Interannual Variability of the Madden-Julian Oscillations in Indian Summer Monsoon Rainfall

1992 ◽  
Vol 5 (9) ◽  
pp. 973-978 ◽  
Author(s):  
S. V. Singh ◽  
R. H. Kripalani ◽  
D. R. Sikka
Keyword(s):  
Interannual Variability ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Monsoon Rainfall ◽  
Indian Summer Monsoon Rainfall ◽  
Summer Monsoon Rainfall

scholarly journals The synergistic impact of ENSO and IOD on the Indian Summer Monsoon Rainfall in observations and climate simulations - an information theory perspective

2020 ◽  
Author(s):  
Praveen Kumar Pothapakula ◽  
Cristina Primo ◽  
Silje Sørland ◽  
Bodo Ahrens
Keyword(s):  
Interannual Variability ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Information Exchange ◽  
Climate Model ◽  
Monsoon Rainfall ◽  
Indian Summer Monsoon Rainfall ◽  
Indian Subcontinent ◽  
Summer Monsoon Rainfall ◽  
Core Region

Abstract. El-Niño southern oscillation (ENSO) and Indian Ocean Dipole (IOD) are two well-know temporal oscillations in the sea surface temperature (SST), which both are thought to influence the interannual variability of the 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 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. We test IE quantification with various estimators (the Linear, Kernel, and Kraskov estimators) for robustness. Next, 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). 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 the 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 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, the GCM simulation shows realistic SST patterns and moisture transport during the various ENSO and IOD phases. This confirms, once again, 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.

scholarly journals A soft-computing ensemble approach (SEA) to forecast Indian summer monsoon rainfall

2017 ◽  
Vol 24 (2) ◽  
pp. 308-314 ◽  
Author(s):  
Nisha Kurian ◽  
T. Venugopal ◽  
Jatin Singh ◽  
M. M. Ali
Keyword(s):  
Soft Computing ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Monsoon Rainfall ◽  
Indian Summer Monsoon Rainfall ◽  
Summer Monsoon Rainfall ◽  
Ensemble Approach
Sign in / Sign up

Export Citation Format

Share Document