Wind-induced losses, or undercatch, can have a substantial impact on precipitation gauge observations, especially in alpine environments that receive a substantial amount of frozen precipitation and may be exposed to high winds. A network of NOAH II all-weather gauges installed in the Snowy Mountains since 2006 provides an opportunity to evaluate the magnitude of undercatch in an Australian alpine environment. Data from two intercomparison sites were used with NOAH II gauges with different configurations of wind fences installed: unfenced, WMO standard double fence intercomparison reference (full DFIR) fences, and an experimental half-sized double fence (half DFIR). It was found that average ambient temperature over 6-h periods was sufficient to classify the precipitation phase as snow, mixed precipitation, or rain in a statistically robust way. Empirical catch ratio relationships (i.e., the quotient of observations from two gauges), based on wind speed, ambient temperature, and measured precipitation amount, were established for snow and mixed precipitation. An adjustment scheme to correct the unfenced NOAH II gauge data using the catch ratio relationships was cross validated with independent data from two additional sites, as well as from the intercomparison sites themselves. The adjustment scheme was applied to the observed precipitation amounts at the other sites with unfenced NOAH II gauges. In the worst-case scenario, it was found that the observed precipitation amount would need to be increased by 52% to match what would have been recorded had adequate shielding been installed. However, gauges that were naturally well protected, and those below about 1400 m, required very little adjustment. Spatial analysis showed that the average seasonal undercatch was between 6% and 15% for gauges above 1000 m MSL.

Snowmelt from the seasonal snowpack in the Australian Alps is a significant source of water for irrigated agriculture, electricity generation, and environmental flows in the Murray–Darling Basin. Previous studies have reported negative decadal to multidecadal trends in maximum snow depth, snow season duration, and snow‐covered area. Here, we characterise the energy balance of this marginal maritime snowpack for the first time. Turbulent fluxes measured using the eddy covariance and bulk aerodynamic methods are compared; discrepancies are attributed to the differing assumptions of the methods and characteristics of the measurement site. We examine the variability of the individual energy balance components and the drivers of snowmelt, and we find that incoming longwave radiation is the dominant control on snowmelt, providing more than 80% of the total energy to the snowpack over the season. During a midwinter rain‐on‐snow event, the advected rain heat flux provided 8% of the daily total, with the incoming longwave flux still accounting for almost 80%. The ground heat flux contributes a small proportion of the seasonal total but increases in patchy or intermittent snow cover. Comparing these results with those of studies in other maritime locations, we find that the turbulent fluxes are likely to make a proportionally higher contribution to the energy balance due to the short Australian snow season, underpinning the sensitivity of this environment to climate variability and change. These results extend the limited body of knowledge on highly marginal snowpacks and may be relevant to other regions with no direct measurements of the energy balance.

Seasonal snowpacks in marginal snow environments are typically warm and nearly isothermal, exhibiting high inter‐ and intra‐annual variability. Measurements of snow depth and snow water equivalent were made across a small subalpine catchment in the Australian Alps over two snow seasons in order to investigate the extent and implications of snowpack spatial variability in this marginal setting. The distribution and dynamics of the snowpack were found to be influenced by upwind terrain, vegetation, solar radiation, and slope. The role of upwind vegetation was quantified using a novel parameter based on gridded vegetation height. The elevation range of the catchment was relatively modest (185 m), and elevation impacted distribution but not dynamics. Two characteristic features of marginal snowpack behaviour are presented. Firstly, the evolution of the snowpack is described in terms of a relatively unstable accumulation state and a highly stable ablation state, as revealed by temporal variations in the mean and standard deviation of snow water equivalent. Secondly, the validity of partitioning the snow season into distinct accumulation and ablation phases is shown to be compromised in such a setting. Snow at the most marginal locations may undergo complete melt several times during a season and, even where snow cover is more persistent, ablation processes begin to have an effect on the distribution of the snowpack early in the season. Our results are consistent with previous research showing that individual point measurements are unable to fully represent the variability in the snowpack across a catchment, and we show that recognising and addressing this variability are particularly important for studies in marginal snow environments.