Articles | Volume 12, issue 3
https://doi.org/10.5194/gmd-12-1241-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-1241-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
02 Apr 2019
Model evaluation paper |
| 02 Apr 2019
| 02 Apr 2019
Ensemble forecasts of air quality in eastern China – Part 2: Evaluation of the MarcoPolo–Panda prediction system, version 1
Anna Katinka Petersen
CORRESPONDING AUTHOR
Max Planck Institute for Meteorology, Hamburg, Germany
Guy P. Brasseur
Max Planck Institute for Meteorology, Hamburg, Germany
National Center for Atmospheric Research, Boulder, CO, USA
Idir Bouarar
Max Planck Institute for Meteorology, Hamburg, Germany
Johannes Flemming
European Centre for Medium-Range Weather Forecasts, Reading, UK
Michael Gauss
Norwegian Meteorological Institute, Oslo, Norway
Fei Jiang
Nanjing University, Nanjing, China
Rostislav Kouznetsov
Finnish Meteorological Institute, Helsinki, Finland
Richard Kranenburg
TNO, Utrecht, the Netherlands
Bas Mijling
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Vincent-Henri Peuch
European Centre for Medium-Range Weather Forecasts, Reading, UK
Matthieu Pommier
Norwegian Meteorological Institute, Oslo, Norway
Arjo Segers
TNO, Utrecht, the Netherlands
Mikhail Sofiev
Finnish Meteorological Institute, Helsinki, Finland
Renske Timmermans
TNO, Utrecht, the Netherlands
Ronald van der A
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Nanjing University of Information Science and Technology, Nanjing, China
Stacy Walters
National Center for Atmospheric Research, Boulder, CO, USA
Ying Xie
Shanghai Meteorological Service, Shanghai, China
Jianming Xu
Shanghai Meteorological Service, Shanghai, China
Guangqiang Zhou
Shanghai Meteorological Service, Shanghai, China
Viewed
Total article views: 3,464 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Oct 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,320 | 1,048 | 96 | 3,464 | 72 | 65 |
- HTML: 2,320
- PDF: 1,048
- XML: 96
- Total: 3,464
- BibTeX: 72
- EndNote: 65
Total article views: 2,533 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 02 Apr 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,961 | 508 | 64 | 2,533 | 57 | 52 |
- HTML: 1,961
- PDF: 508
- XML: 64
- Total: 2,533
- BibTeX: 57
- EndNote: 52
Total article views: 931 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Oct 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 359 | 540 | 32 | 931 | 15 | 13 |
- HTML: 359
- PDF: 540
- XML: 32
- Total: 931
- BibTeX: 15
- EndNote: 13
Viewed (geographical distribution)
Total article views: 3,464 (including HTML, PDF, and XML)
Thereof 3,101 with geography defined
and 363 with unknown origin.
Total article views: 2,533 (including HTML, PDF, and XML)
Thereof 2,248 with geography defined
and 285 with unknown origin.
Total article views: 931 (including HTML, PDF, and XML)
Thereof 853 with geography defined
and 78 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
27 citations as recorded by crossref.
