Extended Data Fig. 3: ENSO persistence barrier in proxies and selected simulations.
From: Increased frequency of multi-year El Niño–Southern Oscillation events across the Holocene
(a) The evolution of ENSO persistence barrier (PB) strength from proxy reconstructions. The relationship between rENSO on x-axis, and PB strength on y-axis. The blue line shows the linear fit. Blue circles in (b) provides reference diameters of the circles (proportional to data length), and the p value in Pearson correlation is shown in the legend. (c) The correlation between rENSO and PB strength in proxies and 4 selected simulations over the Holocene. PB is derived from the autocorrelation function (ACF) of Niño 3.4 SST anomalies which is a function of initial months t and lag months τ. Following Jin et al. (2020)64, for a calendar month t, we identify \({\tau }_{B}\left(t\right)\) as the specific lag of maximum ACF decline, which is calculated as the lag gradient in the time step of 1 month as \({PB}\left(t\right)=\{\frac{r\left[t,{\tau }_{B}\left(t\right)-1\right]-r\left[t,{\tau }_{B}\left(t\right)+1\right]}{2}\}={\max }_{\tau }\{\frac{r\left[t,\tau -1\right]-r\left[t,\tau +1\right]}{2}\}\) where \({PB}\left(t\right)\) is the maximum gradient for each month. The intensity of the PB is then estimated using the sum of monthly \({PB}\left(t\right)\) as \({PB}=\mathop{\sum }\nolimits_{t=1}^{12}{PB}(t)\).
