Articles | Volume 7, issue 6
https://doi.org/10.5194/gmd-7-2817-2014
© Author(s) 2014. 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-7-2817-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Uncertainty in Lagrangian pollutant transport simulations due to meteorological uncertainty from a mesoscale WRF ensemble
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Colorado, USA
NOAA Earth System Research Laboratory, Boulder, Colorado, USA
J. Brioude
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Colorado, USA
NOAA Earth System Research Laboratory, Boulder, Colorado, USA
Laboratoire de l'Atmosphere et des Cyclones, UMR8105, CNRS-Meteo France-Universite La Reunion, La Reunion, France
S. McKeen
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Colorado, USA
NOAA Earth System Research Laboratory, Boulder, Colorado, USA
J. S. Holloway
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Colorado, USA
NOAA Earth System Research Laboratory, Boulder, Colorado, USA
retired
Viewed
Total article views: 4,494 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 23 Jul 2014)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,463 | 1,891 | 140 | 4,494 | 161 | 177 |
- HTML: 2,463
- PDF: 1,891
- XML: 140
- Total: 4,494
- BibTeX: 161
- EndNote: 177
Total article views: 3,848 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 02 Dec 2014)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,133 | 1,597 | 118 | 3,848 | 150 | 171 |
- HTML: 2,133
- PDF: 1,597
- XML: 118
- Total: 3,848
- BibTeX: 150
- EndNote: 171
Total article views: 646 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 23 Jul 2014)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
330 | 294 | 22 | 646 | 11 | 6 |
- HTML: 330
- PDF: 294
- XML: 22
- Total: 646
- BibTeX: 11
- EndNote: 6
Cited
35 citations as recorded by crossref.
- A multi-model approach to monitor emissions of CO<sub>2</sub> and CO from an urban–industrial complex I. Super et al. 10.5194/acp-17-13297-2017
- Evaluation of Heavy Precipitation Simulated by the WRF Model Using 4D-Var Data Assimilation with TRMM 3B42 and GPM IMERG over the Huaihe River Basin, China L. Yi et al. 10.3390/rs10040646
- Growth of the Decision Tree: Advances in Bottom‐Up Climate Change Risk Management P. Ray et al. 10.1111/1752-1688.12701
- Errors in top-down estimates of emissions using a known source W. Angevine et al. 10.5194/acp-20-11855-2020
- Assessment of an atmospheric transport model for annual inverse estimates of California greenhouse gas emissions J. Bagley et al. 10.1002/2016JD025361
- Four-dimensional variational inversion of black carbon emissions during ARCTAS-CARB with WRFDA-Chem J. Guerrette & D. Henze 10.5194/acp-17-7605-2017
- Long-term high frequency measurements of ethane, benzene and methyl chloride at Ragged Point, Barbados: Identification of long-range transport events A. Archibald et al. 10.12952/journal.elementa.000068
- Optimizing a dynamic fossil fuel CO<sub>2</sub> emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO<sub>2</sub>, CO, NO<sub><i>x</i></sub>, and SO<sub>2</sub> I. Super et al. 10.5194/gmd-13-2695-2020
- Industrial point source CO2 emission strength estimation with aircraft measurements and dispersion modelling F. Carotenuto et al. 10.1007/s10661-018-6531-8
- Top‐down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin Y. Cui et al. 10.1002/2014JD023002
- Calibration of a multi-physics ensemble for estimating the uncertainty of a greenhouse gas atmospheric transport model L. Díaz-Isaac et al. 10.5194/acp-19-5695-2019
- Reproducibility of Surface Wind and Tracer Transport Simulations over Complex Terrain Using 5-, 3-, and 1-km-Grid Models T. Sekiyama & M. Kajino 10.1175/JAMC-D-19-0241.1
- Shallow Cumulus in WRF Parameterizations Evaluated against LASSO Large-Eddy Simulations W. Angevine et al. 10.1175/MWR-D-18-0115.1
- Vulnerability assessment of drinking water supply under climate uncertainty using a river contamination risk (RANK) model F. Behzadi et al. 10.1016/j.envsoft.2021.105294
- Airborne observations of mercury emissions from the Chicago/Gary urban/industrial area during the 2013 NOMADSS campaign L. Gratz et al. 10.1016/j.atmosenv.2016.09.051
- Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study A. Karion et al. 10.5194/acp-19-2561-2019
- Meteorological modeling relevant to mesoscale and regional air quality applications: a review R. McNider & A. Pour-Biazar 10.1080/10962247.2019.1694602
