Abstract
In recent years, there has been an increase in interest in estimating probable maximum precipitation (PMP) by numerical weather model (NWM)-based precipitation maximization methods, mainly, the moisture optimization method, storm transposition method, and their combination. This study addresses a quantitative comparison of the effectiveness of each precipitation maximization method regarding the increase in precipitation depths and a discussion on their functions for maximizing precipitation depths. To achieve such a comparison, this study conducted a numerical experiment using the moisture optimization method, which proportionally increases relative humidity using the integrated water vapor transport criterion, and the storm transposition method, which geospatially shifts atmospheric boundary conditions in the weather research and forecasting (WRF) model to maximize atmospheric river (AR)-induced precipitation depths over the Columbia River Basin. Our findings suggest that the storm transposition method should also be considered an essential method in the NWM-based precipitation maximization rather than relying solely on optimizing atmospheric moisture. This study also found that even for ARs with historically small amounts of precipitation over a specified basin, it is possible to increase precipitation depths significantly over the basin by using the storm transposition method. This finding implies that, for maximizing precipitation using the storm transposition method, it is important to select storms that historically did not directly hit the basin but were located around the basin as well, unlike the conventional approach of selecting storms solely based on precipitation depth over the basin. This finding also suggests that the storm transposition method is essential, particularly for estimating long-duration PMP that may cover a whole season, given the contribution of precipitation increase in each single storm event to the snowpack accumulation and reservoir storage for a long duration. Lastly, this study has shown that including the transposition method together with the moisture optimization method can increase precipitation amounts and give a higher upper bound for NWM-based precipitation maximization, especially in AR-dominated regions.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions.
Acknowledgments
This study was supported by US Army Corps of Engineers (USACE) Grant 3-20B35-Department of Army Engi-W912HZ-17-2-0001. The CFSR dataset (ds093.0, doi:10.5065/D69K487J for 1979 to 2010, ds094.0, doi:10.5065/D61C1TXF for 2011 to present), and the 20CRv2c dataset (ds131.2, doi:10.5065/D6N877TW) were obtained through the NCAR/UCAR Research Data Archive. The PRISM dataset was obtained from the PRISM Climate Group (http://www.prism.oregonstate.edu/).
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Published In
Journal of Hydrologic Engineering
Volume 28 • Issue 1 • January 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Mar 11, 2022
Accepted: Aug 26, 2022
Published online: Oct 31, 2022
Published in print: Jan 1, 2023
Discussion open until: Mar 31, 2023
ASCE Technical Topics:
- Climates
- Comparative studies
- Engineering fundamentals
- Environmental engineering
- Hydrologic engineering
- Hydrology
- Meteorology
- Methodology (by type)
- Models (by type)
- Moisture
- Numerical methods
- Numerical models
- Optimization models
- Precipitation
- Research methods (by type)
- Retention basins
- Stilling basins
- Storms
- Water and water resources
- Water treatment
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Cited by
- Yusuke Hiraga, Yoshihiko Iseri, Michael D. Warner, Angela M. Duren, John F. England, M. Levent Kavvas, Response of Precipitation Increases to Changes in Atmospheric Moisture and Its Flux in the Columbia River Basin: WRF Model–Based Precipitation Maximization for PMP Studies, Journal of Hydrologic Engineering, 10.1061/JHYEFF.HEENG-6169, 29, 3, (2024).