70 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. 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
4. 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
5. 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
6. Effects of data assimilation on the global aerosol key optical properties simulations X. Yin et al. 10.1016/j.atmosres.2016.03.016
7. 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
8. Air pollution in Asia K. Vadrevu et al. 10.1016/j.envpol.2014.09.006
9. Estimating Aerosol Emissions by Assimilating Remote Sensing Observations into a Global Transport Model N. Schutgens et al. 10.3390/rs4113528
10. Evaluation of a relationship between aerosols and surface downward shortwave flux through an integrative analysis of modeling and observation D. Goto et al. 10.1016/j.atmosenv.2011.11.032
11. 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
12. 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
13. 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
14. Distributed input observers to integrate satellite data with 3-D atmospheric models D. McGuffin et al. 10.1016/j.compchemeng.2019.106525
15. 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
16. 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
17. Assimilating spaceborne lidar dust extinction can improve dust forecasts J. Escribano et al. 10.5194/acp-22-535-2022
18. 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
19. Bayesian Merging of MISR and MODIS Aerosol Optical Depth Products Using Error Distributions From AERONET M. Singh et al. 10.1109/JSTARS.2017.2734331
20. 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
21. Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
22. 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
23. 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
24. 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
25. Chemical Data Assimilation—An Overview A. Sandu & T. Chai 10.3390/atmos2030426
26. 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
27. 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
28. 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
29. Aerosol data assimilation using data from Himawari‐8, a next‐generation geostationary meteorological satellite K. Yumimoto et al. 10.1002/2016GL069298
30. Mesoscale Data Assimilation for a Local Severe Rainfall Event with the NHM–LETKF System M. Kunii 10.1175/WAF-D-13-00032.1
31. Assimilating aerosol observations with a “hybrid” variational-ensemble data assimilation system C. Schwartz et al. 10.1002/2013JD020937
32. 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
33. 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
34. 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
35. Sensitivity tests for an ensemble Kalman filter for aerosol assimilation N. Schutgens et al. 10.5194/acp-10-6583-2010
36. A review of aerosol optical properties and radiative effects Y. Liu et al. 10.1007/s13351-014-4045-z
37. Evaluating the impact of assimilating CALIOP-derived aerosol extinction profiles on a global mass transport model J. Zhang et al. 10.1029/2011GL047737
38. Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic K. Han et al. 10.3390/app11041959
39. 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
40. 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
41. 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
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. 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
44. Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods Y. Choi et al. 10.1029/2019MS001890
45. Experiments with the assimilation of fine aerosols using an ensemble Kalman filter M. Pagowski & G. Grell 10.1029/2012JD018333
46. Wind for Transporting Materials—Transport Processes of Aerosols in the Atmosphere— T. TAKEMURA 10.5359/jawe.37.192
47. 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
48. RETRACTED ARTICLE: Evaluation of agricultural climate and regional agricultural economic efficiency based on remote sensing analysis X. Lu 10.1007/s12517-021-07153-9
49. 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
50. 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
51. 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
52. Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin Y. Wang et al. 10.5194/acp-14-12031-2014
53. 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
54. Enhanced Simulation of an Asian Dust Storm by Assimilating GCOM-C Observations Y. Cheng et al. 10.3390/rs13153020
55. 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
56. Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. 10.1029/2019JD031465
57. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
58. 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
59. 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
60. 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
61. Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
62. Reducing multisensor satellite monthly mean aerosol optical depth uncertainty: 1. Objective assessment of current AERONET locations J. Li et al. 10.1002/2016JD025469
63. 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
64. Simultaneous three-dimensional variational assimilation of surface fine particulate matter and MODIS aerosol optical depth C. Schwartz et al. 10.1029/2011JD017383
65. 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
66. Evaluating the impact of multisensor data assimilation on a global aerosol particle transport model J. Zhang et al. 10.1002/2013JD020975
67. 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
68. JRAero: the Japanese Reanalysis for Aerosol v1.0 K. Yumimoto et al. 10.5194/gmd-10-3225-2017
69. 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
70. Classifying Asian dust aerosols and their columnar optical properties using fuzzy clustering L. Wu & Q. Zeng 10.1002/2013JD020751