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Intensification scenarios in projected precipitation using stochastic weather generators: a case study of central Oklahoma

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Abstract

Previous studies have investigated the character and distribution of intense precipitation events across the United States. Increasing trends in intense, daily precipitation events at heavy (90–< 95th percentile), very heavy (95–< 99th percentile), and extreme (≥ 99th percentile) thresholds have all been reported. However, no previous studies have investigated the potential application of stochastic weather generators in determining future, site-specific distributions of such intense precipitation occurrences. In this study, two scenarios of future changes in intense precipitation for Weatherford, Oklahoma were examined through the use of a specific weather generator, SYNTOR, and by examination of heavy, very heavy, and extreme precipitation categories. All precipitation events across the three categories were increased multiple times by eight different percentages ranging from 5% to 75%, while precipitation events within the three categories were simultaneously increased by 14%, 20%, and 30%, respectively. Projected changes in the occurrence and categorical thresholds of intense precipitation events, as well as total monthly and annual precipitation and wet-dry transition probabilities, were assessed. The findings of this study show that projected increases in intense precipitation ranging from 5% to 40% are plausible and within the margin of error, based on the application of the two intensification scenarios to the synthetically generated weather data. Overall, the precipitation intensification scenarios markedly impacted estimates of intense precipitation, as well as average annual and monthly precipitation totals, but did not markedly impact the temporal distribution of precipitation annually or across seasons, nor the transition probabilities of projected precipitation between wet and dry days. Precipitation intensification scenarios can ultimately benefit in simulating erosion, runoff, and crop productivity responses to future precipitation distributions in agricultural watersheds of the Southern Great Plains as well as other locations.

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Acknowledgements

The authors thank Dr. Jurgen Garbrecht for his useful insights during the course of designing the study. The authors also thank National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) for making Weatherford precipitation data available for the study. Finally, the authors thank the anonymous reviewers for their critical reviews on an earlier version of the manuscript.

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Authors and Affiliations

  1. Columbia River Inter-Tribal Fish Commission (CRITFC), Portland, OR, 97232, USA

    Sanjeev Joshi

  2. Morris K. Udall and Stewart L. Udall Foundation, Tucson, AZ, 85701, USA

    David Brown

  3. ARS Grazinglands Research Laboratory, U.S. Department of Agriculture, El Reno, OK, 73036, USA

    Phil Busteed

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  1. Sanjeev Joshi
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  2. David Brown
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  3. Phil Busteed
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Contributions

S.J., D.B., and P.B. conceived and designed the study; S.J. completed data analysis and wrote the first draft of the manuscript; all authors revised and proofread the manuscript leading to its final submission to the journal.

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Correspondence to Sanjeev Joshi.

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Joshi, S., Brown, D. & Busteed, P. Intensification scenarios in projected precipitation using stochastic weather generators: a case study of central Oklahoma. Theor Appl Climatol 144, 1285–1296 (2021). https://doi.org/10.1007/s00704-021-03599-9

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