Reconstructing climatic modes of variability from proxy records using ClimIndRec version 1.0

Abstract

Modes of climate variability strongly impact our climate and thus human society. Nevertheless, the statistical properties of these modes remain poorly known due to the short time frame of instrumental measurements. Reconstructing these modes further back in time using statistical learning methods applied to proxy records is useful for improving our understanding of their behaviour. For doing so, several statistical methods exist, among which principal component regression is one of the most widely used in paleoclimatology. Here, we provide the software ClimIndRec to the climate community; it is based on four regression methods (principal component regression, PCR; partial least squares, PLS; elastic net, Enet; random forest, RF) and cross-validation (CV) algorithms, and enables the systematic reconstruction of a given climate index. A prerequisite is that there are proxy records in the database that overlap in time with its observed variations. The relative efficiency of the methods can vary, according to the statistical properties of the mode and the proxy records used. Here, we assess the sensitivity to the reconstruction technique. ClimIndRec is modular as it allows different inputs like the proxy database or the regression method. As an example, it is here applied to the reconstruction of the North Atlantic Oscillation by using the PAGES 2k database. In order to identify the most reliable reconstruction among those given by the different methods, we use the modularity of ClimIndRec to investigate the sensitivity of the methodological setup to other properties such as the number and the nature of the proxy records used as predictors or the targeted reconstruction period. We obtain the best reconstruction of the North Atlantic Oscillation (NAO) using the random forest approach. It shows significant correlation with former reconstructions, but exhibits higher validation scores.

Major Differences in Regional Climate Impact Between High‐ and Low‐Latitude Volcanic Eruptions

“…The SEA of the temporal response of the reconstructed NAO is shown in Figure 2. Except for the summer response to NH eruptions the analysis indicates that the mean response of the NAO to volcanic eruptions is longer than the 1–3 year duration of the forcing, which is consistent with studies of the winter NAO (Michel et al., 2020; Sjolte, Sturm, et al., 2018). The apparent shorter duration of the summer response to NH eruptions could depend on the choice of the volcanic eruptions used in the SEA, although sensitivity tests show that our results for the NAO response generally is robust with respect to selection of volcanic eruptions (Figure ).…”

“…(2015) and Michel et al. (2020) (Figure ) support the findings of a positive winter NAO after EQ eruptions as well as the negative winter NAO following NH eruptions (Figure ). In the latter case, the response in the reconstructions by Ortega et al.…”

A 2,000-year Bayesian NAO reconstruction from the Iberian Peninsula

“…The chronology of the sediment deposition of the CIM12-04A core was previously determined by Sánchez-López et al 60 . It was derived using the activity-depth profile of 210 Pb in the uppermost 9 cm of the core together with six AMS 14 Climate datasets. We used the NAO extended winter index (Jan-May) spanning the period 1824-2012 CE to produce the NAO influence reconstruction.…”

“…From a methodological point of view, most previously published NAO reconstructions have been based on the use of some variant of regression models, often coupled with Principal Components Analysis (PCA) 14 and references therein . By contrast, richer models using Bayesian inference have been extensively used during the last decade for age-depth chronological building 28 – 30 as well as for climate and environmental reconstructions using biological proxies 31 – 34 .…”

“…This importance of the NAO for explaining European climate variability ( Fig. 1) has encouraged a number of initiatives to produce NAO reconstructions across different timescales [7][8][9][10][11][12][13][14] . However, these are still challenged within the paleoclimate community, partly because there is a widespread use of ambiguous terminology.…”