101 citations as recorded by crossref.

1. Validation of an hourly resolved global aerosol model in answer to solar electricity generation information needs M. Schroedter-Homscheidt & A. Oumbe
2. Development of four-dimensional variational assimilation system based on the GRAPES–CUACE adjoint model (GRAPES–CUACE-4D-Var V1.0) and its application in emission inversion C. Wang et al.
3. Modeling study of PM2.5 pollutant transport across cities in China's Jing–Jin–Ji region during a severe haze episode in December 2013 C. Jiang et al.
4. Saltation transport rate in unsteady wind variations P. Wang & X. Zheng
5. The combined effects of heterogeneous chemistry and aerosol-radiation interaction on severe haze simulation by atmospheric chemistry model in Middle-Eastern China Z. Liu et al.
6. Inverse modeling of the 2021 spring super dust storms in East Asia J. Jin et al.
7. Temporal and spatial variations in sand and dust storm events in East Asia from 2007 to 2016: Relationships with surface conditions and climate change L. An et al.
8. Improving the Non-Hydrostatic Numerical Dust Model by Integrating Soil Moisture and Greenness Vegetation Fraction Data with Different Spatiotemporal Resolutions M. Yu et al.
9. A Transformer-based neural network for global short-range dust forecasting S. Du et al.
10. Development of GRAPES-CUACE adjoint model version 2.0 and its application in sensitivity analysis of ozone pollution in north China C. Wang et al.
11. 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.
12. Spatially varying parameter estimation for dust emissions using reduced-tangent-linearization 4DVar J. Jin et al.
13. High-resolution anthropogenic emission inventory for China (2015–2024): Spatiotemporal changes and environmental application D. Li et al.
14. Sensitivity studies of aerosol data assimilation and direct radiative feedbacks in modeling dust aerosols H. Wang & T. Niu
15. Impacts of PBL schemes on PM2.5 simulation and their responses to aerosol-radiation feedback in GRAPES_CUACE model during severe haze episodes in Jing-Jin-Ji, China Y. Peng et al.
16. An air quality forecasting system in Beijing - Application to the study of dust storm events in China in May 2008 Q. Zhang et al.
17. A new parameterization of uptake coefficients for heterogeneous reactions on multi-component atmospheric aerosols Y. Zhou et al.
18. Mesoscale modeling study of the interactions between aerosols and PBL meteorology during a haze episode in Jing–Jin–Ji (China) and its nearby surrounding region – Part 1: Aerosol distributions and meteorological features H. Wang et al.
19. Aerosol–cloud interaction in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on mesoscale numerical weather prediction under haze pollution conditions in Jing–Jin–Ji in China W. Zhang et al.
20. A multisource observation study of the severe prolonged regional haze episode over eastern China in January 2013 H. Wang et al.
21. A hybrid XGBoost-SMOTE model for optimization of operational air quality numerical model forecasts H. Ke et al.
22. Investigation of the influence of mineral dust on airborne particulate matter during the COVID-19 epidemic in spring 2020 over China L. Liang et al.
23. Overview of current limitations and challenges in data and methods for assessing the health effects of sand and dust storms under the climate change scenario A. Tobias et al.
24. Variability in the correlation between satellite-derived liquid cloud droplet effective radius and aerosol index over the northern Pacific Ocean S. Tan et al.
25. The application study of the revised IMPROVE atmospheric extinction algorithm in atmospheric chemistry model focusing on improving low visibility prediction in eastern China C. Han et al.
26. Chemistry‐Weather Interacted Model System GRAPES_Meso5.1/CUACE CW V1.0: Development, Evaluation and Application in Better Haze/Fog Prediction in China H. Wang et al.
27. Tracking sensitive source areas of different weather pollution types using GRAPES-CUACE adjoint model C. Wang et al.
28. Quantifying Mechanisms of Aeolian Dust Emission: Field Measurements at Etosha Pan, Namibia G. Wiggs et al.
29. Improved method of visibility parameterization focusing on high humidity and aerosol concentrations during fog–haze events: Application in the GRAPES_CAUCE model in Jing-Jin-Ji, China Y. Peng et al.
