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

Abstract

The North Atlantic Oscillation (NAO) is the major atmospheric mode that controls winter European climate variability because its strength and phase determine regional temperature, precipitation and storm tracks. The NAO spatial structure and associated climatic impacts over Europe are not stationary making it crucial to understanding its past evolution in order to improve the predictability of future scenarios. In this regard, there has been a dramatic increase in the number of studies aimed at reconstructing past NAO variability, but the information related to decadal-scale NAO evolution beyond the last millennium is scarce and inconclusive. We present a new 2,000-year multi-annual, proxy-based reconstruction of local NAO impact, with associated uncertainties, obtained by a Bayesian approach. This new local NAO reconstruction is obtained from a mountain lacustrine sedimentary archive of the Iberian Peninsula. This geographical area is not included in previous NAO reconstructions despite being a widely used region for instrumental-based NAO measurements. We assess the main external forcings (i.e., volcanic eruptions and solar activity) on NAO variability which, on a decadal scale, show that a low number of sunspots correlate to low NAO values. By comparison with other previously published NAO reconstructions in our analyses we can test the stationarity of the solar influence on the NAO signal across a latitudinal gradient based on the position of the employed archives for each NAO reconstruction. Inconclusive results on the volcanic forcing on NAO variability over decadal time-scales indicates the need for further studies. Moreover, we highlight the potential role of other North Atlantic modes of variability (i.e., East Atlantic pattern) on the non-stationary behaviour of the NAO throughout the Common Era, likely via solar forcing.

Climate Patterns in the World’s Longest History of Storm-Erosivity: The Arno River Basin, Italy, 1000–2019 CE

“…In a multi-centennial perspective (1680-2019 CE), Diodato et al (2020a) showed that substantially neutral (winter) NAO states (without a clear dominance of positive or negative phases) correspond to a decline of erosivity extremes throughout the Mediterranean. In the present basin-wide study, we observed (Figure 7E) a predominantly weak anticorrelation between the reconstructed erosivity time-series and the proxy-based multi-annual NAO reconstruction of Hernández et al (2020). These studies highlight the need for a more detailed understanding of the linkages between largescale atmospheric and oceanic oscillations and different erosivity outputs (e.g., average or extreme events), which depend on the geographic context (e.g., large regions or small river basins) and the temporal frame (e.g., seasonal or yearly) in which the hydrological response is assessed.…”

“…(A) Evolution (red arrow indicating the change-point year 1490) of estimated annual rainfall erosivity (blue circles; out-of-scale value in the year 1688) with the relative 95th and 98th percentiles (horizontal bold yellow and pink lines, respectively), and the 11-years Gaussian filtered erosivity series (bold blue curve), (B) decadal-scale variability of the 98th percentile of rainfall erosivity (black curve), (C) wavelet spectrum of the rainfall erosivity time series with bounded colors identifying 0.05 significance areas (the bell-shaped, black contour marks the limit between the reliable region and the region below the contour where the edge effects occur, a.k.a. cone of influence), (D) Atlantic Multidecadal Variability (AMV;Wang et al, 2017), (E) North Atlantic Oscillation (NAO;Hernández et al, 2020). The bottom colored band indicates mean Italian summer (June-July-August) temperature anomalies (°C) with respect to the 1961-1990 climatology(Luterbacher et al, 2016) for the Medieval Climate Anomaly, three phases of the Little Ice Age (with in dark blue the years of the Maunder minimum) and the Modern Warming Period.…”

Assessing the solar variability signature in climate variables by information theory and wavelet coherence

“…Interesting results are also obtained by linear methods on certain dominant factors, such as NAO, which determine the large-scale atmospheric variability in Europe 77 . But this happens when there are no large deviations from linearity in the connection of phenomena.…”

A millennium-long climate history of erosive storms across the Tiber River Basin, Italy, from 725 to 2019 CE

“…( a ) Wavelet spectrum of the rainfall erosivity time-series with bounded colours identifying 0.05 significance areas (the bell-shaped, black contour marks the limit between the reliable region and the region below the contour where the edge effects occur, a.k.a. cone of influence ( b ) North Atlantic Oscillation (annual NAO from Hernández et al 100 ); ( c) Trend of quantile-rainfall erosivity with return period T = 50 years (red curve); ( d) Evolution (red arrow indicating the change-point year 1495) of estimated annual rainfall erosivity (blue circles) with the relative smoothed trend by the 11-year Gaussian function (bold blue curve). The y -right axes in ( c ) is in the reverse-scale.…”