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Winter Storms and Climate Change: Two Competing Forces?
We take a look at how this winter's snowy spells in the north-east of the United States sit in the bigger picture of a warming planet.
Insights8 May 2026
Reviewing winter of 2025/6 in the United States, for those living in the North-East of the United States, there were enough reminders that we can still have cold, snowy winters despite a gradual background warming of the planet. But how does the bigger picture look when we take a step back to understand how snowfall might have changed in recent years?
Those old enough to remember the 1970s and 1980s in the UK will be well aware of the lack of snow in winter. Does the United States have a similar storyline? In order to understand how climate change might be impacting snow in the United States, we’ve used the ERA5 reanalysis snow depth data as a proxy for winter storm activity and combined this with the LitPop open-source global exposure dataset to produce country-wide and state-level exposure-weighted snowfall indices.
The data in the chart below uses the Litpop open-source global exposure dataset to exposure-weight snow depth in the United States as a function of day of the year. The blue filled contours show the range of historical behaviour and the thin black lines the absolute extremes. We can see that snow depth in the US typically seems to peak towards the middle of February.
This year, the exposure-weighted snow depth - in orange - was associated with the two news-worthy peaks in the snowfall depth associated with Winter Storms Fern and Hernando: both “Category Three” on NOAA’s Regional Snowfall Index. Both these storms produced exceptional snowfall depths in populous regions for the time of year that they occurred.
Is this end-of-season snowfall activity just one of those things, or something that we can read more into? To dig in a little further, we’ve plotted below the monthly mean exposure-weighted snow depth for the key winter months in the US over time.
When we split the data since 1980 into two equal periods, whilst December and January show clear drops of 22% and 27% percent respectively, as we look later into winter, February has actually shown an increase of around 11% - whilst March’s decrease is only around 8%.
Without a much deeper dive into the underlying meteorology, it leaves us with an interesting conundrum as to why we’re seeing a mixed picture in terms of changes in snowfall.
Taking a more granular step, we have also looked at the exposure-weighted state-level shifts in snowfall for these four main winter months of December through to March by contrasting the second half of the period to the first. This starts to reveal more interesting structure to the shifts in snow depth over time.
Whilst there are month-to-month shifts obvious around the US, it seems as though most of the Southern states are undergoing a marked downward shift in monthly snow depth. However, some of the states in and around Rockies: specifically, Wyoming, Utah, Nevada and Colorado are showing upward shifts in snow depth for January, February and March
The map for February highlights how many states are impacted by increasing snowfall in more recent years as a whole.
Coming back to the meteorology, there could be a number of reasons for this behaviour:
- A warmer atmosphere holds more moisture, leading to snowier storms when they do occur;
- The increased frequency of La Niña since the turn of the century may be responsible for some of the shifts seen here. La Niña winters tend to promote colder snowier weather in the northern half of the US, with warmer, drier weather to the south;
- Rapid warming of the Arctic has made the jet-stream “wavier” leading to greater likelihood of cold Arctic outbreaks in the US: although this topic is moot within academic
- More locally, several states in the NE US close to the Great Lakes may receive more snow as the lakes have warmed considerably in recent decades, leading to more snowfall as cold air flows over these lakes, known as “Lake Effect Snow”.
Whilst one might imagine that “global warming = less snowfall”, the US Winter Storm season is a good example of how the message of climate change can become tangled up in other factors that can operate at shorter timescales or more regionally that can muddy the waters.
Attempting to extract the signal from the noise can be challenging but is possible, and can help us at least make steps towards understanding what might be happening - and therefore also in making longer-term decisions around risk management.