In India,large-scale climatic oscillations have strong influences on the Indian summer monsoon rainfall(ISMR),which plays a crucial role in India’s agricultural production and economic growth.However,there are limite...In India,large-scale climatic oscillations have strong influences on the Indian summer monsoon rainfall(ISMR),which plays a crucial role in India’s agricultural production and economic growth.However,there are limited studies in India that explore the influences of decadal and multidecadal oscillations on the ISMR and associated El Niño–Southern Oscillation(ENSO).Therefore,in this study we carried out a comprehensive and detailed investigation to understand the influences of ENSO,Pacific decadal oscillation(PDO),and Atlantic multidecadal oscillation(AMO)on ISMR across different regions in India.The statistical significance of ISMR associated with different phases(positive/warm and negative/cold)of ENSO,PDO,and AMO(individual analysis),and combined ENSO–AMO,and ENSO–PDO(coupled analysis)were analysed by using the nonparametric Wilcoxon Rank Sum(WRS)test.The individual analysis results indicate that in addition to the ENSO teleconnection,AMO and PDO significantly affect the spatial patterns of ISMR.Coupled analysis was performed to understand how the phase shift of PDO and AMO has modulated the rainfall during El Niño and La Niña phases.The results indicate that the La Niña associated with a positive PDO phase caused excessive precipitation of about 21%–150%in the peninsular,west–central,and hilly regions compared to the individual effect of ENSO/PDO/AMO on ISMR;similarly,the west–central,coastal,and northwest regions received 15%–56%of excessive rainfall.Moreover,during the El Niño combined with PDO positive(AMO positive),above-normal precipitation was observed in hilly,northeast,and coastal(hilly,northeast,west–central,and coastal)regions,opposite to the results obtained from the individual ENSO analysis.This study emphasizes the importance of accounting the decadal and multidecadal forcing when examining variations in the ISMR during different phases of ENSO events.展开更多
This study presents a model to forecast the Indian summer monsoon rainfall（ISMR）（June-September）based on monthly and seasonal time scales. The ISMR time series data sets are classified into two parts for modeling ...This study presents a model to forecast the Indian summer monsoon rainfall（ISMR）（June-September）based on monthly and seasonal time scales. The ISMR time series data sets are classified into two parts for modeling purposes, viz.,（1） training data set（1871-1960）, and（2） testing data set（1961-2014）.Statistical analyzes reflect the dynamic nature of the ISMR, which couldn＇t be predicted efficiently by statistical and mathematical based models. Therefore, this study suggests the usage of three techniques,viz., fuzzy set, entropy and artificial neural network（ANN）. Based on these techniques, a novel ISMR time series forecasting model is designed to deal with the dynamic nature of the ISMR. This model is verified and validated with training and testing data sets. Various statistical analyzes and comparison studies demonstrate the effectiveness of the proposed model.展开更多
文摘In India,large-scale climatic oscillations have strong influences on the Indian summer monsoon rainfall(ISMR),which plays a crucial role in India’s agricultural production and economic growth.However,there are limited studies in India that explore the influences of decadal and multidecadal oscillations on the ISMR and associated El Niño–Southern Oscillation(ENSO).Therefore,in this study we carried out a comprehensive and detailed investigation to understand the influences of ENSO,Pacific decadal oscillation(PDO),and Atlantic multidecadal oscillation(AMO)on ISMR across different regions in India.The statistical significance of ISMR associated with different phases(positive/warm and negative/cold)of ENSO,PDO,and AMO(individual analysis),and combined ENSO–AMO,and ENSO–PDO(coupled analysis)were analysed by using the nonparametric Wilcoxon Rank Sum(WRS)test.The individual analysis results indicate that in addition to the ENSO teleconnection,AMO and PDO significantly affect the spatial patterns of ISMR.Coupled analysis was performed to understand how the phase shift of PDO and AMO has modulated the rainfall during El Niño and La Niña phases.The results indicate that the La Niña associated with a positive PDO phase caused excessive precipitation of about 21%–150%in the peninsular,west–central,and hilly regions compared to the individual effect of ENSO/PDO/AMO on ISMR;similarly,the west–central,coastal,and northwest regions received 15%–56%of excessive rainfall.Moreover,during the El Niño combined with PDO positive(AMO positive),above-normal precipitation was observed in hilly,northeast,and coastal(hilly,northeast,west–central,and coastal)regions,opposite to the results obtained from the individual ENSO analysis.This study emphasizes the importance of accounting the decadal and multidecadal forcing when examining variations in the ISMR during different phases of ENSO events.
基金supported by the Department of Science and Technology (DST)-SERB, Government of India, under Grant EEQ/ 2016/000021
文摘This study presents a model to forecast the Indian summer monsoon rainfall（ISMR）（June-September）based on monthly and seasonal time scales. The ISMR time series data sets are classified into two parts for modeling purposes, viz.,（1） training data set（1871-1960）, and（2） testing data set（1961-2014）.Statistical analyzes reflect the dynamic nature of the ISMR, which couldn＇t be predicted efficiently by statistical and mathematical based models. Therefore, this study suggests the usage of three techniques,viz., fuzzy set, entropy and artificial neural network（ANN）. Based on these techniques, a novel ISMR time series forecasting model is designed to deal with the dynamic nature of the ISMR. This model is verified and validated with training and testing data sets. Various statistical analyzes and comparison studies demonstrate the effectiveness of the proposed model.
