Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control,
Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,
School of Environmental Science and Engineering,
Nanjing University of Information Science and Technology, Nanjing, China
Delft Institute of Applied Mathematics, Delft University of Technology, Delft, the Netherlands
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control,
Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,
School of Environmental Science and Engineering,
Nanjing University of Information Science and Technology, Nanjing, China
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Total article views: 2,485 (including HTML, PDF, and XML)
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Total
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1,820
590
75
2,485
77
47
45
HTML: 1,820
PDF: 590
XML: 75
Total: 2,485
Supplement: 77
BibTeX: 47
EndNote: 45
Views and downloads (calculated since 09 Mar 2021)
Cumulative views and downloads
(calculated since 09 Mar 2021)
Total article views: 1,810 (including HTML, PDF, and XML)
HTML
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Total
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EndNote
1,423
324
63
1,810
77
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41
HTML: 1,423
PDF: 324
XML: 63
Total: 1,810
Supplement: 77
BibTeX: 42
EndNote: 41
Views and downloads (calculated since 10 Sep 2021)
Cumulative views and downloads
(calculated since 10 Sep 2021)
Total article views: 675 (including HTML, PDF, and XML)
HTML
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BibTeX
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397
266
12
675
5
4
HTML: 397
PDF: 266
XML: 12
Total: 675
BibTeX: 5
EndNote: 4
Views and downloads (calculated since 09 Mar 2021)
Cumulative views and downloads
(calculated since 09 Mar 2021)
Viewed (geographical distribution)
Total article views: 2,485 (including HTML, PDF, and XML)
Thereof 2,281 with geography defined
and 204 with unknown origin.
Total article views: 1,810 (including HTML, PDF, and XML)
Thereof 1,705 with geography defined
and 105 with unknown origin.
Total article views: 675 (including HTML, PDF, and XML)
Thereof 576 with geography defined
and 99 with unknown origin.
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.
When discussing the accuracy of a dust forecast, the shape and position of the plume as well as...