Project 7: Assessing future change in weather patterns associated with heavy rainfall over Bull Run Watershed

Project abstract:  Extreme precipitation is associated with a multitude of impacts on society and the environment. Among these impacts are challenges brought by heavy rainfall to drinking water quality. For example, heavy rainfall can wash sediment into waterways used for drinking water, requiring treatment of the water prior to delivery. This carries management implications for water providers. Anthropogenic climate warming can alter heavy precipitation in two primary ways. First, a warmer atmosphere can hold more water vapor, so all else being equal, rain can be heavier in a warmer climate. Second, storm frequencies and intensities can be altered bringing more or less intense precipitation depending on the direction of change. Understanding how these changes will play out in future decades is critical for anticipating adaptation measures for dealing with future heavy precipitation. In this project, we are focusing on assessing the projected changes in weather patterns currently associated with heavy precipitation over the Bull Run Watershed, the primary source of drinking water for the city of Portland. Using data from climate models provided by numerous modeling centers around the world, we are developing software to recognize patterns in the model simulated atmosphere that are likely to be associated with heavy rainfall over Bull Run. We are then quantifying whether and to what degree these patterns change in coming decades under future warming according to this large suite of climate model output. This work is in partnership with the Portland Water Bureau and currently in the first year of a two year project.
Keywords:
  • Climate Change,
  • Extreme Precipitation,
  • Climate Models
Faculty Mentor: Paul Loikith (http://web.pdx.edu/~ploikith/)

Lab or Team: Climate Science Lab (https://www.pdx.edu/geography/climate-science-lab)

Department: Geography

Community Partner(s):  Portland Water Bureau

Desired Skills (preferred, but not required): Matlab, basic understanding of meteorology, ability to handle large dataset

Tools to be used:  Matlab and/or Python languages
Involves teamwork: Yes