Physical Sciences and Mathematics Commons^™

Classifying Reanalysis Surface Temperature Probability Density Functions (Pdfs) Over North America With Cluster Analysis, Paul C. Loikith, Benjamin R. Lintner, Jinwon Kim, Huikyo Lee

Geography Faculty Publications and Presentations

An important step in projecting future climate change impacts on extremes involves quantifying the underlying probability distribution functions (PDFs) of climate variables. However, doing so can prove challenging when multiple models and large domains are considered. Here an approach to PDF quantification using k-means clustering is considered. A standard clustering algorithm (with k = 5 clusters) is applied to 33 years of daily January surface temperature from two state-of-the-art reanalysis products, the North American Regional Reanalysis and the Modern Era Retrospective Analysis for Research and Applications. The resulting cluster assignments yield spatially coherent patterns that can be broadly related to …