Abstract

Using topographic and climatic variables, we present glacier clusters in the Chilean Andes (17.6-55.4°S), where the Partitioning Around Medoids (PAM) unsupervised machine learning algorithm was utilized. The results classified 23,974 glaciers inside thirteen clusters, which show specific conditions in terms of annual and monthly amounts of precipitation, temperature, and solar radiation. In the Dry Andes, the mean annual values of the five glacier clusters (C1-C5) display precipitation and temperature difference until 400 mm (29 and 33°S) and 8°C (33°S), with mean elevation contrast of 1800 m between glaciers in C1 and C5 clusters (18 to 34°S). While in the Wet Andes the highest differences were observed at the Southern Patagonia Icefield latitude (50°S), where the mean annual values for precipitation and temperature show maritime precipitation above 3700 mm/yr (C12), where the wet Western air plays a key role, and below 1000 mm/yr in the east of Southern Patagonia Icefield (C10), with differences temperature near of 4°C and mean elevation contrast of 500 m. This classification confirms that Chilean glaciers cannot be grouped only latitudinally, hence contributing to a better understanding of recent glacier volume changes at a regional scale.