Atmospheric River–Induced Precipitation and Snowpack during the Western United States Cold Season

Hisham Eldardiry Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Asif Mahmood Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Xiaodong Chen Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Faisal Hossain Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Bart Nijssen Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Dennis P. Lettenmaier Department of Geography, University of California, Los Angeles, Los Angeles, California

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Abstract

Atmospheric rivers (ARs) are narrow, elongated corridors of high water vapor content transported from tropical and/or extratropical cyclones. We characterize precipitation and snow water equivalent associated with ARs intersecting the western U.S. coast during the cold season (November– March) of water years 1949–2015. For each AR landfalling date, we retrieved the precipitation and relevant hydrometeorological variables from dynamically downscaled atmospheric reanalyses (NCEP–NCAR) using the WRF mesoscale numerical weather prediction model. Landfalling ARs resulted in higher precipitation amounts throughout the domain than did non-AR storms. ARs contributed the most extreme precipitation events during January and February. Daily snow water equivalent (SWE) changes during ARs indicate that high positive net snow accumulation conditions accompany ARs in December, January, and February. We also assess the historical impact of AR storm duration and precipitation frequency by considering the precipitation depth estimated during a 72-h window bounding the AR landfall date. More extreme precipitation amounts are produced by ARs in the South Cascades and Sierra Nevada ranges compared with ARs with landfall farther north. Most AR extreme precipitation events (and lower SWE accumulations) are produced during warm AR dates, especially toward the northern end of our domain. Analysis of ARs during dry and wet years reveals that ARs during wet years are more frequent and produce heavier precipitation and snow accumulation as compared with dry years. Such conditions are evident in drought events that are associated with a reduced frequency of ARs.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Faisal Hossain, fhossain@uw.edu

Abstract

Atmospheric rivers (ARs) are narrow, elongated corridors of high water vapor content transported from tropical and/or extratropical cyclones. We characterize precipitation and snow water equivalent associated with ARs intersecting the western U.S. coast during the cold season (November– March) of water years 1949–2015. For each AR landfalling date, we retrieved the precipitation and relevant hydrometeorological variables from dynamically downscaled atmospheric reanalyses (NCEP–NCAR) using the WRF mesoscale numerical weather prediction model. Landfalling ARs resulted in higher precipitation amounts throughout the domain than did non-AR storms. ARs contributed the most extreme precipitation events during January and February. Daily snow water equivalent (SWE) changes during ARs indicate that high positive net snow accumulation conditions accompany ARs in December, January, and February. We also assess the historical impact of AR storm duration and precipitation frequency by considering the precipitation depth estimated during a 72-h window bounding the AR landfall date. More extreme precipitation amounts are produced by ARs in the South Cascades and Sierra Nevada ranges compared with ARs with landfall farther north. Most AR extreme precipitation events (and lower SWE accumulations) are produced during warm AR dates, especially toward the northern end of our domain. Analysis of ARs during dry and wet years reveals that ARs during wet years are more frequent and produce heavier precipitation and snow accumulation as compared with dry years. Such conditions are evident in drought events that are associated with a reduced frequency of ARs.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Faisal Hossain, fhossain@uw.edu
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  • Amante, C., and B. W. Eakins, 2009: ETOPO1 Global Relief Model converted to PanMap layer format. PANGAEA, https://doi.org/10.1594/PANGAEA.769615.

