Articles | Volume 19, issue 21
https://doi.org/10.5194/acp-19-13445-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-13445-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Nov 2019
Research article |
| 05 Nov 2019
| 05 Nov 2019
Investigating the assimilation of CALIPSO global aerosol vertical observations using a four-dimensional ensemble Kalman filter
Yueming Cheng
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters, Nanjing University of Information Science and
Technology, Nanjing, China
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters, Nanjing University of Information Science and
Technology, Nanjing, China
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Daisuke Goto
National Institute for Environmental Studies, Tsukuba, Japan
Nick A. J. Schutgens
Faculty of Science, Free University of Amsterdam, Amsterdam, the
Netherlands
Guangyu Shi
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters, Nanjing University of Information Science and
Technology, Nanjing, China
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Teruyuki Nakajima
Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, Japan
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- Observing system simulation experiment (OSSE)-quantitative evaluation of lidar observation networks to improve 3D aerosol forecasting in China H. Ye et al. 10.1016/j.atmosres.2022.106069
- Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. 10.5194/amt-13-4645-2020
- JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
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- 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
- Vertical Profiles of Aerosols Induced by Dust, Smoke, and Fireworks in the Cold Region of Northeast China L. Duanmu et al. 10.3390/rs16061098
- An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. 10.5194/gmd-15-3555-2022
28 citations as recorded by crossref.
- Development of the CMA-ChemRA: China Regional Weakly Coupled Chemical-Weather Reanalysis System with product since 2007 T. Zhang et al. 10.1016/j.scitotenv.2024.177552
- Three-dimensional variational assimilation of Lidar extinction profiles: Application to PM2.5 prediction in north China L. Gao et al. 10.1016/j.atmosenv.2021.118828
- The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2 M. Pang et al. 10.5194/gmd-18-3781-2025
- Assimilation of Both Column‐ and Layer‐Integrated Dust Opacity Observations in the Martian Atmosphere T. Ruan et al. 10.1029/2021EA001869
- Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy J. Lin et al. 10.5194/gmd-18-2231-2025
- Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations S. Zhai et al. 10.5194/acp-21-16775-2021
- Assessing the assimilation of Himawari-8 observations on aerosol forecasts and radiative effects during pollution transport from South Asia to the Tibetan Plateau M. Zhao et al. 10.5194/acp-24-235-2024
- 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
- Enhanced Simulation of an Asian Dust Storm by Assimilating GCOM-C Observations Y. Cheng et al. 10.3390/rs13153020
- Assimilating spaceborne lidar dust extinction can improve dust forecasts J. Escribano et al. 10.5194/acp-22-535-2022
- 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
- Seasonal Dependence of Aerosol Data Assimilation and Forecasting Using Satellite and Ground-Based Observations S. Lee et al. 10.3390/rs14092123
- An Overall Uniformity Optimization Method of the Spherical Icosahedral Grid Based on the Optimal Transformation Theory F. Luo et al. 10.3390/atmos12111516
- NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components H. Li et al. 10.5194/gmd-17-8495-2024
- CALIPSO-based aerosol extinction profile estimation from MODIS and MERRA-2 data using a hybrid model of Transformer and CNN Y. Zhen et al. 10.1016/j.scitotenv.2024.176423
- Revealing the sulfur dioxide emission reductions in China by assimilating surface observations in WRF-Chem T. Dai et al. 10.5194/acp-21-4357-2021
- Uncertainty in Aerosol Optical Depth From Modern Aerosol‐Climate Models, Reanalyses, and Satellite Products A. Vogel et al. 10.1029/2021JD035483
- Estimating hourly surface shortwave radiation over northeast of the Tibetan Plateau by assimilating Himawari-8 cloud optical thickness T. Zhang et al. 10.1186/s40562-023-00312-8
- Measurement Report: Determination of aerosol vertical features on different timescales over East Asia based on CATS aerosol products Y. Cheng et al. 10.5194/acp-20-15307-2020
- Impact of CALIPSO profile data assimilation on 3-D aerosol improvement in a size-resolved aerosol model H. Ye et al. 10.1016/j.atmosres.2021.105877
- A Review of Data Assimilation on Aerosol Optical, Radiative, and Climatic Effects Study Y. Cheng et al. 10.1007/s41810-022-00142-9
- Observing system simulation experiment (OSSE)-quantitative evaluation of lidar observation networks to improve 3D aerosol forecasting in China H. Ye et al. 10.1016/j.atmosres.2022.106069
- Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. 10.5194/amt-13-4645-2020
- JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. 10.1029/2022MS003232
- Advances in Atmospheric Radiation: Theories, Models, and Their Applications. Part II: Radiative Transfer Models and Related Applications H. Zhang et al. 10.1007/s13351-024-3089-y
- 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
- Vertical Profiles of Aerosols Induced by Dust, Smoke, and Fireworks in the Cold Region of Northeast China L. Duanmu et al. 10.3390/rs16061098
- An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. 10.5194/gmd-15-3555-2022
Latest update: 08 Aug 2025
Short summary
Aerosol vertical information is critical to quantify the influences of aerosol on the climate and environment; however, large uncertainties still persist in model simulations. Global aerosol vertical distributions are more accurately simulated by assimilating the vertical aerosol extinction coefficients from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP).
Aerosol vertical information is critical to quantify the influences of aerosol on the climate...
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