The Southern Oscillation and its relation to the monsoon rainfall

Bhalme, H. N.; Jadhav, S. K.

doi:10.1002/joc.3370040506

Cited by 71 publications

(45 citation statements)

References 29 publications

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“…Shukla and Paolino (1983) also noted that the anomalous summer monsoon precedes the extreme phase of ENSO in autumn through winter. In other words, the two factors, i.e., the ENSO indices (SOI or SST in the equatorial Pacific) and the snow cover over Eurasia and Tibet, which are highly or moderately correlated with the Indian summer monsoon rainfall (Pant and Parthasarathy, 1981;Bhalme and Jadhav, 1984;Hahn and Shukla, 1976;Dickson, 1984 etc. ) should be inferred as parts of one climate system of global ENSO rather than independent external parameters.…”

Section: B Process Over Eurasia and Indian Oceanmentioning

confidence: 99%

Global Structure of the El Nino/Southern Oscillation

Yasunari

1987

Journal of the Meteorological Society of Japan

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Time evolutions of anomalies of SST and atmospheric parameters over the global domain were investigated for the several ENSO cycles during the period 1964-79, using the data set described in Part I. The principal results are summarized as follows: 1) the eastward propagation of SLP and zonal wind anomalies from the Indian Ocean toward the eastern Pacific is a fundamental nature of ENSO along the tropics and the southern subtropics. 2) the significant anomalies of SLP and circulation field which first appear over the Indian Ocean seem to originate from central Asia or Eurasia.3) the vertical structures of these anomalies over central Asia at the intermediate stages of the cycle (i.e., about one year before the SST maximum (minimum) over the equatorial Pacific) are suggested to represent large-scale cold (warm) air outbreak associated with more (less) than normal snow cover over there. 4) a time-lag teleconnection between the north Pacific and central Asia is found in the circulation field, which seems to have a key role on the mechanism of ENSO cycle.The first two results have substantially confirmed the evidences of ENSO signals from Eurasia and the Indian Ocean toward the equatorial Pacific, which were noted in the surface fields by Barnett (1984,1985a) and Krishnamurti et al. (1986). The third result suggests the important role of Asian monsoon as a connector of the process in the extra-tropics and that in the equatorial Pacific. The fourth result seems to be associated with the interaction between the PNA and the EU (Eurasian) pattern with a time lag of half a year or more. The links between the tropics and the extra-tropics and between the ocean and the continent described above strongly suggest that the ENSO should be understood as a global scale land (cryosphere)-atmosphere-ocean coupled system rather than an atmosphere-ocean coupled system over the equatorial Pacific.

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Section: B Process Over Eurasia and Indian Oceanmentioning

confidence: 99%

Global Structure of the El Nino/Southern Oscillation

Yasunari

1987

Journal of the Meteorological Society of Japan

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“…As an illustration, it must be emphasized that the IMR time series is not basically biennial as it is often assumed, but rather exhibits a triennial oscillation as many monsoon indicators (Bhalme and Jadhav, 1984). Recently, Fasullo (2004) has also questioned the existence of a biennial component in ISM variability.…”

Section: Introductionmentioning

confidence: 99%

Revisiting the Possible Links between the Quasi-Biennial Oscillation and the Indian Summer Monsoon Using NCEP R-2 and CMAP Fields

