Probable Maximum Precipitation in the U.S. Pacific Northwest in a Changing Climate

Chen, Xiaodong; Hossain, Faisal; Leung, L. Ruby

doi:10.1002/2017WR021094

Title: Probable Maximum Precipitation in the U.S. Pacific Northwest in a Changing Climate

Journal Article · Fri Nov 03 00:00:00 EDT 2017 · Water Resources Research

DOI:https://doi.org/10.1002/2017WR021094· OSTI ID:1439698

^[1];

^[2]

Univ. of Washington, Seattle, WA (United States). Dept. of Civil and Environmental Engineering
Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Atmospheric Science and Global Change Div. (ASGC)

The safety of large and aging water infrastructures is gaining attention in water management given the accelerated rate of change in landscape, climate and society. In current engineering practice, such safety is ensured by the design of infrastructure for the Probable Maximum Precipitation (PMP). Recently, several physics-based numerical modeling approaches have been proposed to modernize the conventional and ad hoc PMP estimation approach. However, the underlying physics has not been investigated and thus differing PMP estimates are obtained without clarity on their interpretation. In this study, we present a hybrid approach that takes advantage of both traditional engineering wisdom and modern climate science to estimate PMP for current and future climate conditions. The traditional PMP approach is improved and applied to outputs from an ensemble of five CMIP5 models. This hybrid approach is applied in the Pacific Northwest (PNW) to produce ensemble PMP estimation for the historical (1970-2016) and future (2050-2099) time periods. The new historical PMP estimates are verified by comparing them with the traditional estimates. PMP in the PNW will increase by 50% of the current level by 2099 under the RCP8.5 scenario. Most of the increase is caused by warming, which mainly affects moisture availability, with minor contributions from changes in storm efficiency in the future. Moist track change tends to reduce the future PMP. Compared with extreme precipitation, ensemble PMP exhibits higher internal variation. Thus high-quality data of both precipitation and related meteorological fields (temperature, wind fields) are required to reduce uncertainties in the ensemble PMP estimates.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1439698

Alternate ID(s):: OSTI ID: 1410356

Report Number(s):: PNNL-SA-126184; KP1703010

Journal Information:: Water Resources Research, Vol. 53, Issue 11; ISSN 0043-1397

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 25 works

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