Landfalling Atmospheric Rivers, the Sierra Barrier Jet, and Extreme Daily Precipitation in Northern California’s Upper Sacramento River Watershed

2016 ◽  
Vol 17 (7) ◽  
pp. 1905-1914 ◽  
Author(s):  
F. Martin Ralph ◽  
Jason M. Cordeira ◽  
Paul J. Neiman ◽  
Mimi Hughes
Keyword(s):  
Sierra Nevada ◽  
Complex Terrain ◽  
Detection Method ◽  
Daily Precipitation ◽  
Sacramento River ◽  
Orographic Precipitation ◽  
Atmospheric Rivers ◽  
River Watershed ◽  
Rain Gauges ◽  
Major Floods

Abstract The upper Sacramento River watershed is vital to California’s water supply and is susceptible to major floods. Orographic precipitation in this complex terrain involves both atmospheric rivers (ARs) and the Sierra barrier jet (SBJ). The south-southeasterly SBJ induces orographic precipitation along south-facing slopes in the Mt. Shasta–Trinity Alps, whereas landfalling ARs ascend up and over the statically stable SBJ and induce orographic precipitation along west-facing slopes in the northern Sierra Nevada. This paper explores the occurrence of extreme daily precipitation (EDP) in this region in association with landfalling ARs and the SBJ. The 50 wettest days (i.e., days with EDP) for water years (WYs) 2002–11 based on the average of daily precipitation from eight rain gauges known as the Northern Sierra 8-Station Index (NS8I) are compared to dates from an SSM/I satellite-based landfalling AR-detection method and dates with SBJ events identified from nearby wind profiler data. These 50 days with EDP accounted for 20% of all precipitation during the 10-WY period, or 5 days with EDP per year on average account for one-fifth of WY precipitation. In summary, 46 of 50 (92%) days with EDP are associated with landfalling ARs on either the day before or the day of precipitation, whereas 45 of 50 (90%) days with EDP are associated with SBJ conditions on the day of EDP. Forty-one of 50 (82%) days with EDP are associated with both a landfalling AR and an SBJ. The top 10 days with EDP were all associated with both a landfalling AR and an SBJ.

A Real-Time Algorithm for Merging Radar QPEs with Rain Gauge Observations and Orographic Precipitation Climatology

2014 ◽  
Vol 15 (5) ◽  
pp. 1794-1809 ◽  
Author(s):  
Jian Zhang ◽  
Youcun Qi ◽  
Carrie Langston ◽  
Brian Kaney ◽  
Kenneth Howard
Keyword(s):  
High Resolution ◽  
Complex Terrain ◽  
The United States ◽  
Flash Floods ◽  
Rain Gauge ◽  
Convective Precipitation ◽  
Orographic Precipitation ◽  
Indirect Measure ◽  
Rain Gauges ◽  
Precipitation Climatology

Abstract High-resolution, accurate quantitative precipitation estimation (QPE) is critical for monitoring and prediction of flash floods and is one of the most important drivers for hydrological forecasts. Rain gauges provide a direct measure of precipitation at a point, which is generally more accurate than remotely sensed observations from radar and satellite. However, high-quality, accurate precipitation gauges are expensive to maintain, and their distributions are too sparse to capture gradients of convective precipitation that may produce flash floods. Weather radars provide precipitation observations with significantly higher resolutions than rain gauge networks, although the radar reflectivity is an indirect measure of precipitation and radar-derived QPEs are subject to errors in reflectivity–rain rate (Z–R) relationships. Further, radar observations are prone to blockages in complex terrain, which often result in a poor sampling of orographically enhanced precipitation. The current study aims at a synergistic approach to QPE by combining radar, rain gauge, and an orographic precipitation climatology. In the merged QPE, radar data depict high-resolution spatial distributions of the precipitation and rain gauges provide accurate precipitation measurements that correct potential biases in the radar QPE. The climatology provides a high-resolution background of the spatial precipitation distribution in the complex terrain where radar coverage is limited or nonexistent. The merging algorithm was tested on heavy precipitation events in different areas of the United States and provided a superior QPE to the individual components. The new QPE algorithm is fully automated and can be easily implemented in an operational system.

scholarly journals Hydrologic sensitivity of the Upper San Joaquin River Watershed in California to climate change scenarios

2012 ◽  
Vol 44 (4) ◽  
pp. 723-736 ◽  
Author(s):  
Zili He ◽  
Zhi Wang ◽  
C. John Suen ◽  
Xiaoyi Ma
Keyword(s):  
Climate Change ◽  
Sierra Nevada ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Hydrological Simulation ◽  
River Watershed ◽  
System Sensitivity ◽  
Hspf Model ◽  
San Joaquin River ◽  
San Joaquin River Watershed

