Understanding the Role of Water Vapor Transport in Extreme Precipitation Events in Nepal

Friday, 19 December 2014
Kritika Thapa, State University of New York, Syracuse, NY, United States, Theodore A Endreny, SUNY ESF, Syracuse, NY, United States and Craig R Ferguson, SUNY at Albany, Albany, NY, United States
In the future, IPCC global climate models project increased frequency of atmospheric rivers (ARs), which are concentrated bands of high moisture known to cause extreme precipitation and flooding events. While ARs have been studied in the United States (US) and Europe using reanalyses and satellite remote sensing, few if any studies have applied an AR analysis framework to regions in South Asia. In this research, we develop and test AR detection algorithms for Nepal by modifying a proven algorithm used in the western US and Europe. Nepal faces challenges in forecasting extreme precipitation events due to the region’s complex topography and lack of forecasting infrastructure. Accordingly, any tools that can lead to enhanced lead time of extreme weather forecasts, or help guide water management decisions, will have a substantial positive impact on the region’s coping ability.

Our AR algorithm uses ERA-Interim reanalysis data to compute integrated water vapor transport (kg m-1s-1) and determine the latitude specific threshold values, for four seasons. After detecting AR events, we test if those events correlate with observed extreme daily precipitation events. Extreme precipitation is determined annually and for non-monsoon months. Our initial results indicate that ARs coincide with extreme precipitation mostly in the cold season. We are extending our analyses to better understand how ARs relate to extreme precipitation events in all seasons. New methods to monitor the role of ARs in precipitation events will help manage water resources, which is critical given the melting of Himalayan glaciers that feed major watersheds of Nepal. In addition to understanding extreme events, our study will also aid in a better understanding of seasonal climate anomalies and the global water cycle.