The impact of proxy selection strategies on a millennium-long ensemble of hydroclimatic records in Monsoon Asia

Lea Schneider, Fredrik Charpentier Ljungqvist, Bao Yang, Fahu Chen, Jianhui Chen, Jianyong Li, Zhixin Hao, Quan Sheng Ge, Stefanie Talento, Timothy Osborn, Jürg Luterbacher

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Abstract

Large-scale palaeoclimate reconstructions can be very sensitive to the proxy records they are based on, and hence to the criteria used to select proxy records. Data selection rarely follows objective criteria that are applicable to all types of proxies, including both low- and high-resolution records. Thus, there is a need for a uniform and transparent approach to assess the suitability of input proxy data for a reconstruction. Here, we develop classification criteria that are applicable to multiple proxy types and evaluate different selection strategies using a network of 62 millennium-long terrestrial hydroclimate proxy records from Monsoon Asia. Our results reveal that robust evidence for a coherent climate signal and high dating accuracy are important criteria for benchmarking the suitability of each proxy record. We determine these criteria by reviewing the literature for each record (rather than screening against instrumental data). We show that the proposed selection approach can yield a network with a stronger common signal. By evaluating the uncertainty and centennial variability of composite reconstructions, from differently selected subsets of the proxy network, it appears beneficial to use suitable proxies stemming from different archives, as well as having a dense network of proxy sites. We suggest that future large-scale palaeoclimate reconstructions might be improved by evaluating proxy networks according to the universal categories presented here and, if indicated, removing less suitable records. This will strengthen the climate signal in the final reconstruction, allowing more precise inferences about past climate variability and more robust comparisons with climate model simulations.
Original languageEnglish
Article number105917
JournalQuaternary Science Reviews
Volume223
Early online date24 Sep 2019
DOIs
Publication statusPublished - Nov 2019

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