Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 9
Articles | Volume 14, issue 9
https://doi.org/10.5194/gmd-14-5607-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-5607-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 9
Development and technical paper
 | 
10 Sep 2021
Development and technical paper |  | 10 Sep 2021

Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0

Jianbing Jin, Arjo Segers, Hai Xiang Lin, Bas Henzing, Xiaohui Wang, Arnold Heemink, and Hong Liao

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Latest update: 13 Dec 2024
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Short summary
When discussing the accuracy of a dust forecast, the shape and position of the plume as well as the intensity are key elements. The position forecast determines which locations will be affected, while the intensity only describes the actual dust level. A dust forecast with position misfit directly results in incorrect timing profiles of dust loads. In this paper, an image-morphing-based data assimilation is designed for realigning a simulated dust plume to correct for the position error.
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