Publication Date

Fall 2021

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Meteorology and Climate Science

Advisor

Sen Chiao

Subject Areas

Meteorology

Abstract

Atmospheric rivers (ARs) are affected by large-scale climate variability. We investigate how ARs and snowpack are shaped by arctic oscillation (AO) by examining the synoptic conditions and characteristics of ARs and snowpack in the different phases of AO using forty years (1980-2019) of Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) data, Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) reanalysis data, and in-situ observation data over the eastern Pacific and western U.S. region. More precipitation is found in lower latitudes during negative AO months and farther north in latitude during positive AO months. These are associated with wavelike synoptic patterns in negative AO months while more straight-type synoptic patterns in positive AO months. The AR characteristics are also modulated by the different phase of AO: lower (higher) integrated water vapor transport and total precipitation, shorter (longer) duration of ARs, and less (more) ARs per month were more likely found during positive AO (negative AO) months with regional variability. Finally, snow water equivalent (SWE) tends to be reduced in positive AO phase and in high temperature condition, especially in the recent years, although the robust relationship remains unclear for long-term period. These findings highlight how the characteristics of local extreme weather during ARs can be shaped by large-scale climate variability.

Available for download on Monday, August 28, 2023

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