This study addresses how regional changes to precipitation may be identified by exploring the effect of temporal resolution on trend detection. Climate indices that summarize precipitation characteristics are used with Mann–Kendall monotonic testing to investigate precipitation trends in Portland, Oregon (OR) from 1977 to 2016. Observational records from rain gages are compared with downscaled global climate models to determine trends for the historic (1977–2005) and future (2006–2100) periods. Standard indices created by the Expert Team on Climate Change Detection and Indices (ETCCDI) are deployed. ETCCDI indices that summarize conditions at the annual level are generated alongside a limited number of ETCCDI indices summarized at the monthly level. For the future climate, the indices summarized at the annual level demonstrate trends indicative of an intensifying hydrologic cycle. The historical record depicted by annual indices does not show trends. The historical record is viewed differently by changing the indices to monthly summaries, which causes trend detection to increase and hallmark indicators of an intensifying hydrologic cycle to become apparent.

本研究通过探索时间分辨率对趋势检测的影响来解决如何识别降水的区域变化。总结降水特征的气候指数与 Mann-Kendall 单调测试一起使用，以研究 1977 年至 2016 年俄勒冈州波特兰 (OR) 的降水趋势。将雨量计的观测记录与缩小比例的全球气候模型进行比较，以确定历史 (1977 –2005) 和未来 (2006–2100) 时期。部署了由气候变化检测和指数专家组 (ETCCDI) 创建的标准指数。在年度级别汇总情况的 ETCCDI 指数与有限数量的按月级别汇总的 ETCCDI 指数一起生成。对于未来的气候，在年度一级总结的指数显示了表明水文循环加剧的趋势。年度指数所描绘的历史记录并未显示趋势。通过将指数更改为月度摘要，可以不同地看待历史记录，这会导致趋势检测增加，并使水文循环加剧的标志性指标变得明显。