Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
It is well-known in the dam safety community that many of the methods and data used to estimate extreme rainfall amounts and manage hydrologic risk are outdated and in need of improvement. Community-wide acceptance of previous improvement efforts have been challenged not only by the complexity of the scientific and engineering problems at-hand, but also by difficulties in communicating the complex methods proposed by various parts of the meteorology, hydrology, and engineering communities. The need to both carefully evaluate new approaches and identify solutions with the most potential for acceptance beyond a single regional study has led the states of Colorado and New Mexico to engage a body of scientists and engineers in an innovative “ensemble approach” to updating extreme precipitation estimates. NOAA is at the forefront of one of three technical approaches that make up the “ensemble study”; the three approaches are conducted concurrently and in collaboration with each other. One approach is the conventional deterministic, “storm-based” method, another is a risk-based regional precipitation frequency estimation tool, and the third is an experimental approach utilizing NOAA’s state-of-the-art High Resolution Rapid Refresh (HRRR) physically-based dynamical weather prediction model. The goal of the overall project is to use the individual strengths of these different methods to define an updated and broadly acceptable state of the practice for evaluation and design of dam spillways.
This talk will highlight the NOAA research and NOAA’s role in the overarching goal to better understand and characterize extreme precipitation estimation uncertainty. The research led by NOAA explores a novel high-resolution dataset and post-processing techniques using a super-ensemble of hourly forecasts from the HRRR model. We also investigate how this rich dataset may be combined with statistical methods to optimally cast the data in probabilistic frameworks. NOAA expertise in the physical processes that drive extreme precipitation is further employed to develop careful testing and improved understanding of the limitations of older estimation methods and assumptions.
We will provide examples of how the various methods employed in the study’s ensemble approach may be used in concert with one another, as well as speak to the challenges and rewards of interdisciplinary collaboration. Finally, the presentation will address the implications of including climate change in future extreme precipitation estimation studies.
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