85 citations as recorded by crossref.

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2. Assimilation of Both Column‐ and Layer‐Integrated Dust Opacity Observations in the Martian Atmosphere T. Ruan et al. 10.1029/2021EA001869
3. Comparison of dust optical depth from multi-sensor products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) dust reanalysis over North Africa, the Middle East, and Europe M. Mytilinaios et al. 10.5194/acp-23-5487-2023
4. 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
5. 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
6. Efficient ensemble generation for uncertain correlated parameters in atmospheric chemical models: a case study for biogenic emissions from EURAD-IM version 5 A. Vogel & H. Elbern 10.5194/gmd-14-5583-2021
7. Effects of data assimilation on the global aerosol key optical properties simulations X. Yin et al. 10.1016/j.atmosres.2016.03.016
8. The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation C. Randles et al. 10.1175/JCLI-D-16-0609.1
9. Improving estimation of a record-breaking east Asian dust storm emission with lagged aerosol Ångström exponent observations Y. Cheng et al. 10.5194/acp-24-12643-2024
10. Air pollution in Asia K. Vadrevu et al. 10.1016/j.envpol.2014.09.006
11. Estimating Aerosol Emissions by Assimilating Remote Sensing Observations into a Global Transport Model N. Schutgens et al. 10.3390/rs4113528
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13. Ensemble filter based estimation of spatially distributed parameters in a mesoscale dust model: experiments with simulated and real data V. Khade et al. 10.5194/acp-13-3481-2013
14. Implementation of aerosol assimilation in Gridpoint Statistical Interpolation (v. 3.2) and WRF-Chem (v. 3.4.1) M. Pagowski et al. 10.5194/gmd-7-1621-2014
15. Development of the Ensemble Navy Aerosol Analysis Prediction System (ENAAPS) and its application of the Data Assimilation Research Testbed (DART) in support of aerosol forecasting J. Rubin et al. 10.5194/acp-16-3927-2016
16. Distributed input observers to integrate satellite data with 3-D atmospheric models D. McGuffin et al. 10.1016/j.compchemeng.2019.106525
17. 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
18. Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. 10.1016/j.jes.2022.04.012
19. Aerosol optical depth assimilation for a size-resolved sectional model: impacts of observationally constrained, multi-wavelength and fine mode retrievals on regional scale analyses and forecasts P. Saide et al. 10.5194/acp-13-10425-2013
20. Assimilating spaceborne lidar dust extinction can improve dust forecasts J. Escribano et al. 10.5194/acp-22-535-2022
21. 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
22. Bayesian Merging of MISR and MODIS Aerosol Optical Depth Products Using Error Distributions From AERONET M. Singh et al. 10.1109/JSTARS.2017.2734331
23. 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
24. Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
25. Application of Optimal Interpolation to Spatially and Temporally Sparse Observations of Aerosol Optical Depth N. Miatselskaya et al. 10.3390/atmos14010032
26. A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations D. Wang et al. 10.5194/gmd-15-1821-2022
27. Optimal Interpolation of Aeronet Radiometric Network Observations for the Evaluation of the Aerosol Optical Thickness Distribution in the Eastern European Region N. Miatselskaya et al. 10.1007/s10812-022-01357-x
28. JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
29. 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
30. 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
31. Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts M. Gonçalves Ageitos et al. 10.5194/acp-23-8623-2023
32. 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
33. Chemical Data Assimilation—An Overview A. Sandu & T. Chai 10.3390/atmos2030426
34. Impact of assimilating NOAA VIIRS aerosol optical depth (AOD) observations on global AOD analysis from the Copernicus Atmosphere Monitoring Service (CAMS) S. Garrigues et al. 10.5194/acp-23-10473-2023
35. 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
36. Development of an Ozone Monitoring Instrument (OMI) aerosol index (AI) data assimilation scheme for aerosol modeling over bright surfaces – a step toward direct radiance assimilation in the UV spectrum J. Zhang et al. 10.5194/gmd-14-27-2021
37. Global aerosol model-derived black carbon concentration and single scattering albedo over Indian region and its comparison with ground observations D. Goto et al. 10.1016/j.atmosenv.2011.03.037
38. Aerosol data assimilation using data from Himawari‐8, a next‐generation geostationary meteorological satellite K. Yumimoto et al. 10.1002/2016GL069298
39. Mesoscale Data Assimilation for a Local Severe Rainfall Event with the NHM–LETKF System M. Kunii 10.1175/WAF-D-13-00032.1
40. Long-term variations of global dust emissions and climate control N. Wang & Y. Zhang 10.1016/j.envpol.2023.122847
41. Multiple site ground-based evaluation of carbonaceous aerosol mass concentrations retrieved from CAMS and MERRA-2 over the Indo-Gangetic Plain A. Soni et al. 10.1039/D1EA00067E
