Comment on cp-2021-80

doi:10.5194/cp-2021-80-cc1

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.

Highlights

One of the crucial questions in climate change research is to determine how external radiative forcings bring about climate variation and change, and if the forced response may be distinguished from the internal, unforced variability, and between different forcings
Because the fingerprint of external radiative forcing may or may not be distinct and unique in temperature and moisture, we use the fit of Vaganov–Shashkin Lite (VSL) diagnostic variables GT and GM to binomial distributions to determine whether each simulation is primarily controlled by temperature, moisture, both or neither control at the p
Temperature-sensitive tree ring width (TRW) averaged over all grid boxes, we find scaling factor b not significantly different from 1; in other words, observed and simulated temperature sensitive chronologies agree within uncertainty (Fig. 5, left panel, bALL)

Summary

Introduction

One of the crucial questions in climate change research is to determine how external radiative forcings bring about climate variation and change, and if the forced response may be distinguished from the internal, unforced variability, and between different forcings. Methods are generally based on matching observed changes with patterns derived from climate model simulations, which were driven by single and multiple external forcings, including solar variability, volcanic aerosols, the well-mixed greenhouse gases, orbital variations and land use change. Such analyses have been limited to periods when instrumental observations of physically measurable variables and derived diagnostics are available, with global observation networks becoming dense enough for such studies about 100 to 150 years before present. Such longer-term studies would integrate longer-term responses of the climate system to external radiative forcing, enabling a more complete picture of the equilibrium and transient response, and of the climate sensitivity to external radiative forcing

Results

Discussion

Conclusion