Planetary Snow Cover Changes

Abstract: This talk develops a statistical model and methods to quantify trends in binary snow cover observations (snow presence/absence, not depths).  The methods are used to analyze the Earth’s snow cover record, extracted from weekly satellite pictures, during the period 1972-2024. A two state Markov chain with periodic dynamics is developed for the weekly data arising from each land cell studied. Spatial aspects are handled by allowing cell parameters to spatially vary according to a Besag-York-Mollie model. A Bayesian estimation procedure is constructed to estimate model parameters, trends, and their uncertainty margins. Snow cover is seen to be declining in almost twice as many cells as it is advancing.  While Arctic and European snow cover is found to be rapidly receding, other locations, such as Eastern Canada and Japan, are experiencing advancing snow cover.   An interesting seasonal pattern also emerges in the results.