Articles | Volume 14, issue 6
Research article
29 Jun 2018
Research article |  | 29 Jun 2018

Assessing the performance of the BARCAST climate field reconstruction technique for a climate with long-range memory

Tine Nilsen, Johannes P. Werner, Dmitry V. Divine, and Martin Rypdal

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Cited articles

Beran, J., Feng, Y., Ghosh, S., and Kulik, R.: Long-Memory Processes, Springer, New York, 884 pp., 2013. a
Briffa, K. R., Jones, P. D., Bartholin, T. S., Eckstein, D., Schweingruber, F. H., Karlén, W., Zetterberg, P., and Eronen, M.: Fennoscandian summers from ad 500: temperature changes on short and long timescales, Clim. Dynam., 7, 111–119,, 1992. a
Briffa, K. R., Osborn, T., Schweingruber, F. H., Harris, I. C., Jones, P. D., Shiyatov, S. G., and Vaganov, E.: Low frequency temperature variations from a northern tree ring density network, J. Geophys. Res.-Atmos., 106, 2929–2941,, 2001. a
Christiansen, B.: Reconstructing the NH Mean Temperature: Can Underestimation of Trends and Variability Be Avoided?, J. Climate, 24, 674–692,, 2011. a, b
Christiansen, B. and Ljungqvist, F. C.: Challenges and perspectives for large-scale temperature reconstructions of the past two millennia, Rev. Geophys., 55, 40–96,, 2017. a
Short summary
The BARCAST climate field reconstruction method is tested using synthetic data experiments. It is demonstrated that the output reconstructions have altered statistical properties compared with the input data, but they are also not necessarily consistent with the model assumption of the reconstruction method. The conclusion is that the statistical properties of a reconstruction not only reflect the statistics of the real climate, but they may very well be affected by the manipulation of the data.