The synergistic impact of ENSO and IOD on Indian summer monsoon rainfall in observations and climate simulations – an information theory perspective

Abstract

Abstract. The El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are two well-known temporal oscillations in sea surface temperature (SST), which are both thought to influence the interannual variability of Indian summer monsoon rainfall (ISMR). Until now, there has been no measure to assess the simultaneous information exchange (IE) from both ENSO and IOD to ISMR. This study explores the information exchange from two source variables (ENSO and IOD) to one target (ISMR). First, in order to illustrate the concepts and quantification of two-source IE to a target, we use idealized test cases consisting of linear and nonlinear 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 nonlinear systems. We test IE quantification with various estimators (linear, kernel, and Kraskov estimators) for robustness. Next, the two-source IE from ENSO and IOD to ISMR is investigated in observations, reanalysis, three global climate model (GCM) simulations, and three nested higher-resolution simulations using a regional climate model (RCM). This (1) quantifies IE from ENSO and IOD to ISMR in the natural system and (2) applies IE in the evaluation of the GCM and RCM simulations. The results show that both ENSO and IOD contribute to ISMR interannual variability. Interestingly, significant net synergy is noted in the central parts of the Indian subcontinent, which is India's monsoon core region. This indicates that both ENSO and IOD are synergistic predictors in the monsoon core region. But, 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 reanalyses. Only one nested RCM simulation IE pattern adds value to the corresponding GCM simulation pattern. Only in this case does the GCM simulation show realistic SST patterns and moisture transport during the various ENSO and IOD phases. This confirms, once again, the importance of the choice of 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.

COSMO-CLM Regional Climate Simulations in the CORDEX framework: a review

“…But, when changing the resolution or slightly altering the model configuration, the performance is only marginally modified, compared to if a substantial adjustment is done in the model configuration (such as coupling to a different land model as done for AUS-44), this can alter the performance substantially. The results from this large COSMO-CLM model ensemble indicate that an RCM-modeler can do a lot when it comes to improve the model performance, but if there is information missing in the large-scale GCM forcing on the RCM boundaries, it should not be expected that the RCMs can improve on that (Hall, 2014;Pothapakula et al, 2020;Rana et al, 2020 GCM performance for each region should be considered, or, whether the spread to include GCM´s sensitivity to increasing greenhouse gasses and other forcings (Rineau et al, 2019) should also be evaluated when selecting driving data. We propose that the planning of the GCM-RCM model chain should be done through coordination between the GCM and RCM-modelers, so that we can obtain a model chain that we trust in and is capturing the range of possible future scenarios (Knutti, 2008).…”

“…The model versions used for CORDEX-simulations are COSMO-CLM4-8-17 (Panitz et al, 2014;Keuler et al, 2016;Di Virgilio et al, 2019;Hirsch et al, 2019), multiple versions of COSMO-CLM5 (Sørland et al, 2018;Li et al, 2018) and the accelerated version COSMO-crCLIM (Vautard et al, 2020;Pothapakula et al, 2020). The following sections give short descriptions of the different versions, their main model developments, and new options for different configurations.…”

“…Nevertheless, it is hoped that the RCMs should have a similar performance or improve the results of the reanalysis, in particular for the tropical precipitation where reanalysis have poorer skill (Bosilovich et al, 2008). On the other hand, to investigate if an RCM is adding value to the driving GCMs should be done with respect to whether the GCM has a realistic large-scale atmosphere and ocean representation (e.g., Pothapakula et al, 2020).…”

Oceanic versus terrestrial origin of El Niño Southern Oscillation–associated continental precipitation anomalies

“…Under the influence of La Niña, which always modulates precipitation of oceanic origin that is the most important source of precipitation in the tropical north and south Atlantic Ocean, an increase in precipitation is usually observed. 52 Likewise, there is a significant relationship between the ENSO and precipitation in Asia; 53 particularly, the ENSO contributes to Indian monsoon interannual variability, 18,54 bringing about an increase in the precipitation over the Indian Peninsula during La Niña events. In this region, the influence of recycling supports the importance of precipitation from terrestrial origin.…”

COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

“…Over Europe, groups were encouraged to perform additional simulations at 0.11 • (∼ 12 km) horizontal resolution (Jacob et al, 2020), although Kotlarski et al (2014) for Europe as well as Panitz et al (2014) for Africa found no significant added value in the mean fields with an increase in horizontal resolution. However, added value is found for extreme events and over complex terrain when the grid is refined from 0.44 to 0.11 • over Europe (Prein et al, 2016;Torma et al, 2015).…”