Warming surface temperatures have driven a substantial reduction in the extent and duration of Northern Hemisphere snow cover(1-3). These changes in snow cover affect Earth's climate system via the surface energy budget, and influence freshwater resources across a large proportion of the Northern Hemisphere(4-6). In contrast to snow extent, reliable quantitative knowledge on seasonal snow mass and its trend is lacking(7-9). Here we use the new GlobSnow 3.0 dataset to show that the 1980-2018 annual maximum snow mass in the Northern Hemisphere was, on average, 3,062 +/- 35 billion tonnes (gigatonnes). Our quantification is for March (the month that most closely corresponds to peak snow mass), covers non-alpine regions above 40 degrees N and, crucially, includes a bias correction based on in-field snow observations. We compare our GlobSnow 3.0 estimates with three independent estimates of snow mass, each with and without the bias correction. Across the four datasets, the bias correction decreased the range from 2,433-3,380 gigatonnes (mean 2,867) to 2,846-3,062 gigatonnes (mean 2,938)-a reduction in uncertainty from 33% to 7.4%. On the basis of our bias-corrected GlobSnow 3.0 estimates, we find different continental trends over the 39-year satellite record. For example, snow mass decreased by 46 gigatonnes per decade across North America but had a negligible trend across Eurasia; both continents exhibit high regional variability. Our results enable a better estimation of the role of seasonal snow mass in Earth's energy, water and carbon budgets. Applying a bias correction to a state-of-the-art dataset covering non-alpine regions of the Northern Hemisphere and to three other datasets yields a more constrained quantification of snow mass in March from 1980 to 2018.