Articles | Volume 6, issue 5
https://doi.org/10.5194/gmd-6-1831-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-1831-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
29 Oct 2013
Model evaluation paper |
| 29 Oct 2013
Evaluation of the United States National Air Quality Forecast Capability experimental real-time predictions in 2010 using Air Quality System ozone and NO2 measurements
NOAA Air Resources Laboratory (ARL), NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
Cooperative Institute for Climate and Satellites, University of Maryland, College Park, MD 20740, USA
H.-C. Kim
NOAA Air Resources Laboratory (ARL), NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
Cooperative Institute for Climate and Satellites, University of Maryland, College Park, MD 20740, USA
P. Lee
NOAA Air Resources Laboratory (ARL), NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
NOAA Air Resources Laboratory (ARL), NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
Cooperative Institute for Climate and Satellites, University of Maryland, College Park, MD 20740, USA
Center for Spatial Information Science and Systems (CSISS),George Mason University, Fairfax VA 22030, USA
L. Pan
NOAA Air Resources Laboratory (ARL), NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
Cooperative Institute for Climate and Satellites, University of Maryland, College Park, MD 20740, USA
NOAA/NWS/NCEP/EMC, NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
I.M. Systems Group, Rockville, MD 20852, USA
J. Huang
NOAA/NWS/NCEP/EMC, NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
I.M. Systems Group, Rockville, MD 20852, USA
J. McQueen
NOAA/NWS/NCEP/EMC, NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
M. Tsidulko
NOAA/NWS/NCEP/EMC, NOAA Center for Weather and Climate Prediction, 5830 University Research Court College Park, MD 20740, USA
I.M. Systems Group, Rockville, MD 20852, USA
I. Stajner
NOAA/NWS/OST, Silver Spring, MD 20910, USA
Viewed
Total article views: 5,579 (including HTML, PDF, and XML)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,180 | 2,189 | 210 | 5,579 | 221 | 204 |
- HTML: 3,180
- PDF: 2,189
- XML: 210
- Total: 5,579
- BibTeX: 221
- EndNote: 204
Cumulative views and downloads
(calculated since 02 May 2013)
Total article views: 4,687 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 29 Oct 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,853 | 1,651 | 183 | 4,687 | 207 | 195 |
- HTML: 2,853
- PDF: 1,651
- XML: 183
- Total: 4,687
- BibTeX: 207
- EndNote: 195
Total article views: 892 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 02 May 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 327 | 538 | 27 | 892 | 14 | 9 |
- HTML: 327
- PDF: 538
- XML: 27
- Total: 892
- BibTeX: 14
- EndNote: 9
Cited
53 citations as recorded by crossref.
- Durability evaluation of GFRP rebars in harsh alkaline environment using optimized tree-based random forest model M. Iqbal et al. 10.1016/j.joes.2021.10.012
- Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory H. Kim et al. 10.3390/atmos11010101
- Improving air quality model predictions of organic species using measurement-derived organic gaseous and particle emissions in a petrochemical-dominated region C. Stroud et al. 10.5194/acp-18-13531-2018
- Observations and impacts of transported Canadian wildfire smoke on ozone and aerosol air quality in the Maryland region on June 9–12, 2015 J. Dreessen et al. 10.1080/10962247.2016.1161674
- Performance of various techniques in estimating missing climatological data over snowbound mountainous areas of Karakoram Himalaya N. Kanda et al. 10.1002/met.1699
- Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature T. Chai & R. Draxler 10.5194/gmd-7-1247-2014
- Air Quality Implications of COVID-19 in California S. Pan et al. 10.3390/su12177067
- The Ozone Water–Land Environmental Transition Study: An Innovative Strategy for Understanding Chesapeake Bay Pollution Events J. Sullivan et al. 10.1175/BAMS-D-18-0025.1
- Quantifying Emissions of CO and NOx Using Observations From MOPITT, OMI, TES, and OSIRIS X. Zhang et al. 10.1029/2018JD028670
- Prediction of the Concentration and Source Contributions of PM2.5 and Gas-Phase Pollutants in an Urban Area with the SmartAQ Forecasting System E. Siouti et al. 10.3390/atmos15010008
- Deep learning algorithms based landslide vulnerability modeling in highly landslide prone areas of Tamil Nadu, India S. Saha et al. 10.1007/s12303-024-0044-y
- Impact of biogenic emissions on early summer ozone and fine particulate matter exposure in the Seoul Metropolitan Area of Korea H. Kim et al. 10.1007/s11869-018-0602-4
- Impact of Fire Emissions on U.S. Air Quality from 1997 to 2016–A Modeling Study in the Satellite Era Z. Tao et al. 10.3390/rs12060913
- An Efficient Method for Capturing the High Peak Concentrations of PM2.5 Using Gaussian-Filtered Deep Learning I. Yeo & Y. Choi 10.3390/su132111889
- Explicit Modeling of Meteorological Explanatory Variables in Short-Term Forecasting of Maximum Ozone Concentrations via a Multiple Regression Time Series Framework S. Iglesias-Gonzalez et al. 10.3390/atmos11121304
- Toward enhanced capability for detecting and predicting dust events in the western United States: the Arizona case study M. Huang et al. 10.5194/acp-15-12595-2015
- An evaluation of CMAQ NO2 using observed chemistry‐meteorology correlations M. Harkey et al. 10.1002/2015JD023316
- Assessment of NOx and O3 forecasting performances in the U.S. National Air Quality Forecasting Capability before and after the 2012 major emissions updates L. Pan et al. 10.1016/j.atmosenv.2014.06.020
- Comprehensive evaluation of multi-year real-time air quality forecasting using an online-coupled meteorology-chemistry model over southeastern United States Y. Zhang et al. 10.1016/j.atmosenv.2016.05.006
- Evaluation of modeled surface ozone biases as a function of cloud cover fraction H. Kim et al. 10.5194/gmd-8-2959-2015
- Cross Assessment of Twenty-One Different Methods for Missing Precipitation Data Estimation A. Armanuos et al. 10.3390/atmos11040389
- Climate data verification for assessing climate change in Almaty region of the Republic of Kazakhstan K. Kyrgyzbay et al. 10.1016/j.cliser.2023.100423
- NAQFC Developmental Forecast Guidance for Fine Particulate Matter (PM2.5) P. Lee et al. 10.1175/WAF-D-15-0163.1
- Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance A. Sayeed et al. 10.1016/j.neunet.2019.09.033
- Changes in nitrogen oxides emissions in California during 2005–2010 indicated from top‐down and bottom‐up emission estimates M. Huang et al. 10.1002/2014JD022268
- Impact of the 2008 Global Recession on air quality over the United States: Implications for surface ozone levels from changes in NOx emissions D. Tong et al. 10.1002/2016GL069885
- Fitting the variogram model of nickel laterite using root means square error in Morowali, Central Sulawesi B. Anggara et al. 10.1088/1755-1315/882/1/012042
- Evaluating NOx emission inventories for regulatory air quality modeling using satellite and air quality model data S. Kemball-Cook et al. 10.1016/j.atmosenv.2015.07.002
