Climate of the Past
Climate of the Past
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Articles | Volume 17, issue 5
Articles | Volume 17, issue 5
https://doi.org/10.5194/cp-17-1819-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-17-1819-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 5
Research article
 | 
13 Sep 2021
Research article |  | 13 Sep 2021

Quantifying Southern Annular Mode paleo-reconstruction skill in a model framework

Willem Huiskamp and Shayne McGregor

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Cited articles

Abram, N. J., Mulvaney, R., Vimeux, F., Phipps, S. J., Turner, J., and England, M. H.: Evolution of the Southern Annular Mode during the past millennium, Nat. Clim. Change, 4, 564–569, https://doi.org/10.1038/nclimate2235, 2014. a, b, c, d, e, f, g, h, i, j, k
Bamston, A. G., Chelliah, M., and Goldenberg, S. B.: Documentation of a highly ENSO‐related sst region in the equatorial pacific: Research note, Atmos.-Ocean, 35, 367–383, https://doi.org/10.1080/07055900.1997.9649597, 1997. a
Batehup, R., McGregor, S., and Gallant, A. J. E.: The influence of non-stationary teleconnections on palaeoclimate reconstructions of ENSO variance using a pseudoproxy framework, Clim. Past, 11, 1733–1749, https://doi.org/10.5194/cp-11-1733-2015, 2015. a, b, c, d, e
Bracegirdle, T. J., Holmes, C. R., Hosking, J. S., Marshall, G. J., Osman, M., Patterson, M., and Rackow, T.: Improvements in Circumpolar Southern Hemisphere Extratropical Atmospheric Circulation in CMIP6 Compared to CMIP5, Earth and Space Science, 7, e2019EA001065, https://doi.org/10.1029/2019EA001065, 2020. a, b
Cullen, L. E. and Grierson, P. F.: Multi-decadal scale variability in autumn-winter rainfall in south-western Australia since 1655 AD as reconstructed from tree rings of Callitris Columellaris, Clim. Dynam., 33, 433–444, https://doi.org/10.1007/s00382-008-0457-8, 2009. a, b
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This study investigates the reliability of paleo-reconstructions of the Southern Annular Mode (SAM) using climate model data. We find that reconstructions are able to capture ~ 60 % of the SAM variability at best, with poorer reconstructions managing only 35 %. Reconstructions perform best when they use more proxies sourced from the entire Southern Hemisphere land mass. Future reconstructions should endeavour to address both sampling and proxy–SAM correlation stability uncertainties.
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