31 citations as recorded by crossref.

1. Evaluation of MODIS and two reanalysis aerosol optical depth products over AERONET sites H. Shi et al. 10.1016/j.atmosres.2019.01.009
2. 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
3. Generalized background error covariance matrix model (GEN_BE v2.0) G. Descombes et al. 10.5194/gmd-8-669-2015
4. Improving the sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosols of the Weather Research and Forecasting-Chemistry (WRF-Chem) model with the revised Gridpoint Statistical Interpolation system and multi-wavelength aerosol optical measurements: the dust aerosol observation campaign at Kashi, near the Taklimakan Desert, northwestern China W. Chang et al. 10.5194/acp-21-4403-2021
5. An Observing System Simulation Experiment Framework for Air Quality Forecasts in Northeast Asia: A Case Study Utilizing Virtual Geostationary Environment Monitoring Spectrometer and Surface Monitored Aerosol Data H. Kim et al. 10.3390/rs14020389
6. Assimilating Fengyun-4A observations to improve WRF-Chem PM2.5 predictions in China J. Hong et al. 10.1016/j.atmosres.2021.105878
7. 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
8. Improved Modeling of Spatiotemporal Variations of Fine Particulate Matter Using a Three‐Dimensional Variational Data Fusion Method X. Zhang et al. 10.1029/2020JD033599
9. The Aerosol Module in the Community Radiative Transfer Model (v2.2 and v2.3): accounting for aerosol transmittance effects on the radiance observation operator C. Lu et al. 10.5194/gmd-15-1317-2022
10. Toward Improving Short‐Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals R. Kumar et al. 10.1029/2018JD029009
11. JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
12. Improved PM2.5 predictions of WRF-Chem via the integration of Himawari-8 satellite data and ground observations J. Hong et al. 10.1016/j.envpol.2020.114451
13. Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem A. Raman et al. 10.1016/j.atmosenv.2020.118134
14. Evaluation of MWHS-2 Using a Co-located Ground-Based Radar Network for Improved Model Assimilation S. Liu et al. 10.3390/rs11202338
15. Impact of Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depth and AirNow PM2.5 assimilation on Community Multi‐scale Air Quality aerosol predictions over the contiguous United States T. Chai et al. 10.1002/2016JD026295
16. Impacts of uncertainties in emissions on aerosol data assimilation and short-term PM2.5 predictions over Northeast Asia S. Lee et al. 10.1016/j.atmosenv.2021.118921
17. Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing J. McHenry et al. 10.1080/10962247.2015.1096862
18. 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
19. Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
20. Using Lidar technology to assess regional air pollution and improve estimates of PM2.5 transport in the North China Plain Y. Xiang et al. 10.1088/1748-9326/ab9cfd
21. Limitations of ozone data assimilation with adjustment of NO<sub><i>x</i></sub> emissions: mixed effects on NO<sub>2</sub> forecasts over Beijing and surrounding areas X. Tang et al. 10.5194/acp-16-6395-2016
22. Lidar vertical observation network and data assimilation reveal key processes driving the 3-D dynamic evolution of PM<sub>2.5</sub> concentrations over the North China Plain Y. Xiang et al. 10.5194/acp-21-7023-2021
23. Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions R. Žabkar et al. 10.5194/gmd-8-2119-2015
24. Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter T. Dai et al. 10.1029/2018MS001475
25. 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
26. A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods Y. Tang et al. 10.5194/gmd-10-4743-2017
27. Assimilating a blended dataset of satellite-based estimations and in situ observations to improve WRF-Chem PM2.5 prediction X. Ma et al. 10.1016/j.atmosenv.2023.120284
28. The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation S. Wei et al. 10.5194/gmd-17-795-2024
29. Satellite imagery and products of the 16–17 February 2020 Saharan Air Layer dust event over the eastern Atlantic: impacts of water vapor on dust detection and morphology L. Grasso et al. 10.5194/amt-14-1615-2021
30. Modeling study of a severe aerosol pollution event in December 2013 over Shanghai China: An application of chemical data assimilation J. Wu et al. 10.1016/j.partic.2014.10.008
31. Assimilation of PM2.5 ground base observations to two chemical schemes in WRF-Chem – The results for the winter and summer period M. Werner et al. 10.1016/j.atmosenv.2018.12.016