Interdecadal modulation of interannual <scp>ENSO‐Indian</scp> summer monsoon rainfall teleconnections in observations and <scp>CMIP6</scp> models: Regional patterns

Mahendra, Nimmakanti; Chowdary, Jasti S.; Darshana, Patekar; Sunitha, P. Surya; Parekh, Anant; Gnanaseelan, C.

doi:10.1002/joc.6973

Cited by 27 publications

(38 citation statements)

References 73 publications

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“…Recently, [9] observed that historically r τ fluctuated less in some parts of the Indian monsoon region and more in others (as seen in Fig. S1 (c,d)), alluding thereafter to "epochs" of weaker and stronger "ENSO-ISM teleconnection".…”

Section: Introductionmentioning

confidence: 88%

“…Most of the decadal variability of running window correlations, r τ , should therefore be due to "undersampling"; whereby a characteristic time scale of variability is an artifact of the analysis technique determined by the applied time window length, τ , being the sample size. Because of this undersampling of the true climatological correlation [6,7,8], r, we will refer to r τ as the apparent teleconnection strength.Recently, [9] observed that historically r τ fluctuated less in some parts of the Indian monsoon region and more in others (as seen in Fig. S1 (c,d)), alluding thereafter to "epochs" of weaker and stronger "ENSO-ISM teleconnection".…”

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confidence: 88%

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Indian Ocean influence on the ENSO-monsoon teleconnection is mostly apparent

Bódai

Aneesh

Lee

et al. 2022

Preprint

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“Decadal influence” on the El Nino–Southern Oscillation-Indian summer monsoon (ENSO-ISM) teleconnection has been much studied but with plurality and ambiguity about the concept of influence. Here we provide formal definitions of the apparent influence of a specific factor which enable us to test them as null-hypotheses. Using the recently released Community Earth System Model v2 (CESM2) Large Ensemble (LE) data, we show that a 50% chance for the detection of the apparent Indian Ocean (IO) influence under stationary conditions might take 2000 years of data. However, we find that this influence is mostly apparent indeed, as it originates from fluctuations of the decadal apparent – as opposed to climatological – ENSO variability, which causally influences an IO dipole-like apparent mean state. We also show that no unattributed so-called “decadal influence”, reflected in a deviation from a linear regression model of the teleconnection as a null-hypothesis, can be detected in 20th c. observations even regionally. However, as a new insight, we find our new influence concept to be possibly consistent with such a null-hypothesis.

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Section: Introductionmentioning

confidence: 88%

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confidence: 88%

Indian Ocean influence on the ENSO-monsoon teleconnection is mostly apparent

Bódai

Aneesh

Lee

et al. 2022

Preprint

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“…Observation suggested that the regional Hadley circulation, via NAO in the northern hemisphere and IOD in the southern hemisphere, had roles in the change in ISM behavior (Roy and Collins, 2015). More recently, importance of western north Pacific low-level circulation influence on modulating ENSO-ISM teleconnections is highlighted (Mahendra et al, 2020;Ramu et al, 2020). Such features though well captured in the observation but shown missing in models (Roy and Kripalani, 2019b).…”

Section: Mechanisms: Role Of Natural Factorsmentioning

confidence: 99%

“…Separating models based on High Top or Low Top did not make much difference. Even many CMIP6 models are unable to represent the regional summer rainfall patterns over India associated with ENSO (Mahendra et al 2020).…”

Section: Ism-enso Teleconnectionmentioning

confidence: 99%

Teleconnections between tropical SST modes and Indian summer monsoon in observation and CMIP5 models

Roy

Kripalani

2021

Indian Summer Monsoon Variability

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“…Studying these teleconnections could help in forecasting episodes of extreme precipitation or droughts. The Indian summer monsoon (from June to September) contributing to almost 75% of the country's annual rainfall, shows a considerable link with the El Niño‐Southern Oscillation (ENSO; Mahendra et al ., 2020). The warming of the central and eastern tropical Pacific ocean known as the El Niño phase of ENSO is associated with deficit monsoon rainfall, and the cooling phase (La Niña) brings excess rain (Roy et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

Multivariate analysis of concurrent droughts and their effects on Kharif crops—A copula‐based approach

Muthuvel

Mahesha

2021

Intl Journal of Climatology

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Apart from creating an ecological imbalance, drought events could affect an agrarian country's economy and food security by reducing crop yields. The antecedent meteorological droughts could prolong into hydrological and (or) agricultural droughts and may co-exist as concurrent droughts. The current study aims to comprehensively study Indian concurrent droughts, their effects on crop yield, and possible teleconnection with ENSO (El Niño-Southern Oscillation), adopting a copula-based multivariate approach. The copula functions can replicate the correlation among the variables and keep the dependence structure intact. The concurrent drought characteristics are computed using a multivariate standardized drought index that incorporates the three primary drought indices using the Gaussian copula. Some of the severe concurrent drought years such as 2002, 1987, 1972, and 1965 caused considerable yield losses in Kharif season crops of groundnut, millet, and rice. This prompts to construct quad-variate models involving the crop yield and the three drought indices using the vine copulas that perform better than the elliptical and symmetric Archimedean copula. Though the isolated forms of droughts could cause mild yield losses, the probability of concurrent droughts causing high to exceptional losses is more. Further, the ENSO teleconnection with the concurrent monsoon droughts is analysed and mapped. The above-normal warming of the Nino 3.4 region over the tropical Pacific during the months leading up to the monsoon could signal concurrent monsoon droughts in the areas under the Ganga-Brahmaputra basin at a probability of around 45%. These results could be helpful in drought mitigation measures and policymaking.copula, drought, multivariate analysis, vine copula | INTRODUCTIONIn India, 14.5% of people are malnourished, and 37.9% of children under age five are stunted as of 2018 (Priyadarshini and Abhilash, 2020). Sustaining food security in an evergrowing population is one of the challenges posing the developing countries. With the increasing population, urban expansion could sprawl into agricultural farmlands (Abu Hatab et al., 2019). Thus improving the crop yield with advanced farming machinery, pesticides, insecticides, irrigation practices, or sowing high yielding variety seeds become the need of the hour (Sannigrahi et al., 2021). Despite these measures, the inevitable climate extreme events such as extreme precipitation (Alidoost et al., 2019)

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Interdecadal modulation of interannual ENSO‐Indian summer monsoon rainfall teleconnections in observations and CMIP6 models: Regional patterns

Cited by 27 publications

References 73 publications

Indian Ocean influence on the ENSO-monsoon teleconnection is mostly apparent

Indian Ocean influence on the ENSO-monsoon teleconnection is mostly apparent

Teleconnections between tropical SST modes and Indian summer monsoon in observation and CMIP5 models

Multivariate analysis of concurrent droughts and their effects on Kharif crops—A copula‐based approach

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