30. Study on the contribution of the major desert groups on SDS weather in East Asia combining the model simulation and multiple observations H. Ning et al.
31. Dust Emission Inversion Using Himawari‐8 AODs Over East Asia: An Extreme Dust Event in May 2017 J. Jin et al.
32. A 3D multi-threshold, region-growing algorithm for identifying dust storm features from model simulations M. Yu & C. Yang
33. Modeling study of the effects of entrainment-mixing on fog simulation in the chemistry–weather coupling model GRAPES_Meso5.1/CUACE CW Y. Zhao et al.
34. A multi-scale hybrid neural network retrieval model for dust storm detection, a study in Asia M. Wong et al.
35. Relationships between soil moisture and dust emissions in a bare sandy soil of Mongolia E. Munkhtsetseg et al.
36. Status and Perspectives of the Validation and Evaluation of Wind-Blown Dust Models Using Three-Dimensional Air Quality Models H. Lee & S. Park
37. Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions S. Li et al.
38. Developing an Australian dust early warning system T. Clark & C. Strong
39. Sensitivity analysis and precursor emission sources reduction strategies of O3 for different pollution weather types based on the GRAPES-CUACE adjoint model C. Wang et al.
40. 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.
41. AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE X. Wang et al.
42. Improving short-term forecasting of surface dust concentration in Northern China: Integrating machine learning with multi-numerical models Z. Yi et al.
43. Machine learning for observation bias correction with application to dust storm data assimilation J. Jin et al.
44. An extensive dust storm impact on air quality on 22 November 2018 in Sydney, Australia, using satellite remote sensing and ground data A. Attiya & B. Jones
45. Assessment of Asian Dust Aerosol Model 3 Based on an Asian Dust Case of December 2022 M. Kang & W. Lee
46. Data assimilation of dust aerosol observations for the CUACE/dust forecasting system T. Niu et al.
47. Sensitivity analysis of PM2.5 and O3 co-pollution in Beijing based on GRAPES-CUACE adjoint model Z. Liu et al.
48. Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0 J. Jin et al.
49. Study of Methodology for Estimating PM10Concentration of Asian Dust Using Visibility Data H. Lee et al.
50. Attributions of meteorological and emission factors to the 2015 winter severe haze pollution episodes in China's Jing-Jin-Ji area T. Liu et al.
51. Inverse modeling of black carbon emissions over China using ensemble data assimilation P. Wang et al.
52. Incorporation and improvement of a heterogeneous chemistry mechanism in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on secondary inorganic aerosol and PM2.5 simulations in Middle-Eastern China Z. Liu et al.
53. Description and evaluation of a newly developed emission inventory processing system (EMIPS) W. Chen et al.
54. Assessment of the impacts of cloud chemistry on surface SO2 and sulfate levels in typical regions of China J. Lu et al.
55. The variability of spring sand-dust storm frequency in Northeast Asia from 1980 to 2011 Y. Yang et al.
56. Dust events in Beijing, China (2004–2006): comparison of ground-based measurements with columnar integrated observations Z. Wu et al.
57. Numerical Simulation of the Direct Radiative Effects of Dust Aerosol on the East Asian Winter Monsoon H. Sun & X. Liu
58. National Environmental Meteorological Services in China Z. Kang et al.
59. Comparing the impact of strong and weak East Asian winter monsoon on PM2.5 concentration in Beijing C. Wang et al.
60. The value of satellite observations in the analysis and short-range prediction of Asian dust A. Benedetti et al.
61. The impact of aerosol-ice nuclei-cloud interactions on a typical spring dust-precipitation event in China J. Zhang et al.
62. Sensitive areas for target observation associated with meteorological forecasts for dust storm events in the Beijing–Tianjin–Hebei region L. Yang & W. Duan
63. Advancing operational global aerosol forecasting with machine learning K. Gui et al.
64. Forecasting of Asian dust storm that occurred on May 10–13, 2011, using an ensemble-based data assimilation system K. Yumimoto et al.