To examine the hydrological system sensitivity of the southern Sierra Nevada Mountains of California to climate change scenarios (CCS), five headwater basins in the snow-dominated Upper San Joaquin River Watershed (USJRW) were selected for hydrologic simulations using the Hydrological Simulation Program-Fortran (HSPF) model. A pre-specified set of CCS as projected by the Intergovernmental Panel on Climate Change (IPCC) were adopted as inputs for the hydrologic analysis. These scenarios include temperature increases between 1.5 and 4.5 °C and precipitation variation between 80 and 120% of the baseline conditions. The HSPF model was calibrated and validated with measured historical data. It was then used to simulate the hydrologic responses of the watershed to the projected CCS. Results indicate that the streamflow of USJRW is sensitive to the projected climate change. The total volume of annual streamflow would vary between −41 and +16% compared to the baseline years (1970–1990). Even if the precipitation remains unchanged, the total annual flow would still decrease by 8–23% due to temperature increases. A larger portion of the streamflow would occur earlier in the water year by 15–46 days due to the temperature increases, causing higher seasonal variability of streamflow.

scholarly journals Influence of Atmospheric Rivers on Mountain Snowpack in the Western United States

2018 ◽  
Vol 31 (24) ◽  
pp. 9921-9940 ◽  
Author(s):  
N. Goldenson ◽  
L. R. Leung ◽  
C. M. Bitz ◽  
E. Blanchard-Wrigglesworth
Keyword(s):  
United States ◽  
Sierra Nevada ◽  
Snow Water Equivalent ◽  
Region Of Interest ◽  
Internal Variability ◽  
Western United States ◽  
Historical Period ◽  
Atmospheric Rivers ◽  
Atmospheric River ◽  
The Impact

In the coastal mountains of western North America, most extreme precipitation is associated with atmospheric rivers (ARs), narrow bands of moisture originating in the tropics. Here we quantify how interannual variability in atmospheric rivers influences snowpack in the western United States in observations and a model. We simulate the historical climate with the Model for Prediction Across Scales (MPAS) with physics from the Community Atmosphere Model, version 5 [CAM5 (MPAS-CAM5)], using prescribed sea surface temperatures. In the global variable-resolution domain, regional refinement (at ~30 km) is applied to our region of interest and upwind over the northeast Pacific. To better characterize internal variability, we conduct simulations with three ensemble members over 30 years of the historical period. In the Cascade Range, with some exceptions, winters with more atmospheric river days are associated with less snowpack. In California’s Sierra Nevada, winters with more ARs are associated with greater snowpack. The slope of the linear regression of observed snow water equivalent (SWE) on reanalysis-based AR count has the same sign as that arrived at using the model, but is statistically significant in observations only for California. In spring, internal variance plays an important role in determining whether atmospheric river days appear to be associated with greater or less snowpack. The cumulative (winter through spring) number of atmospheric river days, on the other hand, has a relationship with spring snowpack, which is consistent across ensemble members. Thus, the impact of atmospheric rivers on winter snowpack has a greater influence on spring snowpack than spring atmospheric rivers in the model for both regions and in California consistently in observations.

scholarly journals Skill of Rain–Snow Level Forecasts for Landfalling Atmospheric Rivers: A Multimodel Assessment Using California’s Network of Vertically Profiling Radars

2020 ◽  
Vol 21 (4) ◽  
pp. 751-771 ◽  
Author(s):  
Brian Henn ◽  
Rachel Weihs ◽  
Andrew C. Martin ◽  
F. Martin Ralph ◽  
Tashiana Osborne
Keyword(s):  
Sierra Nevada ◽  
Lead Time ◽  
Flood Hazard ◽  
Critical Factor ◽  
Forecast Model ◽  
Lead Times ◽  
Grid Spacing ◽  
Atmospheric Rivers ◽  
Operational Forecasts ◽  
Resources Planning

AbstractThe partitioning of rain and snow during atmospheric river (AR) storms is a critical factor in flood forecasting, water resources planning, and reservoir operations. Forecasts of atmospheric rain–snow levels from December 2016 to March 2017, a period of active AR landfalls, are evaluated using 19 profiling radars in California. Three forecast model products are assessed: a global forecast model downscaled to 3-km grid spacing, 4-km river forecast center operational forecasts, and 50-km global ensemble reforecasts. Model forecasts of the rain–snow level are compared with observations of rain–snow melting-level brightband heights. Models produce mean bias magnitudes of less than 200 m across a range of forecast lead times. Error magnitudes increase with lead time and are similar between models, averaging 342 m for lead times of 24 h or less and growing to 700–800 m for lead times of greater than 144 h. Observed extremes in the rain–snow level are underestimated, particularly for warmer events, and the magnitude of errors increases with rain–snow level. Storms with high rain–snow levels are correlated with larger observed precipitation rates in Sierra Nevada watersheds. Flood risk increases with rain–snow levels, not only because a greater fraction of the watershed receives rain, but also because warmer storms carry greater water vapor and thus can produce heavier precipitation. The uncertainty of flood forecasts grows nonlinearly with the rain–snow level for these reasons as well. High rain–snow level ARs are a major flood hazard in California and are projected to be more prevalent with climate warming.