42. 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
43. 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
44. Sensitivity tests for an ensemble Kalman filter for aerosol assimilation N. Schutgens et al. 10.5194/acp-10-6583-2010
45. A review of aerosol optical properties and radiative effects Y. Liu et al. 10.1007/s13351-014-4045-z
46. Evaluating the impact of assimilating CALIOP-derived aerosol extinction profiles on a global mass transport model J. Zhang et al. 10.1029/2011GL047737
47. 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
48. OPTIMAL INTERPOLATION OF AERONET RADIOMETRIC NETWORK OBSERVATIONS FOR THE EVALUATION OF THE AEROSOL OPTICAL DEPTH DISTRIBUTION IN THE EASTERN EUROPEAN REGION N. Miatselskaya et al. 10.47612/0514-7506-2022-89-2-246-253
49. Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic K. Han et al. 10.3390/app11041959
50. The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016) E. Di Tomaso et al. 10.5194/essd-14-2785-2022
51. Mineral dust cycle in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) Version 2.0 M. Klose et al. 10.5194/gmd-14-6403-2021
52. 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
53. A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model L. El Amraoui et al. 10.3390/rs14081949
54. An offline constrained data assimilation technique for aerosols: Improving GCM simulations over South Asia using observations from two satellite sensors A. Baraskar et al. 10.1016/j.atmosenv.2016.02.026
55. 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
56. 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
57. Influence of aerosols and thin cirrus clouds on the GOSAT-observed CO<sub>2</sub>: a case study over Tsukuba O. Uchino et al. 10.5194/acp-12-3393-2012
58. Wind for Transporting Materials—Transport Processes of Aerosols in the Atmosphere— T. TAKEMURA 10.5359/jawe.37.192
59. 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
60. Global Scale Inversions from MOPITT CO and MODIS AOD B. Gaubert et al. 10.3390/rs15194813
61. An advanced retrieval algorithm for greenhouse gases using polarization information measured by GOSAT TANSO‐FTS SWIR I: Simulation study N. Kikuchi et al. 10.1002/2015JD024720
62. RETRACTED ARTICLE: Evaluation of agricultural climate and regional agricultural economic efficiency based on remote sensing analysis X. Lu 10.1007/s12517-021-07153-9
63. Simulated aerosol key optical properties over global scale using an aerosol transport model coupled with a new type of dynamic core T. Dai et al. 10.1016/j.atmosenv.2013.10.018
64. African dust particles over the western Caribbean – Part I: Impact on air quality over the Yucatán Peninsula C. Ramírez-Romero et al. 10.5194/acp-21-239-2021
65. Assimilating aerosol optical properties related to size and absorption from POLDER/PARASOL with an ensemble data assimilation system A. Tsikerdekis et al. 10.5194/acp-21-2637-2021
66. Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin Y. Wang et al. 10.5194/acp-14-12031-2014
67. Investigating the assimilation of CALIPSO global aerosol vertical observations using a four-dimensional ensemble Kalman filter Y. Cheng et al. 10.5194/acp-19-13445-2019
68. Enhanced Simulation of an Asian Dust Storm by Assimilating GCOM-C Observations Y. Cheng et al. 10.3390/rs13153020
69. 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
70. Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. 10.1029/2019JD031465
71. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
72. 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
73. 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
74. An improved method for retrieving nighttime aerosol optical thickness from the VIIRS Day/Night Band T. McHardy et al. 10.5194/amt-8-4773-2015
75. The SPRINTARS version 3.80/4D-Var data assimilation system: development and inversion experiments based on the observing system simulation experiment framework K. Yumimoto & T. Takemura 10.5194/gmd-6-2005-2013
76. A Review of Data Assimilation on Aerosol Optical, Radiative, and Climatic Effects Study Y. Cheng et al. 10.1007/s41810-022-00142-9
77. Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
78. Reducing multisensor satellite monthly mean aerosol optical depth uncertainty: 1. Objective assessment of current AERONET locations J. Li et al. 10.1002/2016JD025469
79. Improving PM<sub>2. 5</sub> forecast over China by the joint adjustment of initial conditions and source emissions with an ensemble Kalman filter Z. Peng et al. 10.5194/acp-17-4837-2017
80. 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
81. Evaluating the impact of multisensor data assimilation on a global aerosol particle transport model J. Zhang et al. 10.1002/2013JD020975
82. Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models M. Bocquet et al. 10.5194/acp-15-5325-2015
83. JRAero: the Japanese Reanalysis for Aerosol v1.0 K. Yumimoto et al. 10.5194/gmd-10-3225-2017
84. 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
85. Classifying Asian dust aerosols and their columnar optical properties using fuzzy clustering L. Wu & Q. Zeng 10.1002/2013JD020751