Abstract
In this study we introduce a hybrid ensemble consisting of air quality models operating at both the global and regional scale. The work is motivated by the fact that these different types of models treat specific portions of the atmospheric spectrum with different levels of detail, and it is hypothesized that their combination can generate an ensemble that performs better than mono-scale ensembles. A detailed analysis of the hybrid ensemble is carried out in the attempt to investigate this hypothesis and determine the real benefit it produces compared to ensembles constructed from only global-scale or only regional-scale models. The study utilizes 13 regional and 7 global models participating in the Hemispheric Transport of Air Pollutants phase 2 (HTAP2)-Air Quality Model Evaluation International Initiative phase 3 (AQMEII3) activity and focuses on surface ozone concentrations over Europe for the year 2010. Observations from 405 monitoring rural stations are used for the evaluation of the ensemble performance. The analysis first compares the modelled and measured power spectra of all models and then assesses the properties of the mono-scale ensembles, particularly their level of redundancy, in order to inform the process of constructing the hybrid ensemble. This study has been conducted in the attempt to identify that the improvements obtained by the hybrid ensemble relative to the mono-scale ensembles can be attributed to its hybrid nature. The improvements are visible in a slight increase of the diversity (4 % for the hourly time series, 10 % for the daily maximum time series) and a smaller improvement of the accuracy compared to diversity. Root mean square error (RMSE) improved by 13-16 % compared to G and by 2-3 % compared to R. Probability of detection (POD) and false-alarm rate (FAR) show a remarkable improvement, with a steep increase in the largest POD values and smallest values of FAR across the concentration ranges. The results show that the optimal set is constructed from an equal number of global and regional models at only 15 % of the stations. This implies that for the majority of the cases the regional-scale set of models governs the ensemble. However given the high degree of redundancy that characterizes the regional-scale models, no further improvement could be expected in the ensemble performance by adding yet more regional models to it. Therefore the improvement obtained with the hybrid set can confidently be attributed to the different nature of the global models. The study strongly reaffirms the importance of an in-depth inspection of any ensemble of opportunity in order to extract the maximum amount of information and to have full control over the data used in the construction of the ensemble.
Highlights
In this study we introduce a hybrid ensemble consisting of air quality models operating at both the global and regional scale
The study utilizes 13 regional and 7 global models participating in the Hemispheric Transport of Air Pollutants phase 2 (HTAP2)– Air Quality Model Evaluation International Initiative phase 3 (AQMEII3) activity and focuses on surface ozone concentrations over Europe for the year 2010
Prior to analysing the performance of the different ensembles, we evaluate the individual models against the measurements using conventional statistics as well as the newly developed error apportionment analysis presented by Solazzo and Galmarini (2015)
Summary
It has been widely demonstrated (e.g. Potempsky and Galmarini, 2009) that, when multiple model results are distilled to retain only original and independent contributions (Solazzo et al, 2012a, b) and thereafter statistically combined in what is usually called an ensemble, one obtains results that are systematically superior to the performance of the individual models and can provide more accurate and robust assessments or predictions. Since in this study we are dealing with chemical transport models (CTMs), we should consider that chemical mechanisms span across a wide range of timescales This could constitute an element of diversity for these two groups of the models, the time resolutions for regional- and global-scale models are comparable. As presented in the past, the diversity of modelling approaches is the element that favours a better ensemble product (Kioutsioukis and Galmarini, 2014; Kioutsioukis et al, 2016) In this sense the combination of model results that focus on different scales and that account in a different form for the chemical mechanism has the potential to increase the value of an ensemble to which we will refer on as the hybrid ensemble.
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