The Landfall and Inland Penetration of a Flood-Producing Atmospheric River in Arizona. Part I: Observed Synoptic-Scale, Orographic, and Hydrometeorological Characteristics

2013 ◽  
Vol 14 (2) ◽  
pp. 460-484 ◽  
Author(s):  
Paul J. Neiman ◽  
F. Martin Ralph ◽  
Benjamin J. Moore ◽  
Mimi Hughes ◽  
Kelly M. Mahoney ◽  
...  
Keyword(s):  
Sierra Nevada ◽  
Heat Fluxes ◽  
Back Trajectory ◽  
High Mountain ◽  
Wind Profiler ◽  
Plan View ◽  
Atmospheric Rivers ◽  
Tropical Water ◽  
Northeastern Pacific ◽  
The Impact

Abstract Atmospheric rivers (ARs) are a dominant mechanism for generating intense wintertime precipitation along the U.S. West Coast. While studies over the past 10 years have explored the impact of ARs in, and west of, California’s Sierra Nevada and the Pacific Northwest’s Cascade Mountains, their influence on the weather across the intermountain west remains an open question. This study utilizes gridded atmospheric datasets, satellite imagery, rawinsonde soundings, a 449-MHz wind profiler and global positioning system (GPS) receiver, and operational hydrometeorological observing networks to explore the dynamics and inland impacts of a landfalling, flood-producing AR across Arizona in January 2010. Plan-view, cross-section, and back-trajectory analyses quantify the synoptic and mesoscale forcing that led to widespread precipitation across the state. The analyses show that a strong AR formed in the lower midlatitudes over the northeastern Pacific Ocean via frontogenetic processes and sea surface latent-heat fluxes but without tapping into the adjacent tropical water vapor reservoir to the south. The wind profiler, GPS, and rawinsonde observations document strong orographic forcing in a moist neutral environment within the AR that led to extreme, orographically enhanced precipitation. The AR was oriented nearly orthogonal to the Mogollon Rim, a major escarpment crossing much of central Arizona, and was positioned between the high mountain ranges of northern Mexico. High melting levels during the heaviest precipitation contributed to region-wide flooding, while the high-altitude snowpack increased substantially. The characteristics of the AR that impacted Arizona in January 2010, and the resulting heavy orographic precipitation, are comparable to those of landfalling ARs and their impacts along the west coasts of midlatitude continents.

Selection and application of a rainbow trout toxicity testing procedure for screening Sacramento River Watershed, California samples

2008 ◽  
Vol 150 (1-4) ◽  
pp. 333-349
Author(s):  
Jeffrey L. Miller ◽  
Michael J. Miller ◽  
Victor de Vlaming ◽  
Karen Larsen ◽  
Edward Smith ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Toxicity Testing ◽  
Testing Procedure ◽  
Sacramento River ◽  
River Watershed

Uncertainty in different precipitation products in the case of two atmospheric river events

2021 ◽  
Author(s):  
Alexandre M. Ramos ◽  
Rémy Roca ◽  
Pedro M.M. Soares ◽  
Anna M. Wilson ◽  
Ricardo M. Trigo ◽  
...  
Keyword(s):  
North Atlantic ◽  
Daily Precipitation ◽  
Climate Extremes ◽  
Research Programme ◽  
Late Glacial ◽  
Atmospheric Rivers ◽  
Atmospheric River ◽  
Western Us ◽  
Weather And Climate ◽  
The Tropics

