On the recent strengthening of the relationship between ENSO and northeast monsoon rainfall over South Asia

Kumar, Pankaj; Kumar, Krishan; Rajeevan, M.; Sahai, A. K.

doi:10.1007/s00382-006-0210-0

Cited by 125 publications

(95 citation statements)

References 20 publications

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“…They have shown that the statistical relationship between ENSO and the NEMR has strengthened during the 1980s and 1990s. Kumar et al (2007) made this inference with the rainfall data up to 2000, while Zubair and Ropelewski (2006) made this conclusion with the rainfall data up to 2002. They have shown that the strengthening of the relationship between ENSO and the NEMR is due to stronger easterly wind anomalies and anomalous low-level moisture convergence over the north Indian Ocean.…”

mentioning

confidence: 70%

“…The increasing trend in the NEMR during the recent years could be related to the increasing trend in the positive phase of the Indian Ocean Dipole Mode (Kripalani and Kumar, 2004). The inter-annual variability of the NEMR is linked to the El Niño/Southern Oscillation (ENSO), Indian Ocean Dipole and the EQUINOO (De and Mukhopadhyay, 1999;Bhanu Kumar et al, 2004;Kripalani and Kumar, 2004;Zubair and Ropelewski, 2006;Kumar et al, 2007;Sreekala et al, 2011). The NEMR and IOD are directly related suggesting that the positive (negative) phase enhances (suppresses) the northeast monsoon activity.…”

Section: Inter-annual Variability Of the Nemr And Its Secular Variationmentioning

confidence: 99%

“…Studies of the NEMR variability are limited (Ramaswamy, 1972;Dhar and Rakhecha, 1983;Singh and Sontakke, 1999;Balachandran et al, 2006). Some of the previous studies related the NEMR variability with ocean-atmosphere phenomena such as El Niño/Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) (Bhanu Kripalani and Kumar, 2004;Zubair and Ropelewski, 2006;Kumar et al, 2007). Some recent studies have shown that the interannual variability of the NEMR is significantly influenced by ENSO and that this relationship has strengthened during the recent years.…”

Section: Introductionmentioning

confidence: 99%

“…Some recent studies have shown that the interannual variability of the NEMR is significantly influenced by ENSO and that this relationship has strengthened during the recent years. Zubair and Ropelewski (2006) and Kumar et al (2007) have shown that the recent strengthening in the relationship between ENSO and the NEMR over south Asia is due Figure 1. Seasonal monsoon rainfall (in cm) during the northeast monsoon season (October to December) averaged over the period 1951-2004. to stronger easterly wind anomalies and anomalous low-level moisture convergence over the north Indian Ocean.…”

Section: Introductionmentioning

confidence: 99%

“…In the present study, an interesting aspect of the secular variation of the relationship between ENSO and the NEMR is reported. The secular variations of the relationship between ENSO and the NEMR have been addressed by Zubair and Ropelewski (2006) and Kumar et al (2007). They have shown that the statistical relationship between ENSO and the NEMR has strengthened during the 1980s and 1990s.…”

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confidence: 99%

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Northeast monsoon over India: variability and prediction

Rajeevan

Unnikrishnan

Bhate

et al. 2012

Meteorological Applications

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178

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South peninsular India experiences a large portion of the annual rainfall during the northeast monsoon season (October to December). In this study, the facets of diurnal, intra-seasonal and inter-annual variability of the northeast monsoon rainfall (the NEMR) over India have been examined. The analysis of satellite derived hourly rainfall reveals that there are distinct features of diurnal variation over the land and oceans during the season. Over the land, rainfall peaks during the late afternoon/evening, while over the oceans an early morning peak is observed. The harmonic analysis of hourly data reveals that the amplitude and variance are the largest over south peninsular India. The NEMR also exhibits significant intra-seasonal variability on a 20-40 day time scale. Analysis also shows significant northward propagation of the maximum cloud zone from south of equator to the south peninsula during the season. The NEMR exhibits large inter-annual variability with the co-efficient of variation (CV) of 25%. The positive phases of ENSO and the Indian Ocean Dipole (IOD) are conducive for normal to above normal rainfall activity during the northeast monsoon. There are multi-decadal variations in the statistical relationship between ENSO and the NEMR. During the period 2001-2010 the statistical relationship between ENSO and the NEMR has significantly weakened. The analysis of seasonal rainfall hindcasts for the period 1960-2005 produced by the state-of-the-art coupled climate models, ENSEMBLES, reveals that the coupled models have very poor skill in predicting the inter-annual variability of the NEMR. This is mainly due to the inability of the ENSEMBLES models to simulate the positive relationship between ENSO and the NEMR correctly.

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mentioning

confidence: 70%

Section: Inter-annual Variability Of the Nemr And Its Secular Variationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Northeast monsoon over India: variability and prediction

Rajeevan

Unnikrishnan

Bhate

et al. 2012

Meteorological Applications

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178

161

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The impact of varying seasonal lengths of the rainy seasons of India on its teleconnections with tropical sea surface temperatures

Misra

Bhardwaj

2020

Atmospheric Science Letters

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We present in this paper the interannual variability of seasonal temperature and rainfall in the Indian meteorological subdivisions (IMS) for boreal winter and summer seasons that take in to account the varying length of the seasons. Our study reveals that accounting for the variations in the length of the seasons produces stronger teleconnections between the seasonal anomalies of surface temperature and rainfall over India with corresponding sea surface temperature anomalies of the tropical Oceans (especially over the northern Indian and the equatorial Pacific Oceans) compared to the same teleconnections from fixed length seasons over the IMS. It should be noted that the IMS show significant spatial heterogeneity in these teleconnections.

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Predictability assessment of northeast monsoon rainfall in India using sea surface temperature anomaly through statistical and machine learning techniques

2018

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The socio‐economic growth of India is adversely affected by the abnormal meteorological phenomena of floods and droughts. Thus, rainfall prediction is highly desirable for livelihood and sustainability. In this study, northeast monsoon rainfall (NEMR) is predicted over the Indian peninsular region for the months of October, November, and December using a global sea surface temperature (SST) anomaly as a predictor by linear regression (LR), artificial neural network (ANN), and extreme learning machine (ELM) techniques. The predictions are made by LR, ANN, and ELM models for the period 1990–2016 using the training input (1871–1989) of different time series samples of global SST anomaly data collected from Hadley Centre SST data set (HadSST3). Principal component analysis was used for dimensionality reduction of the data sets, and its application substantially improved the predictive ability of the machine learning techniques. The performance of the PC‐ELM technique with the ensemble method (ESM 8–9) training window is found to be more accurate than the LR and ANN techniques and provides minimal error scores as per the statistical analysis. This study concludes that the global SST anomaly has the potential to be used as a predictor for northeast monsoon rainfall and useful for long‐range climatic projections.

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On the recent strengthening of the relationship between ENSO and northeast monsoon rainfall over South Asia

Cited by 125 publications

References 20 publications

Northeast monsoon over India: variability and prediction

Northeast monsoon over India: variability and prediction

The impact of varying seasonal lengths of the rainy seasons of India on its teleconnections with tropical sea surface temperatures

Predictability assessment of northeast monsoon rainfall in India using sea surface temperature anomaly through statistical and machine learning techniques

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