Claud

Terray

2007

Journal of Climate

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In the past the stratospheric Quasi-Biennial Oscillation (QBO) has sometimes been proposed to explain the tendency for the Indian Summer Monsoon (ISM) to alternate between strong and weak years. In this study, NCEP Reanalysis-2 and CMAP fields are statistically analyzed to assess the relationship between equatorial zonal winds in the stratosphere and ISM. In a first step, it is shown that zonal winds at 15hPa during the preceding winter (January-February) are the best stratospheric predictor of the summer rainfall over the Indian subcontinent as a whole.This relationship mainly holds for August and September, or the late ISM. Surprisingly, the QBO pattern is not significantly associated with the rainfall variability during June-July or the early ISM. CMAP and NCEP R-2 fields corroborate these findings and show that westerly QBO years are associated with a deepening of the monsoon trough over the Gangetic plains and decreased convective activity in the eastern equatorial Indian region. However, further statistical analysis shows that the QBO-ISM link is complex since a westerly QBO phase at 15 hPa in boreal winter leads to a weaker monsoon surface circulation with, in particular, a weakening of the Somali Jet at the beginning of the monsoon, but a much stronger circulation in September. At that time, the Tibetan High is reinforced, the tropical easterly jet at 200 hPa is stronger over India and the local reversed Hadley circulation is also strengthened north of the equator. The mechanisms by which the QBO may affect ISM have been explored through in particular correlations between stratospheric winds and tropopause temperature and pressure fields. Our results provide support for an out of phase behavior of convective activity between the Indian sub-continent and the equatorial Indian Ocean induced by the QBO phase, especially during the late ISM. During a westerly QBO phase, convective activity is, in September, enhanced over India, which brings higher precipitation, compared to the east phase. This work 3 also suggests that the winter QBO at 15 hPa could have some skill in foreshadowing the late ISM.4

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“…The ENSO-monsoon teleconnections involve significant simultaneous relationships between monsoon rainfall and various ENSO indices (Krishna Kumar et al, 1995). It has generally been observed that negative southern oscillation index (SOI) (Bhalme and Jadhav, 1984;Parthasarathy and Pant, 1985) and warmer sea-surface temperature (SST) in the central and eastern equatorial Pacific are associated with lower monsoon rainfall and drought conditions (Angell, 1981;Khandekar and Neralla, 1984;Parthasarathy et al, 1988b;De, 1999), reducing crop production over India.…”

Section: Introductionmentioning

confidence: 99%

Impact of El Niño–southern oscillation on Indian foodgrain production

Selvaraju

2003

Intl Journal of Climatology

135

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The impact of El Niño-southern oscillation (ENSO) on Indian foodgrain production was analysed for the period 1950-99. The inverse relationship between sea-surface temperature (SST) anomalies from June to August (JJA) over the NINO3 sector of the tropical Pacific Ocean and Indian foodgrain production anomalies (r = −0.50) was significant at the 1% level. During the warm ENSO phase, the total foodgrain production frequently decreased (12 out of 13 years) by 1 to 15%. In 10 out of 13 cold ENSO-phase years, the total foodgrain production increased from normal. The relationship between the SST-based NINO3 ENSO index and the Kharif season (June-September) foodgrain production anomalies (r = −0.52) was greater than for the Rabi season (October-February) foodgrain production (r = −0.27). The ENSO impact on rice production was greatest among the individual crops. The average drop in rice (Kharif season crop) production during a warm ENSO-phase year was 3.4 million tonnes (7%). In a cold ENSO-phase year the average production increase was 1.3 million tones (3%). Wheat (Rabi season crop) production was also influenced by ENSO, as it depends on the carryover soil water storage from the Kharif season. Sorghum and chickpea production are not significantly influenced by ENSO extremes.Inter-annual fluctuation of the gross value of Indian foodgrain production was very large, reducing up to US$2183 million in a warm ENSO year and increasing up to US$1251 million in a cold ENSO year. On average, a warm ENSO year costs US$773 million and a cold ENSO year had a financial gain of US$437 million from normal.The cumulative probability distributions of foodgrain production anomalies during cold and warm ENSO phases are shifted positively or negatively, relative to the neutral distribution. The warm ENSO forcing significantly (1% level) reduced the probability of above-average production. The cold ENSO forcing moderately increased the above-average foodgrain production over the neutral ENSO phase (5% level). A simple conditional probability forecast based on annual and JJA NINO3 SST predicted the category of foodgrain production in 11 of the 14 years. The results demonstrated that the relationship between NINO3 ENSO index and foodgrain production could be used for agricultural applications and policy decisions on food security for the rapidly growing population in India.

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The Southern Oscillation and its relation to the monsoon rainfall

Cited by 71 publications

References 29 publications

Global Structure of the El Nino/Southern Oscillation

Global Structure of the El Nino/Southern Oscillation

Revisiting the Possible Links between the Quasi-Biennial Oscillation and the Indian Summer Monsoon Using NCEP R-2 and CMAP Fields

Impact of El Niño–southern oscillation on Indian foodgrain production

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