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A suggested method for dispersion model evaluation

机译:色散模型评估的建议方法

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摘要

Too often operational atmospheric dispersion models are evaluated in their ability to replicate short-term concentration maxima, when in fact a valid model evaluation procedure would evaluate a model's ability to replicate ensemble-average patterns in hourly concentration values. A valid model evaluation includes two basic tasks: In Step 1 we should analyze the observations to provide average patterns for comparison with modeled patterns, and in Step 2 we should account for the uncertainties inherent in Step 1 so we can tell whether differences seen in a comparison of performance of several models are statistically significant. Using comparisons of model simulation results from AERMOD and ISCST3 with tracer concentration values collected during the EPRI Kincaid experiment, a candidate model evaluation procedure is demonstrated that assesses whether a model has the correct total mass at the receptor level (crosswind integrated concentration values) and whether a model is correctly spreading the mass laterally (lateral dispersion), and assesses the uncertainty in characterizing the transport. The use of the BOOT software (preferably using the ASTMD 6589 resampling procedure) is suggested to provide an objective assessment of whether differences in model performance between models are significant.
机译:经常评估大气弥散模型在复制短期浓度最大值时的能力,而实际上,有效的模型评估程序会以小时浓度值评估模型复制整体平均模式的能力。有效的模型评估包括两个基本任务:在步骤1中,我们应分析观察值以提供平均模式,以便与建模模式进行比较;在步骤2中,我们应考虑步骤1中固有的不确定性,以便我们可以判断是否存在差异。几个模型的性能比较在统计上是显着的。通过将AERMOD和ISCST3的模型仿真结果与EPRI Kincaid实验期间收集的示踪剂浓度值进行比较,证明了候选模型评估程序可评估模型在受体水平上是否具有正确的总质量(侧风积分浓度值)以及是否模型正确地将质量横向扩散(横向分散),并评估表征运输的不确定性。建议使用BOOT软件(最好使用ASTMD 6589重采样程序)来客观评估模型之间的模型性能差异是否重大。

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