Privacy Policy Disclaimer
  Advanced SearchBrowse




Journal Article

Ranking and characterization of precipitation extremes for the past 113 years for Indian western Himalayas


Raj,  Saurav
External Organizations;


Shukla,  Roopam
Potsdam Institute for Climate Impact Research;

Trigo,  Ricardo M.
External Organizations;

Merz,  Bruno
External Organizations;

Rathinasamy,  Maheswaran
External Organizations;

Ramos,  Alexandre M.
External Organizations;

Agarwal,  Ankit
External Organizations;

External Ressource
No external resources are shared
Fulltext (public)

(Postprint), 4MB

Supplementary Material (public)
There is no public supplementary material available

Raj, S., Shukla, R., Trigo, R. M., Merz, B., Rathinasamy, M., Ramos, A. M., Agarwal, A. (2021): Ranking and characterization of precipitation extremes for the past 113 years for Indian western Himalayas. - International Journal of Climatology, 41, 15, 6602-6615.

Cite as: https://publications.pik-potsdam.de/pubman/item/item_25651
Globally, mountain systems are unevenly exposed to risks of extreme precipitation. Within the Himalayan region, precipitation extremes are a rising concern, but their current understanding is limited. In this study, we use 113 years of precipitation data to rank and characterize precipitation extremes in the Indian Western Himalayas (IWH). Our statistical ranking method integrates precipitation spatial extent and its intensity across different durations for determining the severity of extreme events. The proposed ranking method accounts for multi-day duration ranking method to capture persistent precipitation episodes. Results show that the method accurately detects and ranks the most extreme precipitation events that occurred in the IWH and indicate locations of these events. Our results highlight that critical long duration events in the region (e.g., 10 days) are missed at ranks at shorter duration (e.g., 2–3 days), thereby highlighting the importance to multi-day precipitation extremes ranking. In addition, the proposed ranking method provides information about the event duration that will be associated with the highest impact on society, carrying high significance. Our findings are valuable for flood risk management and disaster risk reduction.