- Machine learning for observation bias correction with application to dust storm data assimilation J. Jin et al. 10.5194/acp-19-10009-2019
- Fires as a source of annual ambient PM2.5 exposure and chronic health impacts in Europe S. Chowdhury et al. 10.1016/j.scitotenv.2024.171314
- Contrasting chemical environments in summertime for atmospheric ozone across major Chinese industrial regions: the effectiveness of emission control strategies Z. Liu et al. 10.5194/acp-21-10689-2021
- The effect of accounting for public holidays on the skills of the atmospheric composition model SILAM v.5.7 Y. Fatahi et al. 10.5194/gmd-14-7459-2021
- Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution W. Wu et al. 10.1021/acs.est.3c09122
- Chemistry‐Weather Interacted Model System GRAPES_Meso5.1/CUACE CW V1.0: Development, Evaluation and Application in Better Haze/Fog Prediction in China H. Wang et al. 10.1029/2022MS003222
- Synergy of Using Nadir and Limb Instruments for Tropospheric Ozone Monitoring (SUNLIT) V. Sofieva et al. 10.5194/amt-15-3193-2022
- Advances in air quality modeling and forecasting A. Baklanov & Y. Zhang 10.1016/j.glt.2020.11.001
- Modelling of the public health costs of fine particulate matter and results for Finland in 2015 J. Kukkonen et al. 10.5194/acp-20-9371-2020
- NOx Emissions Reduction and Rebound in China Due to the COVID‐19 Crisis J. Ding et al. 10.1029/2020GL089912
- Intercomparison of Air Quality Models in a Megacity: Toward an Operational Ensemble Forecasting System for São Paulo A. Deroubaix et al. 10.1029/2022JD038179
- Bioaerosols in the atmosphere at two sites in Northern Europe in spring 2021: Outline of an experimental campaign M. Sofiev et al. 10.1016/j.envres.2022.113798
- Real-time numerical source apportionment of PM2.5 concentrations over the Yangtze River Delta region, China G. Zhou et al. 10.1016/j.atmosenv.2020.118104
- Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields M. Sofiev et al. 10.1016/j.scitotenv.2023.165800
- Tree-ring N isotopic ratio increased with increasing latitude and decreasing N availability in pine stands across Finland A. Smolander et al. 10.1016/j.ecolind.2023.110604
- Do atmospheric events explain the arrival of an invasive ladybird (Harmonia axyridis) in the UK? P. Siljamo et al. 10.1371/journal.pone.0219335
- Seasonal Characteristics of Forecasting Uncertainties in Surface PM2.5 Concentration Associated with Forecast Lead Time over the Beijing-Tianjin-Hebei Region Q. Du et al. 10.1007/s00376-023-3060-3
- Snow Samples Combined With Long-Range Transport Modeling to Reveal the Origin and Temporal Variability of Black Carbon in Seasonal Snow in Sodankylä (67°N) O. Meinander et al. 10.3389/feart.2020.00153
- Development and Evaluation of a North America Ensemble Wildfire Air Quality Forecast: Initial Application to the 2020 Western United States “Gigafire” P. Makkaroon et al. 10.1029/2022JD037298
- A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS) R. Kumar et al. 10.1029/2020JD032554
- Optimization research on air quality numerical model forecasting effects based on deep learning methods W. Wang et al. 10.1016/j.atmosres.2022.106082
- An inter-comparative evaluation of PKU-FUEL global SO2 emission inventory J. Luo et al. 10.1016/j.scitotenv.2020.137755
- Mitigated PM2.5Changes by the Regional Transport During the COVID‐19 Lockdown in Shanghai, China Y. Gu et al. 10.1029/2021GL092395
- Deep Learning‐Based Ensemble Forecasts and Predictability Assessments for Surface Ozone Pollution A. Zhang et al. 10.1029/2022GL102611
- Shipping and algae emissions have a major impact on ambient air mixing ratios of non-methane hydrocarbons (NMHCs) and methanethiol on Utö Island in the Baltic Sea H. Hellén et al. 10.5194/acp-24-4717-2024
- Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1 G. Brasseur et al. 10.5194/gmd-12-33-2019
- Numerical simulation of an extreme haze pollution event over the North China Plain based on initial and boundary condition ensembles X. LI et al. 10.1080/16742834.2019.1671136
25 citations as recorded by crossref.
