El Nino events have a direct causal relationship with monsoon strength and timing.
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Peer-reviewed literature establishes that El Niño–Southern Oscillation (ENSO) events have a demonstrated climatic teleconnection and causal relationship with Indian summer monsoon rainfall, directly modulating its strength and variability.
There is an established evidence of climatic teleconnection between El Niño–Southern Oscillation (ENSO) and Indian summer monsoon rainfall (ISMR) during June through September. Against the long‐recognized negative correlation between ISMR and ENSO, unusual experiences of some recent years motivate the search for some other causal climatic variable, influencing the rainfall over the Indian subcontinent. Influence of recently identified Equatorial Indian Ocean Oscillation (EQUINOO, atmospheric part of Indian Ocean Dipole mode) is being investigated in this regard. However, the dynamic nature of cause‐effect relationship burdens a robust and consistent prediction. In this study, (1) a Bayesian dynamic linear model (BDLM) is proposed to capture the dynamic relationship between large‐scale circulation indices and monthly variation of ISMR and (2) EQUINOO is used along with ENSO information to establish their concurrent effect on monthly variation of ISMR. This large‐scale circulation information is used in the form of corresponding indices as exogenous input to BDLM, to predict the monthly ISMR. It is shown that the Indian monthly rainfall can be modeled in a better way using these two climatic variables concurrently (correlation coefficient between observed and predicted rainfall is 0.82), especially in those years when negative correlation between ENSO and ISMR is not well reflected (i.e., 1997, 2002, etc.). Apart from the efficacy of capturing the dynamic relationship by BDLM, this study further establishes that monthly variation of ISMR is influenced by the concurrent effects of ENSO and EQUINOO.
AbstractThe intensity of Indian summer monsoon rainfall (ISMR) over Central India (CI) is known to be positively correlated with the dust aerosol loading over the Arabian Sea (AS) on short time scales of about a week. However, global oscillations such as the El-Nino Southern Oscillation (ENSO) modulate both the rainfall over India and aerosol loading over the AS. This study uses long-term satellite-based aerosol and gridded rainfall datasets to explore the correlation between AS aerosol and CI rainfall and their relationship to ENSO. It is found that the highest correlation is during El-Nino (0.53), followed by Normal (0.44) and La-Nina (0.34) years, closely following the overall dust aerosol loading over the AS. Spatially, irrespective of the phase of ENSO, the high aerosol loading conditions are associated with increased winds over the AS, shifting eastward towards the Indian mainland and enhancing rainfall over CI and elsewhere across the Indian landmass. In contrast, the low aerosol loading conditions over the AS are associated with reduced winds, shifting westward away from the Indian mainland, suppressing rainfall over CI. In response to anthropogenic climate change, the El-Nino-like conditions are likely to increase in the future, making the dust aerosol-induced monsoon rainfall enhancement/modulation significant.
AbstractThis study presents the interannual variation in the summer monsoon rainfall during the El Nino Southern Oscillation (ENSO) phases, that is, El Nino and La Nina throughout the Indian subcontinent and its subregions during 1986–2010. The analysis includes the performance assessments of the regional climate model (RegCM4) in simulating Indian summer monsoon rainfall through comparison with India Meteorological Department rainfall data. Observation clearly demonstrates that the El Nino/La Nina produced weaker/strong monsoon rainfall over India and it increases the interannual variability of the southwest monsoon. The capability and skill of RegCM4's Grell and Mix99 cumulus parameterization scheme in simulating Indian summer monsoon rainfall associated with extreme climate are usually higher in “dry” conditions rather below average for the accurate simulation of “wet” conditions. Also, model performance was good in defining the characteristics, spatial distribution, and trend of a dry spell during ENSO phases with observation. The model‐simulated spatial and temporal value of wet spell during ENSO produces overestimated value over all India.
For flood-prone, developing nations where hydrological data is scarce, an innovative methodological approach is essential. This study aims to explore the potentiality of modelling daily evapotranspiration time series by checking causal relationship among the available climate variables in a flood-prone, data-deficient region like Samar in the Philippines. First, to verify if the available variables (rainfall, air pressure and the four (4) Niño Sea Surface Temperature (SST) Indices) have direct effects to evapotranspiration, a causality test called Convergent Cross-Mapping (CCM) was used. Inter
To develop scientific literacy in today's global era, however, it is important that students learn about interactions within the Earth's systems worldwide. A unit exploring El Nino and La Nina-phenomena that can result in extreme weather events in locations all around the world-can help bridge this gap and broaden students awareness of global issues. As a doctoral student and classroom teacher, these authors conducted a successful project-oriented exploration of El Nino with a sixth-grade class in Bexley, Ohio, and would like to share their experiences. Their students had just completed a unit
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