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Spatial performance of four climate field reconstruction methods targeting the Common Era

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2011-06-15
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American Geophysical Union
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The spatial skill of four climate field reconstruction (CFR) methods is investigated using pseudoproxy experiments (PPEs) based on two millennial-length general circulation model simulations. Results indicate that presently available global and hemispheric CFRs for the Common Era likely suffer from spatial uncertainties not previously characterized. No individual method produced CFRs with universally superior spatial error statistics, making it difficult to advocate for one method over another. Northern Hemisphere means are shown to be insufficient for evaluating spatial skill, indicating that the spatial performance of future CFRs should be rigorously tested for dependence on proxy type and location, target data and employed methodologies. Observed model-dependent methodological performance also indicates that CFR methods must be tested across multiple models and conclusions from PPEs should be carefully evaluated against the spatial statistics of real-world climatic fields. Citation: Smerdon, J. E., A. Kaplan, E. Zorita, J. F. Gonzalez-Rouco, and M. N. Evans (2011), Spatial performance of four climate field reconstruction methods targeting the Common Era, Geophys. Res. Lett., 38, L11705, doi: 10.1029/2011GL047372.
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Copyright 2011 by the American Geophysical Union. Supported in part by NSF grants ATM0902436 and ATM0902715, by NASA grant NNX09AF44G, by NOAA grants NA07OAR4310060 and NA10OAR4320137, and by the European Project Millennium. Supplementary materials can be accessed at http://www.ldeo.columbia.edu/similar to jsmerdon/2011_grl_supplement.html. LDEO contribution 7471.
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Ammann, C. M., F. Joos, D. S. Schimel, B. L. Otto‐Bliesner, and R. A. Tomas (2007), Solar influence on climate during the past millennium: Results from transient simulations with the NCAR Climate System Model, Proc. Natl. Acad. Sci. U. S. A., 104, 3713–3718, doi:10.1073/pnas.0605064103. Christiansen, B., T. Schmith, and P. Thejll (2009), A surrogate ensemble study of climate reconstruction methods: Stochasticity and robustness, J. Clim., 22, 951–976, doi:10.1175/2008JCLI2301.1. Golub, G. H., M. Heath, and G. Wahba (1979), Generalized cross‐validation as a method for choosing a good ridge parameter, Technometrics, 21, 215–223, doi:10.2307/1268518. González Rouco, J. F., H. Beltrami, E. Zorita, and H. von Storch (2006), Simulation and inversion of borehole temperature profiles in surrogate climates: Spatial distribution and surface coupling, Geophys. Res. Lett., 33, L01703, doi:10.1029/2005GL024693. Hansen, P. C. (1997), Rank‐Deficient and Discrete Ill‐Posed Problems: Numerical Aspects of Linear Inversion, SIAM Monogr. Math. Model. Comput., 247 pp., Soc. for Ind. and Appl. Math., Philadelphia, Pa. Hegerl, G. C., et al. (2007), Detection of human influence on a new, validated 1500‐year climate reconstruction, J. Clim., 20, 650–666, doi:10.1175/JCLI4011.1. Hoerl, A. E., and R. W. Kennard (1970), Ridge regression: Biased estimation for non‐orthogonal problems, Technometrics, 12, 55–67, doi:10.2307/1267351. Jansen, E., et al. (2007), Palaeoclimate, in Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., pp. 433–497, Cambridge Univ. Press, Cambridge, U. K. Lee, T. C. K., F. W. Zwiers, and M. Tsao (2008), Evaluation of proxy‐based millennial reconstruction methods, Clim. Dyn., 31, 263–281, doi:10.1007/s00382-007-0351-9. Mann, M. E., R. S. Bradley, and M. K. Hughes (1998), Global‐scale temperature patterns and climate forcing over the past six centuries, Nature, 392, 779–787, doi:10.1038/33859. Mann, M. E., S. Rutherford, E. Wahl, and C. Ammann (2007), Robustness of proxy‐based climate field reconstruction methods, J. Geophys. Res., 112, D12109, doi:10.1029/2006JD008272. Mann, M. E., et al. (2008), Proxy‐based reconstructions of hemispheric and global surface temperature variations over the past two millennia, Proc. Natl. Acad. Sci. U. S. A., 105, 13,252–13,257, doi:10.1073/pnas.0805721105. Mann, M. E., et al. (2009), Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly, Science, 326, 1256–1260, doi:10.1126/science.1177303. Schneider, T. (2001), Analysis of incomplete climate data: Estimation of mean values and covariance matrices and imputation of missing values, J. Clim., 14, 853–871, doi:10.1175/1520-0442(2001)014<0853: AOICDE>2.0.CO;2. Smerdon, J. E., and A. Kaplan (2007), Comments on “Testing the fidelity of methods used in proxy‐based reconstructions of past climate”: The role of the standardization interval, J. Clim., 20, 5666–5670, doi:10.1175/2007JCLI1794.1. Smerdon, J. E., A. Kaplan, and D. E. Amrhein (2010), Erroneous model field representations in multiple pseudoproxy studies: Corrections and implications, J. Clim., 23, 5548–5554, doi:10.1175/2010JCLI3742.1. Smerdon, J. E., A. Kaplan, D. Chang, and M. N. Evans (2011), A pseudoproxy evaluation of the CCA and RegEM methods for reconstructing climate fields of the last millennium, J. Clim., 24, 1284–1309, doi:10.1175/2010JCLI4110.1. von Storch, H., E. Zorita, J. M. Jones, Y. Dimitriev, F. González Rouco, and S. F. B. Tett (2004), Reconstructing past climate from noisy data, Science, 306, 679–682, doi:10.1126/science.1096109. von Storch, H., E. Zorita, J. M. Jones, F. González Rouco, and S. F. B. Tett (2006), Response to comment on “Reconstructing past climate from noisy data,” Science, 312, 529c, doi:10.1126/science.1121571.
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