期刊名称：Tellus A: Dynamic Meteorology and Oceanography
电子版ISSN：1600-0870
出版年度：1999
卷号：51
期号：3
页码：412-430
DOI：10.3402/tellusa.v51i3.13468
摘要：In the World Ocean, densest waters found on the continental shelves induce density drivendownsloping currents that can influence the deep ocean water masses properties. This processis poorly represented in z-coordinate ocean models, especially in Ocean General CirculationModel (OGCM) with coarse resolution in both horizontal and vertical directions. Consequently,continental shelves appear to be too isolated from the open ocean, whereas the density remainstoo low in the deep ocean. This study presents a simple parameterization of downsloping flowdesigned for z-coordinate, coarse resolution ocean model. At the shelf break, when the densityon the shelf is higher than that in the neighbouring deep water column, a downsloping currentis set up. This current is linearly related to the horizontal density gradient between the twoadjacent boxes, using a prescribed coefficient. For simplicity, a uniform value of the coefficientis used here, although it should ideally vary in space. From the shelf, the downsloping flow isassumed to go downward along the slope until it reaches a level of equal density. An upwardreturn flow of equal magnitude maintains the conservation of mass. This parameterization hasbeen implemented in an OGCM and two experiments, with and without this scheme, have beenintegrated until equilibrium using restoring boundary conditions. The impact of the downslopingparameterization on the global ocean is dominated by the improvement of the Antarcticbottom water circulation and water mass properties. The parameterization increases the densityof the deep ocean and tends to reduce the intensity and depth of the North Atlantic deep watercirculation, which is in better agreement with observations. As a result of a higher exchangewith the open ocean, the properties of continental shelf waters are also improved, with a markedreduction of the Antarctic shelves salinities. Therefore, this simple parameterization leads to asignificant improvement of the model results, at little computational cost.
