19 Jul 2021
19 Jul 2021
Status: this preprint is currently under review for the journal CP.

Climate Change Detection and Attribution using observed and simulated Tree-Ring Width

Jörg Franke1,2,, Michael Neil Evans2,3,, Andrew Schurer4, and Gabriele Clarissa Hegerl4 Jörg Franke et al.
  • 1Institute of Geography, University of Bern, Switzerland
  • 2Oeschger Centre for Climate Change Research, University of Bern, Switzerland
  • 3Department of Geology and Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland 20742, USA
  • 4School of GeoSciences, The University of Edinburgh, Edinburgh, United Kingdom
  • These authors contributed equally to this work.

Abstract. The detection and attribution (D&A) of paleoclimatic change to external radiative forcing relies on regression of statistical reconstructions on simulations. However, this procedure may be biased by assumptions of stationarity and univariate linear response of the underlying paleoclimatic observations. Here we perform a D&A study via regression of tree ring width (TRW) observations on TRW simulations which are forward modeled from climate simulations. Temperature and moisture-sensitive TRW simulations show distinct patterns in time and space. Temperature-sensitive TRW observations and simulations are significantly correlated for northern hemisphere averages, and their variation is attributed most closely to volcanically forced simulations. In decadally smoothed temporal fingerprints, we find the observed responses to be significantly larger and/or more persistent than the simulated responses. The pattern of simulated TRW of moisture-limited trees is consistent with the observed anomalies in the two years following major volcanic eruptions. We can for the first time attribute this spatiotemporal fingerprint in moisture limited tree-ring records to volcanic forcing. These results suggest that use of nonlinear and multivariate proxy system models in paleoclimatic detection and attribution studies may permit more realistic, spatially resolved and multivariate fingerprint detection studies, and evaluation of the climate sensitivity to external radiative forcing, than has previously been possible.

Jörg Franke et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on cp-2021-80', Anonymous Referee #1, 11 Oct 2021
  • RC2: 'Comment on cp-2021-80', Kevin Anchukaitis, 28 Jan 2022

Jörg Franke et al.

Jörg Franke et al.


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Short summary
Detection and attribution is a statistical method to evaluate if external factors or random variability cause climatic changes. We use for the first time a comparison of simulated and observed tree-ring width that circumvents many limitations of previous studies relying on climate reconstructions. We detect and attribute variability in temperature limited trees to strong volcanic eruption and for the first time detect a spatial pattern in the growth of moisture sensitive trees after eruptions.