Primary Modes of Northern Hemisphere Snowfall Particle Size Distributions

A comprehensive understanding of snowfall microphysics is crucial for enhancingthe accuracy of remote sensing snowfall retrievals. However, variations in regional and seasonalsnow particle size distributions (PSDs) contribute substantial uncertainty. Here, we examinesnowfall PSDs from across the Northern Hemisphere, applying Principal Component Analysis(PCA) to disdrometer observations with the aim of identifying dominant modes of variabilityacross varying regional climates. The PCA revealed three Empirical Orthogonal Functions (EOFs)that account for a combined 95% of the variability across the dataset, which are attributed to latentlinear embeddings of snowfall intensity (EOF1), snowfall character (EOF2) and snowfall regime(EOF3). Examining point clusters with the highest combined EOF values reveals six distinct modesof variability (i.e., Principal Component [PC] groups) with unique PSD traits. These groups arethen correlated with environmental factors using data from collocated vertically pointing radar,surface meteorology, and reanalysis to assist in assigning physical attributes. The first and secondPC groups, linked to EOF1’s intensity embedding, are described by their PSD intercepts, snowfallrates, and reflectivity and Doppler velocity values, representing low and high intensity snowfallmodes, respectively. The third and fourth PC groups, associated with EOF2’s character embedding,are defined by temperature, fall speed, and density, indicative of cold, fluffy snowfall and warm,dense snowfall, respectively. The fifth and sixth PC groups, related to EOF3’s regime embedding,are distinguished by their PSD slope, snowfall rate, and reflectivity profiles, signifying shallow,weak convective systems with small particles, and deep, stratiform snowfall events with largeaggregates, respectively.