66 citations as recorded by crossref.

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2. Aerosol Data Assimilation Using Data from Fengyun-3A and MODIS: Application to a Dust Storm over East Asia in 2011 X. Xia et al. 10.1007/s00376-018-8075-9
3. 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
4. Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. 10.1029/2019JD031465
5. Aerosol analysis and forecast in the European Centre for Medium‐Range Weather Forecasts Integrated Forecast System: 2. Data assimilation A. Benedetti et al. 10.1029/2008JD011115
6. Lidar data assimilation method based on CRTM and WRF-Chem models and its application in PM2.5 forecasts in Beijing X. Cheng et al. 10.1016/j.scitotenv.2019.05.186
7. Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. 10.5194/amt-13-4645-2020
8. Identifying chemical aerosol signatures using optical suborbital observations: how much can optical properties tell us about aerosol composition? M. Kacenelenbogen et al. 10.5194/acp-22-3713-2022
9. PM10 data assimilation over south Korea to Asian dust forecasting model with the optimal interpolation method E. Lee et al. 10.1007/s13143-013-0009-y
10. Dust storm forecasting through coupling LOTOS-EUROS with localized ensemble Kalman filter M. Pang et al. 10.1016/j.atmosenv.2023.119831
11. Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0 J. Jin et al. 10.5194/gmd-14-5607-2021
12. Assessment of meteorology vs. control measures in the China fine particular matter trend from 2013 to 2019 by an environmental meteorology index S. Gong et al. 10.5194/acp-21-2999-2021
13. Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0 E. Di Tomaso et al. 10.5194/gmd-10-1107-2017
14. Spatially varying parameter estimation for dust emissions using reduced-tangent-linearization 4DVar J. Jin et al. 10.1016/j.atmosenv.2018.05.060
15. Sensitivity studies of aerosol data assimilation and direct radiative feedbacks in modeling dust aerosols H. Wang & T. Niu 10.1016/j.atmosenv.2012.09.066
16. Data assimilation of CALIPSO aerosol observations T. Sekiyama et al. 10.5194/acp-10-39-2010
17. Sensitivity tests for an ensemble Kalman filter for aerosol assimilation N. Schutgens et al. 10.5194/acp-10-6583-2010
18. Assessment of regional aerosol radiative effects under the SWAAMI campaign – Part 1: Quality-enhanced estimation of columnar aerosol extinction and absorption over the Indian subcontinent H. Pathak et al. 10.5194/acp-19-11865-2019
19. Models transport Saharan dust too low in the atmosphere: a comparison of the MetUM and CAMS forecasts with observations D. O'Sullivan et al. 10.5194/acp-20-12955-2020
20. The variability of spring sand-dust storm frequency in Northeast Asia from 1980 to 2011 Y. Yang et al. 10.1007/s13351-013-0112-0
21. Effects of data assimilation on the global aerosol key optical properties simulations X. Yin et al. 10.1016/j.atmosres.2016.03.016
22. The value of satellite observations in the analysis and short-range prediction of Asian dust A. Benedetti et al. 10.5194/acp-19-987-2019
23. 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
24. Study on the applicability of key parameters from dust emission scheme in WRF/Chem over northwestern China W. Zhao et al. 10.1088/1755-1315/358/2/022058
25. Dust storm ensemble forecast experiments in East Asia J. Zhu et al. 10.1007/s00376-009-8218-0
26. Observation operator for the assimilation of aerosol type resolving satellite measurements into a chemical transport model M. Schroedter-Homscheidt et al. 10.5194/acp-10-10435-2010
27. Online coupled regional meteorology chemistry models in Europe: current status and prospects A. Baklanov et al. 10.5194/acp-14-317-2014
28. 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
29. Assimilation of ground versus lidar observations for PM<sub>10</sub> forecasting Y. Wang et al. 10.5194/acp-13-269-2013
30. 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
31. Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth B. Sič et al. 10.5194/amt-9-5535-2016
32. 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
33. Inverse modeling of the 2021 spring super dust storms in East Asia J. Jin et al. 10.5194/acp-22-6393-2022
34. Aerosol forecast over the Mediterranean area during July 2013 (ADRIMED/CHARMEX) L. Menut et al. 10.5194/acp-15-7897-2015
35. 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
