Spatial patterns of snow distribution in the sub-Arctic

Abstract. The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, carbon flux. However, is not well understood, therefore, it modeled, which can lead substantial uncertainties cover representations. To capture key hydro-ecological controls distribution, we carried out intensive field studies over multiple years for two small (2017–2019; ∼ 2.5 km2) study sites located Seward Peninsula Alaska. Using an suite observations (> 22 000 data points), developed simple models equivalent (SWE) using factors such as topographic characteristics, vegetation characteristics based greenness (normalized different index, NDVI), metric approximating winds. most successful model was random forest, both all years, able accurately complexity variability across sites. Approximately 86 % SWE could be accounted for, average, by forest at Factors that impacted year-to-year included NDVI, elevation, represent coarse microtopography (topographic position TPI), while slope, wind, fine were less important. characterization patterns will used validate improve modeling Department Energy's Earth system improved understanding topography, dynamics regions globe.