2018
DOI: 10.1029/2017jd028081
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Numerical Evaluation of the Modern and Future Origins of Atmospheric River Moisture Over the West Coast of the United States

Abstract: Atmospheric rivers (ARs) are one of the major causes of extreme precipitation and flooding in many regions around the world and have been found to contribute substantially to global poleward moisture transport. However, the evaporative origin of the moisture in ARs remains unclear, at least on climatological timescales. Here we use the water tracer and water isotope-enabled Community Atmosphere Model version 5 (CAM5) model to examine the moisture sources of ARs that impact the West Coast of the United States. … Show more

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Cited by 36 publications
(45 citation statements)
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“…The interpretations about differences in water sources between average and drought conditions were very clear in our case given that δ 18 O and δ 2 H were higher in 2015 precipitation compared to 2016 precipitation. Precipitation was more enriched in 2015 because of smaller fractionation rates due to the higher temperatures in this year, consistent with model simulations (Liu et al, ; Nusbaumer et al, ; Nusbaumer & Noone, ). This strong contrast in precipitation isotopes between years enhanced our ability to demonstrate that summer baseflow during the drought did not originate from the recent precipitation.…”
Section: Discussionsupporting
confidence: 84%
“…The interpretations about differences in water sources between average and drought conditions were very clear in our case given that δ 18 O and δ 2 H were higher in 2015 precipitation compared to 2016 precipitation. Precipitation was more enriched in 2015 because of smaller fractionation rates due to the higher temperatures in this year, consistent with model simulations (Liu et al, ; Nusbaumer et al, ; Nusbaumer & Noone, ). This strong contrast in precipitation isotopes between years enhanced our ability to demonstrate that summer baseflow during the drought did not originate from the recent precipitation.…”
Section: Discussionsupporting
confidence: 84%
“…One relevant aspect of ARs for understanding their temperature evolution is that they source moisture both locally and remotely. The majority of winter (DJF) moisture comes from the Northeast Pacific (Nusbaumer & Noone, ), yet a number of case studies have demonstrated examples of both large‐scale advection and local moisture convergence as the dominant mechanism (e.g., Dacre et al, ; Sodemann & Stohl, ). Our results (Figure ) likewise suggest that AR temperature evolution varies across the AR's lifespan, depending on the season and region of eventual landfall.…”
Section: Discussionmentioning
confidence: 99%
“…Water tagging has been implemented in the atmospheric component of CESM with new infrastructure within CAM and CLM to facilitate a variety of applications. For instance, the scheme has already been used to examine global (Singh et al, ) and regional (Dyer et al, ) variations in moisture source, as well as to determine the average moisture sources for specific weather phenomena (Nusbaumer & Noone, ). This water tagging can be applied to water isotopologues as well, allowing one to determine the impact of moisture source and pathway changes on the isotope ratios for a particular region (Tabor et al, ; Zhu et al, ).…”
Section: Model Descriptionmentioning
confidence: 99%
“…Efforts to simulate water isotope ratios in climate models span at least half a decade. Earlier isotope-enabled simulations typically included only the atmosphere and land surface (Field et al, 2014;Hoffmann et al, 1998;Joussaume et al, 1984;Jouzel et al, 1987;Jouzel et al, 1991;Mathieu et al, 2002;Noone & Simmonds, 2002;Noone & Sturm, 2010;Werner et al, 2011), and have been found to be reliable in reproducing the extensive database of precipitation observations from the Global Network for Isotopes in Precipitation (GNIP) (IAEA/ WMO, 2016). There are fewer more recent atmospheric models with isotopic tracers that have been compared to isotope ratios of tropospheric water vapor from satellite or in situ observations (notably, Schmidt et al, 2005Nusbaumer et al, 2017).…”
Section: Introductionmentioning
confidence: 99%