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Spatial performance of four climate field reconstruction methods targeting the Common Era
Author(s) -
Smerdon J. E.,
Kaplan A.,
Zorita E.,
GonzálezRouco J. F.,
Evans M. N.
Publication year - 2011
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2011gl047372
Subject(s) - proxy (statistics) , climatology , spatial ecology , northern hemisphere , spatial analysis , general circulation model , spatial correlation , spatial variability , field (mathematics) , environmental science , common spatial pattern , computer science , statistics , climate change , geology , machine learning , mathematics , ecology , pure mathematics , oceanography , biology
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.