Articles | Volume 17, issue 7
https://doi.org/10.5194/acp-17-4837-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-17-4837-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Improving PM2. 5 forecast over China by the joint adjustment of initial conditions and source emissions with an ensemble Kalman filter
Zhen Peng
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Nanjing University, Nanjing, China
National Center for Atmospheric Research, Boulder, Colorado, USA
National Center for Atmospheric Research, Boulder, Colorado, USA
National Center for Atmospheric Research, Boulder, Colorado, USA
Institute of Urban Meteorology, CMA, Beijing, China
Junmei Ban
National Center for Atmospheric Research, Boulder, Colorado, USA
Viewed
Total article views: 3,998 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 26 Aug 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,628 | 1,261 | 109 | 3,998 | 85 | 124 |
- HTML: 2,628
- PDF: 1,261
- XML: 109
- Total: 3,998
- BibTeX: 85
- EndNote: 124
Total article views: 3,552 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 13 Apr 2017)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,348 | 1,123 | 81 | 3,552 | 66 | 96 |
- HTML: 2,348
- PDF: 1,123
- XML: 81
- Total: 3,552
- BibTeX: 66
- EndNote: 96
Total article views: 446 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 26 Aug 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
280 | 138 | 28 | 446 | 19 | 28 |
- HTML: 280
- PDF: 138
- XML: 28
- Total: 446
- BibTeX: 19
- EndNote: 28
Viewed (geographical distribution)
Total article views: 3,998 (including HTML, PDF, and XML)
Thereof 3,964 with geography defined
and 34 with unknown origin.
Total article views: 3,552 (including HTML, PDF, and XML)
Thereof 3,525 with geography defined
and 27 with unknown origin.
Total article views: 446 (including HTML, PDF, and XML)
Thereof 439 with geography defined
and 7 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
62 citations as recorded by crossref.
- Revealing the sulfur dioxide emission reductions in China by assimilating surface observations in WRF-Chem T. Dai et al. 10.5194/acp-21-4357-2021
- Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions S. Li et al. 10.5194/gmd-16-4171-2023
- Length Scale Analyses of Background Error Covariances for EnKF and EnSRF Data Assimilation S. Park et al. 10.3390/atmos13020160
- Multi-scale three-dimensional variational data assimilation for high-resolution aerosol observations: Methodology and application Z. Zang et al. 10.1007/s11430-022-9974-4
- Wildfire aerosols and their impact on weather: A case study of the August 2021 fires in Greece using the WRF‐Chem model A. Rovithakis & A. Voulgarakis 10.1002/asl.1267
- Development of a three-dimensional variational assimilation system for lidar profile data based on a size-resolved aerosol model in WRF–Chem model v3.9.1 and its application in PM<sub>2.5</sub> forecasts across China Y. Liang et al. 10.5194/gmd-13-6285-2020
- Development of Three‐Dimensional Variational Data Assimilation Method of Aerosol for the CMAQ Model: An Application for PM2.5 and PM10 Forecasts in the Sichuan Basin Z. Zhang et al. 10.1029/2020EA001614
- Impact of model resolution and its representativeness consistency with observations on operational prediction of PM2.5 with 3D-VAR data assimilation Y. Wei et al. 10.1016/j.apr.2024.102141
- Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
- Air Quality Forecasting with Inversely Updated Emissions for China H. Wu et al. 10.1021/acs.estlett.3c00266
- The optical properties, physical properties and direct radiative forcing of urban columnar aerosols in the Yangtze River Delta, China B. Zhuang et al. 10.5194/acp-18-1419-2018
- Impact of 3DVAR assimilation of surface PM2.5 observations on PM2.5 forecasts over China during wintertime S. Feng et al. 10.1016/j.atmosenv.2018.05.049
- The impacts of background error covariance on particulate matter assimilation and forecast: An ideal case study with a modal aerosol model over China J. Pang & X. Wang 10.1016/j.scitotenv.2021.147417
- Ozone variability and the impacts of associated synoptic patterns over China during summer 2016–2020 based on a regional atmospheric composition reanalysis dataset X. Kou et al. 10.1016/j.atmosenv.2024.120919
