64 citations as recorded by crossref.

1. 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
2. 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
3. Length Scale Analyses of Background Error Covariances for EnKF and EnSRF Data Assimilation S. Park et al. 10.3390/atmos13020160
4. 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
5. 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
6. 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 PM2.5 forecasts across China Y. Liang et al. 10.5194/gmd-13-6285-2020
7. 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
8. 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
9. Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
10. Air Quality Forecasting with Inversely Updated Emissions for China H. Wu et al. 10.1021/acs.estlett.3c00266
11. 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
12. 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
13. 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
14. 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
15. Impact of Assimilating Meteorological Observations on Source Emissions Estimate and Chemical Simulations Z. Peng et al. 10.1029/2020GL089030
16. 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
17. 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
18. 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
19. Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
20. 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
21. An improved PM2.5 forecasting method based on correlation denoising and ensemble learning strategy Z. Zhang & D. Xia 10.1007/s13762-022-04525-w
22. Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic K. Han et al. 10.3390/app11041959
23. 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
24. Impacts of meteorological conditions on the NASM pollution data assimilation system S. Zhang et al. 10.1016/j.aosl.2024.100586
25. Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast J. Bi et al. 10.1021/acs.est.1c05578
26. 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
27. 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
28. 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
29. The 2015 and 2016 wintertime air pollution in China: SO2 emission changes derived from a WRF-Chem/EnKF coupled data assimilation system D. Chen et al. 10.5194/acp-19-8619-2019
30. 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
31. An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. 10.5194/gmd-15-3555-2022
32. 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
33. 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
34. 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
35. 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
36. Toward targeted observations of the meteorological initial state for improving the PM2.5 forecast of a heavy haze event that occurred in the Beijing–Tianjin–Hebei region L. Yang et al. 10.5194/acp-22-11429-2022
37. Regional pollution loading in winter months over India using high resolution WRF-Chem simulation R. Jat et al. 10.1016/j.atmosres.2020.105326
38. 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
39. 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
40. 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
41. 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
42. 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
43. 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
44. RETRACTED ARTICLE: Evaluation of agricultural climate and regional agricultural economic efficiency based on remote sensing analysis X. Lu 10.1007/s12517-021-07153-9
45. Seasonal Dependence of Aerosol Data Assimilation and Forecasting Using Satellite and Ground-Based Observations S. Lee et al. 10.3390/rs14092123
46. Global Scale Inversions from MOPITT CO and MODIS AOD B. Gaubert et al. 10.3390/rs15194813
47. 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
48. 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
49. 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
50. 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
51. Assimilating Himawari-8 AHI aerosol observations with a rapid-update data assimilation system X. Xia et al. 10.1016/j.atmosenv.2019.116866
52. 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
53. 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
54. Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM2.5 S. Park et al. 10.5194/gmd-15-2773-2022
55. 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
56. 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
57. 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
58. Human mortality attributable to outdoor air pollution in China during the period 2016–2020 G. Liu et al. 10.1088/2752-5309/acd3a0
59. 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
60. Top-down vehicle emission inventory for spatial distribution and dispersion modeling of particulate matter W. Andreão et al. 10.1007/s11356-020-08476-y
61. 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
62. Assimilation of Aerosol Optical Depth Into the Warn‐on‐Forecast System for Smoke (WoFS‐Smoke) T. Jones et al. 10.1029/2022JD037454
63. 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
64. 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