Waiting Time and Clustering of Indian Summer Monsoon Daily Precipitation Extremes

ABSTRACT The characterisation of temporal variability of Indian summer monsoon precipitation events in a warming world is critically important for the densely populated and predominantly agrarian Indian region due to obvious socio‐economic impacts. In this study, the temporal distribution of Indian summer monsoon daily precipitation events is analysed in terms of waiting time between events and serial clustering of events. The fractional Poisson exponent and extremal index are used as the quantifiers for this purpose, respectively. It is demonstrated that the waiting time between extreme precipitation events is power‐law distributed with long‐range dependence. This indicates that there is a finite probability of recurrence of rarer extreme events within a season. The waiting time between extreme precipitation events is becoming shorter in central India, western India and northeast India due to global warming. The extremal index analysis of extreme precipitation events suggests that there is a strong tendency of serial clustering of precipitation extremes over India. Our results also suggest that barring southern peninsular India, there will be an overall increase in the tendency of serial clustering of extreme precipitation events in a warming climate. Our findings of temporal variability of extreme precipitation over India due to climate change may exacerbate the already serious urban flooding problem due to human activity.

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Publication Details

Journal
International Journal of Climatology
Published
2025-08-11
DOI
https://doi.org/10.1002/joc.70067
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00

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article

Waiting Time and Clustering of Indian Summer Monsoon Daily Precipitation Extremes

B. N. Goswami, Suneet Dwivedi, Christian L. E. Franzke
International Journal of Climatology
Climate variability and models
article

Waiting Time and Clustering of Indian Summer Monsoon Daily Precipitation Extremes

B. N. Goswami, Suneet Dwivedi, Christian L. E. Franzke
article en

Abstract

ABSTRACT The characterisation of temporal variability of Indian summer monsoon precipitation events in a warming world is critically important for the densely populated and predominantly agrarian Indian region due to obvious socio‐economic impacts. In this study, the temporal distribution of Indian summer monsoon daily precipitation events is analysed in terms of waiting time between events and serial clustering of events. The fractional Poisson exponent and extremal index are used as the quantifiers for this purpose, respectively. It is demonstrated that the waiting time between extreme precipitation events is power‐law distributed with long‐range dependence. This indicates that there is a finite probability of recurrence of rarer extreme events within a season. The waiting time between extreme precipitation events is becoming shorter in central India, western India and northeast India due to global warming. The extremal index analysis of extreme precipitation events suggests that there is a strong tendency of serial clustering of precipitation extremes over India. Our results also suggest that barring southern peninsular India, there will be an overall increase in the tendency of serial clustering of extreme precipitation events in a warming climate. Our findings of temporal variability of extreme precipitation over India due to climate change may exacerbate the already serious urban flooding problem due to human activity.

International Journal of ClimatologyVol. 45(13)
Gauhati University (IN), University of Allahabad (IN), Institute for Basic Science (KR), Pusan National University (KR)
Arthritis National Research Foundation, Department of Science and Technology, Ministry of Science and Technology, India, Fonds National de la Recherche Luxembourg, Gauhati University, Institute for Basic Science, Ministry of Science and ICT, South Korea, Science and Engineering Research Board
Climate action
Openalex Percentile: Top 80%
Climate variability and models
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