Regions of intensification of extreme snowfall under future warming

Abstract

Due to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

Figure 1

Intensification of extreme daily snowfall throughout the century for high-latitudes, decreasing percentiles, particularly in the second half of the century for mid-latitudes, especially Western Europe. Values are relative to the historical baseline (1851–1920). Relative change (in %) of (a,c,e) 99.9th percentile, and (b,d,f) 99.9th expected extreme magnitude; (a,b) 2021–2030, (c,d) 2051–2060, (e,f) 2091–2100. Maps created using the cartopy 0.17 library based on GSHHG shapes.

Figure 2

Strong increase in mean daily snowfall in high latitudes of North America and North-East Asia, decreases in mid-latitudes of North America and Western Eurasia relative to historical baseline (1851–1920), (0% points = baseline) (a) 2021–2030, (b) 2051–2060, (c) 2091–2100. Maps created using the cartopy 0.17 library based on GSHHG shapes.

Figure 3

Contrasting global trends of mean daily snowfall and extreme snowfall measures (elevation below 1000 m, decadal statistics, Northern Hemisphere north of 40 °N, SSP5-RCP8.5). All values are area-weighted and relative to the baseline (1851–1920) climate. (a) Mean, (b) 99.9th percentile, (c) expected extreme magnitude above the 99.9th baseline percentile. Blue line shows the model ensemble median, shaded areas denote the likely range (16.7th to 83.3rd percentiles). Orange line shows statistics for all ten models combined into one time series ensemble.

Figure 4

Population exposed to strongly intensifying and decreasing snowfall events grows in the next decades before a majority of population is experiencing decreasing extreme events at the end of the century. Global population weighted trend of 99.9th percentile (elevation below 1000 m, decadal statistics, Northern Hemisphere north of 40 °N, SSP5-RCP8.5). Binned according to change relative to the baseline (1851–1920) climate. Coloured area represents the population weighted percentage of cells in the respective bin. Population is fixed to a 2020 estimate.

Figure 5

Regional differences of changes in daily snowfall statistics (elevation below 1000 m, decadal statistics, SSP5-RCP8.5). All values are relative to the baseline (1851–1920) climate. (a) Mean, (b) 99.9th percentile, (c) expected extreme magnitude above the 99.9th baseline percentile. Blue line shows the model ensemble median, shaded areas denote the likely range (16.7th to 83.3rd percentiles). Orange line shows statistics for all ten models combined into one time series ensemble.

Figure 6

Regional differences in the trend of number of days with surface temperature between $-2.5$ ${}^{\circ }$C and $-1.5$ ${}^{\circ }$C (elevation below 1000 m, decadal statistics, SSP5-RCP8.5). All values are relative to the baseline (1851–1920) climate. Blue line shows the model ensemble median, shaded areas denote the likely range (16.7th to 83.3rd percentiles). Orange line shows statistics for all ten models combined into one time series ensemble.