Estimating robust melt factors and temperature thresholds for snow modelling across the Northern Hemisphere

Abstract. There are two important limitations to understanding large-scale impacts of environmental change on snow resources, 1) observational snow data at the point scale are highly limited, and 2) extrapolation using models can be challenging due to data availability and performance. This paper seeks to address these limitations using widely available climate network station data combined with a temperature-index snow model to derive estimates of mean snow water equivalent conditions across the Northern Hemisphere. Hydrological models commonly use very simple snow accumulation and melt models based on air temperature information, namely, a temperature threshold for snow accumulation as well as for snowmelt, and a melt factor. This utility emerges due to the simplicity, efficiency, and generally good performance of such models if sufficient calibration information is available. At scales beyond single gauged catchments, the estimation of the temperature thresholds and the melt factor has been difficult due to a lack of observations on snow accumulation and melt. Using a recently published Northern Hemisphere snow water equivalent dataset (NH-SWE) and co-located climate station observations of temperature and precipitation (5,560 sites across the Northern Hemisphere), this work provides the first large-scale and long-term (1950–2023) evaluation of a simple temperature index snow model and its parameters across a diverse range of snow climates. Our study reveals that the 0 °C as snowfall-air temperature threshold captures most snowfall events, especially in cold climates, but risks missing 11 % of snowfall events, especially in climates with regular near-freezing temperatures. Similarly, an air temperature threshold for snowmelt of 0 °C reproduces well most daily snowmelt observations, but may lead to an earlier than observed onset of the melt season. Estimated melt factors converge towards 3–5 mm °C⁻¹ day⁻¹ for deeper snowpack climates (> 300 mm), but their estimation may be more challenging for colder climates with shallower snowpacks (< 300 mm) , conditions where the inferred melt factors have much higher interannual variability. The temperature-index snow model performs consistently well across the available Northern Hemisphere data set for estimating long-term mean values of seasonal snow cover onset, snowmelt season onset, mean snow accumulation and snowmelt rates, but challenges may arise due to biases in temperature records or solid precipitation undercatch. This study provides valuable insights into temperature-threshold snowfall modelling and temperature-index melt modelling for applications across diverse climates and environments, and the results should help refine modelling approaches to enhance our understanding of snowpack responses to global warming.