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Open Access Publications from the University of California

Scholarly Works (8 results)

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  • Peer Reviewed
UC Santa Barbara Previously Published Works (2024)
Atmospheric rivers (ARs) reach High Mountain Asia (HMA) about 10 days per month during the winter and spring, resulting in about 20 mm day-1 of precipitation. However, a few events may exceed 100 mm day-1, providing most of the total winter precipitation and increasing the risk of precipitation-triggered landslides and flooding, particularly when the height of the height of the 0 ∘C isotherm, or freezing level is above-average. This study shows that from 1979 to 2015, integrated water vapor transport (IVT) during ARs that reach Western HMA has increased 16% while the freezing level has increased up to 35 m. HMA ARs that have an above-average freezing level result in 10-40% less frozen precipitation compared to ARs with a below-average freezing level. To evaluate the importance of these trends in the characteristics of ARs, we investigate mesoscale processes leading to orographic precipitation using Advanced Weather Research and Forecasting (ARW-WRF) simulations at 6.7 km spatial resolution. We contrast two above- and below- average freezing level AR events with otherwise broadly similar characteristics and show that with a 50-600 m increase in freezing level, the above-average AR resulted in 10-70% less frozen precipitation than the below-average event. This study contributes to a better understanding of climate change-related impacts within HMAs hydrological cycle and the associated hazards to vulnerable communities living in the region.
    Cover page: Influence of the freezing level on atmospheric rivers in High Mountain Asia: WRF case studies of orographic precipitation extremes.
    • Article
    • Peer Reviewed
    San Francisco Estuary and Watershed Science, Volume 16, Issue 4 (2018)

    https://doi.org/10.15447/sfews.2018v16iss4art1

    California is regularly affected by floods and droughts, primarily as a result of too many or too few atmospheric rivers (ARs). This study analyzes a 2-decade-long hourly precipitation data set from 176 California weather stations and a 3-hourly AR chronology to report variations in rainfall events across California and their association with ARs. On average, 10–40 and 60–120 hours of rainfall in southern and northern California, respectively, are responsible for more than half of annual rainfall accumulations. Approximately 10% to 30% of annual precipitation at locations across the state is from only one large storm. On average, northern California receives 25 to 45 rainfall events annually (40% to 50% of which are AR-related). These events typically last longer and have higher event-precipitation totals than those in southern California. Northern California also receives more AR landfalls with longer durations and stronger Integrated Vapor Transport (IVT). On average, ARs contribute 79%, 76%, and 68% of extreme-rainfall accumulations (i.e., top 5% events annually) in the north coast, northern Sierra, and Transverse Ranges of southern California, respectively.

    The San Francisco Bay Area terrain gap in the California Coast Range allows more AR water vapor to reach inland over the Delta and Sacramento Valley, and thus influences precipitation in the Delta’s catchment. This is particularly important for extreme precipitation in the northern Sierra Nevada, including river basins above Oroville Dam and Shasta Dam.

    This study highlights differences between rainfall and AR characteristics in coastal versus inland northern California — differences that largely determine the regional geography of flood risks and water reliability. These analyses support water resource, flood, levee, wetland, and ecosystem management within the catchment of the San Francisco Estuary system by describing regional characteristics of ARs and their influence on rainfall on an hourly time-scale.

     

    • 1 supplemental PDF
    Cover page: Hourly Analyses of the Large Storms and Atmospheric Rivers that Provide Most of California’s Precipitation in Only 10 to 100 Hours per YearCreative Commons 'BY' version 4.0 license
    • Article
    • Peer Reviewed
    Applied Math & Comp Sci (2019)
      Cover page: Defining Uncertainties Through Comparison of Atmospheric River Tracking Methods Defining Uncertainties Through Comparison of Atmospheric River Tracking Methods
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2020)
        Cover page: Increases in Future AR Count and Size: Overview of the ARTMIP Tier 2 CMIP5/6 Experiment
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2018)
        Abstract. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the MERRA-2 reanalysis from January 1980 to June of 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month proof of concept trial run designed to illustrate the utility and feasibility of the ARTMIP project.
          Cover page: Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Project Goals and Experimental DesignCreative Commons 'BY' version 4.0 license
          • Article
          • Peer Reviewed
          UC Irvine Previously Published Works (2018)
            Cover page: Supplementary material to "Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Project Goals and Experimental Design"Creative Commons 'BY' version 4.0 license
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2019)
            Atmospheric rivers (ARs) are now widely known for their association with high-impact weather events and long-term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR-related metrics based on 20+ different AR identification and tracking methods applied to Modern-Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria-based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all-method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR-related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR-related research to consider.
              Cover page: The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River ClimatologyCreative Commons 'BY' version 4.0 license
              • Article
              • Peer Reviewed
              UC Irvine Previously Published Works (2018)
              The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month proof-of-concept trial run designed to illustrate the utility and feasibility of the ARTMIP project.
                Cover page: Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design
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