Articles | Volume 18, issue 10
https://doi.org/10.5194/acp-18-7509-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-18-7509-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 May 2018
Research article |
| 30 May 2018
Quantifying errors in surface ozone predictions associated with clouds over the CONUS: a WRF-Chem modeling study using satellite cloud retrievals
Young-Hee Ryu
National Center for Atmospheric Research, Boulder, CO, USA
Alma Hodzic
CORRESPONDING AUTHOR
National Center for Atmospheric Research, Boulder, CO, USA
Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France
Jerome Barre
National Center for Atmospheric Research, Boulder, CO, USA
now at: European Centre for Medium-Range Weather Forecasts, Reading, UK
Gael Descombes
National Center for Atmospheric Research, Boulder, CO, USA
Patrick Minnis
NASA Langley Research Center, Hampton, VA, USA
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Cited
15 citations as recorded by crossref.
- Learning Calibration Functions on the Fly: Hybrid Batch Online Stacking Ensembles for the Calibration of Low-Cost Air Quality Sensor Networks in the Presence of Concept Drift E. Bagkis et al. 10.3390/atmos13030416
- Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review A. Yafouz et al. 10.1007/s11270-021-04989-5
- Exploring the Potential of Statistical Modeling to Retrieve the Cloud Base Height from Geostationary Satellites: Applications to the ABI Sensor on Board of the GOES-R Satellite Series P. Jiménez & T. McCandless 10.3390/rs13030375
- Sensitivity of Meteorological Skill to Selection of WRF‐Chem Physical Parameterizations and Impact on Ozone Prediction During the Lake Michigan Ozone Study (LMOS) M. Abdi‐Oskouei et al. 10.1029/2019JD031971
- Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations P. Cheng et al. 10.1016/j.atmosenv.2021.118751
- Role of Upwind Precipitation in Transboundary Pollution and Secondary Aerosol Formation: A Case Study during the KORUS-AQ Field Campaign Y. Ryu et al. 10.1175/JAMC-D-21-0162.1
- Comprehensive isoprene and terpene gas-phase chemistry improves simulated surface ozone in the southeastern US R. Schwantes et al. 10.5194/acp-20-3739-2020
- Analysis of the Effect of Optical Properties of Black Carbon on Ozone in an Urban Environment at the Yangtze River Delta, China J. An et al. 10.1007/s00376-021-0367-9
- Response of surface ozone over the continental United States to UV radiation declines from the expected recovery of stratospheric ozone A. Hodzic & S. Madronich 10.1038/s41612-018-0045-5
- Chemical Characteristics and Ozone Production in the Northern Colorado Front Range G. Pfister et al. 10.1029/2019JD030544
- Air Quality in the Northern Colorado Front Range Metro Area: The Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ) F. Flocke et al. 10.1029/2019JD031197
- Evaluation of PM2.5 fluxes in the “2+26” cities: Transport pathways and intercity contributions M. Qi et al. 10.1016/j.apr.2021.03.011
- A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS) R. Kumar et al. 10.1029/2020JD032554
- High spatial resolution WRF-Chem model over Asia: Physics and chemistry evaluation P. Sicard et al. 10.1016/j.atmosenv.2020.118004
- Toward a Better Regional Ozone Forecast Over CONUS Using Rapid Data Assimilation of Clouds and Meteorology in WRF‐Chem Y. Ryu et al. 10.1029/2019JD031232
15 citations as recorded by crossref.
- Learning Calibration Functions on the Fly: Hybrid Batch Online Stacking Ensembles for the Calibration of Low-Cost Air Quality Sensor Networks in the Presence of Concept Drift E. Bagkis et al. 10.3390/atmos13030416
- Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review A. Yafouz et al. 10.1007/s11270-021-04989-5
- Exploring the Potential of Statistical Modeling to Retrieve the Cloud Base Height from Geostationary Satellites: Applications to the ABI Sensor on Board of the GOES-R Satellite Series P. Jiménez & T. McCandless 10.3390/rs13030375
- Sensitivity of Meteorological Skill to Selection of WRF‐Chem Physical Parameterizations and Impact on Ozone Prediction During the Lake Michigan Ozone Study (LMOS) M. Abdi‐Oskouei et al. 10.1029/2019JD031971
- Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations P. Cheng et al. 10.1016/j.atmosenv.2021.118751
- Role of Upwind Precipitation in Transboundary Pollution and Secondary Aerosol Formation: A Case Study during the KORUS-AQ Field Campaign Y. Ryu et al. 10.1175/JAMC-D-21-0162.1
- Comprehensive isoprene and terpene gas-phase chemistry improves simulated surface ozone in the southeastern US R. Schwantes et al. 10.5194/acp-20-3739-2020
- Analysis of the Effect of Optical Properties of Black Carbon on Ozone in an Urban Environment at the Yangtze River Delta, China J. An et al. 10.1007/s00376-021-0367-9
- Response of surface ozone over the continental United States to UV radiation declines from the expected recovery of stratospheric ozone A. Hodzic & S. Madronich 10.1038/s41612-018-0045-5
- Chemical Characteristics and Ozone Production in the Northern Colorado Front Range G. Pfister et al. 10.1029/2019JD030544
- Air Quality in the Northern Colorado Front Range Metro Area: The Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ) F. Flocke et al. 10.1029/2019JD031197
- Evaluation of PM2.5 fluxes in the “2+26” cities: Transport pathways and intercity contributions M. Qi et al. 10.1016/j.apr.2021.03.011
- A Novel Ensemble Design for Probabilistic Predictions of Fine Particulate Matter Over the Contiguous United States (CONUS) R. Kumar et al. 10.1029/2020JD032554
- High spatial resolution WRF-Chem model over Asia: Physics and chemistry evaluation P. Sicard et al. 10.1016/j.atmosenv.2020.118004
- Toward a Better Regional Ozone Forecast Over CONUS Using Rapid Data Assimilation of Clouds and Meteorology in WRF‐Chem Y. Ryu et al. 10.1029/2019JD031232
Latest update: 04 Jun 2023
Short summary
We investigate whether errors in cloud predictions can significantly impact the ability of air quality models to predict surface ozone over the US during summer 2013. The comparison with satellite data shows that the model predicts ~ 55 % of clouds in the right locations and underpredicts cloud thickness. The error in daytime ozone is estimated to be 1–5 ppb and represents ~ 40 % of the ozone bias. The accurate predictions of clouds particularly benefits ozone predictions in urban areas.
We investigate whether errors in cloud predictions can significantly impact the ability of air...
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