- Machine learning for observation bias correction with application to dust storm data assimilation J. Jin et al. 10.5194/acp-19-10009-2019
- Fires as a source of annual ambient PM2.5 exposure and chronic health impacts in Europe S. Chowdhury et al. 10.1016/j.scitotenv.2024.171314
- Contrasting chemical environments in summertime for atmospheric ozone across major Chinese industrial regions: the effectiveness of emission control strategies Z. Liu et al. 10.5194/acp-21-10689-2021
- The effect of accounting for public holidays on the skills of the atmospheric composition model SILAM v.5.7 Y. Fatahi et al. 10.5194/gmd-14-7459-2021
- Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution W. Wu et al. 10.1021/acs.est.3c09122
- Chemistry‐Weather Interacted Model System GRAPES_Meso5.1/CUACE CW V1.0: Development, Evaluation and Application in Better Haze/Fog Prediction in China H. Wang et al. 10.1029/2022MS003222
- Synergy of Using Nadir and Limb Instruments for Tropospheric Ozone Monitoring (SUNLIT) V. Sofieva et al. 10.5194/amt-15-3193-2022
- Advances in air quality modeling and forecasting A. Baklanov & Y. Zhang 10.1016/j.glt.2020.11.001
- Modelling of the public health costs of fine particulate matter and results for Finland in 2015 J. Kukkonen et al. 10.5194/acp-20-9371-2020
- NOx Emissions Reduction and Rebound in China Due to the COVID‐19 Crisis J. Ding et al. 10.1029/2020GL089912
- Intercomparison of Air Quality Models in a Megacity: Toward an Operational Ensemble Forecasting System for São Paulo A. Deroubaix et al. 10.1029/2022JD038179
- Bioaerosols in the atmosphere at two sites in Northern Europe in spring 2021: Outline of an experimental campaign M. Sofiev et al. 10.1016/j.envres.2022.113798
- Real-time numerical source apportionment of PM2.5 concentrations over the Yangtze River Delta region, China G. Zhou et al. 10.1016/j.atmosenv.2020.118104
- Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields M. Sofiev et al. 10.1016/j.scitotenv.2023.165800
- Tree-ring N isotopic ratio increased with increasing latitude and decreasing N availability in pine stands across Finland A. Smolander et al. 10.1016/j.ecolind.2023.110604
- Do atmospheric events explain the arrival of an invasive ladybird (Harmonia axyridis) in the UK? P. Siljamo et al. 10.1371/journal.pone.0219335
- Seasonal Characteristics of Forecasting Uncertainties in Surface PM2.5 Concentration Associated with Forecast Lead Time over the Beijing-Tianjin-Hebei Region Q. Du et al. 10.1007/s00376-023-3060-3
- Snow Samples Combined With Long-Range Transport Modeling to Reveal the Origin and Temporal Variability of Black Carbon in Seasonal Snow in Sodankylä (67°N) O. Meinander et al. 10.3389/feart.2020.00153
- Development and Evaluation of a North America Ensemble Wildfire Air Quality Forecast: Initial Application to the 2020 Western United States “Gigafire” P. Makkaroon et al. 10.1029/2022JD037298
- A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS) R. Kumar et al. 10.1029/2020JD032554
- Optimization research on air quality numerical model forecasting effects based on deep learning methods W. Wang et al. 10.1016/j.atmosres.2022.106082
- An inter-comparative evaluation of PKU-FUEL global SO2 emission inventory J. Luo et al. 10.1016/j.scitotenv.2020.137755
- Mitigated PM2.5Changes by the Regional Transport During the COVID‐19 Lockdown in Shanghai, China Y. Gu et al. 10.1029/2021GL092395
- Deep Learning‐Based Ensemble Forecasts and Predictability Assessments for Surface Ozone Pollution A. Zhang et al. 10.1029/2022GL102611
- Shipping and algae emissions have a major impact on ambient air mixing ratios of non-methane hydrocarbons (NMHCs) and methanethiol on Utö Island in the Baltic Sea H. Hellén et al. 10.5194/acp-24-4717-2024
2 citations as recorded by crossref.
- Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1 G. Brasseur et al. 10.5194/gmd-12-33-2019
- Numerical simulation of an extreme haze pollution event over the North China Plain based on initial and boundary condition ensembles X. LI et al. 10.1080/16742834.2019.1671136
Latest update: 25 Apr 2024
Short summary
An operational multi-model forecasting system for air quality is providing daily forecasts of ozone, nitrogen oxides, and particulate matter for 37 urban areas of China. The paper presents the evaluation of the different forecasts performed during the first year of operation.
An operational multi-model forecasting system for air quality is providing daily forecasts of...