- Sensitivity Analysis of Atmospheric Dispersion Simulations by FLEXPART to the WRF-Simulated Meteorological Predictions in a Coastal Environment C. Srinivas et al. 10.1007/s00024-015-1104-z
- On the capability to model the background and its uncertainty of CTBT-relevant radioxenon isotopes in Europe by using ensemble dispersion modeling P. De Meutter et al. 10.1016/j.jenvrad.2016.07.033
- Evaluation of an Air Pollution Forecasting System Based on Micro-Pulse Lidar Cruising Measurements in the South China Sea Y. Tang et al. 10.3390/rs13152855
- Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6 J. Clemens et al. 10.5194/gmd-17-4467-2024
- A Long-Term WRF Meteorological Archive for Dispersion Simulations: Application to Controlled Tracer Experiments F. Ngan & A. Stein 10.1175/JAMC-D-16-0345.1
- Characteristics of STILT footprints driven by KIM model simulated meteorological fields: implication for developing near real-time footprints S. Kenea et al. 10.1007/s44273-023-00016-7
- Impact of inherent meteorology uncertainty on air quality model predictions R. Gilliam et al. 10.1002/2015JD023674
- Firewood residential heating – local versus remote influence on the aerosol burden C. Betancourt et al. 10.5194/acp-21-5953-2021
- Ensemble Dispersion Simulation of a Point-Source Radioactive Aerosol Using Perturbed Meteorological Fields over Eastern Japan T. Sekiyama et al. 10.3390/atmos12060662
- Lagrangian transport simulations of volcanic sulfur dioxide emissions: Impact of meteorological data products L. Hoffmann et al. 10.1002/2015JD023749
- Uncertainty quantification of atmospheric transport and dispersion modelling using ensembles for CTBT verification applications P. De Meutter & A. Delcloo 10.1016/j.jenvrad.2022.106918
- The Environmental Effects of the April 2020 Wildfires and the Cs-137 Re-Suspension in the Chernobyl Exclusion Zone: A Multi-Hazard Threat R. Baró et al. 10.3390/atmos12040467
- Top‐down estimate of methane emissions in California using a mesoscale inverse modeling technique: The San Joaquin Valley Y. Cui et al. 10.1002/2016JD026398
- Chasing parts in quadrillion: applications of dynamical downscaling in atmospheric pollutant transport modelling during field campaigns A. Poulidis et al. 10.1186/s40645-024-00642-x
- Air quality simulation of NOX over the tropical coastal city Chennai in southern India with FLEXPART-WRF S. Madala et al. 10.1016/j.atmosenv.2015.12.052
- Instrumentation and measurement strategy for the NOAA SENEX aircraft campaign as part of the Southeast Atmosphere Study 2013 C. Warneke et al. 10.5194/amt-9-3063-2016
- Sources of uncertainty in atmospheric dispersion modeling in support of Comprehensive Nuclear–Test–Ban Treaty monitoring and verification system S. Mekhaimr & M. Abdel Wahab 10.1016/j.apr.2019.03.008
- Impact of data assimilation and aerosol radiation interaction on Lagrangian particle dispersion modelling M. Jia et al. 10.1016/j.atmosenv.2020.118179
34 citations as recorded by crossref.
- A multi-model approach to monitor emissions of CO<sub>2</sub> and CO from an urban–industrial complex I. Super et al. 10.5194/acp-17-13297-2017
- Evaluation of Heavy Precipitation Simulated by the WRF Model Using 4D-Var Data Assimilation with TRMM 3B42 and GPM IMERG over the Huaihe River Basin, China L. Yi et al. 10.3390/rs10040646
- Growth of the Decision Tree: Advances in Bottom‐Up Climate Change Risk Management P. Ray et al. 10.1111/1752-1688.12701
- Errors in top-down estimates of emissions using a known source W. Angevine et al. 10.5194/acp-20-11855-2020
- Assessment of an atmospheric transport model for annual inverse estimates of California greenhouse gas emissions J. Bagley et al. 10.1002/2016JD025361
- Four-dimensional variational inversion of black carbon emissions during ARCTAS-CARB with WRFDA-Chem J. Guerrette & D. Henze 10.5194/acp-17-7605-2017
- Long-term high frequency measurements of ethane, benzene and methyl chloride at Ragged Point, Barbados: Identification of long-range transport events A. Archibald et al. 10.12952/journal.elementa.000068
- Optimizing a dynamic fossil fuel CO<sub>2</sub> emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO<sub>2</sub>, CO, NO<sub><i>x</i></sub>, and SO<sub>2</sub> I. Super et al. 10.5194/gmd-13-2695-2020
- Industrial point source CO2 emission strength estimation with aircraft measurements and dispersion modelling F. Carotenuto et al. 10.1007/s10661-018-6531-8
- Top‐down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin Y. Cui et al. 10.1002/2014JD023002