    • Crossref
    • Export Citation
  • Bao, J. W., S. A. Michelson, P. J. Neiman, F. M. Ralph, and J. M. Wilczak, 2006: Interpretation of enhanced integrated water vapor bands associated with extratropical cyclones: Their formation and connection to tropical moisture. Mon. Wea. Rev., 134, 10631080, https://doi.org/10.1175/MWR3123.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barth, N. A., G. Villarini, M. A. Nayak, and K. White, 2017: Mixed populations and annual flood frequency estimates in the western United States: The role of atmospheric rivers. Water Resour. Res., 53, 257269, https://doi.org/10.1002/2016WR019064.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Browning, K. A., and C. W. Pardoe, 1973: Structure of low-level jet streams ahead of mid-latitude cold fronts. Quart. J. Roy. Meteor. Soc., 99, 619638, https://doi.org/10.1002/qj.49709942204.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cayan, D. R., M. D. Dettinger, S. A. Kammerdiener, J. M. Caprio, and D. H. Peterson, 2001: Changes in the onset of spring in the western United States. Bull. Amer. Meteor. Soc., 82, 399415, https://doi.org/10.1175/1520-0477(2001)082<0399:CITOOS>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, X., and F. Hossain, 2016: Revisiting extreme storms of the past 100 years for future safety of large water management infrastructures. Earth’s Future, 4, 306322, https://doi.org/10.1002/2016EF000368.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, X., F. Hossain, and L. R. Leung, 2017: Establishing a numerical modeling framework for hydrologic engineering analyses of extreme storm events. J. Hydrol. Eng., 22, 04017016, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001523.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Daly, C., R. P. Neilson, and D. L. Phillips, 1994: A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 33, 140158, https://doi.org/10.1175/1520-0450(1994)033<0140:ASTMFM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M., 2011: Climate change, atmospheric rivers, and floods in California–A multimodel analysis of storm frequency and magnitude changes. J. Amer. Water Resour. Assoc., 47, 514523, https://doi.org/10.1111/j.1752-1688.2011.00546.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M., 2013: Atmospheric rivers as drought busters on the U.S. West Coast. J. Hydrometeor., 14, 17211732, https://doi.org/10.1175/JHM-D-13-02.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M., 2016: Historical and future relations between large storms and droughts in California. San Francisco Estuary Watershed Sci., 14 (2), https://doi.org/10.15447/sfews.2016v14iss2art1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M., F. M. Ralph, T. Das, P. J. Neiman, and D. R. Cayan, 2011: Atmospheric rivers, floods and the water resources of California. Water, 3, 445478, https://doi.org/10.3390/w3020445.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M., F. M. Ralph, and J. J. Rutz, 2018: Empirical return periods of the most intense vapor transports during historical atmospheric river landfalls on the U.S. West Coast. J. Hydrometeor., 19, 13631377, https://doi.org/10.1175/JHM-D-17-0247.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eiras-Barca, J., A. M. Ramos, J. G. Pinto, R. M. Trigo, M. L. Liberato, and G. Miguez-Macho, 2018: The concurrence of atmospheric rivers and explosive cyclogenesis in the North Atlantic and North Pacific basins. Earth Syst. Dyn., 9, 91102, https://doi.org/10.5194/esd-9-91-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eldardiry, H., E. Habib, and Y. Zhang, 2015: On the use of radar-based quantitative precipitation estimates for precipitation frequency analysis. J. Hydrol., 531, 441453, https://doi.org/10.1016/j.jhydrol.2015.05.016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gershunov, A., T. Shulgina, F. M. Ralph, D. A. Lavers, and J. J. Rutz, 2017: Assessing the climate-scale variability of atmospheric rivers affecting western North America. Geophys. Res. Lett., 44, 79007908, https://doi.org/10.1002/2017GL074175.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffin, D., and K. J. Anchukaitis, 2014: How unusual is the 2012–2014 California drought? Geophys. Res. Lett., 41, 90179023, https://doi.org/10.1002/2014GL062433.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guan, B., and D. E. Waliser, 2015: Detection of atmospheric rivers: Evaluation and application of an algorithm for global studies. J. Geophys. Res. Atmos., 120, 12 51412 535, https://doi.org/10.1002/2015JD024257.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guan, B., N. P. Molotch, D. E. Waliser, E. J. Fetzer, and P. J. Neiman, 2010: Extreme snowfall events linked to atmospheric rivers and surface air temperature via satellite measurements. Geophys. Res. Lett., 37, L20401, https://doi.org/10.1029/2010GL044696.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guan, B., D. E. Waliser, F. M. Ralph, E. J. Fetzer, and P. J. Neiman, 2016: Hydrometeorological characteristics of rain-on-snow events associated with atmospheric rivers. Geophys. Res. Lett., 43, 29642973, https://doi.org/10.1002/2016GL067978.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hagos, S. M., L. R. Leung, J. H. Yoon, J. Lu, and Y. Gao, 2016: A projection of changes in landfalling atmospheric river frequency and extreme precipitation over western North America from the Large Ensemble CESM simulations. Geophys. Res. Lett., 43, 13571363, https://doi.org/10.1002/2015GL067392.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S. Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, https://doi.org/10.1175/MWR3199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hosking, J. R., and J. Wallis, 1997: Regional Frequency Analysis: An Approach Based on L-Moments. Cambridge University Press, 242 pp.

