Articles | Volume 7, issue 4
https://doi.org/10.5194/gmd-7-1621-2014
© 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-7-1621-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
13 Aug 2014
Development and technical paper |
| 13 Aug 2014
Implementation of aerosol assimilation in Gridpoint Statistical Interpolation (v. 3.2) and WRF-Chem (v. 3.4.1)
M. Pagowski
NOAA Earth System Research Laboratory (ESRL), Boulder, Colorado, USA
National Center for Atmospheric Research, Boulder, Colorado, USA
G. A. Grell
NOAA Earth System Research Laboratory (ESRL), Boulder, Colorado, USA
M. Hu
NOAA Earth System Research Laboratory (ESRL), Boulder, Colorado, USA
H.-C. Lin
National Center for Atmospheric Research, Boulder, Colorado, USA
C. S. Schwartz
National Center for Atmospheric Research, Boulder, Colorado, USA
Viewed
Total article views: 5,879 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 Apr 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,209 | 2,438 | 232 | 5,879 | 265 | 313 |
- HTML: 3,209
- PDF: 2,438
- XML: 232
- Total: 5,879
- BibTeX: 265
- EndNote: 313
Total article views: 4,890 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 13 Aug 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,775 | 1,907 | 208 | 4,890 | 247 | 304 |
- HTML: 2,775
- PDF: 1,907
- XML: 208
- Total: 4,890
- BibTeX: 247
- EndNote: 304
Total article views: 989 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 Apr 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 434 | 531 | 24 | 989 | 18 | 9 |
- HTML: 434
- PDF: 531
- XML: 24
- Total: 989
- BibTeX: 18
- EndNote: 9
Cited
38 citations as recorded by crossref.
- Vertical distribution and transport characteristics of ozone pollution based on lidar observation network and data assimilation over the Pearl River Delta, China Y. Pan et al. 10.1016/j.atmosres.2024.107643
- Evaluation of MODIS and two reanalysis aerosol optical depth products over AERONET sites H. Shi et al. 10.1016/j.atmosres.2019.01.009
- Impact of the OMI aerosol optical depth on analysis increments through coupled meteorology–aerosol data assimilation for an Asian dust storm E. Lee et al. 10.1016/j.rse.2017.02.013
- Generalized background error covariance matrix model (GEN_BE v2.0) G. Descombes et al. 10.5194/gmd-8-669-2015
- Improving the sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosols of the Weather Research and Forecasting-Chemistry (WRF-Chem) model with the revised Gridpoint Statistical Interpolation system and multi-wavelength aerosol optical measurements: the dust aerosol observation campaign at Kashi, near the Taklimakan Desert, northwestern China W. Chang et al. 10.5194/acp-21-4403-2021
- An Observing System Simulation Experiment Framework for Air Quality Forecasts in Northeast Asia: A Case Study Utilizing Virtual Geostationary Environment Monitoring Spectrometer and Surface Monitored Aerosol Data H. Kim et al. 10.3390/rs14020389
- Assimilating Fengyun-4A observations to improve WRF-Chem PM2.5 predictions in China J. Hong et al. 10.1016/j.atmosres.2021.105878
- Improvement of the Aerosol Forecast and Analysis Over East Asia With Joint Assimilation of Two Geostationary Satellite Observations Y. Cheng et al. 10.1029/2022GL099908
- Improved Modeling of Spatiotemporal Variations of Fine Particulate Matter Using a Three‐Dimensional Variational Data Fusion Method X. Zhang et al. 10.1029/2020JD033599
- The Aerosol Module in the Community Radiative Transfer Model (v2.2 and v2.3): accounting for aerosol transmittance effects on the radiance observation operator C. Lu et al. 10.5194/gmd-15-1317-2022
- A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS) R. Kumar et al. 10.5194/essd-17-1807-2025
- Toward Improving Short‐Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals R. Kumar et al. 10.1029/2018JD029009
- Improving WRF-Chem PM2.5 predictions by combining data assimilation and deep-learning-based bias correction X. Ma et al. 10.1016/j.envint.2024.109199
- JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
- Improved PM2.5 predictions of WRF-Chem via the integration of Himawari-8 satellite data and ground observations J. Hong et al. 10.1016/j.envpol.2020.114451
- Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem A. Raman et al. 10.1016/j.atmosenv.2020.118134
- Evaluation of MWHS-2 Using a Co-located Ground-Based Radar Network for Improved Model Assimilation S. Liu et al. 10.3390/rs11202338
