大气numerical models中确定下边界条件的精度
On the accuracy with which the lower boundary conditions can be determined in numerical models of the atmosphere
摘要：
由于气候预测主要被认为是第二类预测，因此，评估这些边界条件的确定精度是必不可少的，以便我们能够找到一个合理的答案，即气候是否可以以足够的精度进行预测。因此，我们的贡献主要集中在准确性的感热和水蒸气，预测所需的数值模式的大气中使用的能量和水通量平衡方程的耦合设置，可以确定的通量。在地球表面附近的界面子层的参数化方案和充分湍流层以上提出和讨论的文件，存在相当程度的不确定性。结果表明，Monin-Obukhov相似律的通用功能，充分湍流大气表层的参数化方案的基础上所固有的很大的不确定性反映了相当大的分散在复杂的现场活动的结果。这种不确定性也影响了这些参数化方案中所用的水蒸气的梯度理查森数、湍流普朗特数Pr_t和湍流施密特数Sc_{t,q}（以及湍流刘易斯-谢苗诺夫数LS_{t,q}）的结果。有人认为，固有的不确定性使气候无法以足够的准确度进行预测。
英文摘要：
Since the prediction of climate is mainly considered as a prediction of second kind, it is indispensable to assess the accuracy with which these boundary conditions can be determined so that we can find a reasonable answer, whether climate is predictable with a sufficient degree of accuracy or not. Therefore, our contribution is mainly focused on the accuracy with which the fluxes of sensible heat and water vapor, required for predicting the lower boundary conditions in numerical models of the atmosphere using the coupled set of energy and water flux balance equations for the Earth's surface, can be determined. The parameterization schemes for the interfacial sublayer in the immediate vicinity of the Earth's surface and for the fully turbulent layer above presented and discussed here document that an appreciable degree of uncertainty exists. It is shown that the great uncertainty inherent in the universal functions of the Monin-Obukhov similarity laws on which the parameterization schemes for the fully turbulent atmospheric surface layer are based is reflected by the considerable scatter in the results of sophisticated field campaigns. This uncertainty affects also the results for the gradient-Richardson number, the turbulent Prandtl number, Pr_t, and the turbulent Schmidt number, Sc_{t,q}, (and the turbulent Lewis-Semenov number, LS_{t,q}) for water vapor used in such parameterization schemes. It is argued that the inherent uncertainty prevents that climate is predictable with a sufficient degree of accuracy.
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