Application of performance indicators based on observation uncertainty to evaluate a Europe-wide model simulation at urban scale

Abstract : In the frame of the European Consortium for Modeling of Air Pollution and Climate Strategies (EC4MACS) the CHIMERE chemistry transport model has been run over Europe for the entire year 2009 with a spatial resolution of 7 km with the aim of assessing the urban impact on daily exceedances of PM and NO2 in European cities. In order to better capture these urban impacts improvements on urban scale meteorology, vertical resolution and emissions have been implemented. In the current work an evaluation of the model results against the AIRBASE European monitoring network measurements is done using model performance indicators (MPC) based on observation uncertainty. The MPC used in this approach, constructed on the hypothesis that model results are allowed the same margin of uncertainty as measurements, are developed for four statistical indicators (Root Mean Square Error, Normalized Mean Bias, Normalized Mean Standard Deviation and correlation) to summarize the model-observation errors in terms of phase, amplitude and bias. The utility of this approach is to provide a performance scale to inform the user on the expected value an indicator should reach for a particular modeling application. These indicators are then used to identify the strengths and weaknesses of the model application in terms of geographical areas, cities, pollutants and/or period of the year.
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Communication dans un congrès
33. International Technical Meeting on Air Pollution Modelling and its Application (ITM 2013), Aug 2013, Miami, United States
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  • HAL Id : ineris-00973718, version 1
  • INERIS : EN-2013-447

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Philippe Thunis, Bertrand Bessagnet, Etienne Terrenoire, Augustin Colette. Application of performance indicators based on observation uncertainty to evaluate a Europe-wide model simulation at urban scale. 33. International Technical Meeting on Air Pollution Modelling and its Application (ITM 2013), Aug 2013, Miami, United States. 〈ineris-00973718〉

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