    • Crossref
    • Export Citation
  • Hu, X. M., M. Xue, R. A. McPherson, E. Martin, D. H. Rosendahl, and L. Qiao, 2018: Precipitation dynamical downscaling over the Great Plains. J. Adv. Model. Earth Syst., 10, 421447, https://doi.org/10.1002/2017MS001154.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huning, L. S., B. Guan, D. E. Waliser, and D. P. Lettenmaier, 2019: Sensitivity of seasonal snowfall attribution to atmospheric rivers and their reanalysis-based detection. Geophys. Res. Lett., 46, 794803. https://doi.org/10.1029/2018GL080783.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jordan, R., 1991: A one-dimensional temperature model for a snow cover: Technical documentation for SNTERERM.89. Special Rep. 9116, Cold Region Research and Engineers Laboratory, U.S. Army Corps of Engineers, Hanover, NH, 61 pp.

  • Kain, J., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kain, J., and J. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47, 27842802, https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kain, J., and J. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 165–170.

    • Crossref
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kistler, R., and Coauthors, 2001: The NCEP–NCAR 50-year reanalysis: Monthly means CD-ROM and documentation. Bull. Amer. Meteor. Soc., 82, 247267, https://doi.org/10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Konrad, C. P., and M. D. Dettinger, 2017: Flood runoff in relation to water vapor transport by atmospheric rivers over the Western United States, 1949–2015. Geophys. Res. Lett., 44, 11 45611 462, https://doi.org/10.1002/2017GL075399.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lamjiri, M. A., M. D. Dettinger, F. M. Ralph, and B. Guan, 2017: Hourly storm characteristics along the US West Coast: Role of atmospheric rivers in extreme precipitation. Geophys. Res. Lett., 44, 70207028, https://doi.org/10.1002/2017GL074193.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Leung, L. R., and Y. Qian, 2009: Atmospheric rivers induced heavy precipitation and flooding in the western US simulated by the WRF regional climate model. Geophys. Res. Lett., 36, L03820, https://doi.org/10.1029/2008GL036445.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994: A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophy. Res., 99, 14 41514 428, https://doi.org/10.1029/94JD00483.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, C., and Coauthors, 2017: Continental-scale convection-permitting modeling of the current and future climate of North America. Climate Dyn., 49, 7195, https://doi.org/10.1007/s00382-016-3327-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Livneh, B., E. A. Rosenberg, C. Lin, B. Nijssen, V. Mishra, K. M. Andreadis, E. P. Maurer, and D. P. Lettenmaier, 2013: A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States: Update and extensions. J. Climate, 26, 93849392, https://doi.org/10.1175/JCLI-D-12-00508.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lorente-Plazas, R., T. P. Mitchell, G. Mauger, and E. P. Salathé Jr., 2018: Local enhancement of extreme precipitation during atmospheric rivers as simulated in a regional climate model. J. Hydrometeor., 19, 14291446, https://doi.org/10.1175/JHM-D-17-0246.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maurer, E. P., A. W. Wood, J. C. Adam, D. P. Lettenmaier, and B. Nijssen, 2002: A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States. J. Climate, 15, 32373251, https://doi.org/10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McMahon, G., S. M. Gregonis, S. W. Waltman, J. M. Omernik, T. D. Thorson, J. A. Freeouf, A. H. Rorick, and J. E. Keys, 2001: Developing a spatial framework of common ecological regions for the conterminous United States. Environ. Manage., 28, 293316, https://doi.org/10.1007/s0026702429.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one-and two-moment schemes. Mon. Wea. Rev., 137, 9911007, https://doi.org/10.1175/2008MWR2556.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nayak, M. A., G. Villarini, and D. A. Lavers, 2014: On the skill of numerical weather prediction models to forecast atmospheric rivers over the central United States. Geophys. Res. Lett., 41, 43544362, https://doi.org/10.1002/2014GL060299.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neiman, P. J., F. M. Ralph, G. A. Wick, J. D. Lundquist, and M. D. Dettinger, 2008: Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the West Coast of North America based on eight years of SSM/I satellite observations. J. Hydrometeor., 9, 2247, https://doi.org/10.1175/2007JHM855.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neiman, P. J., A. B. White, F. M. Ralph, D. J. Gottas, and S. I. Gutman, 2009: A water vapour flux tool for precipitation forecasting. Proc. Inst. Civ. Eng.: Water Manage., 162, 8394, https://doi.org/10.1680/wama.2009.162.2.83.

