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

摘要

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- 95(th) percentile), very heavy (95- 99(th) percentile), and extreme (= 99(th) 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.