Detecting change in precipitation indices using observed (1977-2016) and modeled future climate data in Portland, Oregon, USA

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.

Automated summary

This study examines how temporal resolution affects trend detection in precipitation patterns in Portland, Oregon. By using climate indices and Mann-Kendall monotonic testing, the researchers found that annual indices suggest an intensifying hydrologic cycle in the future, while monthly summaries can reveal more apparent indicators of this trend in historical records.