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Accurate estimation of the potential "upper limit" for extreme precipitation is critical for dam safety and water resources management, as dam failures pose significant risks to life and property. Methods used to estimate the theoretical upper limit of precipitation are often outdated and in need of updating. The rarity of extreme events means that old storms with limited observational data are often used to define the upper bound of precipitation. Observations of many important old storms are limited in spatial and temporal coverage, and sometimes of dubious quality. This reduces confidence in flood hazard assessments used in dam safety evaluations and leads to unknown or uncertain societal risk. This paper describes a method for generating and applying ensembles of high-resolution, state-of-the-art numerical model simulations of historical past extreme precipitation events to meet contemporary stakeholder needs. The method was designed as part of a research-to-application-focused partnership project to update state dam safety rules in Colorado and New Mexico. The results demonstrated multiple stakeholder and user benefits that were applied directly into storm analyses utilized for extreme rainfall estimation, and diagnostics were developed and ultimately used to update Colorado state dam safety rules, officially passed in January 2020. We discuss how what started as a prototype research foray to meet a specific user need may ultimately inform wider adoption of numerical simulations for water resources risk assessment, and how the historical event downscaling method performed offers near-term, implementable improvements to current dam safety flood risk estimates that can better serve society today. [ABSTRACT FROM AUTHOR]

The NOAA National Water Model (NWM) became operational in August 2016, producing the first ever real-time, distributed, continuous set of hydrologic forecasts over the continental United States (CONUS). This project uses integrated hydrometeorological assessment methods to investigate the utility of the NWM to predict catastrophic flooding associated with an extreme rainfall event that occurred in Ellicott City, Maryland, on 27–28 May 2018. Short-range forecasts (0–18-h lead time) from the NWM version 1.2 are explored, focusing on the quantitative precipitation forecast (QPF) forcing from the High-Resolution Rapid Refresh (HRRR) model and the corresponding NWM streamflow forecast. A comprehensive assessment of multiscale hydrometeorological processes are considered using a combination of object-based, grid-based, and hydrologic point-based verification. Results highlight the benefits and risks of using a distributed hydrologic modeling tool such as the NWM to connect operational CONUS-scale atmospheric forcings to local impact predictions. For the Ellicott City event, reasonably skillful QPF in several HRRR model forecast cycles produced NWM streamflow forecasts in the small Ellicott City basin that were suggestive of flash flood potential. In larger surrounding basins, the NWM streamflow response was more complex, and errors were found to be governed by both hydrologic process representation, as well as forcing errors. The integrated, hydrometeorological multiscale analysis method demonstrated here guides both research and ongoing model development efforts, along with providing user education and engagement to ultimately engender improved flash flood prediction. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) are well-known producers of precipitation along the U.S. West Coast. Depending on their intensity, orientation, and location of landfall, some ARs penetrate inland and cause heavy rainfall and flooding hundreds of miles from the coast. Climate change is projected to potentially alter a variety of AR characteristics and impacts. This study examines potential future changes in moisture transport and precipitation intensity, type, and distribution for a high-impact landfalling AR event in the U.S. Pacific Northwest using an ensemble of high-resolution numerical simulations produced under projected future thermodynamic changes. Results indicate increased total precipitation in all future simulations, although there is considerable model spread in both domain-averaged and localized inland precipitation totals. Notable precipitation enhancements across inland locations such as Idaho’s Sawtooth Mountain Range are present in four out of six future simulations. The most marked inland precipitation increases are shown to occur by way of stronger and deeper moisture transport that more effectively crosses Oregon’s Coastal and Cascade mountain ranges, essentially “spilling over” into the Snake River Valley and fueling orographic precipitation in the Sawtooth Mountains. Moisture transport enhancements are shown to have both thermodynamic and dynamic contributions, with both enhanced absolute environmental moisture and localized lower- and midlevel dynamics contributing to amplified inland moisture penetration. Precipitation that fell as snow in the present-day simulation becomes rain in the future simulations for many mid- and high-elevation locations, suggesting potential for enhanced flood risk for these regions in future climate instances of similar events. [ABSTRACT FROM AUTHOR]

