The tenth IMSC, Beijing, China, 2007 - International Meetings on ...

A multiple surrogate data study of reconstruction skills
Speaker: Bo Christiansen
Bo Christiansen
Danish Meteorological Institute
boc@dmi.dk
Torben Schmith
Danish Meteorological Institute
Peter <strong>The</strong>jll
Danish Meteorological Institute
Reconstruction methods may differ in many details but they basically rely on a statistical
relationship between proxy data and observations. However, the statistical properties and
robustness of such methods are not well known which has led to the current vivid discussion
about the quality of published reconstructions. Of particular concern has been the methods'
ability to catch low frequency variability.
In this paper we will present a systematic study of reconstruction methods. <strong>The</strong> methods
include both global-mean reconstructions, field reconstructions based on Principal
Components and Canonical Correlation Analysis, and the regularized EM algorithm.
Based on a climate simulation of the period AD 1500-2000 with the ECHAM4/OPYC3
Ocean-Atmosphere General Circulation Model we use a novel technique to generate an
ensemble of surrogate fields with the same temporal and spatial characteristics as the original
modelled surface temperature field. This technique also allows us to control the strength of the
decadal-multidecadal variability in the surrogate fields. We apply the reconstruction methods
to each member of the ensemble of surrogate worlds: we train the reconstruction method on a
subperiod (defining the set of surrogate proxies by degrading a number of gridbox timeseries)
and reconstruct the remaining years. <strong>The</strong> multi-world approach will allow us to make statistical
robust estimates both of the mean properties of the different reconstruction methods and their
statistical variance and significance.
Meiyu since 1736 over Middle-Lower Reaches of Yangtze River
Speaker: Quansheng Ge
Quansheng Ge
Institute of Geographical Sciences and Natural Resources Researches, CAS
geqs@igsnrr.ac.cn
Jingyun Zheng
Institute of Geographical Sciences and Natural Resources Researches, CAS
Zhixin Hao
Institute of Geographical Sciences and Natural Resources Researches, CAS
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