Extreme precipitation from the South-Asian monsoon season combines with significant topographic relief within the Himalayan region to cause landslides that result in hundreds to thousands of fatalities each year. While there are few consistent and publicly available in-situ estimates of rainfall across this region, satellite products and global climate models provide insight into the extreme precipitation patterns that may impact the frequency of landsliding. In this work, we analyzed several extreme precipitation indices using data from a global climate model and the satellite-based Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis product to represent extreme precipitation over High Mountain Asia. We then compared the temporal distribution of extreme precipitation to a global database of landslides to better understand the spatiotemporal distribution of potential landslide triggering factors. We found that these indices successfully model the seasonality of landslide activity across the region, but other aspects of spatiotemporal variability require additional information and analysis before they can be applied more broadly.

Extreme precipitation in the Himalayan landslide hotspot

Pascale S.;
2020

Abstract

Extreme precipitation from the South-Asian monsoon season combines with significant topographic relief within the Himalayan region to cause landslides that result in hundreds to thousands of fatalities each year. While there are few consistent and publicly available in-situ estimates of rainfall across this region, satellite products and global climate models provide insight into the extreme precipitation patterns that may impact the frequency of landsliding. In this work, we analyzed several extreme precipitation indices using data from a global climate model and the satellite-based Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis product to represent extreme precipitation over High Mountain Asia. We then compared the temporal distribution of extreme precipitation to a global database of landslides to better understand the spatiotemporal distribution of potential landslide triggering factors. We found that these indices successfully model the seasonality of landslide activity across the region, but other aspects of spatiotemporal variability require additional information and analysis before they can be applied more broadly.
Advances in Global Change Research
1087
1111
Stanley T.; Kirschbaum D.B.; Pascale S.; Kapnick S.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/850735
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