Reduced frequency and size of late-twenty-first-century snowstorms over North America

Abstract

Understanding how snowstorms may change in the future is critical for estimating impacts on water resources and the Earth and socioeconomic systems that depend on them. Here we use snowstorms as a marker to assess the mesoscale fingerprint of climate change, providing a description of potential changes in winter weather event occurrence, character and variability in central and eastern North America under a high anthropogenic emissions pathway. Snowstorms are segmented and tracked using high-resolution, snow water equivalent output from dynamically downscaled simulations which, unlike global climate models, can resolve important mesoscale features such as banded snow. Significant decreases are found in the frequency and size of snowstorms in a pseudo-global warming simulation, including those events that produce the most extreme snowfall accumulations. Early and late boreal winter months show particularly robust proportional decreases in snowstorms and snow water equivalent accumulations.

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Fig. 1: Seasonal comparisons between CTRL and PGW.
Fig. 2: Spatial climatology of snow events.
Fig. 3: Snow event counts.
Fig. 4: Weekly per cent difference between the two epochs.

Data availability

The dynamically downscaled simulation output is available from NCAR’s Research Data Archive40.

Code availability

The source code56 for the snow event identification and tracking is available from https://github.com/ahaberlie/Future_Snow.

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Acknowledgements

We thank K. Ikeda and A. Prein for their assistance in accessing and interpreting the Liu et al.15 output. This research was supported by National Science Foundation grant no. ATM-1637225.

Author information

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Authors

Contributions

W.A. conceived the study. A.H. and W.A. led on the design of the study and analysed the data. A.H. constructed the tracking algorithm. V.G. led on the simulation output verification. All authors contributed to writing the manuscript, with W.A. as lead manuscript author and A.H. as lead author for the Methods.

Corresponding author

Correspondence to Walker S. Ashley.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Martin Baxter, Anthony Broccoli and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Comparison to climatology.

October–April 2003–2013 a) SNODAS average SWE (mm) and b) the absolute difference between WRF-CTRL and SNODAS mean SWE shown as a per cent of the total mean SNODAS SWE. As discussed in the manuscript, 2004–05 season was omitted from analysis due to missing WRF data. Hatched areas on both figures indicate locations where SNODAS data were not available or both WRF-CTRL and SNODAS did not record any SWE during the analysis period.

Extended Data Fig. 2 Event detection and tracking.

Demonstration of the various sources of climatological calculations from CTRL, namely, a) total accumulation of snow (liquid water equivalent) from January 13th 2001 to January 16th 2001, b) a ‘slice’ within a qualifying swath with the lowest (0.1mm / 3-hr), 50th percentile (0.46mm / 3-hr), and 90th percentile (2.08mm / 3-hr) snowfall totals (liquid water equivalent) denoted by the colour fill. The black outline is the spatial extent of the swath (that is, where the swath produced at least 0.1mm / 3-hr liquid water equivalent totals), c) the spatial extent of the occurrence of 3-hr liquid water equivalent snowfall totals exceeding the 50th percentile within this swath, and d) the spatial extent of the occurrence of 3-hr liquid water equivalent snowfall totals exceeding the 90th percentile within this swath.

Extended Data Fig. 3 Mean seasonal SWE accumulations.

Mean seasonal SWE accumulations (2004–2005 excluded) for (a) CTRL, (b) PGW, and accumulated SWE (c) differences and (d) per cent differences.

Extended Data Fig. 4 Spatial climatology of 90th percentile snow events.

Mean annual (a, b) swath counts, and (c) swath count difference and (d) per cent difference between (a) CTRL and (b) PGW for only 90th percentile snow events. The areas in grey experienced no qualifying swaths during the study period.

Extended Data Fig. 5 Per cent change in midwinter moderate and extreme intensity snowstorms.

Per cent difference in (a) 50th and (b) 90th percentile swath event counts between CTRL and PGW for the months of January and February.

Supplementary information

Supplementary Information

Supplementary Table 1.

Source data

Source Data Fig. 1

Data used in construction of seasonal comparisons between CTRL and PGW.

Source Data Fig. 3

Data used in construction of seasonal and subseasonal variability in swath counts and snow water equivalent (SWE) per season (October–April) for CTRL and PGW, panels a–d.

Source Data Fig. 4

Data used in construction of weekly per cent difference between the two epochs.

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Ashley, W.S., Haberlie, A.M. & Gensini, V.A. Reduced frequency and size of late-twenty-first-century snowstorms over North America. Nat. Clim. Chang. 10, 539–544 (2020). https://doi.org/10.1038/s41558-020-0774-4

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