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	<journal>
		<journal_title>Climate of the Past</journal_title>
		<journal_url>www.clim-past.net</journal_url>
		<issn>1814-9324</issn>
		<eissn>1814-9332</eissn>
		<volume_number>6</volume_number>
		<issue_number>2</issue_number>
		<publication_year>2010</publication_year>
	</journal>
	<doi>10.5194/cp-6-273-2010</doi>
	<article_url>http://www.clim-past.net/6/273/2010/</article_url>
	<abstract_html>http://www.clim-past.net/6/273/2010/cp-6-273-2010.html</abstract_html>
	<fulltext_pdf>http://www.clim-past.net/6/273/2010/cp-6-273-2010.pdf</fulltext_pdf>
	<start_page>273</start_page>
	<end_page>279</end_page>
	<publication_date>2010-04-20</publication_date>
	<article_title content_type="html">Technical Note: Correcting for signal attenuation from noisy proxy data in climate reconstructions</article_title>
	<authors>
		<author numeration="1" affiliations="1,4">
			<name>C. M. Ammann</name>
			<email>ammann@ucar.edu</email>
		</author>
		<author numeration="2" affiliations="2,4">
			<name>M. G. Genton</name>
		</author>
		<author numeration="3" affiliations="3,4">
			<name>B. Li</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO 80307-3000, USA</affiliation>
		<affiliation numeration="2" content_type="html">Department of Statistics, Texas A&amp;M University, College Station, TX 77843-3143, USA</affiliation>
		<affiliation numeration="3" content_type="html">Department of Statistics, Purdue University, West Lafayette, IN 47907, USA</affiliation>
		<affiliation numeration="4" content_type="html">These authors contributed equally to this work.</affiliation>
	</affiliations>
	<abstract content_type="html">Regression-based climate reconstructions scale one or more noisy
proxy records against a (generally) short instrumental data series. Based on
that relationship, the indirect information is then used to estimate that
particular measure of climate back in time. A well-calibrated proxy
record(s), if stationary in its relationship to the target, should
faithfully preserve the mean amplitude of the climatic variable. However, it
is well established in the statistical literature that traditional
regression parameter estimation can lead to substantial amplitude
attenuation if the predictors carry significant amounts of noise. This issue
is known as &quot;Measurement Error&quot; (Fuller, 1987; Carroll et al.,
2006). Climate proxies derived from tree-rings, ice cores, lake sediments,
etc., are inherently noisy and thus all regression-based reconstructions
could suffer from this problem. Some recent applications attempt to ward off
amplitude attenuation, but implementations are often complex (Lee et
al., 2008) or require additional information, e.g. from climate models
(Hegerl et al., 2006, 2007). Here we explain the cause
of the problem and propose an easy, generally applicable, data-driven
strategy to effectively correct for attenuation (Fuller, 1987;
Carroll et al., 2006), even at annual resolution. The impact is illustrated
in the context of a Northern Hemisphere mean temperature
reconstruction. An inescapable trade-off for achieving an unbiased
reconstruction is an increase in variance, but for many climate applications
the change in mean is a core interest.</abstract>
	<references>
		<reference numeration="1" content_type="text"> Akritas, M. G. and Bershady, M. A.: Linear regression for astronomical data with measurement errors and intrinsic scatter, The Astrophys. J., 470, 706–714, 1996. </reference>
		<reference numeration="2" content_type="text"> Allen, M. R. and Stott, P. A.: Estimating signal amplitudes in optimal fingerprinting, part i: Theory, Clim. Dynam., 21, 477–491, 2003. </reference>
		<reference numeration="3" content_type="text"> Ammann, C. M., Joos, F., Schimel, D. S., Otto-Bliesner, B. L., and Tomas, R. A.: Solar influence on climate during the past millennium: Results from transient simulations with the ncar climate system model, P. Natl. Acad. Sci. USA, 104, 3713–3718, 2007. </reference>
		<reference numeration="4" content_type="text"> Ammann, C. M. and Wahl, E. R.: The importance of the geophysical context in statistical evaluations of climate reconstruction procedures, Clim. Change, 85, 71–88, 2007. </reference>
		<reference numeration="5" content_type="text"> Briffa, K. R., Osborn, T. J., Schweingruber, F. H., Harris, I. C., Jones, P. D., Shiyatov, S. G., and Vaganov, E. A.: Low-frequency temperature variations from a northern tree ring density network, J. Geophys. Res.-Atmos., 106, 2929–2941, 2001. </reference>
		<reference numeration="6" content_type="text"> Bürger, G., Fast, I., and Cubasch, U.: Climate reconstruction by regression – 32 variations on a theme, Tellus A, 58, 227–235, 2006. </reference>
