Multifactorial Atmospheric River Tracking for Understanding Regional Hydrometeorological Effects in the US and the Arctic

Atmospheric rivers (ARs), the long narrow filaments of enhanced water vapor transport in the lower extratropical troposphere, are important to the global hydrological cycle and regional water resources. In this thesis, we presented data-driven research on ARs affecting surface hydrometeorology in the US and the Arctic. We developed a multifactorial AR tracking design combining climatological thresholds, image processing, and statistical methods to create large ensembles of AR indices for answering the questions of concern with uncertainty quantification aided by detailed data visualization.

In the first study, We created an ensemble of 162 AR indices for the US West Coast and Midwest based on four factors---moisture fields, climatological thresholds, shape criteria, and duration thresholds. We found that an optimal AR detection algorithm should be adaptive to the types of impact to be addressed, the associated physical mechanisms in the affected regions, season, and event durations. Integrated water vapor (IWV) can represent the broad-stroke presence and accumulation of precipitation in regions studied. Longer duration thresholds also led to higher accumulated precipitation. Combined moisture with wind fields using integrated water vapor transport (IVT), is necessary to get extreme West Coast AR orographic precipitation. $IWV$ well represents moderate to extreme Midwest AR precipitation events for all seasons. Combination of IVT and IWV is useful to get snapshots of extreme precipitation events.

ARs are conspicuous pathways for poleward moisture transport, and are likely integral to the ongoing Arctic amplification. We further created 12 Arctic AR indices using the ERA5 and MERRA-2 reanalysis data and presented an atlas of Arctic AR climatology. The time series analysis of the AR event counts from the AR indices showed overall upward trends from the mid-1990s to 2019. Spatial exploratory analysis of these indices revealed that the AR frequency of occurrence maxima shifted poleward from over-land in 1980--1999 to over the Arctic Ocean and its outlying Seas in 2000--2019. Regions across the Atlantic, the Arctic, to the Pacific Oceans trended higher AR occurrence, surface temperature, and column-integrated moisture. Meanwhile, ARs were increasingly responsible for the rising moisture transport into the Arctic. Even though the increase of Arctic AR occurrence was primarily associated with long-term Arctic surface warming and moistening, the effects of changing atmospheric circulation could stand out locally, such as on the Pacific side over the Chukchi Sea. The changing teleconnection patterns strongly modulated AR activities in time and space, with prominent anomalies in the Arctic-Pacific sector during the latest decade. 

The bootstrap estimates show that synoptic circulations associated with teleconnection patterns, jet stream, and storm track appeared to modulate the most extreme Arctic ARs into the Arctic according to the extreme-event criteria-based AR index. Along AR’s track, strong eddy kinetic energy, enhanced warming and moistening, increased downward longwave radiation, and associated sea ice concentration decline were observed. Particularly, during the negative phase of the Pacific-North American pattern in the winter, Arctic warming and Eurasian/North American continents cooling, the so-called "Warm Arctic-cold continent" pattern, were detected at the same time. The climate characteristics in Greenland were strongly dependent on the phase of NAO, with significant surface warming and moisturizing during the negative phase but cooling and drying in the positive phase. While during the positive phase of the Arctic Oscillation, North American warming and Eurasian warming were observed simultaneously.  

To the end, this work advanced our understanding of the variability in AR climatological characteristics and the associated hydrometeorology attributable to various aspects of ARs revealed by the detection methods. Such statistical and physical understanding will improve AR predictions in a changing climate and bridge a knowledge gap in Arctic Amplification.