36. Background error statistics for aerosol variables from WRF/Chem predictions in Southern California Z. Zang et al. 10.1007/s13143-015-0063-8
37. An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature J. Zhang et al. 10.5194/acp-16-6475-2016
38. Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
39. Machine learning for observation bias correction with application to dust storm data assimilation J. Jin et al. 10.5194/acp-19-10009-2019
40. Improvement of aerosol optical properties modeling over Eastern Asia with MODIS AOD assimilation in a global non-hydrostatic icosahedral aerosol transport model T. Dai et al. 10.1016/j.envpol.2014.06.021
41. A hybrid XGBoost-SMOTE model for optimization of operational air quality numerical model forecasts H. Ke et al. 10.3389/fenvs.2022.1007530
42. Utilizing Cloud Computing to address big geospatial data challenges C. Yang et al. 10.1016/j.compenvurbsys.2016.10.010
43. Forecasting of Asian dust storm that occurred on May 10–13, 2011, using an ensemble-based data assimilation system K. Yumimoto et al. 10.1016/j.partic.2015.09.001
44. Assessing the impact of Chinese FY-3/MERSI AOD data assimilation on air quality forecasts: Sand dust events in northeast China Y. Bao et al. 10.1016/j.atmosenv.2019.02.026
45. Applying an ensemble Kalman filter to the assimilation of AERONET observations in a global aerosol transport model N. Schutgens et al. 10.5194/acp-10-2561-2010
46. 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
47. Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin Y. Wang et al. 10.5194/acp-14-12031-2014
48. 3D assimilation and radiative impact assessment of aerosol black carbon over the Indian region using aircraft, balloon, ground-based, and multi-satellite observations N. Kala et al. 10.5194/acp-23-12801-2023
49. A 3D multi-threshold, region-growing algorithm for identifying dust storm features from model simulations M. Yu & C. Yang 10.1080/13658816.2016.1250900
50. Real-time air quality forecasting, part II: State of the science, current research needs, and future prospects Y. Zhang et al. 10.1016/j.atmosenv.2012.02.041
51. Real-time air quality forecasting, part I: History, techniques, and current status Y. Zhang et al. 10.1016/j.atmosenv.2012.06.031
52. Dust Model Intercomparison Between ADAM and CFORS/Dust For Asian Dust Case in 2007 (March 28 - April 3) S. Kim et al. 10.2151/sola.7A-007
53. Numerical simulation and evaluation of Asian dust events observed in Mongolia in spring 2011 E. Lee et al. 10.1007/s13143-013-0012-3
54. Numerical Studies on a Severe Dust Storm in East Asia Using WRF-Chem X. Yu et al. 10.4236/acs.2017.71008
55. Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia Z. Liu et al. 10.1029/2011JD016159
56. Dust Emission Inversion Using Himawari‐8 AODs Over East Asia: An Extreme Dust Event in May 2017 J. Jin et al. 10.1029/2018MS001491
57. Simultaneous assimilation of Fengyun-4A and Himawari-8 aerosol optical depth retrieval to improve air quality simulations during one storm event over East Asia X. Xia et al. 10.3389/feart.2023.1057299
58. 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
59. Enhancement of OMI aerosol optical depth data assimilation using artificial neural network A. Ali et al. 10.1007/s00521-012-1178-9
60. Surface observation of sand and dust storm in East Asia and its application in CUACE/Dust Y. Wang et al. 10.5194/acp-8-545-2008
61. RETRACTED ARTICLE: On using stacked neural network for multi-sensor data merging to enhance aerosol data assimilation A. Ali et al. 10.1007/s00521-012-1318-2
62. A regional scale chemical transport modeling of Asian aerosols with data assimilation of AOD observations using optimal interpolation technique B. Adhikary et al. 10.1016/j.atmosenv.2008.08.031
63. Development and evaluation of an operational SDS forecasting system for East Asia: CUACE/Dust C. Zhou et al. 10.5194/acp-8-787-2008
64. Estimates of Health Impacts and Radiative Forcing in Winter Haze in Eastern China through Constraints of Surface PM2.5 Predictions M. Gao et al. 10.1021/acs.est.6b03745
65. Operational retrieval of Asian sand and dust storm from FY-2C geostationary meteorological satellite and its application to real time forecast in Asia X. Hu et al. 10.5194/acp-8-1649-2008
66. A three-dimensional variational data assimilation system for a size-resolved aerosol model: Implementation and application for particulate matter and gaseous pollutant forecasts across China D. Wang et al. 10.1007/s11430-019-9601-4