Tyrell Cooper, The College of Wooster

Class Year:

2024

Mentor:

Dong Liang, Ph.D. Victoria Coles, Ph.D.

Abstract:

Synoptic climatology describes the relationship between the climate system and certain surface conditions. Past synoptic relationship studies have focused on longer and broader surface conditions. This project aims to provide results that will benefit near-shore communities by focusing on extreme weather events, climate extremes. Correlations made between climate modes and climate extremes are seen to be stronger than with average weather patterns (St. Laurent et al., 2022). Climate extremes are more harmful due to their severity of effects than shifting average weather behaviors. For that reason, we correlated the climate modes North Atlantic Oscillation and Pacific Decadal Oscillation to 16 climate extreme indices. We first connected 39 years of historical sea level pressure (SLP) to weather data, temperature and precipitation. We utilized the principal component analysis (PCA) to reduce high dimensionality among the SLP data. The self-organizing map (SOM) algorithm created sets of grids of pressure patterns and seasonal (monthly) distribution histograms were also generated. The weather data was fitted against the 16 climate extreme indices and grouped within three categories: extreme cold, heat, and precipitation. We then visualized the probability of climate extreme occurrence during the SOM’s seasonal distribution with star plots. Finally, scatter plots were created to represent the correlation between climate extreme probability and climate mode index. These final plots provide us with the likelihood of extreme events occurring and the respective state of climate mode. 

Location:

Chesapeake Biological Laboratory