Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds

Chen, Xiaodong; Leung, L. Ruby; Wigmosta, Mark S.; Richmond, Marshall C.

doi:10.1029/2019jd030468

Cited by 49 publications

(52 citation statements)

References 74 publications

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“…Because of their warmer temperatures, ARs disproportionately contribute to rain-on-snow events that increase the ratio of streamflow to precipitation 137,138 . In general, snowpack ablates more during AR than non-AR events because of the higher temperatures, but increased long-wave radiation also plays a secondary role 139 . The importance of rain-on-snow events in contributing to run-off is demonstrated by the signifi cant increase of the run-off-to-precipitation ratio with (74%) and without (43%) pre-existing snowpack during AR landfall in the western USA 139 .…”

Section: Greenland/arcticmentioning

confidence: 99%

Responses and impacts of atmospheric rivers to climate change

Payne

Demory

Leung

et al. 2020

Nat Rev Earth Environ

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250

240

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Atmospheric rivers (ARs) are synoptic-scale features characterized by their striking geometry-extending thousands of kilometres in length and an order of magni tude less in width 1-and vertically coherent low-level moisture transport concentrated in the bottom 3 km of the atmosphere 2 (Fig. 1). In total, ARs are estimated to accomplish as much as 90% of poleward moisture transport 3,4 , which, in the North Pacific, averages 700 kg m −1 s −1 (Fig. 1b), more than twice the mean annual discharge found at the mouth of the Amazon River 5. ARs do not describe continuous moisture transport. Rather, they are continually evolving pathways that incorporate moisture from local convergence and evaporation along their track 6,7 or, in select cases, from distant source regions in the tropics or subtropics 8-12. Owing to the complexity of their evolution, our baseline knowledge of AR characteristics at the global scale is uncertain due to the dependency on identification algorithms (Box 1), with factors such as genesis, development and termination only recently being explored 13,14. However, ARs are known to operate as one part of a larger, synoptic-scale dynamical system driving the poleward transport of sensible and latent heat 4,15. They are generally found in the vicinity of extratropical cyclones. Over the North Pacific, for example, 85% of ARs are paired with extratropical cyclones 16 , consistent with their observed relationship with baroclinic instabilities and the mid-latitude storm track 3,6. However, this relationship is nuanced; only 45% of extratropical cyclones over the same region are associated with an AR 16. Similar non-linear relationships are observed in the North Atlantic, where the evolution and life cycle of a single AR can span that of several cyclones 9. While the phenomena are clearly related, their relationship is interactive, with potential implications on the inten sification of storms and the severity of precipitation impacts on land 17,18. Indeed, given their intense moisture transport and moist-neutrality, ARs exhibit conditions that are ideal for forced precipitation, either through interaction with topography or ascent along a warm conveyor belt or frontal boundary 19. Thus, when ARs make landfall, they can have a range of hydrological impacts, including precipitation extremes and related hazards,

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Section: Greenland/arcticmentioning

confidence: 99%

Responses and impacts of atmospheric rivers to climate change

Payne

Demory

Leung

et al. 2020

Nat Rev Earth Environ

Self Cite

250

240

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“…The skill of regional models in simulating these signals has been recognized for more than two decades through studies on multiple continents (e.g., Marinucci et al 1995;Qian 2003, 2009;Insel et al 2010;Cardoso et al 2013). Improving the representation of orographic forcing also improves simulations of extreme precipitation in mountains, such as that induced by atmospheric rivers (e.g., Leung and Qian 2009;Chen et al 2018). In fact, in mountainous regions, well-configured regional models may produce better estimates of total annual rain and snow than current observational estimates (Lundquist et al 2019) and improve understanding of processes driving surface hydrologic extremes associated with landfalling atmospheric rivers in mountainous areas (Chen et al 2019).…”

Section: E674mentioning

confidence: 99%

The Ongoing Need for High-Resolution Regional Climate Models: Process Understanding and Stakeholder Information

Gutowski

Ullrich

Hall

et al. 2020

Bulletin of the American Meteorological Society

127

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Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.

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“…Operational entities in this region such as the NWS and California Nevada River Forecast Center (CNRFC) rely heavily on gauge-based QPE adjusted for orographic effects, such as Precipitation-Elevation Regressions on Independent Slopes Model (PRISM; Daly et al 1994Daly et al , 2017 for forecast evaluation on scales from several hours to daily. However, it is important within the context of the AQPI project to understand the behavior of various QPE products at resolutions of interest to AQPI stakeholders, which range from event totals down to subhourly and grid spacings of a few kilometers, which are necessary for accurate representation of surface hydrologic processes in complex terrain (Chen et al 2019). Understanding the performance of existing high-resolution QPE datasets can then inform how new observations are used and how the experimental quantitative precipitation forecasts (QPFs) can be evaluated.…”

Section: Introductionmentioning

confidence: 99%

On the Uncertainty of High-Resolution Hourly Quantitative Precipitation Estimates in California

Bytheway

Hughes

Mahoney

et al. 2020

Journal of Hydrometeorology

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The Bay Area of California and surrounding region receives much of its annual precipitation during the October–March wet season, when atmospheric river events bring periods of heavy rain that challenge water managers and may exceed the capacity of storm sewer systems. The complex terrain of this region further complicates the situation, with terrain interactions that are not currently captured in most operational forecast models and inadequate precipitation measurements to capture the large variability throughout the area. To improve monitoring and prediction of these events at spatial and temporal resolutions of interest to area water managers, the Bay Area Advanced Quantitative Precipitation Information project was developed. To quantify improvements in forecast precipitation, model validation studies require a reference dataset to compare against. In this paper we examine 10 gridded, high-resolution (≤10 km, hourly) precipitation estimates to assess the uncertainty of high-resolution quantitative precipitation estimates (QPE) in areas of complex terrain. The products were linearly interpolated to 3-km grid spacing, which is the resolution of the operational forecast model to be validated. Substantial differences exist between the various products at accumulation periods ranging from hourly to annual, with standard deviations among the products exceeding 100% of the mean. While the products seem to agree fairly well on the timing of precipitation, intensity estimates differ, sometimes by an order of magnitude. The results highlight both the need for additional observations and the need to account for uncertainty in the reference dataset when validating forecasts in this area.

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Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds

Cited by 49 publications

References 74 publications

Responses and impacts of atmospheric rivers to climate change

Responses and impacts of atmospheric rivers to climate change

The Ongoing Need for High-Resolution Regional Climate Models: Process Understanding and Stakeholder Information

On the Uncertainty of High-Resolution Hourly Quantitative Precipitation Estimates in California

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