A series of precipitation events impacted the Pacific Northwest during the first two weeks of November 2006. This sequence was punctuated by a particularly potent inland-penetrating atmospheric river (AR) that produced record-breaking precipitation across the region during 5-7 November. The precipitation caused destructive flooding as far inland as Montana's Glacier National Park, 800 km from the Pacific Ocean. This study investigates the inland penetration of moisture during the event using a 4-1.33-km grid spacing configuration of the Weather Research and Forecasting (WRF) modeling system. A high-resolution simulation allowed an analysis of interactions between the strong AR and terrain features such as the Cascade Mountains and the Columbia River Gorge (CR Gorge). Moisture transport in the vicinity of the Cascades is assessed using various metrics. The most efficient pathway for moisture penetration was through the gap (i.e., CR Gap) between Mt. Adams and Mt. Hood, which includes the CR Gorge. While the CR Gap is a path of least resistance through the Cascades, most of the total moisture transport that survived transit past the Cascades overtopped the mountain barrier itself. This is due to the disparity between the length of the ridge (~800 km) and relatively narrow width of the CR Gap (~93 km). Moisture transport reductions were larger across the Washington Cascades and the southern-central Oregon Cascades than through the CR Gap. During the simulation, drying ratios through the CR Gap (9.3%) were notably less than over adjacent terrain (19.6%-30.6%). Drying ratios decreased as moisture transport intensity increased. [ABSTRACT FROM AUTHOR]

Model simulations of the 2013 Colorado Front Range floods are performed using 4-km horizontal grid spacing to evaluate the impact of using explicit convection (EC) versus parameterized convection (CP) in the model convective physics 'gray zone.' Significant differences in heavy precipitation forecasts are found across multiple regions in which heavy rain and high-impact flooding occurred. The relative contribution of CP-generated precipitation to total precipitation suggests that greater CP scheme activity in areas upstream of the Front Range flooding may have led to significant downstream model error. Heavy convective precipitation simulated by the Kain-Fritsch CP scheme in particular led to an alteration of the low-level moisture flux and moisture transport fields that ultimately prevented the generation of heavy precipitation in downstream areas as observed. An updated, scale-aware version of the Kain-Fritsch scheme is also tested, and decreased model errors both up- and downstream suggest that scale-aware updates yield improvements in the simulation of this event. Comparisons among multiple CP schemes demonstrate that there are model convective physics gray zone considerations that significantly impact the simulation of extreme rainfall in this event. [ABSTRACT FROM AUTHOR]

An analysis of atmospheric rivers (ARs) as defined by an automated AR detection tool based on integrated water vapor transport (IVT) and the connection to heavy precipitation in the southeast United States (SEUS) is performed. Climatological water vapor and water vapor transport fields are compared between the U.S. West Coast (WCUS) and the SEUS, highlighting stronger seasonal variation in integrated water vapor in the SEUS and stronger seasonal variation in IVT in the WCUS. The climatological analysis suggests that IVT values above ~500 kg m−1 s−1 (as incorporated into an objective identification tool such as the AR detection tool used here) may serve as a sensible threshold for defining ARs in the SEUS. Atmospheric river impacts on heavy precipitation in the SEUS are shown to vary on an annual cycle, and a connection between ARs and heavy precipitation during the nonsummer months is demonstrated. When identified ARs are matched to heavy precipitation days (>100 mm day−1), an average match rate of ~41% is found. Results suggest that some aspects of an AR identification framework in the SEUS may offer benefit in forecasting heavy precipitation, particularly at medium- to longer-range forecast lead times. However, the relatively high frequency of SEUS heavy precipitation cases in which an AR is not identified necessitates additional careful consideration and incorporation of other critical aspects of heavy precipitation environments such that significant predictive skill might eventually result. [ABSTRACT FROM AUTHOR]