Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 20, issue 6
Articles | Volume 20, issue 6
https://doi.org/10.5194/acp-20-3589-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-3589-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 6
Research article
 | 
25 Mar 2020
Research article |  | 25 Mar 2020

Application of linear minimum variance estimation to the multi-model ensemble of atmospheric radioactive Cs-137 with observations

Daisuke Goto, Yu Morino, Toshimasa Ohara, Tsuyoshi Thomas Sekiyama, Junya Uchida, and Teruyuki Nakajima

Viewed

Total article views: 2,090 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,447 577 66 2,090 60 75
  • HTML: 1,447
  • PDF: 577
  • XML: 66
  • Total: 2,090
  • BibTeX: 60
  • EndNote: 75
Views and downloads (calculated since 15 Oct 2019)
Cumulative views and downloads (calculated since 15 Oct 2019)

Viewed (geographical distribution)

Total article views: 2,090 (including HTML, PDF, and XML) Thereof 1,975 with geography defined and 115 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 02 Apr 2025
Download
Short summary
To obtain reliable distribution of atmospheric Cs-137 emitted from the Fukushima accident, we proposed a multi-model ensemble (MME) method using observations. We found the MME-estimated Cs-137 concentrations using all available observations had lower bias, lower uncertainty, higher correlation and higher precision against the observations compared to single-model results. It can be applied not only to the Cs-137 distribution but also any atmospheric materials such as PM2.5 distribution.
Read more
Share
Altmetrics
Final-revised paper
Preprint