- Impact of Assimilating Meteorological Observations on Source Emissions Estimate and Chemical Simulations Z. Peng et al. 10.1029/2020GL089030
- The optimization of SO2 emissions by the 4DVAR and EnKF methods and its application in WRF-Chem Y. Hu et al. 10.1016/j.scitotenv.2023.163796
- 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
- Assessment of the Meteorological Impact on Improved PM2.5 Air Quality Over North China During 2016–2019 Based on a Regional Joint Atmospheric Composition Reanalysis Data‐Set X. Kou et al. 10.1029/2020JD034382
- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
- Multiconstituent Data Assimilation With WRF‐Chem/DART: Potential for Adjusting Anthropogenic Emissions and Improving Air Quality Forecasts Over Eastern China C. Ma et al. 10.1029/2019JD030421
- An improved PM2.5 forecasting method based on correlation denoising and ensemble learning strategy Z. Zhang & D. Xia 10.1007/s13762-022-04525-w
- Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic K. Han et al. 10.3390/app11041959
- The carbon sink in China as seen from GOSAT with a regional inversion system based on the Community Multi-scale Air Quality (CMAQ) and ensemble Kalman smoother (EnKS) X. Kou et al. 10.5194/acp-23-6719-2023
- Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast J. Bi et al. 10.1021/acs.est.1c05578
- 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
- Assessing the assimilation of Himawari-8 observations on aerosol forecasts and radiative effects during pollution transport from South Asia to the Tibetan Plateau M. Zhao et al. 10.5194/acp-24-235-2024
- The 2015 and 2016 wintertime air pollution in China: SO<sub>2</sub> emission changes derived from a WRF-Chem/EnKF coupled data assimilation system D. Chen et al. 10.5194/acp-19-8619-2019
- Development and application of a hybrid long-short term memory – three dimensional variational technique for the improvement of PM2.5 forecasting X. Lu et al. 10.1016/j.scitotenv.2020.144221
- An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. 10.5194/gmd-15-3555-2022
- 3DVAR Aerosol Data Assimilation and Evaluation Using Surface PM2.5, Himawari-8 AOD and CALIPSO Profile Observations in the North China Z. Zang et al. 10.3390/rs14164009
- A 6-year-long (2013–2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC L. Kong et al. 10.5194/essd-13-529-2021
- Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods U. Dash et al. 10.1016/j.envpol.2023.121099
- Observing system simulation experiment (OSSE)-quantitative evaluation of lidar observation networks to improve 3D aerosol forecasting in China H. Ye et al. 10.1016/j.atmosres.2022.106069
- Toward targeted observations of the meteorological initial state for improving the PM2.5forecast of a heavy haze event that occurred in the Beijing–Tianjin–Hebei region L. Yang et al. 10.5194/acp-22-11429-2022
- Regional pollution loading in winter months over India using high resolution WRF-Chem simulation R. Jat et al. 10.1016/j.atmosres.2020.105326
- Inverting the East Asian Dust Emission Fluxes Using the Ensemble Kalman Smoother and Himawari-8 AODs: A Case Study with WRF-Chem v3.5.1 T. Dai et al. 10.3390/atmos10090543
- RETRACTED ARTICLE: Soil erosion and regional industrial upgrading in the Yangtze River surrounding area based on ecological evaluation Y. Jiajia et al. 10.1007/s12517-021-07354-2
- 基于高分辨率气溶胶观测资料的多尺度三维变分同化及预报 增. 臧 et al. 10.1360/SSTe-2022-0026
- Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman smoother: observing system simulation experiments (OSSEs) A. Tsikerdekis et al. 10.5194/gmd-15-3253-2022
- Improvement of PM2.5 forecast over China by the joint adjustment of initial conditions and emissions with the NLS-4DVar method S. Zhang et al. 10.1016/j.atmosenv.2021.118896
- Combined effect of surface PM2.5 assimilation and aerosol-radiation interaction on winter severe haze prediction in central and eastern China Y. Peng et al. 10.1016/j.apr.2023.101802
- RETRACTED ARTICLE: Evaluation of agricultural climate and regional agricultural economic efficiency based on remote sensing analysis X. Lu 10.1007/s12517-021-07153-9
- Seasonal Dependence of Aerosol Data Assimilation and Forecasting Using Satellite and Ground-Based Observations S. Lee et al. 10.3390/rs14092123
- Global Scale Inversions from MOPITT CO and MODIS AOD B. Gaubert et al. 10.3390/rs15194813