    • Search Google Scholar
    • Export Citation
  • Neiman, P. J., L. J. Schick, F. M. Ralph, M. Hughes, and G. A. Wick, 2011: Flooding in western Washington: The connection to atmospheric rivers. J. Hydrometeor., 12, 13371358, https://doi.org/10.1175/2011JHM1358.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Niu, G. Y., and Coauthors, 2011: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J. Geophys. Res., 116, D12109, https://doi.org/10.1029/2010JD015139.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Omernik, J. M., 2004: Perspectives on the nature and definition of ecological regions. Environ. Manage., 34, S27S38, https://doi.org/10.1007/s00267-003-5197-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Overeem, A., T. A. Buishand, and I. Holleman, 2009: Extreme rainfall analysis and estimation of depth-duration-frequency curves using weather radar. Water Resour. Res., 45, W10424, https://doi.org/10.1029/2009WR007869.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peterson, T. C., X. Zhang, M. Brunet-India, and J. L. Vázquez-Aguirre, 2008: Changes in North American extremes derived from daily weather data. J. Geophys. Res., 113, D07113, https://doi.org/10.1029/2007JD009453.

    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., and M. D. Dettinger, 2011: Storms, floods, and the science of atmospheric rivers. Eos, Trans. Amer. Geophys. Union, 92, 265266, https://doi.org/10.1029/2011EO320001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., and M. D. Dettinger, 2012: Historical and national perspectives on extreme West Coast precipitation associated with atmospheric rivers during December 2010. Bull. Amer. Meteor. Soc., 93, 783790, https://doi.org/10.1175/BAMS-D-11-00188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., P. J. Neiman, and G. A. Wick, 2004: Satellite and CALJET aircraft observations of atmospheric rivers over the eastern North Pacific Ocean during the winter of 1997/98. Mon. Wea. Rev., 132, 17211745, https://doi.org/10.1175/1520-0493(2004)132<1721:SACAOO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., P. J. Neiman, G. A. Wick, S. I. Gutman, M. D. Dettinger, D. R. Cayan, and A. B. White, 2006: Flooding on California’s Russian River: Role of atmospheric rivers. Geophys. Res. Lett., 33, L13801, https://doi.org/10.1029/2006GL026689.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., T. Coleman, P. J. Neiman, R. J. Zamora, and M. D. Dettinger, 2013: Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal northern California. J. Hydrometeor., 14, 443459, https://doi.org/10.1175/JHM-D-12-076.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., and Coauthors, 2014: A vision for future observations for western U.S. extreme precipitation and flooding. J. Contemp. Water Res. Educ., 153, 1632, https://doi.org/10.1111/j.1936-704X.2014.03176.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., M. D. Dettinger, M. M. Cairns, T. J. Galarneau, and J. Eylander, 2018: Defining “atmospheric river”: How the Glossary of Meteorology helped resolve a debate. Bull. Amer. Meteor. Soc., 99, 837839, https://doi.org/10.1175/BAMS-D-17-0157.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., and Coauthors, 2019: ARTMIP-early start comparison of atmospheric river detection tools: How many atmospheric rivers hit northern California’s Russian River watershed? Climate Dyn., 52, 49734994, https://doi.org/10.1007/s00382-018-4427-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Regonda, S. K., B. Rajagopalan, M. Clark, and J. Pitlick, 2005: Seasonal cycle shifts in hydroclimatology over the western United States. J. Climate, 18, 372384, https://doi.org/10.1175/JCLI-3272.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosen, J., 2017: California rains put spotlight on atmospheric rivers. Science, 355, 787, https://doi.org/10.1126/science.355.6327.787.

