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.

先前的研究已经调查了全美国强降水事件的特征和分布。在重（90- <95增加激烈，日降水量事件趋势^个百分点），非常重（95 - <99^个百分点），和极端（≥99^日百分位数）阈值均已报告。但是，以前没有研究调查随机天气生成器在确定此类强降水发生的未来，特定地点分布方面的潜在应用。在这项研究中，通过使用特定的天气生成器SYNTOR以及通过检查强，极重和极端降水类别，检查了俄克拉何马州韦瑟福德的强降水未来变化的两种情况。这三个类别中的所有降水事件均以5％至75％的八个不同百分比多次增加，而这三个类别中的降水事件分别分别增加了14％，20％和30％。预计发生的强降水事件的变化和绝对阈值，评估了每月和每年的总降水量和干湿过渡概率。这项研究的结果表明，根据两种强度情景对合成生成的天气数据的应用，预计强降水在5％至40％范围内的增长可能是合理的，并且在误差范围之内。总体而言，降水集约方案显着影响强降水的估计以及年平均和月平均降水总量，但不显着影响每年或整个季节的降水时间分布，也不影响预计的降水在干湿日之间的过渡概率。 。降水集约化方案最终可以在模拟侵蚀，径流，