- Evaluating a fire smoke simulation algorithm in the National Air Quality Forecast Capability (NAQFC) by using multiple observation data sets during the Southeast Nexus (SENEX) field campaign L. Pan et al. 10.5194/gmd-13-2169-2020
- Monitoring Total Suspended Sediment Concentration in Spatiotemporal Domain over Teluk Lipat Utilizing Landsat 8 (OLI) F. Sa’ad et al. 10.3390/app11157082
- Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach N. Balashov et al. 10.1175/JAMC-D-16-0110.1
- OMI NO2 column densities over North American urban cities: the effect of satellite footprint resolution H. Kim et al. 10.5194/gmd-9-1111-2016
- Improving Sports Outcome Prediction Process Using Integrating Adaptive Weighted Features and Machine Learning Techniques C. Lu et al. 10.3390/pr9091563
- Air pollution analysis in Northwestern South America: A new Lagrangian framework A. Casallas et al. 10.1016/j.scitotenv.2023.167350
- A novel CMAQ-CNN hybrid model to forecast hourly surface-ozone concentrations 14 days in advance A. Sayeed et al. 10.1038/s41598-021-90446-6
- Impacts of Potential CO2-Reduction Policies on Air Quality in the United States M. Trail et al. 10.1021/acs.est.5b00473
- Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction A. Casallas et al. 10.3390/s22228790
- Regional evaluation of the performance of the global CAMS chemical modeling system over the United States (IFS cycle 47r1) J. Williams et al. 10.5194/gmd-15-4657-2022
- Long-term NOx trends over large cities in the United States during the great recession: Comparison of satellite retrievals, ground observations, and emission inventories D. Tong et al. 10.1016/j.atmosenv.2015.01.035
- Real-time 7-day forecast of pollen counts using a deep convolutional neural network Y. Lops et al. 10.1007/s00521-019-04665-0
- RETRACTED ARTICLE: Imputation of missing precipitation data using KNN, SOM, RF, and FNN A. Sahoo & D. Ghose 10.1007/s00500-022-07029-4
- Impact of Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depth and AirNow PM2.5 assimilation on Community Multi‐scale Air Quality aerosol predictions over the contiguous United States T. Chai et al. 10.1002/2016JD026295
- The Variability of Ozone Sensitivity to Anthropogenic Emissions with Biogenic Emissions Modeled by MEGAN and BEIS3 E. Kim et al. 10.3390/atmos8100187
- Design of an early alert system for PM2.5 through a stochastic method and machine learning models N. Celis et al. 10.1016/j.envsci.2021.10.030
- Nonpoint pollution loading forecast and assessment of optimal area of constructed wetland in dam watershed considering climate change scenario uncertainty H. Yi et al. 10.1016/j.ecoleng.2020.105910
- The effects of forest canopy shading and turbulence on boundary layer ozone P. Makar et al. 10.1038/ncomms15243
- A Spatial Econometric Analysis of Weather Effects on Milk Production X. Fan & J. Ma 10.3390/earth5030026
- Applying sustainable development goals in financial forecasting using machine learning techniques A. Chang et al. 10.1002/csr.2694
- Approximation of photovoltaic characteristics curves using Bézier Curve M. Louzazni & S. Al-Dahidi 10.1016/j.renene.2021.04.103
- Regional scale air quality modelling system in India: issues, challenges and suggestive framework N. Shukla et al. 10.1007/s12517-023-11474-2
- Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems J. Radtke et al. 10.5194/amt-17-2833-2024
- Evaluation of ocean wave power utilizing COWCLIP 2.0 datasets: a CMIP5 model assessment A. Yadav et al. 10.1007/s00382-024-07402-z
- Reactive nitrogen in and around the northeastern and mid-Atlantic US: sources, sinks, and connections with ozone M. Huang et al. 10.5194/acp-25-1449-2025
53 citations as recorded by crossref.
