Effect of large-scale oceanic and atmospheric processes on the Indian summer monsoon

Lenka, Smrutishree; Devi, Rani; Joseph, C.M.; Gouda, K. C.

doi:10.1007/s00704-021-03896-3

Cited by 8 publications

(2 citation statements)

References 119 publications

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“…The inter-annual variability of ISMR has a profound impact on Indian agriculture and economy, being the principal source of rainfall for the Indian subcontinent. El Niño-Southern Oscillation (ENSO), a recurring inter-annual phenomenon caused by sea surface temperature (SST) anomalies over the equatorial Pacific Ocean, is identified as the most prominent climate driver of ISMR (Ihara et al, 2007;Rajeevan and Pai, 2007;Varikoden and Preethi, 2013;Schulte et al, 2020;Lenka et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Hydrological Changes in Godavari River Basin Under the Impacts of El-Niño

Thakur,

Kasiviswanathan,

Teutschbein

et al. 2024

Proc. IAHS

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Abstract. El Niño–Southern Oscillation (ENSO) is the most prominent driver of the inter-annual variability of Indian summer monsoon rainfall (ISMR). This study focuses on understanding the hydrological variations in Godavari River Basin (GRB) due to the weakening of ISMR during El Niño years (1980–2008), using the variable infiltration capacity (VIC) model. The entire basin was discretized into 1325 uniform grids of resolution 0.15°×0.15° (about 16.65 km), and hydrological parameters of the basin were analysed at each grid level for various El Niño events. Based on the Oceanic Niño Index (ONI), obtained from National Oceanic and Atmospheric Administration (NOAA), El Niño events occurred in the past were subclassified into weak (2004 and 2006), moderate (1986, 1994 and 2002), strong (1987 and 1991) and very strong (1982, 1987) events. For this study, VIC model was run for the period 1980–2008 and a composite of El Niño and normal years (1981, 1985, 1989, 1990, 1992, 1993, 1996, 2001 and 2003) was prepared to assess the impacts of El Niño events on the hydrology of GRB. Our results showed a negative correlation of precipitation, abstractions and soil moisture with the increasing magnitude of El Niño events. The quantum of precipitation was reduced during El Niño years compared to normal years, which showed the basin's exposure to more frequent droughts during El Niño events.

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Section: Introductionmentioning

confidence: 99%

Assessment of Hydrological Changes in Godavari River Basin Under the Impacts of El-Niño

Thakur,

Kasiviswanathan,

Teutschbein

et al. 2024

Proc. IAHS

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“…Some recent researchers have identified a clear connection of ENSO and IOD with ISM onset, demise, length of ISM and also with the monsoon seasonal rainfall (Yadav et al 2013, Gouda et al 2017, Ashok, TEJAVATH 2019, Hrudya et al 2020, Lenka et al 2022 but the clear connection with the impact of MJO is still missing. The interannual variability of the MJO on various time scale have association with the large-scale phenomena like ENSO (Slingo et al 1999, Tseng et al 2020, Dasgupta et al 2021 and in turn to the monsoon system (Madden and Julian 1971).…”

Section: Introductionmentioning

confidence: 99%

Dynamical influence of MJO phases on the onset of Indian monsoon

Lenka

Gouda

Devi

et al. 2023

Environ. Res. Commun.

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There is a need to understand the onset of monsoon dynamics as the date of onset of monsoon (DOM) is an important parameter in framing all the policy for the imminent season like crop choice, sowing schedule, disaster management, power distribution etc. It is observed that the interannual variability of the DOM in India is about 7-8 days, making it more challenge to predict this at long lead. The MJO phases are linked with the different convection centres and hence, influences the global circulation process and the rainfall. In this paper the dynamical influence of the different phases of MJO are being quantified on DOM and its progress in continental India by using the multi-source atmospheric and oceanic parameters like wind structure, outgoing longwave radiation (OLR), sea surface temperature (SST). The linkage of the active and inactive phases of MJO along with the favourable conditions for DOM is obtained by using the pentad analysis of associated parameters in different clusters for both the wet and dry phases of MJO along with the strength for the period 1980-2018. Also the dynamics are studied for the early, normal and late onset years separately to understand the relation better. It is inferred that the wet (dry) phase leads to early (late) monsoon onset over Kerala (MOK) in India. To address the progress of monsoon the DOM in Rajasthan (MOR) is considered and the rainfall anomalies during MOK-MOR period are linked to the MJO phases. It is inferred that the wet MJO phase with negative OLR anomaly triggers the fast progress of monsoon over India. This understanding will surely help operational researchers and the NWP modellers for improving the methodologies for the advanced and accurate prediction of DOM.

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