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    Object-Based Verification of Atmospheric River Predictions in the Northeast Pacific 

    Source: Weather and Forecasting:;2021:;volume( 036 ):;issue: 004:;page 1575
    Author(s): DeHaan, Laurel L.;Martin, Andrew C.;Weihs, Rachel R.;Delle Monache, Luca;Ralph, F. Martin
    Publisher: American Meteorological Society
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    Reaping Rewards from River and Rain: Applications of California’s Russian River Hydrometeorological Observing Network (RHONET) 

    Source: Bulletin of the American Meteorological Society:;2021:;volume( 102 ):;issue: 008:;page 737
    Author(s): Sumargo, Edwin; Wilson, Anna M.; Martin Ralph, F.; Weihs, Rachel; White, Allen; Jasperse, James; Asgari-Lamjiri, Maryam; Turnbull, Stephen; Downer, Charles; Delle Monache, Luca
    Publisher: American Meteorological Society
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    Evaluation of Atmospheric River Predictions by the WRF Model Using Aircraft and Regional Mesonet Observations of Orographic Precipitation and Its Forcing 

    Source: Journal of Hydrometeorology:;2018:;volume 019:;issue 007:;page 1097
    Author(s): Martin, Andrew; Ralph, F. Martin; Demirdjian, Reuben; DeHaan, Laurel; Weihs, Rachel; Helly, John; Reynolds, David; Iacobellis, Sam
    Publisher: American Meteorological Society
    Abstract: AbstractAccurate forecasts of precipitation during landfalling atmospheric rivers (ARs) are critical because ARs play a large role in water supply and flooding for many regions. In this study, we have used hundreds of ...
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    The Hydrometeorological Observation Network in California’s Russian River Watershed: Development, Characteristics and Key Findings from 1997 to 2019 

    Source: Bulletin of the American Meteorological Society:;2020:;volume( ):;issue: -
    Author(s): Sumargo, Edwin;Wilson, Anna M.;Ralph, F. Martin;Weihs, Rachel;White, Allen;Jasperse, James;Asgari-Lamjiri, Maryam;Turnbull, Stephen;Downer, Charles;Delle Monache, Luca
    Publisher: American Meteorological Society
    Abstract: The Russian River Hydrometeorological Observing Network (RHONET) is a unique suite of high-resolution in-situ and remote-sensing observations deployed over 20 years to address both scientific and operational gaps in ...
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    Observations and Predictability of a High-Impact Narrow Cold-Frontal Rainband over Southern California on 2 February 2019 

    Source: Weather and Forecasting:;2020:;volume( 035 ):;issue: 005:;page 2083
    Author(s): Cannon, Forest;Oakley, Nina S.;Hecht, Chad W.;Michaelis, Allison;Cordeira, Jason M.;Kawzenuk, Brian;Demirdjian, Reuben;Weihs, Rachel;Fish, Meredith A.;Wilson, Anna M.;Ralph, F. Martin
    Publisher: American Meteorological Society
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    Reaping Rewards from River and Rain: Applications of California’s Russian River Hydrometeorological Observing Network (RHONET) 

    Source: Bulletin of the American Meteorological Society:;2021:;volume( 102 ):;issue: 008
    Author(s): Sumargo, Edwin; Wilson, Anna M.; Martin Ralph, F.; Weihs, Rachel; White, Allen; Jasperse, James; Asgari-Lamjiri, Maryam; Turnbull, Stephen; Downer, Charles; Delle Monache, Luca
    Publisher: American Meteorological Society
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    West-WRF 34-Year Reforecast: Description and Validation 

    Source: Journal of Hydrometeorology:;2023:;volume( 024 ):;issue: 011:;page 2125
    Author(s): Cobb, Alison; Steinhoff, Daniel; Weihs, Rachel; Delle Monache, Luca; DeHaan, Laurel; Reynolds, David; Cannon, Forest; Kawzenuk, Brian; Papadopolous, Caroline; Ralph, F. M.
    Publisher: American Meteorological Society
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    Deep Learning of a 200-Member Ensemble with a Limited Historical Training to Improve the Prediction of Extreme Precipitation Events 

    Source: Monthly Weather Review:;2024:;volume( 152 ):;issue: 007:;page 1587
    Author(s): Ghazvinian, Mohammadvaghef; Delle Monache, Luca; Afzali Gorooh, Vesta; Steinhoff, Daniel; Sengupta, Agniv; Hu, Weiming; Simpson, Matthew; Weihs, Rachel; Papadopoulos, Caroline; Mulrooney, Patrick; Kawzenuk, Brian; Mascioli, Nora; Ralph, Fred Martin
    Publisher: American Meteorological Society
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