- Dynamics-based estimates of decline trend with fine temporal variations in China's PM2.5 emissions Z. Peng et al. 10.5194/acp-23-14505-2023
- Quantifying the impact of particle matter on mortality and hospitalizations in four Brazilian metropolitan areas W. Andreão et al. 10.1016/j.jenvman.2020.110840
- Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China Y. Hu et al. 10.5194/acp-22-13183-2022
- Improving PM2.5 predictions during COVID-19 lockdown by assimilating multi-source observations and adjusting emissions L. Chen et al. 10.1016/j.envpol.2021.118783
- Assimilating Himawari-8 AHI aerosol observations with a rapid-update data assimilation system X. Xia et al. 10.1016/j.atmosenv.2019.116866
- Assimilating AOD retrievals from GOCI and VIIRS to forecast surface PM2.5 episodes over Eastern China J. Pang et al. 10.1016/j.atmosenv.2018.02.011
- Development and application of the WRFDA-Chem three-dimensional variational (3DVAR) system: aiming to improve air quality forecasting and diagnose model deficiencies W. Sun et al. 10.5194/acp-20-9311-2020
- Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM<sub>2.5</sub> S. Park et al. 10.5194/gmd-15-2773-2022
- A new approach for optimizing air pollutant emissions using Newtonian relaxation and the coupled WRF-CAMx model: a case study in Xuzhou city, China Y. Li et al. 10.1007/s12517-020-06002-5
- Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model J. Moon et al. 10.1016/j.atmosenv.2024.120490
- A Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) for emission estimates: system development and application S. Feng et al. 10.5194/gmd-16-5949-2023
- Human mortality attributable to outdoor air pollution in China during the period 2016–2020 G. Liu et al. 10.1088/2752-5309/acd3a0
- Evaluating the Impact of Emissions Regulations on the Emissions Reduction During the 2015 China Victory Day Parade With an Ensemble Square Root Filter K. Chu et al. 10.1002/2017JD027631
- Top-down vehicle emission inventory for spatial distribution and dispersion modeling of particulate matter W. Andreão et al. 10.1007/s11356-020-08476-y
- A nonlinear least squares four-dimensional variational data assimilation system for PM2.5 forecasts (NASM): Description and preliminary evaluation S. Zhang et al. 10.1016/j.apr.2021.03.003
- Assimilation of Aerosol Optical Depth Into the Warn‐on‐Forecast System for Smoke (WoFS‐Smoke) T. Jones et al. 10.1029/2022JD037454
- A new inverse modeling approach for emission sources based on the DDM-3D and 3DVAR techniques: an application to air quality forecasts in the Beijing–Tianjin–Hebei region X. Cheng et al. 10.5194/acp-21-13747-2021
- Aerosol optical depth assimilation for a modal aerosol model: Implementation and application in AOD forecasts over East Asia J. Pang et al. 10.1016/j.scitotenv.2020.137430
62 citations as recorded by crossref.
- Revealing the sulfur dioxide emission reductions in China by assimilating surface observations in WRF-Chem T. Dai et al. 10.5194/acp-21-4357-2021
- Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions S. Li et al. 10.5194/gmd-16-4171-2023
- Length Scale Analyses of Background Error Covariances for EnKF and EnSRF Data Assimilation S. Park et al. 10.3390/atmos13020160
- Multi-scale three-dimensional variational data assimilation for high-resolution aerosol observations: Methodology and application Z. Zang et al. 10.1007/s11430-022-9974-4
- Wildfire aerosols and their impact on weather: A case study of the August 2021 fires in Greece using the WRF‐Chem model A. Rovithakis & A. Voulgarakis 10.1002/asl.1267
- Development of a three-dimensional variational assimilation system for lidar profile data based on a size-resolved aerosol model in WRF–Chem model v3.9.1 and its application in PM<sub>2.5</sub> forecasts across China Y. Liang et al. 10.5194/gmd-13-6285-2020
- Development of Three‐Dimensional Variational Data Assimilation Method of Aerosol for the CMAQ Model: An Application for PM2.5 and PM10 Forecasts in the Sichuan Basin Z. Zhang et al. 10.1029/2020EA001614
- Impact of model resolution and its representativeness consistency with observations on operational prediction of PM2.5 with 3D-VAR data assimilation Y. Wei et al. 10.1016/j.apr.2024.102141
- Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
