Articles | Volume 20, issue 6
https://doi.org/10.5194/acp-20-3589-2020
https://doi.org/10.5194/acp-20-3589-2020
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

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Daisuke Goto on behalf of the Authors (20 Jan 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (24 Jan 2020) by Jianping Huang
RR by Anonymous Referee #2 (01 Feb 2020)
RR by Anonymous Referee #1 (03 Feb 2020)
ED: Publish as is (07 Feb 2020) by Jianping Huang

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Daisuke Goto on behalf of the Authors (13 Mar 2020)   Author's adjustment   Manuscript
EA: Adjustments approved (14 Mar 2020) by Jianping Huang
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.
Altmetrics
Final-revised paper
Preprint