  • Rutz, J. J., W. J. Steenburgh, and F. M. Ralph, 2014: Climatological characteristics of atmospheric rivers and their inland penetration over the western United States. Mon. Wea. Rev., 142, 905921, https://doi.org/10.1175/MWR-D-13-00168.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shields, C. A., and Coauthors, 2018: Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Project goals and experimental design. Geosci. Model Dev., 11, 24552474, https://doi.org/10.5194/gmd-11-2455-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the Advanced Research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp., https://doi.org/10.5065/D6DZ069T.

    • Crossref
    • Export Citation
  • Swain, D. L., M. Tsiang, M. Haugen, D. Singh, A. Charland, B. Rajaratnam, and N. S. Diffenbaugh, 2014: The extraordinary California drought of 2013/2014: Character, context, and the role of climate change [in “Explaining Extreme Events of 2013 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 95 (9), S3S6, https://doi.org/10.1175/1520-0477-95.9.S1.1.

    • Search Google Scholar
    • Export Citation
  • Trujillo, E., and N. P. Molotch, 2014: Snowpack regimes of the western United States. Water Resour. Res., 50, 56115623, https://doi.org/10.1002/2013WR014753.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, J., and V. R. Kotamarthi, 2014: Downscaling with a nested regional climate model in near-surface fields over the contiguous United States. J. Geophys. Res. Atmos., 119, 87788797, https://doi.org/10.1002/2014JD021696.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wayand, N. E., J. D. Lundquist, and M. P. Clark, 2015: Modeling the influence of hypsometry, vegetation, and storm energy on snowmelt contributions to basins during rain-on-snow floods. Water Resour. Res., 51, 85518569, https://doi.org/10.1002/2014WR016576.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • White, A. B., and Coauthors, 2012: NOAA’s rapid response to the Howard A. Hanson Dam flood risk management crisis. Bull. Amer. Meteor. Soc., 93, 189207, https://doi.org/10.1175/BAMS-D-11-00103.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, Z.-L., and Coauthors, 2011: The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins. J. Geophys. Res., 116, D12110, https://doi.org/10.1029/2010JD015140.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Young, A. M., K. T. Skelly, and J. M. Cordeira, 2017: High-impact hydrologic events and atmospheric rivers in California: An investigation using the NCEI Storm Events Database. Geophys. Res. Lett., 44, 33933401, https://doi.org/10.1002/2017GL073077.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhu, Y., and R. E. Newell, 1998: A proposed algorithm for moisture fluxes from atmospheric rivers. Mon. Wea. Rev., 126, 725735, https://doi.org/10.1175/1520-0493(1998)126<0725:APAFMF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
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