- Air Quality Forecasting with Inversely Updated Emissions for China H. Wu et al. 10.1021/acs.estlett.3c00266
- The optical properties, physical properties and direct radiative forcing of urban columnar aerosols in the Yangtze River Delta, China B. Zhuang et al. 10.5194/acp-18-1419-2018
- Impact of 3DVAR assimilation of surface PM2.5 observations on PM2.5 forecasts over China during wintertime S. Feng et al. 10.1016/j.atmosenv.2018.05.049
- The impacts of background error covariance on particulate matter assimilation and forecast: An ideal case study with a modal aerosol model over China J. Pang & X. Wang 10.1016/j.scitotenv.2021.147417
- Ozone variability and the impacts of associated synoptic patterns over China during summer 2016–2020 based on a regional atmospheric composition reanalysis dataset X. Kou et al. 10.1016/j.atmosenv.2024.120919
- Impact of Assimilating Meteorological Observations on Source Emissions Estimate and Chemical Simulations Z. Peng et al. 10.1029/2020GL089030
- The optimization of SO2 emissions by the 4DVAR and EnKF methods and its application in WRF-Chem Y. Hu et al. 10.1016/j.scitotenv.2023.163796
- 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
- Assessment of the Meteorological Impact on Improved PM2.5 Air Quality Over North China During 2016–2019 Based on a Regional Joint Atmospheric Composition Reanalysis Data‐Set X. Kou et al. 10.1029/2020JD034382
- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
- Multiconstituent Data Assimilation With WRF‐Chem/DART: Potential for Adjusting Anthropogenic Emissions and Improving Air Quality Forecasts Over Eastern China C. Ma et al. 10.1029/2019JD030421
- An improved PM2.5 forecasting method based on correlation denoising and ensemble learning strategy Z. Zhang & D. Xia 10.1007/s13762-022-04525-w
- Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic K. Han et al. 10.3390/app11041959
- The carbon sink in China as seen from GOSAT with a regional inversion system based on the Community Multi-scale Air Quality (CMAQ) and ensemble Kalman smoother (EnKS) X. Kou et al. 10.5194/acp-23-6719-2023
- Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast J. Bi et al. 10.1021/acs.est.1c05578
- 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
- Assessing the assimilation of Himawari-8 observations on aerosol forecasts and radiative effects during pollution transport from South Asia to the Tibetan Plateau M. Zhao et al. 10.5194/acp-24-235-2024
- The 2015 and 2016 wintertime air pollution in China: SO<sub>2</sub> emission changes derived from a WRF-Chem/EnKF coupled data assimilation system D. Chen et al. 10.5194/acp-19-8619-2019
- Development and application of a hybrid long-short term memory – three dimensional variational technique for the improvement of PM2.5 forecasting X. Lu et al. 10.1016/j.scitotenv.2020.144221
- An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. 10.5194/gmd-15-3555-2022
- 3DVAR Aerosol Data Assimilation and Evaluation Using Surface PM2.5, Himawari-8 AOD and CALIPSO Profile Observations in the North China Z. Zang et al. 10.3390/rs14164009
- A 6-year-long (2013–2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC L. Kong et al. 10.5194/essd-13-529-2021
- Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods U. Dash et al. 10.1016/j.envpol.2023.121099
- Observing system simulation experiment (OSSE)-quantitative evaluation of lidar observation networks to improve 3D aerosol forecasting in China H. Ye et al. 10.1016/j.atmosres.2022.106069
- Toward targeted observations of the meteorological initial state for improving the PM2.5forecast of a heavy haze event that occurred in the Beijing–Tianjin–Hebei region L. Yang et al. 10.5194/acp-22-11429-2022
- Regional pollution loading in winter months over India using high resolution WRF-Chem simulation R. Jat et al. 10.1016/j.atmosres.2020.105326
- Inverting the East Asian Dust Emission Fluxes Using the Ensemble Kalman Smoother and Himawari-8 AODs: A Case Study with WRF-Chem v3.5.1 T. Dai et al. 10.3390/atmos10090543
- RETRACTED ARTICLE: Soil erosion and regional industrial upgrading in the Yangtze River surrounding area based on ecological evaluation Y. Jiajia et al. 10.1007/s12517-021-07354-2
- 基于高分辨率气溶胶观测资料的多尺度三维变分同化及预报 增. 臧 et al. 10.1360/SSTe-2022-0026
- Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman smoother: observing system simulation experiments (OSSEs) A. Tsikerdekis et al. 10.5194/gmd-15-3253-2022
- Improvement of PM2.5 forecast over China by the joint adjustment of initial conditions and emissions with the NLS-4DVar method S. Zhang et al. 10.1016/j.atmosenv.2021.118896
- Combined effect of surface PM2.5 assimilation and aerosol-radiation interaction on winter severe haze prediction in central and eastern China Y. Peng et al. 10.1016/j.apr.2023.101802
- RETRACTED ARTICLE: Evaluation of agricultural climate and regional agricultural economic efficiency based on remote sensing analysis X. Lu 10.1007/s12517-021-07153-9
- Seasonal Dependence of Aerosol Data Assimilation and Forecasting Using Satellite and Ground-Based Observations S. Lee et al. 10.3390/rs14092123
- Global Scale Inversions from MOPITT CO and MODIS AOD B. Gaubert et al. 10.3390/rs15194813
- Dynamics-based estimates of decline trend with fine temporal variations in China's PM2.5 emissions Z. Peng et al. 10.5194/acp-23-14505-2023
- Quantifying the impact of particle matter on mortality and hospitalizations in four Brazilian metropolitan areas W. Andreão et al. 10.1016/j.jenvman.2020.110840
- Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China Y. Hu et al. 10.5194/acp-22-13183-2022
- Improving PM2.5 predictions during COVID-19 lockdown by assimilating multi-source observations and adjusting emissions L. Chen et al. 10.1016/j.envpol.2021.118783
- Assimilating Himawari-8 AHI aerosol observations with a rapid-update data assimilation system X. Xia et al. 10.1016/j.atmosenv.2019.116866
- Assimilating AOD retrievals from GOCI and VIIRS to forecast surface PM2.5 episodes over Eastern China J. Pang et al. 10.1016/j.atmosenv.2018.02.011
- Development and application of the WRFDA-Chem three-dimensional variational (3DVAR) system: aiming to improve air quality forecasting and diagnose model deficiencies W. Sun et al. 10.5194/acp-20-9311-2020
- Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM<sub>2.5</sub> S. Park et al. 10.5194/gmd-15-2773-2022
- A new approach for optimizing air pollutant emissions using Newtonian relaxation and the coupled WRF-CAMx model: a case study in Xuzhou city, China Y. Li et al. 10.1007/s12517-020-06002-5
- Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model J. Moon et al. 10.1016/j.atmosenv.2024.120490
- A Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) for emission estimates: system development and application S. Feng et al. 10.5194/gmd-16-5949-2023
- Human mortality attributable to outdoor air pollution in China during the period 2016–2020 G. Liu et al. 10.1088/2752-5309/acd3a0
- Evaluating the Impact of Emissions Regulations on the Emissions Reduction During the 2015 China Victory Day Parade With an Ensemble Square Root Filter K. Chu et al. 10.1002/2017JD027631
- Top-down vehicle emission inventory for spatial distribution and dispersion modeling of particulate matter W. Andreão et al. 10.1007/s11356-020-08476-y
- A nonlinear least squares four-dimensional variational data assimilation system for PM2.5 forecasts (NASM): Description and preliminary evaluation S. Zhang et al. 10.1016/j.apr.2021.03.003
- Assimilation of Aerosol Optical Depth Into the Warn‐on‐Forecast System for Smoke (WoFS‐Smoke) T. Jones et al. 10.1029/2022JD037454
- A new inverse modeling approach for emission sources based on the DDM-3D and 3DVAR techniques: an application to air quality forecasts in the Beijing–Tianjin–Hebei region X. Cheng et al. 10.5194/acp-21-13747-2021
- Aerosol optical depth assimilation for a modal aerosol model: Implementation and application in AOD forecasts over East Asia J. Pang et al. 10.1016/j.scitotenv.2020.137430
Latest update: 20 Nov 2024
Short summary
In order to improve the forecasting of atmospheric aerosols over China, the ensemble square root filter algorithm was extended to simultaneously optimize the chemical initial conditions and primary and precursor emissions. This system was applied to assimilate hourly surface PM2.5 measurements. The forecasts with the optimized initial conditions and emissions typically outperformed those from the control experiment without data assimilation.
In order to improve the forecasting of atmospheric aerosols over China, the ensemble square root...
Altmetrics
Final-revised paper
Preprint