- Unveiling 3-D evolution and mechanisms of ozone pollution in Changzhou, China: Insights from lidar observations and modelling Z. Liu et al. 10.1016/j.envpol.2024.124556
- 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
- Impacts of uncertainties in emissions on aerosol data assimilation and short-term PM2.5 predictions over Northeast Asia S. Lee et al. 10.1016/j.atmosenv.2021.118921
- Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM 2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing J. McHenry et al. 10.1080/10962247.2015.1096862
- The impact of multi-species surface chemical observation assimilation on air quality forecasts in China Z. Peng et al. 10.5194/acp-18-17387-2018
- Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
- Using Lidar technology to assess regional air pollution and improve estimates of PM2.5 transport in the North China Plain Y. Xiang et al. 10.1088/1748-9326/ab9cfd
- Limitations of ozone data assimilation with adjustment of NOx emissions: mixed effects on NO2 forecasts over Beijing and surrounding areas X. Tang et al. 10.5194/acp-16-6395-2016
- Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain Y. Xiang et al. 10.5194/acp-21-7023-2021
- Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions R. Žabkar et al. 10.5194/gmd-8-2119-2015
- Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
- Estimation of aerosol properties over the Chinese desert region with MODIS AOD assimilation in a global model X. Yin et al. 10.1016/j.accre.2016.04.001
- A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods Y. Tang et al. 10.5194/gmd-10-4743-2017
- Impact of Assimilating GEMS Aerosol Optical Depth on Asian Dust Storm Prediction: Comparative Assessment with MODIS Observation E. Lee et al. 10.1007/s13143-025-00407-6
- Shipborne lidar measurements of ozone over the southeastern coastal regions of China in winter L. Lv et al. 10.1016/j.envres.2025.121165
- Assimilating a blended dataset of satellite-based estimations and in situ observations to improve WRF-Chem PM2.5 prediction X. Ma et al. 10.1016/j.atmosenv.2023.120284
- The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation S. Wei et al. 10.5194/gmd-17-795-2024
- Satellite imagery and products of the 16–17 February 2020 Saharan Air Layer dust event over the eastern Atlantic: impacts of water vapor on dust detection and morphology L. Grasso et al. 10.5194/amt-14-1615-2021
- Vertical structure and transport characteristic of aerosol and O3 during the emergency control period in Wuhan, China, using vehicle-lidar observations Y. Pan et al. 10.1016/j.atmosenv.2024.120762
- Modeling study of a severe aerosol pollution event in December 2013 over Shanghai China: An application of chemical data assimilation J. Wu et al. 10.1016/j.partic.2014.10.008
- Assimilation of PM2.5 ground base observations to two chemical schemes in WRF-Chem – The results for the winter and summer period M. Werner et al. 10.1016/j.atmosenv.2018.12.016
36 citations as recorded by crossref.
- Vertical distribution and transport characteristics of ozone pollution based on lidar observation network and data assimilation over the Pearl River Delta, China Y. Pan et al. 10.1016/j.atmosres.2024.107643
- Evaluation of MODIS and two reanalysis aerosol optical depth products over AERONET sites H. Shi et al. 10.1016/j.atmosres.2019.01.009
- Impact of the OMI aerosol optical depth on analysis increments through coupled meteorology–aerosol data assimilation for an Asian dust storm E. Lee et al. 10.1016/j.rse.2017.02.013
- Generalized background error covariance matrix model (GEN_BE v2.0) G. Descombes et al. 10.5194/gmd-8-669-2015
- Improving the sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosols of the Weather Research and Forecasting-Chemistry (WRF-Chem) model with the revised Gridpoint Statistical Interpolation system and multi-wavelength aerosol optical measurements: the dust aerosol observation campaign at Kashi, near the Taklimakan Desert, northwestern China W. Chang et al. 10.5194/acp-21-4403-2021
- An Observing System Simulation Experiment Framework for Air Quality Forecasts in Northeast Asia: A Case Study Utilizing Virtual Geostationary Environment Monitoring Spectrometer and Surface Monitored Aerosol Data H. Kim et al. 10.3390/rs14020389
- Assimilating Fengyun-4A observations to improve WRF-Chem PM2.5 predictions in China J. Hong et al. 10.1016/j.atmosres.2021.105878
