| Summary: | Atmospheric rivers (ARs) are filaments of enhanced water vapor transport in the atmosphere. Globally, ARs play a key role in the meridional moisture transport. Regionally,ARs can either serve as freshwater suppliers or culprits behind many of the weather hazards. ARs and their impacts have been studied extensively. However, what controls the variability of ARs on different time scales remains largely unknown. In particular, further studies are especially needed to better understand the relative role of circulation (dynamic) variability versus moisture (thermodynamic) variability, internal variability versus sea surface temperature (SST)/ sea ice variability and anthropogenic forcing versus internal variability originated from SST/sea ice variability in controlling the variability of ARs and their associated precipitation on different time scales. In addition, reanalyses have long been used as proxies of observations in AR studies. Yet, the representation of ARs and their associated precipitation in reanalyses remain unknown. Although satellite observations have also been used to study ARs, previous satellite-based AR studies used only the moisture component (integrated water vapor or IWV) to detect ARs. While ARs have been defined as filaments of enhanced moisture transport in the atmosphere, detecting ARs with only the moisture field would inevitably run the risk of detecting those filamentary features with high moisture content, but relatively weak transport component. In this dissertation, we will address the research gaps above from five different angles. First, we investigate the relative role of SST/sea ice versus internal variability in driving the interannual variability of winter AR activities over the North Hemisphere. We show that, while both SST/sea ice and internal variability play roles in driving the interannual AR variability, their roles differ across ocean basins. Over the North Pacific, SST/sea ice variability exerts substantially stronger control on the AR variability compared to interval ...
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