TOOL FOR EXPLORATORY ANALYSIS OF OSPM MODEL PERFORMANCE FOR LONG TIME SERIES

Abstract: The Danish Operational Street Pollution Model, OSPM, has for two decades been successfully applied in many cities worldwide as recently reviewed by Key words: model validation, street canyon, urban air pollution, OSPM, exploratory data analysis. INTRODUCTION The OSPM (Operational Street Pollution Model) has been evaluated and applied by a wide range of users worldwide (see: Kakosimos et al. 2010) for modelling urban air pollution at street level. Proper model validation protocols and best modelling practise have been discussed in the scientific community for many years, lately in the COST 732 action (URL 1) and in the Forum for Air quality Modelling in Europe (FAIRMODE, URL 2). A document produced by COST 732 provides general guidance on model evaluation protocols (Britter and Schatzmann, 2007). Model validation is also relevant in context of the European Air Quality Directive (EC, 2008) that is mentioning models as a method to assess air quality with respect to compliance with limit values. The directive defines some model quality objectives that are now interpreted and discussed within FAIRMODE, and performed tests have revealed some ambiguities in the interpretation of those objectives (e.g. Gidhagen at al. 2011). This paper aims at contributing to the discussion. Model quality objectives are in the directive as in other guidelines formulated in terms of quantitative statistical analysis, e.g. maximum uncertainty presented for the annual average or for percentiles. However this statistical analysis might obscure deficiencies of the model, and model results could be "right for the wrong reason", i.e. the model quality objective might be fulfilled even if the model fails to reproduce some essential features in observations. Therefore Di Sabatini et al. (2008) recommended for the case of CFD models a combination of qualitative (exploratory data analysis) and quantitative (statistical analysis) evaluations. The usefulness in identifying model errors by means of qualitative data analysis using an automated Excel workbook was presented by Olesen et al. (2008). This work focuses on the evaluation of OSPM and presents a similar approach suggesting a combined evaluation strategy of qualitative and quantitative analysis. Even though OSPM is a parameterised semi-empirical model with much simpler physics compared to the CFD models this evaluation strategy is applicable. This approach and the here presented Excel evaluation tool can easily be used also by other models of this type