Next Article in Journal
Climatic Variability and Land Use Change in Kamala Watershed, Sindhuli District, Nepal
Previous Article in Journal
A Global ETCCDI-Based Precipitation Climatology from Satellite and Rain Gauge Measurements
Previous Article in Special Issue
Watershed Response to Climate Change and Fire-Burns in the Upper Umatilla River Basin, USA
Article Menu
Issue 1 (March) cover image

Export Article

Open AccessArticle
Climate 2017, 5(1), 10;

Precipitation Intensity Trend Detection using Hourly and Daily Observations in Portland, Oregon

Department of Geography, Portland State University, Portland, OR 97201, USA
Author to whom correspondence should be addressed.
Academic Editors: Daniele Bocchiola, Claudio Cassardo and Guglielmina Diolaiuti
Received: 23 September 2016 / Revised: 5 February 2017 / Accepted: 13 February 2017 / Published: 18 February 2017
(This article belongs to the Special Issue Impact of Climate Change on Water Resources)
Full-Text   |   PDF [2083 KB, uploaded 22 February 2017]   |  


The intensity of precipitation is expected to increase in response to climate change, but the regions where this may occur are unclear. The lack of certainty from climate models warrants an examination of trends in observational records. However, the temporal resolution of records may affect the success of trend detection. Daily observations are often used, but may be too coarse to detect changes. Sub-daily records may improve detection, but their value is not yet quantified. Using daily and hourly records from 24 rain gages in Portland, Oregon (OR), trends in precipitation intensity and volume are examined for the period of 1999–2015. Daily intensity is measured using the Simple Daily Intensity Index, and this method is adapted to measure hourly scale intensity. Kendall’s tau, a non-parametric correlation coefficient, is used for monotonic trend detection. Field significance and tests for spatial autocorrelation using Moran’s Index are used to determine the significance of group hypothesis tests. Results indicate that the hourly data is superior in trend detection when compared with daily data; more trends are detected with hourly scale data at both the 5% and 10% significance levels. Hourly records showed a significant increase in 6 of 12 months, while daily records showed a significant increase in 4 of 12 months at the 10% significance level. At both scales increasing trends were concentrated in spring and summer months, while no winter trends were detected. Volume was shown to be increasing in most months experiencing increased intensity, and is a probable driver of the intensity trends observed. View Full-Text
Keywords: climate; precipitation intensity; hourly precipitation; hydrology; trend analysis climate; precipitation intensity; hourly precipitation; hydrology; trend analysis

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Cooley, A.; Chang, H. Precipitation Intensity Trend Detection using Hourly and Daily Observations in Portland, Oregon. Climate 2017, 5, 10.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Climate EISSN 2225-1154 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top