions of a relevant pathology.
Peak vorticity of starting and stopping vortices are 26 s−1 and 5 s−1, respectively.
Manipulation of (1a)–(1c) yields a prognostic equation for the linearized version of Ertel's potential vorticity (hereafter EPV and symbolized as q ∗) to read begin{array}rcl@ frac{partial}{partial t^ Big underbrace{ frac{partial v^{partial x^- frac{partial u^{partial y^ - frac{f^{{c^^{2}} p^_{equiv q^ Big) + v^ beta^ = 0, end{array} (2).
Both formulations have velocity and layer depth as prognostic variables, but the exterior calculus framework leads to a conserved diagnostic potential vorticity.
In addition to this approach, we are able to characterize vortices in heart chambers and establish a relationship between atrial vorticity and a septal defect.
The global estimation of vorticity fields also provides useful information such as formation and evolution of vortices within heart chambers.
Temporal averaging of the ensemble vorticity means based on four or more selected time frames (when the vortices are the strongest) is performed.
This does not mean we should ignore prognostic information.
How can we work fighting spirit into our prognostic algorithms.
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