Ben Page, “A Statistical Method to Analyze Climate Change Impacts on Mid-Latitude Weather Patterns”
Mentor: Paul Robber, Atmospheric Sciences
Poster #137

The goal of this project is to analyze reanalysis upper-level atmospheric data – data that has been synthesized to show a complete picture of what past weather and climates looked like – to determine if climate change is changing weather patterns at mid-latitudes. In this case, the focus is on the continental United States from 1950 to 2022 using monthly reanalysis data collected from the European Center for Medium-Range Weather Forecasts (ECMWF) and its Re-Analysis (ERA5) database. The statistical analysis software JMP was used to group the data based on similarities using the statistical method of k-means clustering. Each cluster average provides a representation of an atmospheric pattern, and referencing individual days within those clusters tells us whether these were associated with extreme weather events (heat waves, drought, flooding, etc.). We then examine whether there has been a change in frequency in these clusters (patterns) in the period from 1950-2022.