Articles | Volume 16, issue 24
https://doi.org/10.5194/acp-16-15629-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-15629-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
20 Dec 2016
Research article |
| 20 Dec 2016
Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data
Ioannis Kioutsioukis
University of Patras, Department of Physics, University Campus 26504 Rio, Patras, Greece
European Commission, Joint Research Centre, Directorate for Energy, Transport and Climate, Air and Climate Unit, Ispra (VA), Italy
Aarhus University, Department of Environmental Science, Roskilde, Denmark
Efisio Solazzo
European Commission, Joint Research Centre, Directorate for Energy, Transport and Climate, Air and Climate Unit, Ispra (VA), Italy
Roberto Bianconi
Enviroware srl, Concorezzo (MB), Italy
Alba Badia
Earth Sciences Department, Barcelona Supercomputing Center (BSC-CNS), Barcelona, Spain
Alessandra Balzarini
Ricerca sul Sistema Energetico (RSE) SpA, Milan, Italy
Rocío Baró
University of Murcia, Department of Physics, Physics of the Earth, Campus de Espinardo, Ed. CIOyN, 30100 Murcia, Spain
Roberto Bellasio
Enviroware srl, Concorezzo (MB), Italy
Dominik Brunner
Laboratory for Air Pollution and Environmental Technology, Empa, Dubendorf, Switzerland
Charles Chemel
Centre for Atmospheric & Instrumentation Research, University of Hertfordshire, College Lane, Hatfield, AL10 9AB, UK
Gabriele Curci
Department of Physical and Chemical Sciences, University of L'Aquila, L'Aquila, Italy
Center of Excellence for the forecast of Severe Weather (CETEMPS), University of L'Aquila, L'Aquila, Italy
Hugo Denier van der Gon
Netherlands Organization for Applied Scientific Research (TNO), Utrecht, the Netherlands
Johannes Flemming
ECMWF, Shinfield Park, Reading, RG2 9AX, UK
Renate Forkel
Karlsruher Institut für Technologie (KIT), IMK-IFU, Kreuzeckbahnstr. 19, 82467 Garmisch-Partenkirchen, Germany
Lea Giordano
Laboratory for Air Pollution and Environmental Technology, Empa, Dubendorf, Switzerland
Pedro Jiménez-Guerrero
University of Murcia, Department of Physics, Physics of the Earth, Campus de Espinardo, Ed. CIOyN, 30100 Murcia, Spain
Marcus Hirtl
Zentralanstalt für Meteorologie und Geodynamik, ZAMG, 1190 Vienna, Austria
Oriol Jorba
Earth Sciences Department, Barcelona Supercomputing Center (BSC-CNS), Barcelona, Spain
Astrid Manders-Groot
Netherlands Organization for Applied Scientific Research (TNO), Utrecht, the Netherlands
Lucy Neal
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Juan L. Pérez
Environmental Software and Modelling Group, Computer Science School – Technical University of Madrid, Campus de Montegancedo – Boadilla del Monte, 28660 Madrid, Spain
Guidio Pirovano
Ricerca sul Sistema Energetico (RSE) SpA, Milan, Italy
Roberto San Jose
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Nicholas Savage
Zentralanstalt für Meteorologie und Geodynamik, ZAMG, 1190 Vienna, Austria
Wolfram Schroder
Leibniz Institute for Tropospheric Research, Permoserstr. 15, 04318 Leipzig, Germany
Ranjeet S. Sokhi
Centre for Atmospheric & Instrumentation Research, University of Hertfordshire, College Lane, Hatfield, AL10 9AB, UK
Dimiter Syrakov
National Institute of Meteorology and Hydrology, Bulgarian Academy of Sciences, 66 Tzarigradsko shaussee Blvd., 1784 Sofia, Bulgaria
Paolo Tuccella
Department of Physical and Chemical Sciences, University of L'Aquila, L'Aquila, Italy
Center of Excellence for the forecast of Severe Weather (CETEMPS), University of L'Aquila, L'Aquila, Italy
Johannes Werhahn
Karlsruher Institut für Technologie (KIT), IMK-IFU, Kreuzeckbahnstr. 19, 82467 Garmisch-Partenkirchen, Germany
Ralf Wolke
Leibniz Institute for Tropospheric Research, Permoserstr. 15, 04318 Leipzig, Germany
Christian Hogrefe
Atmospheric Modelling and Analysis Division, Environmental Protection Agency, Research, Triangle Park, USA
Stefano Galmarini
CORRESPONDING AUTHOR
European Commission, Joint Research Centre, Directorate for Energy, Transport and Climate, Air and Climate Unit, Ispra (VA), Italy
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Cited
16 citations as recorded by crossref.
