Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 22, issue 23
Articles | Volume 22, issue 23
https://doi.org/10.5194/acp-22-15313-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-15313-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 23
Research article
 | 
02 Dec 2022
Research article |  | 02 Dec 2022

Cluster-based characterization of multi-dimensional tropospheric ozone variability in coastal regions: an analysis of lidar measurements and model results

Claudia Bernier, Yuxuan Wang, Guillaume Gronoff, Timothy Berkoff, K. Emma Knowland, John T. Sullivan, Ruben Delgado, Vanessa Caicedo, and Brian Carroll

Viewed

Total article views: 1,734 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,276 419 39 1,734 125 33 33
  • HTML: 1,276
  • PDF: 419
  • XML: 39
  • Total: 1,734
  • Supplement: 125
  • BibTeX: 33
  • EndNote: 33
Views and downloads (calculated since 23 Mar 2022)
Cumulative views and downloads (calculated since 23 Mar 2022)

Viewed (geographical distribution)

Total article views: 1,734 (including HTML, PDF, and XML) Thereof 1,787 with geography defined and -53 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Jul 2024
Download
Short summary
Coastal regions are susceptible to variable and high ozone which is difficult to simulate. We developed a method to characterize large datasets of multi-dimensional measurements from lidar instruments taken in coastal regions. Using the clustered ozone groups, we evaluated model performance in simulating the coastal ozone variability vertically and diurnally. The approach allowed us to pinpoint areas where the models succeed in simulating coastal ozone and areas where there are still gaps.
Read more
Altmetrics
Final-revised paper
Preprint