Despite the importance of precipitation phase to global hydroclimate simulations, many land surface models use spatially uniform air temperature thresholds to partition rain and snow. Here we show, through the analysis of a 29-year observational dataset (n = 17.8 million), that the air temperature at which rain and snow fall in equal frequency varies significantly across the Northern Hemisphere, averaging 1.0 °C and ranging from –0.4 to 2.4 °C for 95% of the stations. Continental climates generally exhibit the warmest rain–snow thresholds and maritime the coolest. Simulations show precipitation phase methods incorporating humidity perform better than air temperature-only methods, particularly at relative humidity values below saturation and air temperatures between 0.6 and 3.4 °C. We also present the first continuous Northern Hemisphere map of rain–snow thresholds, underlining the spatial variability of precipitation phase partitioning. These results suggest precipitation phase could be better predicted using humidity and air temperature in large-scale land surface model runs.

Previous work demonstrates conflicting evidence regarding the influence of snowmelt timing on forest net ecosystem exchange (NEE). Based on 15 years of eddy covariance measurements in Colorado, years with earlier snowmelt exhibited less net carbon uptake during the snow ablation period, which is a period of high potential for productivity. Earlier snowmelt aligned with colder periods of the seasonal air temperature cycle relative to later snowmelt. We found that the colder ablation‐period air temperatures during these early snowmelt years lead to reduced rates of daily NEE. Hence, earlier snowmelt associated with climate warming, counterintuitively, leads to colder atmospheric temperatures during the snow ablation period and concomitantly reduced rates of net carbon uptake. Using a multilinear‐regression (R2 = 0.79, P < 0.001) relating snow ablation period mean air temperature and peak snow water equivalent (SWE) to ablation‐period NEE, we predict that earlier snowmelt and decreased SWE may cause a 45% reduction in midcentury ablation‐period net carbon uptake.

Predicting the phase of precipitation is fundamental to water supply and hazard forecasting. Phase prediction methods (PPMs) are used to predict snow fraction, or the ratio of snowfall to total precipitation. Common temperature‐based regression (Dai method) and threshold at freezing (0°C) PPMs had comparable accuracy to a humidity‐based PPM (TRH method) using 6 and 24 h observations. Using a daily climate data set from 1980 to 2015, the TRH method estimates 14% and 6% greater precipitation‐weighted snow fraction than the 0°C and Dai methods, respectively. The TRH method predicts four times less area with declining snow fraction than the Dai method (2.1% and 8.1% of the study domain, respectively) from 1980 to 2015, with the largest differences in the Cascade and Sierra Nevada mountains and southwestern U.S. Future Representative Concentration Pathway (RCP) 8.5 projections suggest warming temperatures of 4.2°C and declining relative humidity of 1% over the 21st century. The TRH method predicts a smaller reduction in snow fraction than temperature‐only PPMs by 2100, consistent with lower humidity buffering declines in snow fraction caused by regional warming.