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Challenges and perspectives for large‐scale temperature reconstructions of the past two millennia
Author(s) -
Christiansen Bo,
Ljungqvist Fredrik Charpentier
Publication year - 2017
Publication title -
reviews of geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.087
H-Index - 156
eISSN - 1944-9208
pISSN - 8755-1209
DOI - 10.1002/2016rg000521
Subject(s) - proxy (statistics) , climate change , scale (ratio) , climatology , spatial ecology , volcano , temporal scales , environmental science , climatic variability , variance (accounting) , geology , computer science , geography , cartography , seismology , machine learning , ecology , oceanography , accounting , business , biology
Knowledge of the temperature variability during the last one to two millennia is important for providing a perspective to present‐day climate excursions, for assessing the sensitivity of the climate to different forcings, and for providing a test bed for climate models. Since systematic instrumental temperature records only extend back to the nineteenth century, such knowledge mainly relies on climate‐sensitive proxy data. Here we critically assess some of the many challenges related to large‐scale multiproxy temperature reconstructions. We begin with a review of available large‐scale temperature reconstructions, focusing on the differences in low‐frequency variability and the response to natural forcings such as major volcanic eruptions and changes in total solar irradiance. Then, we discuss different proxy selection strategies, review previously used reconstruction methods, and discuss their ability to reconstruct the amplitude of the low‐frequency variability. To shed additional light on the challenges of large‐scale reconstructions, we investigate the spatial and temporal correlation structures in the observed temperature field and discuss the implications of these correlation structures regarding the required number and positions of proxies. We demonstrate how the unavoidable uncertainty related to noisy proxies will show up as bias and variance in the reconstruction and that the partition between these forms of errors depends on the reconstruction method. Pseudo‐proxy experiments are conducted to further discuss the influence of noise and the requirements regarding the geographical location and number of proxies necessary for reliably reconstructing the low‐frequency variability. We conclude with recommendations for future large‐scale temperature reconstructions.

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