Articles | Volume 21, issue 10
https://doi.org/10.5194/cp-21-1801-2025
https://doi.org/10.5194/cp-21-1801-2025
Research article
 | 
22 Oct 2025
Research article |  | 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

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Cited articles

Acevedo, W., Fallah, B., Reich, S., and Cubasch, U.: Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model, Clim. Past, 13, 545–557, https://doi.org/10.5194/cp-13-545-2017, 2017. 
Annan, J. D., Hargreaves, J. C., Mauritsen, T., McClymont, E., and Ho, S. L.: Can we reliably reconstruct the mid-Pliocene Warm Period with sparse data and uncertain models?, Clim. Past, 20, 1989–1999, https://doi.org/10.5194/cp-20-1989-2024, 2024. 
Bhend, J., Franke, J., Folini, D., Wild, M., and Brönnimann, S.: An ensemble-based approach to climate reconstructions, Clim. Past, 8, 963–976, https://doi.org/10.5194/cp-8-963-2012, 2012. 
Cardinali, C., Pezzulli, S., and Andersson, E.: Influence-matrix diagnostic of a data assimilation system, Q. J. Roy. Meteor. Soc., 130, 2767–2786, https://doi.org/10.1256/qj.03.205, 2004. 
Dalaiden, Q., Goosse, H., Rezsöhazy, J., and Thomas, E. R.: Reconstructing atmospheric circulation and sea-ice extent in the West Antarctic over the past 200 years using data assimilation, Clim. Dynam., 57, 3479–3503, https://doi.org/10.1007/s00382-021-05879-6, 2021. 
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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 that DA with estimated errors outperformed previous studies.
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