Estimating 750 years of temperature variations and uncertainties in the Pyrenees by tree-ring reconstructions and climate simulations

I Dorado Liñán,I Heinrich,J P Montávez,F González-Rouco,U Büntgen,E Zorita,E Gutiérrez,J J Gómez-Navarro,G Helle,M Brunet

doi:10.5194/cp-8-919-2012

Abstract

Abstract. Past temperature variations are usually inferred from proxy data or estimated using general circulation models. Comparisons between climate estimations derived from proxy records and from model simulations help to better understand mechanisms driving climate variations, and also offer the possibility to identify deficiencies in both approaches. This paper presents regional temperature reconstructions based on tree-ring maximum density series in the Pyrenees, and compares them with the output of global simulations for this region and with regional climate model simulations conducted for the target region. An ensemble of 24 reconstructions of May-to-September regional mean temperature was derived from 22 maximum density tree-ring site chronologies distributed over the larger Pyrenees area. Four different tree-ring series standardization procedures were applied, combining two detrending methods: 300-yr spline and the regional curve standardization (RCS). Additionally, different methodological variants for the regional chronology were generated by using three different aggregation methods. Calibration verification trials were performed in split periods and using two methods: regression and a simple variance matching. The resulting set of temperature reconstructions was compared with climate simulations performed with global (ECHO-G) and regional (MM5) climate models. The 24 variants of May-to-September temperature reconstructions reveal a generally coherent pattern of inter-annual to multi-centennial temperature variations in the Pyrenees region for the last 750 yr. However, some reconstructions display a marked positive trend for the entire length of the reconstruction, pointing out that the application of the RCS method to a suboptimal set of samples may lead to unreliable results. Climate model simulations agree with the tree-ring based reconstructions at multi-decadal time scales, suggesting solar variability and volcanism as the main factors controlling preindustrial mean temperature variations in the Pyrenees. Nevertheless, the comparison also highlights differences with the reconstructions, mainly in the amplitude of past temperature variations and in the 20th century trends. Neither proxy-based reconstructions nor model simulations are able to perfectly track the temperature variations of the instrumental record, suggesting that both approximations still need further improvements.

Highlights

Estimations of future climate change indicate that variations at regional scales may be larger than the global average (IPCC, 2007)
The PCA performed on the set of maximum density (MXD) chronologies reveals that the first principal component (PC1) is dominant and www.clim-past.net/8/919/2012/
We provide a set of newly developed May-to-September mean temperature reconstructions for the Pyrenees that represent an improvement in comparison to the reconstruction by Buntgen et al (2008), our reconstructions still do not perfectly match the low-frequency variations of the instrumental record

Summary

Introduction

Estimations of future climate change indicate that variations at regional scales may be larger than the global average (IPCC, 2007) These regional projections are hampered by the limited knowledge of the mechanisms that give rise to variability at multi-decadal and longer time scales. Tree-rings may contain useful information on past environmental conditions, which can be used to reconstruct past climate using statistical relationships to a target climate variable (Fritts, 1976; Cook and Kairiukstis, 1990) In this respect, tree-ring width and density are the most widely used proxies for the last millennium, and their links to seasonal temperatures have been extensively studied (Briffa et al, 2002, 2004; Buntgen et al, 2006, 2007, 2008; Esper et al, 2002, 2005a; Grudd, 2008). The technique applied to transform tree-ring parameters to meteorological units implies a challenge: whereas simple linear regression methods may underestimate low-frequency variability, variance matching, in the following referred to as scaling, shows better performance in retaining large-scale variations but at the expense of inflated error estimates (Esper et al, 2005b; Zorita et al, 2010; McCarrol et al, 2011)

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