		<reference numeration="7" content_type="text"> Carroll, R. J. and Ruppert, D.: The use and misuse of orthogonal regression in linear errors-in-variables models, Am. Stat., 50, 1–6, 1996. </reference>
		<reference numeration="8" content_type="text"> Carroll, R. J., Ruppert, D., Stefanski, L. A., and Crainiceanu, C. M.: Measurement error in nonlinear models: A modern perspective, 2nd Edition, Chapman &amp; Hall, Boca Raton, FL, 2006. </reference>
		<reference numeration="9" content_type="text"> Christiansen, B., Schmith, T., and Thejll, P.: A surrogate ensemble study of climate reconstruction methods: Stochasticity and robustness, J. Climate, 22, 951–976, doi:10.1175/2008JCLI2301.1, 2009. </reference>
		<reference numeration="10" content_type="text"> Crowley, T. J. and Lowery, T. S.: How warm was the medieval warm period?, Ambio, 29, 51–54, 2000. </reference>
		<reference numeration="11" content_type="text"> Esper, J., Cook, E. R., and Schweingruber, F. H.: Low-frequency signals in long tree-ring chronologies for reconstructing past temperature variability, Science, 295, 2250–2253, 2002. </reference>
		<reference numeration="12" content_type="text"> Esper, J., Frank, D. C., Wilson, R. J. S., and Briffa, K. R.: Effect of scaling and regression on reconstructed temeprature amplitude for the past millenium, Geophys. Res. Lett., 32, L07711, doi:10.1029/2004GL021236, 2005. </reference>
		<reference numeration="13" content_type="text"> Fritts, H. C., Guiot, J., Gordon, G. A., and Schweingruber, F. H.: Methods of calibration, verification and reconstruction, in: Methods of dendrochronology: Applications in the environmental sciences, edited by: Cook, E. R. and Kairiankstis, L. A., Kluwer Academic Publications, 1990. </reference>
		<reference numeration="14" content_type="text"> Fuller, W. A.: Measurement error models, Wiley, New York, NY., 1987. </reference>
		<reference numeration="15" content_type="text"> Hegerl, G. C., Crowley, T. J., Hyde, W. T., and Frame, D. J.: Climate sensitivity constrained by temperature reconstructions over the past seven centuries, Nature, 440, 1029–1032, 2006. </reference>
		<reference numeration="16" content_type="text"> Hegerl, G. C., Crowley, T. J., Allen, M., Hyde, W. T., Pollack, H. N., Smerdon, J., and Zorita, E.: Detection of human influence on a new, validated 1500-year temperature reconstruction, J. Climate, 20, 650–666, 2007. </reference>
		<reference numeration="17" content_type="text"> Huang, S. P., Pollack, H. N., and Shen, P. Y.: Temperature trends ever the past five centuries reconstructed from borehole temperatures, Nature, 403, 756–758, 2000. </reference>
		<reference numeration="18" content_type="text"> Isobe, T., Feigelson, E. D., Akritas, M. G., and Babu, G. J.: Linear regression in astronomy. I., The Astrophys. J., 364, 104–113, 1990. </reference>
		<reference numeration="19" content_type="text"> Jones, P. D., Briffa, K. R., Barnett, T. P., and Tett, S. F. B.: High-resolution palaeoclimatic records for the last millennium: Interpretation, integration and comparison with general circulation model control-run temperatures, Holocene, 8, 455–471, 1998. </reference>
		<reference numeration="20" content_type="text"> Jones, P. D., Osborn, T. J., and Briffa, K. R.: The evolution of climate over the last millennium, Science, 292, 662–667, 2001. </reference>
		<reference numeration="21" content_type="text"> Juckes, M. N., Allen, M. R., Briffa, K. R., Esper, J., Hegerl, G. C., Moberg, A., Osborn, T. J., and Weber, S. L.: Millennial temperature reconstruction intercomparison and evaluation, Clim. Past, 3, 591–609, 2007. </reference>
		<reference numeration="22" content_type="text"> Kelly, B. C.: Some aspects of measurement error in linear regression of astronomical data, The Astrophys. J., 665, 1489–1506, 2007. </reference>
		<reference numeration="23" content_type="text"> Küttel, M., Luterbacher, J., Zorita, E., Xoplaki, E., Riedwyl, N., and Wanner, H.: Testing a european winter surface temperature reconstruction in a surrogate climate, Geophys. Res. Lett., 34, L07710, doi:10.1029/2006GL027907, 2007. </reference>
		<reference numeration="24" content_type="text"> Lee, T. C. K., Zwiers, F. W., and Tsao, M.: Evaluation of proxy-based millennial reconstruction methods, Clim. Dynam., 31, 263–281, 2008. </reference>
		<reference numeration="25" content_type="text"> Li, B., Nychka, D. W., and Ammann, C. M.: The `hockey stick&apos; and the 1990s: A statistical perspective on reconstructing hemispheric temperatures, Tellus A, 59, 591–598, 2007. </reference>
