Preprints
https://doi.org/10.5194/egusphere-2025-1389
https://doi.org/10.5194/egusphere-2025-1389
08 Apr 2025
 | 08 Apr 2025

Observation error estimation in climate proxies with data assimilation and innovation statistics

Atsushi Okazaki, Diego Carrio, Quentin Dalaiden, Jarrah Harrison-Lofthouse, Shunji Kotsuki, and Kei Yoshimura

Abstract. Data assimilation (DA) has been successfully applied in paleoclimate reconstruction. DA combines model simulations and climate proxies based on their error sizes. Therefore, the error information is crucial for DA to work optimally. However, little attention has been paid to the observation errors in the previous studies, especially when the proxies are assimilated directly. This study assessed the feasibility of innovation statistics, a method developed for numerical weather prediction, for estimating observation errors in climate reconstruction and its impact on reconstruction skills. For this purpose, we conducted offline-DA experiments over 1870–2000. Here, we assimilated stable water isotope records from ice cores, tree-ring cellulose, and corals. We found that the innovation statistics-based approach correctly estimated the observation errors, even with the offline-DA scheme. Although the accuracy of the estimation depended on the sample size and accuracy of the prior error covariance, the estimation generally improved the reconstruction skills. The reconstruction skills with the estimated observation errors were comparable to those with errors defined differently. In contrast with those other methods, however, the innovation statistics-based approach offers an objective and systematic way to estimate observation errors with light computational cost. As such, the innovation statistics-based approach should contribute to improving the reconstruction skills and observation networks.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Share

Journal article(s) based on this preprint

22 Oct 2025
Observation error estimation in climate proxies with data assimilation and innovation statistics
Atsushi Okazaki, Diego S. Carrió, Quentin Dalaiden, Jarrah Harrison-Lofthouse, Shunji Kotsuki, and Kei Yoshimura
Clim. Past, 21, 1801–1819, https://doi.org/10.5194/cp-21-1801-2025,https://doi.org/10.5194/cp-21-1801-2025, 2025
Short summary
Atsushi Okazaki, Diego Carrio, Quentin Dalaiden, Jarrah Harrison-Lofthouse, Shunji Kotsuki, and Kei Yoshimura

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-1389', Lili Lei, 19 Apr 2025
    • AC1: 'Reply on RC1', Atsushi Okazaki, 01 Jul 2025
  • RC2: 'Comment on egusphere-2025-1389', Anonymous Referee #2, 27 Apr 2025
    • AC2: 'Reply on RC2', Atsushi Okazaki, 01 Jul 2025

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-1389', Lili Lei, 19 Apr 2025
    • AC1: 'Reply on RC1', Atsushi Okazaki, 01 Jul 2025
  • RC2: 'Comment on egusphere-2025-1389', Anonymous Referee #2, 27 Apr 2025
    • AC2: 'Reply on RC2', Atsushi Okazaki, 01 Jul 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish subject to minor revisions (review by editor) (14 Jul 2025) by Francesco Muschitiello
AR by Atsushi Okazaki on behalf of the Authors (07 Aug 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (12 Aug 2025) by Francesco Muschitiello
AR by Atsushi Okazaki on behalf of the Authors (12 Aug 2025)  Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Atsushi Okazaki on behalf of the Authors (20 Oct 2025)   Author's adjustment   Manuscript
EA: Adjustments approved (20 Oct 2025) by Francesco Muschitiello

Journal article(s) based on this preprint

22 Oct 2025
Observation error estimation in climate proxies with data assimilation and innovation statistics
Atsushi Okazaki, Diego S. Carrió, Quentin Dalaiden, Jarrah Harrison-Lofthouse, Shunji Kotsuki, and Kei Yoshimura
Clim. Past, 21, 1801–1819, https://doi.org/10.5194/cp-21-1801-2025,https://doi.org/10.5194/cp-21-1801-2025, 2025
Short summary
Atsushi Okazaki, Diego Carrio, Quentin Dalaiden, Jarrah Harrison-Lofthouse, Shunji Kotsuki, and Kei Yoshimura
Atsushi Okazaki, Diego Carrio, Quentin Dalaiden, Jarrah Harrison-Lofthouse, Shunji Kotsuki, and Kei Yoshimura

Viewed

Total article views: 897 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
798 80 19 897 22 42
  • HTML: 798
  • PDF: 80
  • XML: 19
  • Total: 897
  • BibTeX: 22
  • EndNote: 42
Views and downloads (calculated since 08 Apr 2025)
Cumulative views and downloads (calculated since 08 Apr 2025)

Viewed (geographical distribution)

Total article views: 891 (including HTML, PDF, and XML) Thereof 891 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Oct 2025
Download

The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Short summary
Data assimilation (DA) has been used to reconstruct paleoclimate fields. DA integrates model simulations and climate proxies based on their error sizes. Consequently, error information is vital for DA to function optimally. This study estimated observation errors using "innovation statistics" and demonstrated DA with estimated errors outperformed previous studies.
Share