<p>One of the World Climate Research Programme Grand Challenges is to evaluate whether existing observations are enough to underpin the assessment of weather and climate extremes. In this study, we focus on extreme associated with Atmospheric Rivers (ARs). ARs are characterized by intense moisture transport usually from the tropics to the extra-tropics. They can either be beneficial, providing critical water supply, or hazardous, when excessive precipitation accumulation leads to floods. Here, we examine the uncertainty in gridded precipitation products included in the Frequent Rainfall Observations on GridS (FROGS) database during two atmospheric river events in distinct Mediterranean climates: one in California, USA, and another in Portugal. FROGS is composed of gridded daily-precipitation products on a common 1∘×1∘ grid to facilitate intercomparison and assessment exercises. The database includes satellite, ground-based and reanalysis products. Results show that the precipitation products based on satellite data, individually or combined with other products, perform least well in capturing daily precipitation totals over land during both cases studied here. The reanalysis and the gauge-based products show the best agreement with local ground stations. As expected, there is an overall underestimation of precipitation by the different products. For the Portuguese AR, the multi-product ensembles reveal mean absolute percentage errors between -25% and -60%. For the Western US case, the range is from -60% to -100 %. </p><p> </p><p>Acknowledgments</p><p>The financial support for this work was possible through the following FCT project: HOLMODRIVE—North Atlantic Atmospheric Patterns Influence on Western Iberia Climate: From the Late Glacial to the Present (PTDC/CTA-GEO/29029/2017). A.M. Ramos was supported by the Scientific Employment Stimulus 2017 from Fundação para a Ciência e a Tecnologia (FCT, CEECIND/00027/2017). </p><p> </p>

Tracking the storage and dissipation of atmospheric river storm water in the Russian River watershed using GPS elastic displacements

2021 ◽  
Author(s):  
Ellen Knappe ◽  
Adrian Borsa ◽  
Hilary Martens ◽  
Donald Argus ◽  
Zachary Hoylman ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Storage ◽  
Heavy Precipitation ◽  
Storm Water ◽  
Hydrologic Models ◽  
Effective Technique ◽  
Atmospheric Rivers ◽  
River Watershed ◽  
Russian River ◽  
Flooding Events

<p>GPS is emerging as an effective technique to estimate changes in total water storage at Earth's surface.  In California's mountains, GPS indicates that more subsurface storage is lost during drought and gained during years of heavy precipitation than predicted by hydrology models [Argus et al. 2017].  Atmospheric rivers provide a majority of the annual precipitation in coastal environments across North America. The Russian River watershed is often affected by these large storms, which can produce extensive flooding events. In this study, we estimate changes in water storage for the 2017 water year (October 2016 – September 2017), a historically wet year in California, in which more than 20 atmospheric rivers impacted the Russian River watershed. Using GPS displacements, we quantify the water gained during higher intensity atmospheric rivers. We further resolve the time it takes for the storm water to dissipate: that is, we distinguish between water that runs off into rivers and water that is stored in the ground as soil moisture. Finally, we investigate the empirical relationships between GPS displacement and precipitation, evapotranspiration, and soil moisture estimates with the aim of improving constraints to hydrologic models.</p>

Modulation of Atmospheric Rivers by Mesoscale Frontal Waves and Latent Heating: Comparison of Two U.S. West Coast Events

2021 ◽  
Author(s):  
Allison C. Michaelis ◽  
Andrew C. Martin ◽  
Meredith A. Fish ◽  
Chad W. Hecht ◽  
F. Martin Ralph
Keyword(s):  
Moisture Transport ◽  
Initial Conditions ◽  
Vapor Transport ◽  
Latent Heating ◽  
Dynamic Precipitation ◽  
Atmospheric Rivers ◽  
River Watershed ◽  
Diabatic Processes ◽  
Low Altitude ◽  
Russian River

AbstractA complex and underexplored relationship exists between atmospheric rivers (ARs) and mesoscale frontal waves (MFWs). The present study further explores and quantifies the importance of diabatic processes to MFW development and the AR-MFW interaction by simulating two ARs impacting Northern California’s flood-vulnerable Russian River watershed using the Model for Prediction Across Scales-Atmosphere (MPAS-A) with and without the effects of latent heating. Despite the storms’ contrasting characteristics, diabatic processes within the system were critical to the development of MFWs, the timing and magnitude of integrated vapor transport (IVT), and precipitation impacts over the Russian River watershed in both cases. Low-altitude circulations and lower-tropospheric moisture content in and around the MFWs are considerably reduced without latent heating, contributing to a decrease in moisture transport, moisture convergence, and IVT. Differences in IVT are not consistently dynamic (i.e., wind-driven) or thermodynamic (i.e., moisture-driven), but instead vary by case and by time throughout each event. For one event, AR conditions over the watershed persisted for 6 h less and the peak IVT occurred 6 h earlier and was reduced by ~17%; weaker orographic and dynamic precipitation forcings reduced precipitation totals by ~64%. Similarly, turning off latent heating shortened the second event by 24 h and reduced precipitation totals by ~49%; the maximum IVT over the watershed was weakened by ~42% and delayed by 18 h. Thus, sufficient representation of diabatic processes, and by inference, water vapor initial conditions, is critical for resolving MFWs, their feedbacks on AR evolution, and associated precipitation forecasts on watershed scales.

Sign in / Sign up

Export Citation Format

Share Document