Atmospheric tracer experiment uncertainties related to model evaluation
Atmospheric tracer experiment uncertainties related to model evaluation
复制标题
与模型评估相关的大气示踪剂实验不确定性
DOI：
10.1016/j.envsoft.2013.10.003
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
S. Castelli
中科院分区：
文献类型：
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作者：
D. Anfossi;S. Castelli
空气质量模型的验证和确认基于与示踪剂实验中收集的观测数据的比较。这项工作的目标是评估使用实际现场测量时可能影响模型评估和验证的典型错误。为此选择了 KATREX 数据集，因为两个不同的团队在同一地点的采样器上采样并分析了浓度，因此可以在相同的气象条件下提供独立的估计。示踪剂在两个不同的高度发射，因此四个数据集可用于分析。比较两个团队的观察结果，同样通过统计分析，发现平均误差为 22.5%，中位误差为 14%。然后考虑高斯和拉格朗日粒子模型的预测，研究这种不确定性对模型验证的影响。因此，模型的性能可以被认为是“好”或不好，取决于用于评估的数据集。
The verification and validation of air quality models is based on comparisons with observational data that can be collected in tracer experiments. The goal of this work is to assess the typical errors that can affect the model evaluation and validation when using real field measurements. The KATREX dataset was chosen for this purpose, since two different teams sampled and analysed concentrations at co-located samplers, therefore providing independent estimates in the same meteorological conditions. Tracers were emitted at two different heights, therefore four datasets are available for the analysis. Comparing the observations of the two teams, also through a statistical analysis, a mean error of 22.5% and a median error of 14% were found. The effect of this uncertainty in the validation of models was then investigated considering the predictions of a Gaussian and a Lagrangian particle models. It followed that the performances of the models could be considered ‘good’ or not depending on which dataset was used for the evaluation.
DOI：
10.1016/j.jmarsys.2008.03.011
发表时间：
2009-02
期刊：
Journal of marine systems : journal of the European Association of Marine Sciences and Techniques
影响因子：
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作者：
C. Stow;J. Jolliff;D. McGillicuddy;S. Doney;J. Icarus Allen;Marjorie A.M. Friedrichs;Kenneth A. Rose;P. Wallhead
通讯作者：
C. Stow;J. Jolliff;D. McGillicuddy;S. Doney;J. Icarus Allen;Marjorie A.M. Friedrichs;Kenneth A. Rose;P. Wallhead