Science Source
The Uneven Response of Different Snow Measures to Human-Induced Climate Warming
- Compares the effect of human-induced climate warming on different snow measures in the western United States by calculating the time required to achieve a statistically significant linear trend in the different measures, using time series derived from regionally downscaled global climate models
- The measures examined include the water content of the spring snowpack, total cold-season snowfall, fraction of winter precipitation that falls as snow, length of the snow season, and fraction of cold-season precipitation retained in the spring snowpack, as well as temperature and precipitation
- Finds that temperature and the fraction of winter precipitation that falls as snow exhibit significant trends first, followed in 5–10 years by the fraction of cold-season precipitation retained in the spring snowpack, and later still by the water content of the spring snowpack
- Finds that change in total cold-season snowfall is least detectable of all the measures, since it is strongly linked to precipitation, which has large natural variability and only a weak anthropogenic trend in the western United States
- Finds that averaging over increasingly wider areas monotonically increases the signal-to-noise ratio of the 1950–2025 linear trend from 0.15 to 0.37, depending on the snow measure
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