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- Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown E. Solazzo et al. 10.5194/acp-17-3001-2017
- Forecasting Particulate Pollution in an Urban Area: From Copernicus to Sub-Km Scale A. Pappa & I. Kioutsioukis 10.3390/atmos12070881
- Two-scale multi-model ensemble: is a hybrid ensemble of opportunity telling us more? S. Galmarini et al. 10.5194/acp-18-8727-2018
- Improving Air Quality Predictions over the United States with an Analog Ensemble L. Delle Monache et al. 10.1175/WAF-D-19-0148.1
- Analog versus multi-model ensemble forecasting: A comparison for renewable energy resources A. Pappa et al. 10.1016/j.renene.2023.01.030
- Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework E. Solazzo et al. 10.5194/acp-17-10435-2017
- Advances in air quality research – current and emerging challenges R. Sokhi et al. 10.5194/acp-22-4615-2022
- Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3 U. Im et al. 10.5194/acp-18-8929-2018
- Seasonal ozone vertical profiles over North America using the AQMEII3 group of air quality models: model inter-comparison and stratospheric intrusions M. Astitha et al. 10.5194/acp-18-13925-2018
- Application of linear minimum variance estimation to the multi-model ensemble of atmospheric radioactive Cs-137 with observations D. Goto et al. 10.5194/acp-20-3589-2020
- Regional effects of atmospheric aerosols on temperature: an evaluation of an ensemble of online coupled models R. Baró et al. 10.5194/acp-17-9677-2017
- Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3 U. Im et al. 10.5194/acp-18-5967-2018
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16 citations as recorded by crossref.
- Analog ensemble technique to post-process WRF-CAMx ozone and particulate matter forecasts E. Solomou et al. 10.1016/j.atmosenv.2021.118439
- Air pollution emission inventory using national high-resolution spatial parameters for the Nordic countries and analysis of PM2.5 spatial distribution for road transport and machinery and off-road sectors V. Paunu et al. 10.5194/essd-16-1453-2024
- Ensemble-Based Forecast of Volcanic Clouds Using FALL3D-8.1 A. Folch et al. 10.3389/feart.2021.741841
- Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown E. Solazzo et al. 10.5194/acp-17-3001-2017
- Forecasting Particulate Pollution in an Urban Area: From Copernicus to Sub-Km Scale A. Pappa & I. Kioutsioukis 10.3390/atmos12070881
- Two-scale multi-model ensemble: is a hybrid ensemble of opportunity telling us more? S. Galmarini et al. 10.5194/acp-18-8727-2018
- Improving Air Quality Predictions over the United States with an Analog Ensemble L. Delle Monache et al. 10.1175/WAF-D-19-0148.1
- Analog versus multi-model ensemble forecasting: A comparison for renewable energy resources A. Pappa et al. 10.1016/j.renene.2023.01.030
- Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework E. Solazzo et al. 10.5194/acp-17-10435-2017
- Advances in air quality research – current and emerging challenges R. Sokhi et al. 10.5194/acp-22-4615-2022
- Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3 U. Im et al. 10.5194/acp-18-8929-2018
- Seasonal ozone vertical profiles over North America using the AQMEII3 group of air quality models: model inter-comparison and stratospheric intrusions M. Astitha et al. 10.5194/acp-18-13925-2018
- Application of linear minimum variance estimation to the multi-model ensemble of atmospheric radioactive Cs-137 with observations D. Goto et al. 10.5194/acp-20-3589-2020
- Regional effects of atmospheric aerosols on temperature: an evaluation of an ensemble of online coupled models R. Baró et al. 10.5194/acp-17-9677-2017
- Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3 U. Im et al. 10.5194/acp-18-5967-2018
- Evaluation and uncertainty estimation of the impact of air quality modelling on crop yields and premature deaths using a multi-model ensemble E. Solazzo et al. 10.1016/j.scitotenv.2018.03.317
Latest update: 18 Apr 2024
Short summary
Four ensemble methods are applied to two annual AQMEII datasets and their performance is compared for O3, NO2 and PM10. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill at each station over the single models and the ensemble mean. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way.
Four ensemble methods are applied to two annual AQMEII datasets and their performance is...
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