摘要: |
深层叶绿素最大值(Deep Chlorophyll Maximum,DCM)现象的数值模拟是研究海洋表层生态系统和全球碳循环的重要组成部分之一。但是由于自身的复杂性和观测的局限性,数值模式中物理参数的不确定性给模拟结果带来了一定程度的误差。其中,垂向湍流扩散(vertical turbulence diffusion)系数就是模式所包含的物理参数中很难直接通过观测来确定的参数,它在模式中的来源和取值往往具有很大的不确定性。本文通过条件非线性最优(参数)扰动(CNOP-P)方法,研究了垂向湍流扩散系数的不确定性对模式模拟结果的影响。我们发现垂向湍流扩散系数对整个水柱的浮游植物生物量和DCM的模拟产生最大影响的CNOP型扰动位于生产力层的上半部分。并且,去掉生产力层内湍流扩散系数的误差,模式模拟的改进程度最高达到了80%。可见,垂向湍流扩散对生态系统的发展和保持起着极其重要的作用,改进垂向湍流扩散系数的不确定性,对DCM的数值模拟有着重要意义。 |
关键词: 物理参数 湍流扩散系数 不确定性 条件非线性最优扰动(CNOP) |
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The study of the uncertainty related to the coefficients of vertical turbulence diffusion in an ocean ecosystem model |
Gao YongLi
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Institute of Ocenology, Chinese Academy of Sciences
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Abstract: |
The simulation of deep chlorophyll maximum (DCM) is one of the most important parts in the study of the ocean surface ecosystem and the global carbon cycle. But the physical parameters in the numerical model usually bring various errors to the output results because the complex of themselves and the scare observation. The coefficient of vertical turbulence diffusion among the physical parameters is hard to be decided by the observation directly, so it always has very large uncertainty in the model. This paper studied the influence of the turbulence diffusion to the output results in the numerical model by the Conditional Nonlinear Optimal Perturbation Method (Related to Parameters). We find that the strongest perturbation of the vertical turbulence diffusion occurred in the productivity layer. And we prove that the improvement of the model outputs is quite evident after taking off the perturbation of the vertical turbulence diffusion in the productivity layer. It illustrates that the physical condition is very important for the development and maintain of the ocean ecosystem model. |
Key words: vertical turbulence diffusion physical parameters uncertainty CNOP |