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We study the forced response of the teleconnection between the ElNino-Southern Oscillation (ENSO) and global precipitation in general and theIndian summer monsoon (IM) in particular in the Max Planck Institute GrandEnsemble. The forced response of the teleconnection is defined as thetime-dependence of a correlation coefficient evaluated over the ensemble. Theensemble-wise variability is taken either wrt. spatial averages or dominantspatial modes in the sense of Maximal Covariance Analysis or CanonicalCorrelation Analysis or EOF analysis. We find that the strengthening of theENSO-IM teleconnection is robustly or consistently featured in view of all fourteleconnection representations, whether sea surface temperature (SST) or sealevel pressure (SLP) is used to characterise ENSO, and both in the historicalperiod and under the RCP8.5 forcing scenario. The main contributor to thisstrengthening in terms of a linear regression model is the regressioncoefficient, which can outcompete even a declining ENSO variability in view ofusing the SLP. We also find that the forced change of the teleconnection istypically nonlinear by (1) formally rejecting the hypothesis that ergodicityholds, i.e., that expected values of temporal correlation coefficients withrespect to the ensemble equal the ensemble-wise correlation coefficient itself,and also showing that (2) the trivial contributions of the forced changes ofe.g. the mean SST and/or precipitation to temporal correlations areinsignificant here. We also provide, in terms of the test statistics, globalmaps of the degree of nonlinearity/nonergodicity of the forced change of theteleconnection between local precipitation and ENSO.

Nonlinear forced change and nonergodicity: The case of ENSO-Indian monsoon and global precipitation teleconnections