- Improvement of the Aerosol Forecast and Analysis Over East Asia With Joint Assimilation of Two Geostationary Satellite Observations Y. Cheng et al. 10.1029/2022GL099908
- Improved Modeling of Spatiotemporal Variations of Fine Particulate Matter Using a Three‐Dimensional Variational Data Fusion Method X. Zhang et al. 10.1029/2020JD033599
- The Aerosol Module in the Community Radiative Transfer Model (v2.2 and v2.3): accounting for aerosol transmittance effects on the radiance observation operator C. Lu et al. 10.5194/gmd-15-1317-2022
- A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS) R. Kumar et al. 10.5194/essd-17-1807-2025
- Toward Improving Short‐Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals R. Kumar et al. 10.1029/2018JD029009
- Improving WRF-Chem PM2.5 predictions by combining data assimilation and deep-learning-based bias correction X. Ma et al. 10.1016/j.envint.2024.109199
- JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
- Improved PM2.5 predictions of WRF-Chem via the integration of Himawari-8 satellite data and ground observations J. Hong et al. 10.1016/j.envpol.2020.114451
- Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem A. Raman et al. 10.1016/j.atmosenv.2020.118134
- Evaluation of MWHS-2 Using a Co-located Ground-Based Radar Network for Improved Model Assimilation S. Liu et al. 10.3390/rs11202338
- Unveiling 3-D evolution and mechanisms of ozone pollution in Changzhou, China: Insights from lidar observations and modelling Z. Liu et al. 10.1016/j.envpol.2024.124556
- 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
- Impacts of uncertainties in emissions on aerosol data assimilation and short-term PM2.5 predictions over Northeast Asia S. Lee et al. 10.1016/j.atmosenv.2021.118921
- Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM 2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing J. McHenry et al. 10.1080/10962247.2015.1096862
- The impact of multi-species surface chemical observation assimilation on air quality forecasts in China Z. Peng et al. 10.5194/acp-18-17387-2018
- Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
- Using Lidar technology to assess regional air pollution and improve estimates of PM2.5 transport in the North China Plain Y. Xiang et al. 10.1088/1748-9326/ab9cfd
- Limitations of ozone data assimilation with adjustment of NOx emissions: mixed effects on NO2 forecasts over Beijing and surrounding areas X. Tang et al. 10.5194/acp-16-6395-2016
- Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM2.5 concentrations over the North China Plain Y. Xiang et al. 10.5194/acp-21-7023-2021
- Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions R. Žabkar et al. 10.5194/gmd-8-2119-2015
- Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
- Estimation of aerosol properties over the Chinese desert region with MODIS AOD assimilation in a global model X. Yin et al. 10.1016/j.accre.2016.04.001
- A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods Y. Tang et al. 10.5194/gmd-10-4743-2017
- Impact of Assimilating GEMS Aerosol Optical Depth on Asian Dust Storm Prediction: Comparative Assessment with MODIS Observation E. Lee et al. 10.1007/s13143-025-00407-6
- Shipborne lidar measurements of ozone over the southeastern coastal regions of China in winter L. Lv et al. 10.1016/j.envres.2025.121165
- Assimilating a blended dataset of satellite-based estimations and in situ observations to improve WRF-Chem PM2.5 prediction X. Ma et al. 10.1016/j.atmosenv.2023.120284
- The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation S. Wei et al. 10.5194/gmd-17-795-2024
- Satellite imagery and products of the 16–17 February 2020 Saharan Air Layer dust event over the eastern Atlantic: impacts of water vapor on dust detection and morphology L. Grasso et al. 10.5194/amt-14-1615-2021
- Vertical structure and transport characteristic of aerosol and O3 during the emergency control period in Wuhan, China, using vehicle-lidar observations Y. Pan et al. 10.1016/j.atmosenv.2024.120762
2 citations as recorded by crossref.
- Modeling study of a severe aerosol pollution event in December 2013 over Shanghai China: An application of chemical data assimilation J. Wu et al. 10.1016/j.partic.2014.10.008
- Assimilation of PM2.5 ground base observations to two chemical schemes in WRF-Chem – The results for the winter and summer period M. Werner et al. 10.1016/j.atmosenv.2018.12.016
Saved (final revised paper)
Saved (preprint)
Latest update: 02 Nov 2025
