Articles | Volume 23, issue 2
https://doi.org/10.5194/acp-23-1641-2023
https://doi.org/10.5194/acp-23-1641-2023
Research article
 | 
27 Jan 2023
Research article |  | 27 Jan 2023

How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent

Jianbing Jin, Bas Henzing, and Arjo Segers

Related authors

A Transformer-based agent model of GEOS-Chem v14.2.2 for informative prediction of PM2.5 and O3 levels to future emission scenarios: TGEOS v1.0
Dehao Li, Jianbing Jin, Guoqiang Wang, Mijie Pang, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-2186,https://doi.org/10.5194/egusphere-2025-2186, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Optimizing Ammonia Emissions for PM2.5 Mitigation: Environmental and Health Co-Benefits in Eastern China
Keqin Tang, Haoran Zhang, Ge Xu, Fengyi Chang, Yang Xu, Ji Miao, Xian Cui, Jianbin Jin, Baojie Li, Ke Li, Hong Liao, and Nan Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-1407,https://doi.org/10.5194/egusphere-2025-1407, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
NMVOC emission optimization in China through assimilating formaldehyde retrievals from multiple satellite products
Canjie Xu, Jianbing Jin, Ke Li, Yinfei Qi, Ji Xia, Hai Xiang Lin, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-140,https://doi.org/10.5194/egusphere-2025-140, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
South Asia ammonia emission inversion through assimilating IASI observations
Ji Xia, Yi Zhou, Li Fang, Yingfei Qi, Dehao Li, Hong Liao, and Jianbing Jin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3938,https://doi.org/10.5194/egusphere-2024-3938, 2025
Short summary
Observational operator for fair model evaluation with ground NO2 measurements
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024,https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
How to trace the origins of short-lived atmospheric species: an Arctic example
Anderson Da Silva, Louis Marelle, Jean-Christophe Raut, Yvette Gramlich, Karolina Siegel, Sophie L. Haslett, Claudia Mohr, and Jennie L. Thomas
Atmos. Chem. Phys., 25, 5331–5354, https://doi.org/10.5194/acp-25-5331-2025,https://doi.org/10.5194/acp-25-5331-2025, 2025
Short summary
Dust-producing weather patterns of the North American Great Plains
Stuart Evans
Atmos. Chem. Phys., 25, 4833–4845, https://doi.org/10.5194/acp-25-4833-2025,https://doi.org/10.5194/acp-25-4833-2025, 2025
Short summary
High-resolution air quality maps for Bucharest using a mixed-effects modeling framework
Camelia Talianu, Jeni Vasilescu, Doina Nicolae, Alexandru Ilie, Andrei Dandocsi, Anca Nemuc, and Livio Belegante
Atmos. Chem. Phys., 25, 4639–4654, https://doi.org/10.5194/acp-25-4639-2025,https://doi.org/10.5194/acp-25-4639-2025, 2025
Short summary
Construction and application of a pollen emissions model based on phenology and random forests
Jiangtao Li, Xingqin An, Zhaobin Sun, Caihua Ye, Qing Hou, Yuxin Zhao, and Zhe Liu
Atmos. Chem. Phys., 25, 3583–3602, https://doi.org/10.5194/acp-25-3583-2025,https://doi.org/10.5194/acp-25-3583-2025, 2025
Short summary
The impact of uncertainty in black carbon's refractive index on simulated optical depth and radiative forcing
Ruth A. R. Digby, Knut von Salzen, Adam H. Monahan, Nathan P. Gillett, and Jiangnan Li
Atmos. Chem. Phys., 25, 3109–3130, https://doi.org/10.5194/acp-25-3109-2025,https://doi.org/10.5194/acp-25-3109-2025, 2025
Short summary

Cited articles

Ackermann, I. J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F. S., and Shankar, U.: Modal aerosol dynamics model for Europe: Development and first applications, Atmos. Environ., 32, 2981–2999, 1998. a
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, 1989. a
Andreae, M. O. and Crutzen, P. J.: Atmospheric aerosols: Biogeochemical sources and role in atmospheric chemistry, Science, 276, 1052–1058, 1997. a
Ångström, A.: On the Atmospheric Transmission of Sun Radiation and on Dust in the Air, Geografiska Annaler, 11, 156–166, 1929. a, b
Baker, A., Kelly, S., Biswas, K., Witt, M., and Jickells, T.: Atmospheric deposition of nutrients to the Atlantic Ocean, Geophys. Res. Lett., 30, 2296, https://doi.org/10.1029/2003GL018518, 2003. a
Download
Short summary
Aerosol models and satellite retrieval algorithms rely on different aerosol size assumptions. In practice, differences between simulations and observations do not always reflect the difference in aerosol amount. To avoid inconsistencies, we designed a hybrid assimilation approach. Different from a standard aerosol optical depth (AOD) assimilation that directly assimilates AODs, the hybrid one estimates aerosol size parameters by assimilating Ängström observations before assimilating the AODs.
Share
Altmetrics
Final-revised paper
Preprint