Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 12
Articles | Volume 18, issue 12
https://doi.org/10.5194/gmd-18-3781-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3781-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 12
Methods for assessment of models
 | 
25 Jun 2025
Methods for assessment of models |  | 25 Jun 2025

The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2

Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han

Supplement

https://doi.org/10.5194/gmd-18-3781-2025-supplement

Data sets

CALIPSO Lidar Level 2 Aerosol Profile, V4-21 NASA/LARC/SD/ASDC https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmAPro-Standard-V4-21

Materials for GMD-2024-113 Mijie Pang https://doi.org/10.5281/zenodo.14846965

Model code and software

xxcvvv/open-PyFilter: pyfilter_v1.1 Mijie Pang https://doi.org/10.5281/zenodo.14036308

LOTOS-EUROS-v2.2 for GMD-2024-113 (restricted access) Arjo Segers https://doi.org/10.5281/zenodo.14039267

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Short summary
Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
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