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Two-scale multi-model ensemble : is a hybrid ensemble of opportunity telling us more ?

Stefano Galmarini 1 Ioannis Kioutsioukis 2 Efisio Solazzo 1 Ummugulsum Alyuz Alessandra Balzarini 3 Roberto Bellasio Anna M. K. Benedictow 4 Roberto Bianconi Johannes Bieser Jorgen Brandt 5 Jesper H. Christensen 5 Augustin Colette 6 Gabriele Curci Yanko Davila 4 Xinyi Dong 7 Johannes Flemming Xavier V. Francis Andrea Fraser Joshua Fu 7 Daven K. Henze Christian Hogrefe Ulas Im 5 Marta G. Vivanco 8 Pedro Jimenez-Guerrero 9 Jan Eiof Jonson 4 Nutthida Kitwiroon 10 Astrid Manders 11 Rohit Mathur Laura Palacios-Pena 9 Guido Pirovano 3 Luca Pozzoli 1 Marje Prank 12 Martin G. Schultz 4 Ranjeet S. Sokhi Kengo Sudo Paolo Tuccella Toshihiko Takemura 13 Takashi Sekiya Alper Unal
1 IES - JRC Institute for Environment and Sustainability
2 Department of Physics [Patras]
3 RSE - Ricerca sul Sistema Energetico
4 MET - Norwegian Meteorological Institute [Oslo]
5 ENVS - Department of Environmental Science [Roskilde]
6 INERIS - Institut National de l'Environnement Industriel et des Risques
7 The University of Tennessee [Knoxville]
8 CIEMAT - Centro de Investigaciones Energéticas Medioambientales y Tecnológicas [Madrid]
9 Universidad de Murcia
10 King‘s College London
11 TNO - The Netherlands Organisation for Applied Scientific Research
12 FMI - Finnish Meteorological Institute
13 Kyushu University [Fukuoka]
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.
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Stefano Galmarini, Ioannis Kioutsioukis, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, et al.. Two-scale multi-model ensemble : is a hybrid ensemble of opportunity telling us more ?. Atmospheric Chemistry and Physics, European Geosciences Union, 2018, 18, pp.8727-8744. ⟨10.5194/acp-18-8727-2018⟩. ⟨ineris-01863342⟩

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