- Durability evaluation of GFRP rebars in harsh alkaline environment using optimized tree-based random forest model M. Iqbal et al. 10.1016/j.joes.2021.10.012
- Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory H. Kim et al. 10.3390/atmos11010101
- Improving air quality model predictions of organic species using measurement-derived organic gaseous and particle emissions in a petrochemical-dominated region C. Stroud et al. 10.5194/acp-18-13531-2018
- Observations and impacts of transported Canadian wildfire smoke on ozone and aerosol air quality in the Maryland region on June 9–12, 2015 J. Dreessen et al. 10.1080/10962247.2016.1161674
- Performance of various techniques in estimating missing climatological data over snowbound mountainous areas of Karakoram Himalaya N. Kanda et al. 10.1002/met.1699
- Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature T. Chai & R. Draxler 10.5194/gmd-7-1247-2014
- Air Quality Implications of COVID-19 in California S. Pan et al. 10.3390/su12177067
- The Ozone Water–Land Environmental Transition Study: An Innovative Strategy for Understanding Chesapeake Bay Pollution Events J. Sullivan et al. 10.1175/BAMS-D-18-0025.1
- Quantifying Emissions of CO and NOx Using Observations From MOPITT, OMI, TES, and OSIRIS X. Zhang et al. 10.1029/2018JD028670
- Prediction of the Concentration and Source Contributions of PM2.5 and Gas-Phase Pollutants in an Urban Area with the SmartAQ Forecasting System E. Siouti et al. 10.3390/atmos15010008
- Deep learning algorithms based landslide vulnerability modeling in highly landslide prone areas of Tamil Nadu, India S. Saha et al. 10.1007/s12303-024-0044-y
- Impact of biogenic emissions on early summer ozone and fine particulate matter exposure in the Seoul Metropolitan Area of Korea H. Kim et al. 10.1007/s11869-018-0602-4
- Impact of Fire Emissions on U.S. Air Quality from 1997 to 2016–A Modeling Study in the Satellite Era Z. Tao et al. 10.3390/rs12060913
- An Efficient Method for Capturing the High Peak Concentrations of PM2.5 Using Gaussian-Filtered Deep Learning I. Yeo & Y. Choi 10.3390/su132111889
- Explicit Modeling of Meteorological Explanatory Variables in Short-Term Forecasting of Maximum Ozone Concentrations via a Multiple Regression Time Series Framework S. Iglesias-Gonzalez et al. 10.3390/atmos11121304
- Toward enhanced capability for detecting and predicting dust events in the western United States: the Arizona case study M. Huang et al. 10.5194/acp-15-12595-2015
- An evaluation of CMAQ NO2 using observed chemistry‐meteorology correlations M. Harkey et al. 10.1002/2015JD023316
- Assessment of NOx and O3 forecasting performances in the U.S. National Air Quality Forecasting Capability before and after the 2012 major emissions updates L. Pan et al. 10.1016/j.atmosenv.2014.06.020
- Comprehensive evaluation of multi-year real-time air quality forecasting using an online-coupled meteorology-chemistry model over southeastern United States Y. Zhang et al. 10.1016/j.atmosenv.2016.05.006
- Evaluation of modeled surface ozone biases as a function of cloud cover fraction H. Kim et al. 10.5194/gmd-8-2959-2015
- Cross Assessment of Twenty-One Different Methods for Missing Precipitation Data Estimation A. Armanuos et al. 10.3390/atmos11040389
- Climate data verification for assessing climate change in Almaty region of the Republic of Kazakhstan K. Kyrgyzbay et al. 10.1016/j.cliser.2023.100423
- NAQFC Developmental Forecast Guidance for Fine Particulate Matter (PM2.5) P. Lee et al. 10.1175/WAF-D-15-0163.1
- Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance A. Sayeed et al. 10.1016/j.neunet.2019.09.033
- Changes in nitrogen oxides emissions in California during 2005–2010 indicated from top‐down and bottom‐up emission estimates M. Huang et al. 10.1002/2014JD022268
- Impact of the 2008 Global Recession on air quality over the United States: Implications for surface ozone levels from changes in NOx emissions D. Tong et al. 10.1002/2016GL069885