		<reference numeration="26" content_type="text"> Luterbacher, J., Dietrich, D., Xoplaki, E., Grosjean, M., and Wanner, H.: European seasonal and annual temperature variability, trends, and extremes since 1500, Science, 303, 1499–1503, 2004. </reference>
		<reference numeration="27" content_type="text"> Mann, M. E., Bradley, R. S., and Hughes, M. K.: Global-scale temperature patterns and climate forcing over the past six centuries, Nature, 392, 779–787, 1998. </reference>
		<reference numeration="28" content_type="text"> Mann, M. E. and Jones, P. D.: Global surface temperatures over the past two millennia, Geophys. Res. Lett., 30(4), 1820, doi:10.1029/2003gl017814, 2003. </reference>
		<reference numeration="29" content_type="text"> Mann, M. E., Rutherford, S., Wahl, E., and Ammann, C.: Robustness of proxy-based climate field reconstruction methods, J. Geophys. Res.-Atmos., 112, D12109, doi:10.1029/2006JD008272, 2007a. </reference>
		<reference numeration="30" content_type="text"> Mann, M. E., Rutherford, S., Wahl, E., and Ammann, C.: Reply, J. Climate, 20, 5671–5674, 2007b. </reference>
		<reference numeration="31" content_type="text"> Mann, M. E., Zhang, Z., Hughes, M. K., Bradley, R. S., Miller, S. K., Rutherford, S., and Ni, F.: Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia, P. Natl. Acad. Sci. USA, 105, 13252–13257, doi:10.1073/pnas.0805721105, 2008. </reference>
		<reference numeration="32" content_type="text"> Moberg, A., Sonechkin, D. M., Holmgren, K., Datsenko, N. M., and Karlen, W.: Highly variable northern hemisphere temperatures reconstructed from low- and high-resolution proxy data, Nature, 433, 613–617, 2005. </reference>
		<reference numeration="33" content_type="text"> Moberg, A., Mohammad, R., and Mauritsen, T.: Analysis of the Moberg et al. (2005) hemispheric temperature reconstruction, Cli. Dynam., 31, 957–971, 2008. </reference>
		<reference numeration="34" content_type="text"> Osborn, T. and Briffa, K. R.: The spatial extent of 20th-century warmth in the context of the past 1200 years, Science, 311, 841–844, 2006. </reference>
		<reference numeration="35" content_type="text"> Osborne, C.: Statistical calibration: A review, Int. Stat. Rev., 59, 309–336, 1991. </reference>
		<reference numeration="36" content_type="text"> Riedwyl, N., Kuettel, M., Luterbacher, J., and Wanner, H.: Comparison of climate field reconstruction techniques: Application to Europe, Clim. Dynam., 32, 381–395, doi:10.1007/s00382-008-0395-5, 2009. </reference>
		<reference numeration="37" content_type="text"> Rutherford, S., Mann, M. E., Osborn, T. J., Bradley, R. S., Briffa, K. R., Hughes, M. K., and Jones, P. D.: Proxy-based northern hemisphere surface temperature reconstructions: Sensitivity to method, predictor network, target season, and target domain, J. Climate, 18, 2308–2329, 2005. </reference>
		<reference numeration="38" content_type="text"> Rutherford, S., Mann, M. E., Wahl, E. R., and Ammann, C. M.: Reply to comment by J. E. Smerdon, J. F. González-Rouco, and E. Zorita on &quot;Robustness of proxy-based climate field reconstruction methods.&quot;, J. Geophys. Res., 113, D18107, doi:10.1029/2008JD009964, 2008. </reference>
		<reference numeration="39" content_type="text"> Smerdon, J. E. and Kaplan, A.: Comments on &quot;Testing the fidelity of methods used in proxy-based reconstructions of past climate&quot;: The role of the standardization interval, J. Climate, 20, 5666–5670, doi:10.1175/2007jcli1794.1, 2007. </reference>
		<reference numeration="40" content_type="text"> Smerdon, J. E., Kaplan, A., and Chang, D.: On the Origin of the standardization sensitivity in RegEM climate field reconstructions, J. Climate, 21, 6710–6723, 2008. </reference>
		<reference numeration="41" content_type="text"> Stone, M.: Cross-validatory choice and assessment of statistical predictions (with discussion), J. Ro. Stat. Soc., Series B, 36, 111–147, 1974. </reference>
		<reference numeration="42" content_type="text"> von Storch, H., Zorita, E., Jones, J. M., Dimitriev, Y., Gonzalez-Rouco, F., and Tett, S. F. B.: Reconstructing past climate from noisy data, Science, 306, 679–682, 2004. </reference>
		<reference numeration="43" content_type="text"> Wahl, E. R., Ritson, D. M., and Ammann, C. M.: Comment on &quot;Reconstructing past climate from noisy data&quot;, Science, 312(529b), doi:10.1126/science.1120866, 2006. </reference>
		<reference numeration="44" content_type="text"> Zorita, E., González-Rouco, F., and Legutke, S.: Testing the Mann et al. (1998) approach to paleoclimate reconstructions in the context of a 1000-yr control simulation with the ECHO-G coupled climate model, J. Climate, 16, 1378–1390, 2003. </reference>
	</references>
</article>

