First Advisor

Paul Loikith

Date of Publication

Summer 9-13-2019

Document Type


Degree Name

Master of Science (M.S.) in Geography




Precipitation (Meteorology) -- Pacific Northwest, Precipitation (Meteorology) -- Oregon -- Portland, Climatic changes, Meteorology



Physical Description

1 online resource (x, 92 pages)


Precipitation timing and magnitude is essential to human, ecological, and economic systems. Climate change may be altering the character of precipitation locally to globally, thus it is vital that resource managers, practitioners, and decision makers understand the nature of this change. This thesis was conducted in partnership with the City of Portland Bureau of Environmental Services (BES), and the Portland Water Bureau (PWB) in order to support resiliency planning around precipitation and precipitation extremes.

This work has two primary phases, which are discussed in chapter 2 and 3 of this thesis. The first phase of this research entails characterization of the large-scale meteorological patterns (LSMPs) associated with high hourly intensity and heavy daily accumulation of precipitation over Portland, OR. Heavy precipitation is associated with a multitude of impacts on urban environments, thus it is important to understand the meteorological drivers behind these events. This phase of work describes the range of meteorological patterns associated with heavy precipitation totals and high intensity precipitation days over the city of Portland, Oregon. The range of large-scale meteorological patterns (LSMPs) associated with high intensity precipitation days are clustered using the self-organizing map (SOM) approach and are defined using sea level pressure, 500 hPa geopotential height, and 250 hPa wind. Results show that an array of LSMPs are associated with heavy precipitation days, the majority of which occur in fall and winter, usually driven by extratropical cyclones and associated atmospheric rivers. Spring and summer heavy and high intensity precipitation days, while less common than in fall and winter, are typically related to upper level disturbances. Examination of two case studies, one occurring in summer and one in winter, supports the ability of the SOMs approach to realistically capture key observed storm types. Methods developed here may be extensible to other locations and results build an observational foundation for validating the ability of climate models to simulate the LSMPs associated with local extremes.

The second phase of this thesis involves evaluation of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) to simulate wet season LSMPs and associated precipitation in the Pacific Northwest of North America. As in the first phase, LSMPs are identified using the self-organizing maps (SOMs) approach, except in this phase all wet season days are included, and defined with sea level pressure, 500 hPa geopotential height, and 250 hPa wind speed. Using SOMs, the range of LSMPs over the region is constructed with reanalysis, providing the target for the multi-model evaluation. Overall, the CMIP5 models are able to reproduce reference LSMPs with reasonable fidelity, though the low pressure LSMPs are generally captured better than the ridging patterns. Furthermore, there is a hierarchy in model ability to capture key LSMPs, with some models exhibiting overall higher fidelity than others. To further evaluate model fidelity, precipitation associated with the LSMPs is evaluated. In general, the observations, reanalysis, and CMIP5 models agree on the LSMPs associated with wet and dry days, but wet patterns are captured somewhat better than dry patterns. The LSMPs associated with the driest and wettest conditions in the PNW are generally overrepresented, while the LSMPs associated with light average daily precipitation across the pacific northwest are underrepresented in the models. Results provide a mechanistic perspective on model fidelity in capturing synoptic climatology and associated precipitation characteristics across the PNW.

This research focuses on Portland and the Pacific Northwest, but has helped to develop methodology that is extensible to any location. The first phase gives us target LSMPs to understand future extreme precipitation over Portland, and the second phase of work lays the groundwork for developing projections of future changes to precipitation and precipitation extremes.

Persistent Identifier

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