Foggy States: Which Weather Conditions Create Fog in the Coastal Northwest?
Forest Ecosystems & Society
Description of project or research opportunity:
Fog and low-level clouds are persistent atmospheric features of western Oregon and Washington. In many ways, fog delivers benefits to local forests, agriculture, and public health by providing shading and supplemental moisture in the hot, dry summer, thereby mitigating negative effects of drought and heat stress on our natural and built communities. However, there has been little research that quantifies why, when, and where fog occurs throughout the year in the Northwest, questions that are critical to uncovering the role fog plays in our past, present, and future. Under the supervision of Dr. Alex Dye and Dr. Christopher Still, the MEP student will conduct two broad tasks: 1) use publicly available climatological datasets to help summarize when and where foggy days have occurred in the past; 2) then, the student will help summarize the weather conditions, including temperature, humidity, and wind speed/direction, that coincide with foggy days. We anticipate the student will analyze a dataset similar to the long-term records available from regional Oregon/Washington airports: https://mesonet.agron.iastate.edu/request/download.phtml. The information the student helps summarize will contribute critical understanding of the conditions that create fog in the Northwest. The project will be conducted 100% remotely, with no required field or laboratory work. Since the project is remote and purely data analysis, the student will need consistent access to a computer with internet connection.
Tasks student will perform:
-Download, organize, and statistically summarize publicly available climatological data -Create visually informative figures, maps, and tables -Read background scientific literature and discuss with Dr. Dye -Meet weekly via Zoom with Dr. Dye to discuss project progress
Special skills required:
-Consistent access to a computer with internet access and the ability to run programs such as Microsoft Word, Excel, R, GIS (e.g. ArcGIS, QGIS, etc). -Familiarity with data analysis and computational processes in Excel, R, MatLab, or other -Familiarity with or ability to learn basic- to intermediate-level statistical techniques -Ability to meet deadlines -Ability to work independently in between supervisory meetings -Familiarity with reading and writing scientific documents.
Hourly rate of pay:
Proposed dates of employment:
Wednesday, January 6, 2021 to Tuesday, June 1, 2021
Anticipated hours worked per week:
Mentored Employment Program
COVID-19 Pandemic Response:
This project will be conducted 100% remotely.