65. Application of a Neural Network to Store and Compute the Optical Properties of Non-Spherical Particles J. Yu et al.
66. The transport and deposition of dust and its impact on phytoplankton growth in the Yellow Sea S. Tan & H. Wang
67. Advances in Urban Meteorological Research in China S. Miao et al.
68. Numerical Modeling of Topography-Modulated Dust Aerosol Distribution and Its Influence on the Onset of East Asian Summer Monsoon H. Sun & X. Liu
69. The Different Impacts of Emissions and Meteorology on PM2.5 Changes in Various Regions in China: A Case Study W. Zhang et al.
70. Impacts of long-range transports from Central and South Asia on winter surface PM2.5 concentrations in China J. Mo et al.
71. Evaluating the contributions of changed meteorological conditions and emission to substantial reductions of PM2.5 concentration from winter 2016 to 2017 in Central and Eastern China W. Zhang et al.
72. Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting M. Pang et al.
73. Aerosol-radiation interaction in the operational atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on mesoscale NWP in Beijing-Tianjin-Hebei, China Y. Peng et al.
74. Radiative feedback of dust aerosols on the East Asian dust storms H. Wang et al.
75. Superimposed effects of typical local circulations driven by mountainous topography and aerosol–radiation interaction on heavy haze in the Beijing–Tianjin–Hebei central and southern plains in winter Y. Peng et al.
76. NO2 Forecasting by China Meteorological Administration Evaluated According to TROPOMI Sentinel-5P Satellite Measurements and Surface Network H. Zhou et al.
77. Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction W. Zhang et al.
78. New Directions: The need to develop process-based emission forecasting models D. Tong et al.
79. Prediction of Asian Dust Days over Northern China Using the KMA-ADAM2 Model S. Hong et al.
80. Source apportionment of SPM by positive matrix factorization and PM2.5 analysis in an urban industrial area P. Khobragade & A. Ahirwar
81. Numerical Studies on a Severe Dust Storm in East Asia Using WRF-Chem X. Yu et al.
82. Sensitivity analysis of atmospheric oxidation capacity in Beijing based on the GRAPES-CUACE adjoint model C. Wang et al.
83. The influence of Asian dust outflow on particle microphysical and optical properties at Mt. Tai in central east China X. Shen et al.
84. The Role of Aerosol‐Radiation Interaction in the Meteorology Prediction at the Weather Scale in the Numerical Weather Prediction Model W. Zhang et al.
85. Numerical modeling of a strong dust event over the south China region in March 2010 K. Chow et al.
86. Simulating Performance of CHIMERE on a Late Autumnal Dust Storm over Northern China S. Ma et al.
87. A gradient boosting-based machine learning framework for improving atmospheric visibility numerical prediction C. Han et al.
88. PM10 concentrations and mass transport during “Red Dawn” – Sydney 23 September 2009 J. Leys et al.
89. Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation Z. Gui et al.
90. Sensitivity Analysis of the Dust-Generation Algorithm in ADAM3 by Incorporating Surface-Wetness Effects Y. Lim et al.
91. Spatial and temporal variations of aerosols around Beijing in summer 2006: 2. Local and column aerosol optical properties H. Matsui et al.
92. Dust Model Intercomparison Between ADAM and CFORS/Dust For Asian Dust Case in 2007 (March 28 - April 3) S. Kim et al.
93. Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China J. Jin et al.
94. Single‐Scattering Properties of Encapsulated Fractal Black Carbon Particles Computed Using the Invariant Imbedding T‐Matrix Method and Deep Learning Approaches X. Wang et al.
95. An improved four-dimensional variation source term inversion model with observation error regularization C. Han et al.
96. Dust storm forecasting through coupling LOTOS-EUROS with localized ensemble Kalman filter M. Pang et al.
97. The impact of aerosol-cloud interaction on mesoscale numerical weather prediction when low-cloud and haze coexist in winter over major polluted regions of China W. Zhang et al.
98. Modelling the 2021 East Asia super dust storm using FLEXPART and FLEXDUST and its comparison with reanalyses and observations H. Tang et al.
99. A new-generation sand and dust storm forecasting system GRAPES_CUACE/Dust: Model development, verification and numerical simulation H. Wang et al.
100. Winter and Summer PM 2.5 Chemical Compositions in Fourteen Chinese Cities J. Cao et al.
101. Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description and preliminary experimental results Y. Liu et al.