Over the past quarter of a century a great deal of theoretical and empirical knowledge concerning atmospheric processes has been developed. Many models attempting to predict atmospheric dispersion effects have been devised, but few have endured, and thus far none has achieved universal applicability, although some have enjoyed widespread popularity. Perhaps among the reasons why most models were or are of limited operational utility is that they failed to adequately incorporate the fact that meteorological and geophysical phenomena are inherently stochastic in nature, and the behavior of such phenomena can be predicted only in statistical terms. Until recently, atmospheric transport models have tended to be deterministic in nature, using estimates of "average" or "worst case" values for computational elements, and have provided for little measure of the probability of occurrence of the predictions. The approach summarized in this paper describes an attempt to remedy that shortcoming, in that itexplicitly recognizes the inherent variability of these natural phenomena and attempts to incorporate that variability into a scheme which explicitly quantitates the uncertainty of prediction. It attempts to go a bit further than other approaches to evaluating environmental effects, in that it not only predicts effects but also allows evaluation of the likelihood of occurrence of the predictions.
在过去的25年中,已经开发了许多有关大气过程的理论和经验知识。已经设计出了许多试图预测大气弥散效应的模型,但是很少有人忍受,尽管到目前为止,有一些模型已经广为流行,但没有一个模型具有普遍适用性。多数模型之所以可用或使用有限的原因之一可能是它们没有充分考虑到气象和地球物理现象本质上是随机的这一事实,并且只能用统计术语来预测这种现象的行为。直到最近,大气传输模型在本质上已趋于确定性,使用计算元素的“平均”或“最坏情况”值的估计,并且几乎没有提供预测发生概率的度量。本文总结的方法描述了一种弥补该缺点的尝试,因为它可以明确地认识到这些自然现象的内在变异性,并试图将这种变异性纳入明确量化预测不确定性的方案中。它试图比其他方法来评估环境影响,因为它不仅可以预测影响,而且可以评估发生预测的可能性。 P>
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