Super-parameterization in ocean modeling: Application to deep convection
Super-parameterization in ocean modeling: Application to deep convection
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DOI：
10.1016/j.ocemod.2010.10.003
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发表时间：
2011-01-01
期刊：
影响因子：
3.2
通讯作者：
Marshall, John
中科院分区：
文献类型：
--
作者：
Campin, Jean-Michel;Hill, Chris;Marshall, John
我们探讨了“超级参数化”（SP）在海洋建模中的功效，其中将局部二-D非静态羽流羽流（FG）模型嵌入在粗粒（CG）静水模型的每个垂直柱中。描述了一种一般的多尺度算法，其中FG模型的趋势投影到CG模型上，进而将FG模型的平均状态限制为将两个模型耦合在一起。该方法在开放海洋深对流模型的背景下进行了测试，并与使用对流调整（HYD）和完整的3-D非静态羽状羽流仿真（NH）相比，与纯静水，粗分辨率模型进行了比较。发现SP模型的计算成本要比完全非静态计算的计算成本要低得多。 （c）2010 Elsevier Ltd.保留所有权利。
We explore the efficacy of "super parameterization" (SP) in ocean modeling in which local 2-d non-hydrostatic plume-resolving fine-grained (FG) models are embedded at each vertical column of a coarse-grained (CG) hydrostatic model. A general multi-scale algorithm is described in which tendencies from the FG models are projected onto the CG model which in turn constrains the average state of the FG models, coupling the two models together. The approach is tested in the context of models of open ocean deep convection and compared with a pure hydrostatic, coarse resolution model using convective adjustment (HYD) and a full 3-d non-hydrostatic plume-resolving simulation (NH). The SP model is found to be greatly superior to HYD at much less computational cost than the fully non-hydrostatic calculation. (C) 2010 Elsevier Ltd. All rights reserved.