- Fitting the variogram model of nickel laterite using root means square error in Morowali, Central Sulawesi B. Anggara et al. 10.1088/1755-1315/882/1/012042
- Evaluating NOx emission inventories for regulatory air quality modeling using satellite and air quality model data S. Kemball-Cook et al. 10.1016/j.atmosenv.2015.07.002
- Evaluating a fire smoke simulation algorithm in the National Air Quality Forecast Capability (NAQFC) by using multiple observation data sets during the Southeast Nexus (SENEX) field campaign L. Pan et al. 10.5194/gmd-13-2169-2020
- Monitoring Total Suspended Sediment Concentration in Spatiotemporal Domain over Teluk Lipat Utilizing Landsat 8 (OLI) F. Sa’ad et al. 10.3390/app11157082
- Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach N. Balashov et al. 10.1175/JAMC-D-16-0110.1
- OMI NO2 column densities over North American urban cities: the effect of satellite footprint resolution H. Kim et al. 10.5194/gmd-9-1111-2016
- Improving Sports Outcome Prediction Process Using Integrating Adaptive Weighted Features and Machine Learning Techniques C. Lu et al. 10.3390/pr9091563
- Air pollution analysis in Northwestern South America: A new Lagrangian framework A. Casallas et al. 10.1016/j.scitotenv.2023.167350
- A novel CMAQ-CNN hybrid model to forecast hourly surface-ozone concentrations 14 days in advance A. Sayeed et al. 10.1038/s41598-021-90446-6
- Impacts of Potential CO2-Reduction Policies on Air Quality in the United States M. Trail et al. 10.1021/acs.est.5b00473
- Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction A. Casallas et al. 10.3390/s22228790
- Regional evaluation of the performance of the global CAMS chemical modeling system over the United States (IFS cycle 47r1) J. Williams et al. 10.5194/gmd-15-4657-2022
- Long-term NOx trends over large cities in the United States during the great recession: Comparison of satellite retrievals, ground observations, and emission inventories D. Tong et al. 10.1016/j.atmosenv.2015.01.035
- Real-time 7-day forecast of pollen counts using a deep convolutional neural network Y. Lops et al. 10.1007/s00521-019-04665-0
- RETRACTED ARTICLE: Imputation of missing precipitation data using KNN, SOM, RF, and FNN A. Sahoo & D. Ghose 10.1007/s00500-022-07029-4
- Impact of Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depth and AirNow PM2.5 assimilation on Community Multi‐scale Air Quality aerosol predictions over the contiguous United States T. Chai et al. 10.1002/2016JD026295
- The Variability of Ozone Sensitivity to Anthropogenic Emissions with Biogenic Emissions Modeled by MEGAN and BEIS3 E. Kim et al. 10.3390/atmos8100187
- Design of an early alert system for PM2.5 through a stochastic method and machine learning models N. Celis et al. 10.1016/j.envsci.2021.10.030
- Nonpoint pollution loading forecast and assessment of optimal area of constructed wetland in dam watershed considering climate change scenario uncertainty H. Yi et al. 10.1016/j.ecoleng.2020.105910
- The effects of forest canopy shading and turbulence on boundary layer ozone P. Makar et al. 10.1038/ncomms15243
- A Spatial Econometric Analysis of Weather Effects on Milk Production X. Fan & J. Ma 10.3390/earth5030026
- Applying sustainable development goals in financial forecasting using machine learning techniques A. Chang et al. 10.1002/csr.2694
- Approximation of photovoltaic characteristics curves using Bézier Curve M. Louzazni & S. Al-Dahidi 10.1016/j.renene.2021.04.103
- Regional scale air quality modelling system in India: issues, challenges and suggestive framework N. Shukla et al. 10.1007/s12517-023-11474-2
- Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems J. Radtke et al. 10.5194/amt-17-2833-2024
- Evaluation of ocean wave power utilizing COWCLIP 2.0 datasets: a CMIP5 model assessment A. Yadav et al. 10.1007/s00382-024-07402-z
- Reactive nitrogen in and around the northeastern and mid-Atlantic US: sources, sinks, and connections with ozone M. Huang et al. 10.5194/acp-25-1449-2025
Saved (final revised paper)
Latest update: 23 Apr 2025
