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Observations and Modelling of Fronts and Frontogenesis

Observations and Modelling of Fronts and Frontogenesis

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APPENDIX B: NUMERICAL METHOD<br />

The equations solved numerically were (28), (30), <strong>and</strong><br />

(33), with the boundary conditions (17) <strong>and</strong> the matching<br />

conditions (20),(23), <strong>and</strong> (29) when appropriate, along with<br />

the evaluations (32) <strong>and</strong> (34). The initial data (27) were<br />

given on a grid <strong>of</strong> 150 points, logarithmically spaced for<br />

small y <strong>and</strong> linearly spaced for large y. Upper layer<br />

characteristics were followed continuously, with new points<br />

added both adjacent to the boundary <strong>and</strong> in the interior when<br />

divergence in the mixed layer separated grid points. De<br />

Szoeke <strong>and</strong> Richman (1984) successfully integrated the<br />

interior layer potential vorticity "backward" (with respect<br />

to the interior layer characteristic curves) along the mixed<br />

layer characteristic curves. It was necessary to maintain<br />

accuracy over longer time scales in the present study, so<br />

this approach was ab<strong>and</strong>oned in favor <strong>of</strong> integrating the<br />

interior layer variables along their appropriate<br />

characteristic curves. Because grid points moved at<br />

different speeds <strong>and</strong> in different directions along the<br />

characteristic curves in the different layers, the values <strong>of</strong><br />

the interior layer variables were interpolated onto the layer<br />

1 grid for solution <strong>of</strong> the diagnostic equations (28), <strong>and</strong> the<br />

resulting interior velocities v2 <strong>and</strong> v3 interpolated back<br />

onto the interior layer grids for time-stepping. A local<br />

quadratic interpolation proved sufficient to maintain

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