Relationships between interannual variability in the Arabian Sea and Indian summer monsoon rainfall

1990 ◽  
Vol 44 (1-4) ◽  
pp. 153-165 ◽  
Author(s):  
S. K. Dube ◽  
M. E. Luther ◽  
J. J. O'Brien
2008 ◽  
Vol 21 (21) ◽  
pp. 5603-5623 ◽  
Author(s):  
Takeshi Izumo ◽  
Clémentde Boyer Montégut ◽  
Jing-Jia Luo ◽  
Swadhin K. Behera ◽  
Sébastien Masson ◽  
...  

Abstract The Indian summer monsoon rainfall has complex, regionally heterogeneous, interannual variations with huge socioeconomic impacts, but the underlying mechanisms remain uncertain. The upwelling along the Somalia and Oman coasts starts in late spring, peaks during the summer monsoon, and strongly cools the sea surface temperature (SST) in the western Arabian Sea. They restrict the westward extent of the Indian Ocean warm pool, which is the main moisture source for the monsoon rainfall. Thus, variations of the Somalia–Oman upwelling can have significant impacts on the moisture transport toward India. Here the authors use both observations and an advanced coupled atmosphere–ocean general circulation model to show that a decrease in upwelling strengthens monsoon rainfall along the west coast of India by increasing the SST along the Somalia–Oman coasts, and thus local evaporation and water vapor transport toward the Indian Western Ghats (mountains). Further observational analysis reveals that such decreases in upwelling are caused by anomalously weak southwesterly winds in late spring over the Arabian Sea that are due to warm SST/increased precipitation anomalies over the Seychelles–Chagos thermocline ridge of the southwestern Indian Ocean (and vice versa for years with strong upwelling/weak west Indian summer monsoon rainfall). The latter SST/precipitation anomalies are often related to El Niño conditions and the strength of the Indonesian–Australian monsoon during the previous winter. This sheds new light on the ability to forecast the poorly predicted Indian monsoon rainfall on a regional scale, helped by a proper ocean observing/forecasting system in the western tropical Indian Ocean.


2020 ◽  
Author(s):  
Praveen Kumar Pothapakula ◽  
Cristina Primo ◽  
Silje Sørland ◽  
Bodo Ahrens

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.


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