2015
DOI: 10.1002/qj.2562
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Influence of extratropical sea‐surface temperature on the Indian summer monsoon: an unexplored source of seasonal predictability

Abstract: Based on extensive analysis of observations and a series of climate model experiments, here we establish that slow variations of northern hemispheric extratropical sea-surface temperature (SST) anomalies can augment seasonal predictability of the south Asian monsoon. The SST conditions and performance of the south Asian monsoon during 2013 boreal summer months (June-September) led us to hypothesize that the strong extratropical SST anomalies in the North Pacific and North Atlantic in conjunction with weak trop… Show more

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Cited by 53 publications
(28 citation statements)
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“…Other natural variabilities like Indian Ocean dipole (Saji et al, 1999), Modoki (Ashok et al, 2007), and Eurasian snow (e.g., Hahn & Shukla, 1976;Saha et al, 2013;Vernekar et al, 1995) also affect the ISM variability. Apart from these, the interannual and interdecadal variabilities of the ISM are also associated with northern extratropical Pacific sea surface temperature (SST; e.g., Chattopadhyay et al, 2015;Krishnamurthy & Krishnamurthy, 2014) and north Atlantic SST (e.g., Chang et al, 2001;Goswami et al, 2006;Srivastava et al, 2002). Furthermore, local factors such as changes in LULC (Halder et al, 2016;Krishnan et al, 2015) and aerosols (Ramanathan et al, 2005) also affect the ISM.…”
Section: Introductionmentioning
confidence: 99%
“…Other natural variabilities like Indian Ocean dipole (Saji et al, 1999), Modoki (Ashok et al, 2007), and Eurasian snow (e.g., Hahn & Shukla, 1976;Saha et al, 2013;Vernekar et al, 1995) also affect the ISM variability. Apart from these, the interannual and interdecadal variabilities of the ISM are also associated with northern extratropical Pacific sea surface temperature (SST; e.g., Chattopadhyay et al, 2015;Krishnamurthy & Krishnamurthy, 2014) and north Atlantic SST (e.g., Chang et al, 2001;Goswami et al, 2006;Srivastava et al, 2002). Furthermore, local factors such as changes in LULC (Halder et al, 2016;Krishnan et al, 2015) and aerosols (Ramanathan et al, 2005) also affect the ISM.…”
Section: Introductionmentioning
confidence: 99%
“…Sabeerali et al . [] have demonstrated that the Climate Forecast System version 2 (CFSv2) [ Saha et al ., ] simulates good ISO characteristics when compared to the best CMIP5 models and it has demonstrated skill at simulating the ISMR and its different modes of variability [ Chattopadhyay et al ., ; George et al ., ; Ramu et al ., ; Abhik et al ., ; Joseph et al ., ; Abhilash et al ., ; Borah et al ., ; Srivastava et al ., ] even though it simulates a dry bias over the Indian landmass [ Goswami et al ., ; Saha et al ., ; George et al ., ]. Goswami et al .…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, the variability in ISM can be seen as a superposition and interaction between these remote teleconnections in addition to its own internal dynamics. Several other studies have also linked the interannual variability of ISM to North Atlantic Oscillation (Goswami et al, 2006) and Pacific Decadal Oscillation (Chattopadhyay et al, 2015).…”
Section: Introductionmentioning
confidence: 99%