87 citations as recorded by crossref.

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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
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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
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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
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18. 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
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20. 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
21. Assimilating spaceborne lidar dust extinction can improve dust forecasts J. Escribano et al. 10.5194/acp-22-535-2022
22. 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
23. Bayesian Merging of MISR and MODIS Aerosol Optical Depth Products Using Error Distributions From AERONET M. Singh et al. 10.1109/JSTARS.2017.2734331
24. 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
25. Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
26. 3DVAR meteorological data assimilation and aerosol impact on the simulation of heat wave 2022 over Haryana using WRF-Chem P. Deb et al. 10.1016/j.apr.2025.102440
27. Application of Optimal Interpolation to Spatially and Temporally Sparse Observations of Aerosol Optical Depth N. Miatselskaya et al. 10.3390/atmos14010032
28. 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
29. 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
30. JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
31. 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
32. 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
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34. 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
35. Chemical Data Assimilation—An Overview A. Sandu & T. Chai 10.3390/atmos2030426
36. 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
37. 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
38. 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
39. 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
40. Aerosol data assimilation using data from Himawari‐8, a next‐generation geostationary meteorological satellite K. Yumimoto et al. 10.1002/2016GL069298
41. Mesoscale Data Assimilation for a Local Severe Rainfall Event with the NHM–LETKF System M. Kunii 10.1175/WAF-D-13-00032.1
42. Long-term variations of global dust emissions and climate control N. Wang & Y. Zhang 10.1016/j.envpol.2023.122847
43. 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
44. 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
45. 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
46. Sensitivity tests for an ensemble Kalman filter for aerosol assimilation N. Schutgens et al. 10.5194/acp-10-6583-2010
47. A review of aerosol optical properties and radiative effects Y. Liu et al. 10.1007/s13351-014-4045-z
48. Evaluating the impact of assimilating CALIOP-derived aerosol extinction profiles on a global mass transport model J. Zhang et al. 10.1029/2011GL047737
49. 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
50. 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
51. Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic K. Han et al. 10.3390/app11041959
52. 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
53. 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
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 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
56. 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
57. 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
58. 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
59. Influence of aerosols and thin cirrus clouds on the GOSAT-observed CO2: a case study over Tsukuba O. Uchino et al. 10.5194/acp-12-3393-2012
60. Wind for Transporting Materials—Transport Processes of Aerosols in the Atmosphere— T. TAKEMURA 10.5359/jawe.37.192
61. 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
62. Global Scale Inversions from MOPITT CO and MODIS AOD B. Gaubert et al. 10.3390/rs15194813
63. 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
64. RETRACTED ARTICLE: Evaluation of agricultural climate and regional agricultural economic efficiency based on remote sensing analysis X. Lu 10.1007/s12517-021-07153-9
65. 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
66. 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
67. 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
68. Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin Y. Wang et al. 10.5194/acp-14-12031-2014
69. 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
70. Enhanced Simulation of an Asian Dust Storm by Assimilating GCOM-C Observations Y. Cheng et al. 10.3390/rs13153020
71. 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
72. Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. 10.1029/2019JD031465
73. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
74. 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
75. 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
76. 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
77. 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
78. A Review of Data Assimilation on Aerosol Optical, Radiative, and Climatic Effects Study Y. Cheng et al. 10.1007/s41810-022-00142-9
79. Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
80. Reducing multisensor satellite monthly mean aerosol optical depth uncertainty: 1. Objective assessment of current AERONET locations J. Li et al. 10.1002/2016JD025469
81. Improving PM2. 5 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
82. 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
83. Evaluating the impact of multisensor data assimilation on a global aerosol particle transport model J. Zhang et al. 10.1002/2013JD020975
84. 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
85. JRAero: the Japanese Reanalysis for Aerosol v1.0 K. Yumimoto et al. 10.5194/gmd-10-3225-2017
86. 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
87. Classifying Asian dust aerosols and their columnar optical properties using fuzzy clustering L. Wu & Q. Zeng 10.1002/2013JD020751