- Calibration of a multi-physics ensemble for estimating the uncertainty of a greenhouse gas atmospheric transport model L. Díaz-Isaac et al. 10.5194/acp-19-5695-2019
- Reproducibility of Surface Wind and Tracer Transport Simulations over Complex Terrain Using 5-, 3-, and 1-km-Grid Models T. Sekiyama & M. Kajino 10.1175/JAMC-D-19-0241.1
- Shallow Cumulus in WRF Parameterizations Evaluated against LASSO Large-Eddy Simulations W. Angevine et al. 10.1175/MWR-D-18-0115.1
- Vulnerability assessment of drinking water supply under climate uncertainty using a river contamination risk (RANK) model F. Behzadi et al. 10.1016/j.envsoft.2021.105294
- Airborne observations of mercury emissions from the Chicago/Gary urban/industrial area during the 2013 NOMADSS campaign L. Gratz et al. 10.1016/j.atmosenv.2016.09.051
- Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study A. Karion et al. 10.5194/acp-19-2561-2019
- Meteorological modeling relevant to mesoscale and regional air quality applications: a review R. McNider & A. Pour-Biazar 10.1080/10962247.2019.1694602
- Sensitivity Analysis of Atmospheric Dispersion Simulations by FLEXPART to the WRF-Simulated Meteorological Predictions in a Coastal Environment C. Srinivas et al. 10.1007/s00024-015-1104-z
- On the capability to model the background and its uncertainty of CTBT-relevant radioxenon isotopes in Europe by using ensemble dispersion modeling P. De Meutter et al. 10.1016/j.jenvrad.2016.07.033
- Evaluation of an Air Pollution Forecasting System Based on Micro-Pulse Lidar Cruising Measurements in the South China Sea Y. Tang et al. 10.3390/rs13152855
- Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6 J. Clemens et al. 10.5194/gmd-17-4467-2024
- A Long-Term WRF Meteorological Archive for Dispersion Simulations: Application to Controlled Tracer Experiments F. Ngan & A. Stein 10.1175/JAMC-D-16-0345.1
- Characteristics of STILT footprints driven by KIM model simulated meteorological fields: implication for developing near real-time footprints S. Kenea et al. 10.1007/s44273-023-00016-7
- Impact of inherent meteorology uncertainty on air quality model predictions R. Gilliam et al. 10.1002/2015JD023674
- Firewood residential heating – local versus remote influence on the aerosol burden C. Betancourt et al. 10.5194/acp-21-5953-2021
- Ensemble Dispersion Simulation of a Point-Source Radioactive Aerosol Using Perturbed Meteorological Fields over Eastern Japan T. Sekiyama et al. 10.3390/atmos12060662
- Lagrangian transport simulations of volcanic sulfur dioxide emissions: Impact of meteorological data products L. Hoffmann et al. 10.1002/2015JD023749
- Uncertainty quantification of atmospheric transport and dispersion modelling using ensembles for CTBT verification applications P. De Meutter & A. Delcloo 10.1016/j.jenvrad.2022.106918
- The Environmental Effects of the April 2020 Wildfires and the Cs-137 Re-Suspension in the Chernobyl Exclusion Zone: A Multi-Hazard Threat R. Baró et al. 10.3390/atmos12040467
- Top‐down estimate of methane emissions in California using a mesoscale inverse modeling technique: The San Joaquin Valley Y. Cui et al. 10.1002/2016JD026398
- Chasing parts in quadrillion: applications of dynamical downscaling in atmospheric pollutant transport modelling during field campaigns A. Poulidis et al. 10.1186/s40645-024-00642-x
- Air quality simulation of NOX over the tropical coastal city Chennai in southern India with FLEXPART-WRF S. Madala et al. 10.1016/j.atmosenv.2015.12.052
- Instrumentation and measurement strategy for the NOAA SENEX aircraft campaign as part of the Southeast Atmosphere Study 2013 C. Warneke et al. 10.5194/amt-9-3063-2016
- Sources of uncertainty in atmospheric dispersion modeling in support of Comprehensive Nuclear–Test–Ban Treaty monitoring and verification system S. Mekhaimr & M. Abdel Wahab 10.1016/j.apr.2019.03.008
Saved (final revised paper)
Saved (preprint)
Latest update: 21 Nov 2024
Short summary
Uncertainty in Lagrangian particle dispersion model simulations was evaluated using an ensemble of WRF meteorological model runs. Uncertainty of tracer concentrations due solely to meteorological uncertainty is 30-40%. Spatial and temporal averaging reduces the uncertainty marginally. Tracer age uncertainty due solely to meteorological uncertainty is 15-20%. These are lower bounds on the uncertainty, because a number of processes are not accounted for in the analysis.
Uncertainty in Lagrangian particle dispersion model simulations was evaluated using an ensemble...