Establishing a Numerical Modeling Framework for Hydrologic Engineering Analyses of Extreme Storm Events
Publication: Journal of Hydrologic Engineering
Volume 22, Issue 8
Abstract
In this study, a numerical modeling framework for simulating extreme storm events was established using the Weather Research and Forecasting (WRF) model. Such a framework is necessary for the derivation of engineering parameters such as probable maximum precipitation that are the cornerstone of large water-management infrastructure design. Here, this framework was built based on a heavy storm that occurred in Nashville, Tennessee (U.S.), in 2010, and verified using two other extreme storms. To achieve the optimal setup, several combinations of model resolutions, initial/boundary conditions (IC/BC), cloud microphysics, and cumulus parameterization schemes were evaluated using multiple metrics of precipitation characteristics. The evaluation suggests that WRF is most sensitive to the IC/BC option. Simulation generally benefits from finer resolutions up to 5 km. At the 15 km level, NCEP2 IC/BC produces better results, whereas NAM IC/BC performs best at the 5 km level. The recommended model configuration from this study is: NAM or NCEP2 IC/BC (depending on data availability), 15 km or 15–5 km nested grids, Morrison microphysics, and Kain-Fritsch cumulus schemes. Validation of the optimal framework suggests that these options are good starting choices for modeling extreme events similar to the test cases. This optimal framework is proposed in response to emerging engineering demands of extreme storm event forecasting and analyses for design, operations, and risk assessment of large water infrastructures.
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Acknowledgments
This study is motivated by an ASCE Task Committee on “Infrastructure Impacts of Landscape-Driven Weather Change” chaired by the second author. Therein, model-based PMPs are currently being explored for modernizing current engineering practice of PMPs based on storms many decades old. The first author was supported by NASA grant NNAX15AC63G. Dr. Ruby Leung acknowledges the support from the U.S. Department of Energy Office of Science Biological and Environmental Research as part of the Regional and Global Climate Modeling Program. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under Contract DE-AC05-76RLO1830.
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Published In
Journal of Hydrologic Engineering
Volume 22 • Issue 8 • August 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jun 4, 2016
Accepted: Jan 19, 2017
Published online: Apr 11, 2017
Published in print: Aug 1, 2017
Discussion open until: Sep 11, 2017
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