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Quality and performance of a PM10 daily forecasting model

机译:PM10每日预测模型的质量和性能

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Particularly in the cold season unfavorable dissemination conditions of the ambient air lead to higher-than-average PM10 concentrations in parts of the western Alpe-Adria-Region, covering the provinces South Tyrol, Carinthia and Styria. Therefore, EU pollution standards cannot be met in the cold season and partial traffic regulation measures are taken in Bolzano, Klagenfurt and Graz, the three capitals in this region. Decision making for these regulations may be based on the average PM10 concentration of the next day provided that reliable forecasts of these values can be offered. In the present paper we show how multiple linear regression models combining information of the present day with meteorological forecasts of the next day can help forecasting daily PM10 concentrations for sites located in the three cities. Special emphasis is given to an appropriate selection of the regressor variables readily available as measured values, factors or meteorological forecasts suitable in operational mode. To reflect the quality of the forecast properly, we define a quality function where prediction errors near the threshold PM10 of 50μgm~(-3) are assumed to be more severe than errors in regions that are either far below or above the threshold. Since December 2004, the forecasts are used as a monitoring and information tool in Graz. Our daily forecasts have been carried out in cooperation with the meteorologists from the ZAMG Styria (Styrian meteorological office). The investigations in terms of the quality function and according possible decision rules show that our prediction models may support future decisions concerning possible traffic restrictions not only in Graz, but also in Bolzano and Klagenfurt.
机译:特别是在寒冷季节,环境空气的不利传播条件导致西部Alpe-Adria-Region部分地区的PM10浓度高于平均水平,覆盖了南蒂罗尔,克恩顿州和施蒂利亚州。因此,在寒冷季节无法达到欧盟的污染标准,并且在该地区的三个首都博尔扎诺,克拉根福和格拉茨采取了部分交通管制措施。这些法规的决策可以基于第二天的平均PM10浓度,前提是可以提供这些值的可靠预测。在本文中,我们展示了将今天的信息与第二天的气象预测结合起来的多重线性回归模型如何帮助预测位于三个城市的站点的每日PM10浓度。特别强调对回归变量的适当选择,这些变量很容易作为适合运行模式的测量值,因子或气象预报而获得。为了正确反映预测的质量,我们定义了一个质量函数,其中假设阈值PM10接近50μgm〜(-3)的预测误差比远低于或高于阈值的区域的误差严重得多。自2004年12月以来,预报已在格拉茨用作监视和信息工具。我们的日常预报是与ZAMG施蒂里亚州(Styrian气象局)的气象学家合作进行的。根据质量函数和可能的决策规则进行的调查表明,我们的预测模型不仅可以支持有关格拉茨,博尔扎诺和克拉根福的可能交通限制的未来决策。

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