Information Synergy Between IOD and ENSO on the Indian Summer Monsoon Rainfall in Observations, Reanalysis, and in GCM-RCM Model Chain.

Abstract:

El-Niño southern oscillation (ENSO) and Indian Ocean Dipole (IOD) are two well-noted temporal oscillations in the sea surface temperature (SST), which both are thought to influence the inter-annual variability of the Indian Summer Monsoon Rainfall (ISMR). We explore the information exchange from two source variables (ENSO and IOD) to one target (ISMR). First, we illustrate the concepts and quantification of two-source IE to a target with idealized test cases consisting of linear as well as non-linear dynamical systems. Our results show that these systems exhibit net synergy (i.e., the combined influence of two sources on a target is greater than the sum of their individual contributions), even with uncorrelated sources in both the linear and non-linear systems. For robustness, we test our IE quantification results with various estimators like the Linear, Kernel, and Kraskov estimators. Thereafter, the two-source IE from ENSO and IOD to the ISMR is investigated in observations, reanalysis, three global climate model (GCM) simulations, and three nested, higher-resolution simulations using a regional climate model (RCM). We aim for (1) quantifying IE from ENSO and IOD to ISMR in the natural system, and (2) apply IE in the evaluation of the GCM and RCM simulations. Our results show that both ENSO and IOD contribute to the ISMR inter-annual variability. Interestingly, significant net synergy is noted in the central parts of the Indian subcontinent, known as India's monsoon core region. This indicates that both ENSO and IOD are synergistic predictors in the monsoon core region. However, they share significant net redundant information in the southern part of the Indian subcontinent. The IE patterns in the GCM simulations differ substantially from the patterns derived from observations and reanalysis. Only one nested RCM simulation IE pattern adds value to the corresponding GCM simulation pattern. Only in this case, the GCM simulation shows realistic SST patterns and moisture transport during the various ENSO and IOD phases. This once again confirms the importance of the choice of the GCM in driving a higher-resolution RCM. This study shows that two-source IE is a useful metric that helps in better understanding the climate system and in process-oriented climate model evaluation.